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4,169 results on '"Groth P"'

1. Search for neutrino doublets and triplets using 11.4 years of IceCube data

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Babu, R., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brisson-Tsavoussis, Z., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Coleman, P., Collin, G. H., Connolly, A., Conrad, J. M., Corley, R., Cowen, D. F., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Durnford, D., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Esmail, W., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Griffin, S., Griswold, S., Groth, K. M., Guevel, D., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamacher, L., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hmaid, R., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kobayashi, Y., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kowalski, M., Kozynets, T., Krieger, N., Krishnamoorthi, J., Krishnan, T., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Lauber, F., Lazar, J. P., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Mand, A., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Parrish, V., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Pyras, L., Raab, C., Rack-Helleis, J., Rad, N., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwirn, S., Sclafani, S., Seckel, D., Seen, L., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stachurska, J., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Carrasco, S. Vergara, Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, F., Yu, S., Yuan, T., Zegarelli, A., Zhang, S., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We report a search for high-energy astrophysical neutrino multiplets, detections of multiple neutrino clusters in the same direction within 30 days, based on an analysis of 11.4 years of IceCube data. A new search method optimized for transient neutrino emission with a monthly time scale is employed, providing a higher sensitivity to neutrino fluxes. This result is sensitive to neutrino transient emission, reaching per-flavor flux of approximately $10^{-10}\ {\rm erg}\ {\rm cm}^{-2}\ {\rm sec}^{-1}$ from the Northern sky in the energy range $E\gtrsim 50$~TeV. The number of doublets and triplets identified in this search is compatible with the atmospheric background hypothesis, which leads us to set limits on the nature of neutrino transient sources with emission timescales of one month.
Published: 2025

2. Observation of Cosmic-Ray Anisotropy in the Southern Hemisphere with Twelve Years of Data Collected by the IceCube Neutrino Observatory

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguado, T., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Babu, R., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brisson-Tsavoussis, Z., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Cochling, C., Coleman, A., Coleman, P., Collin, G. H., Connolly, A., Conrad, J. M., Corley, R., Cowen, D. F., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Durnford, D., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Esmail, W., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Griffin, S., Griswold, S., Groth, K. M., Guevel, D., Günther, C., Gutjahr, P., Gruchot, K., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamacher, L., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Hardy, A., Hayes, W., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hmaid, R., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kobayashi, Y., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kowalski, M., Kozynets, T., Krieger, N., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Mand, A., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Moy, A., Mukherjee, T., Naab, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Parrish, V., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Pyras, L., Raab, C., Rack-Helleis, J., Rad, N., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, E., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwirn, S., Sclafani, S., Seckel, D., Seen, L., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Simmons, A., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stachurska, J., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thorpe, A., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Carrasco, S. Vergara, Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, M., Woodward, H., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zegarelli, A., Zhang, S., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We analyzed the 7.92$\times 10^{11}$ cosmic-ray-induced muon events collected by the IceCube Neutrino Observatory from May 13, 2011, when the fully constructed experiment started to take data, to May 12, 2023. This dataset provides an up-to-date cosmic-ray arrival direction distribution in the Southern Hemisphere with unprecedented statistical accuracy covering more than a full period length of a solar cycle. Improvements in Monte Carlo event simulation and better handling of year-to-year differences in data processing significantly reduce systematic uncertainties below the level of statistical fluctuations compared to the previously published results. We confirm the observation of a change in the angular structure of the cosmic-ray anisotropy between 10 TeV and 1 PeV, more specifically in the 100-300 TeV energy range.
Published: 2024

3. Learning Semantic Association Rules from Internet of Things Data

Author: Karabulut, Erkan, Groth, Paul, and Degeler, Victoria
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Association Rule Mining (ARM) is the task of discovering commonalities in data in the form of logical implications. ARM is used in the Internet of Things (IoT) for different tasks including monitoring and decision-making. However, existing methods give limited consideration to IoT-specific requirements such as heterogeneity and volume. Furthermore, they do not utilize important static domain-specific description data about IoT systems, which is increasingly represented as knowledge graphs. In this paper, we propose a novel ARM pipeline for IoT data that utilizes both dynamic sensor data and static IoT system metadata. Furthermore, we propose an Autoencoder-based Neurosymbolic ARM method (Aerial) as part of the pipeline to address the high volume of IoT data and reduce the total number of rules that are resource-intensive to process. Aerial learns a neural representation of a given data and extracts association rules from this representation by exploiting the reconstruction (decoding) mechanism of an autoencoder. Extensive evaluations on 3 IoT datasets from 2 domains show that ARM on both static and dynamic IoT data results in more generically applicable rules while Aerial can learn a more concise set of high-quality association rules than the state-of-the-art with full coverage over the datasets.
Published: 2024

4. A Policy Document Analysis of Student Digital Rights in the Australian Schooling Context

Author: Sean Groth and Erica Southgate
Abstract: Contemporary education is being undeniably shaped by datafication, and while new algorithmic and automated decision-making processes can have educational benefits, they also raise issues about children's digital rights and education policy responses to these rights. This study mapped how children's digital right to privacy and related human rights concepts are present in education policy documents of Australia's three largest state government departments of education. A children's rights coding framework was developed from the United Nation's 'General comment No. 25 (2021) on children's rights in relation to the digital environment' and used to code the dataset. Two levels of analysis were then undertaken. Level 1 involved code and subcode frequency analyses of concepts related to children's digital rights in policy documents. Level 2 was a descriptive qualitative analysis designed to understand how digital rights were expressed in policy. The study found that although all state government departments of education reflected some elements of children's digital rights, some states had a more complex, sustained and public-facing commitment to expressing these in policy. The study concluded that Australian government departments of education should work towards providing more transparent public-facing policy on children's digital rights that can empower students and their families to make informed decisions within a rapidly shifting digital environment.
Published: 2024
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5. TIGER: Temporally Improved Graph Entity Linker

Author: Zhang, Pengyu, Cao, Congfeng, and Groth, Paul
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Information Retrieval
Abstract: Knowledge graphs change over time, for example, when new entities are introduced or entity descriptions change. This impacts the performance of entity linking, a key task in many uses of knowledge graphs such as web search and recommendation. Specifically, entity linking models exhibit temporal degradation - their performance decreases the further a knowledge graph moves from its original state on which an entity linking model was trained. To tackle this challenge, we introduce \textbf{TIGER}: a \textbf{T}emporally \textbf{I}mproved \textbf{G}raph \textbf{E}ntity Linke\textbf{r}. By incorporating structural information between entities into the model, we enhance the learned representation, making entities more distinguishable over time. The core idea is to integrate graph-based information into text-based information, from which both distinct and shared embeddings are based on an entity's feature and structural relationships and their interaction. Experiments on three datasets show that our model can effectively prevent temporal degradation, demonstrating a 16.24\% performance boost over the state-of-the-art in a temporal setting when the time gap is one year and an improvement to 20.93\% as the gap expands to three years. The code and data are made available at \url{https://github.com/pengyu-zhang/TIGER-Temporally-Improved-Graph-Entity-Linker}.
Published: 2024

6. CYCLE: Cross-Year Contrastive Learning in Entity-Linking

Author: Zhang, Pengyu, Cao, Congfeng, Zaporojets, Klim, and Groth, Paul
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Knowledge graphs constantly evolve with new entities emerging, existing definitions being revised, and entity relationships changing. These changes lead to temporal degradation in entity linking models, characterized as a decline in model performance over time. To address this issue, we propose leveraging graph relationships to aggregate information from neighboring entities across different time periods. This approach enhances the ability to distinguish similar entities over time, thereby minimizing the impact of temporal degradation. We introduce \textbf{CYCLE}: \textbf{C}ross-\textbf{Y}ear \textbf{C}ontrastive \textbf{L}earning for \textbf{E}ntity-Linking. This model employs a novel graph contrastive learning method to tackle temporal performance degradation in entity linking tasks. Our contrastive learning method treats newly added graph relationships as \textit{positive} samples and newly removed ones as \textit{negative} samples. This approach helps our model effectively prevent temporal degradation, achieving a 13.90\% performance improvement over the state-of-the-art from 2023 when the time gap is one year, and a 17.79\% improvement as the gap expands to three years. Further analysis shows that CYCLE is particularly robust for low-degree entities, which are less resistant to temporal degradation due to their sparse connectivity, making them particularly suitable for our method. The code and data are made available at \url{https://github.com/pengyu-zhang/CYCLE-Cross-Year-Contrastive-Learning-in-Entity-Linking}.
Published: 2024

7. AnyMatch -- Efficient Zero-Shot Entity Matching with a Small Language Model

Author: Zhang, Zeyu, Groth, Paul, Calixto, Iacer, and Schelter, Sebastian
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Databases
Abstract: Entity matching (EM) is the problem of determining whether two records refer to same real-world entity, which is crucial in data integration, e.g., for product catalogs or address databases. A major drawback of many EM approaches is their dependence on labelled examples. We thus focus on the challenging setting of zero-shot entity matching where no labelled examples are available for an unseen target dataset. Recently, large language models (LLMs) have shown promising results for zero-shot EM, but their low throughput and high deployment cost limit their applicability and scalability. We revisit the zero-shot EM problem with AnyMatch, a small language model fine-tuned in a transfer learning setup. We propose several novel data selection techniques to generate fine-tuning data for our model, e.g., by selecting difficult pairs to match via an AutoML filter, by generating additional attribute-level examples, and by controlling label imbalance in the data. We conduct an extensive evaluation of the prediction quality and deployment cost of our model, in a comparison to thirteen baselines on nine benchmark datasets. We find that AnyMatch provides competitive prediction quality despite its small parameter size: it achieves the second-highest F1 score overall, and outperforms several other approaches that employ models with hundreds of billions of parameters. Furthermore, our approach exhibits major cost benefits: the average prediction quality of AnyMatch is within 4.4% of the state-of-the-art method MatchGPT with the proprietary trillion-parameter model GPT-4, yet AnyMatch requires four orders of magnitude less parameters and incurs a 3,899 times lower inference cost (in dollars per 1,000 tokens)., Comment: 12 pages excluding references, 3 figures, and 5 tables
Published: 2024

8. Turbulent Pressure Support in Galaxy Clusters -- Impact of the Hydrodynamical Solver

Author: Groth, Frederick, Valentini, Milena, Steinwandel, Ulrich P., Vallés-Pérez, David, and Dolag, Klaus
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: The amount of turbulent pressure in galaxy clusters is still debated, especially as for the impact of the dynamical state and the hydro-method used for simulations. We study the turbulent pressure fraction in the intra cluster medium of massive galaxy clusters. We aim to understand the impact of the hydrodynamical scheme, analysis method, and dynamical state on the final properties of galaxy clusters from cosmological simulations. We perform non-radiative simulations of a set of zoom-in regions of seven galaxy clusters with Meshless Finite Mass (MFM) and Smoothed Particle Hydrodynamics (SPH). We use three different analysis methods based on: $(i)$ the deviation from hydrostatic equilibrium, $(ii)$ the solenoidal velocity component obtained by a Helmholtz-Hodge decomposition, and $(iii)$ the small-scale velocity obtained through a multi-scale filtering approach. We split the sample of simulated clusters into active and relaxed clusters. Our simulations predict an increased turbulent pressure fraction for active compared to relaxed clusters. This is especially visible for the velocity-based methods. For these, we also find increased turbulence for the MFM simulations compared to SPH, consistent with findings from more idealized simulations. The predicted non-thermal pressure fraction varies between a few percent for relaxed clusters and $\approx13\%$ for active ones within the cluster center and increases towards the outskirts. No clear trend with redshift is visible. Our analysis quantitatively assesses the importance played by the hydrodynamical scheme and the analysis method to determine the non-thermal/turbulent pressure fraction. While our setup is relatively simple (non-radiative runs), our simulations show agreement with previous, more idealized simulations, and make a step further toward the understanding of turbulence., Comment: 15 pages, 10 figures, accepted for publication in A&A
Published: 2024

9. An Argument for Expanding Research on Quantitative Pedagogical Content Knowledge

Author: Randall E. Groth
Abstract: Pedagogical content knowledge (PCK) traditionally has been used in research concerning prospective and practicing classroom teachers. This essay argues that PCK is also relevant to other professions including those advancing quantitative reasoning (QR). To illustrate, the case of PCK for teaching QR is considered. Those in fields such as public health, journalism, meteorology, and government increasingly find themselves responsible for helping the public understand an ever-growing amount of quantitative information that has a bearing on societal well-being. Several examples illustrate how such professionals' responsibilities require knowing prevalent QR patterns in society, strategies for fostering sound reasoning, and the general nature of school curricula. Professional organizations in education, colleges of education, and educational researchers would benefit from expanding PCK research to encompass multiple professions. These expanded research and development efforts would simultaneously address urgent societal needs.
Published: 2024

10. Preparing Students for Civic Engagement through Project Citizen

Author: Diana Owen and Alissa Irion-Groth
Abstract: This study examines the effectiveness of the Center for Civic Education's Project Citizen teacher professional development program and curriculum intervention in producing positive student learning outcomes that support civic engagement. Through Project Citizen, students identify and research a problem in their community, explore solutions, consult with stakeholders, and develop an action plan. A three-year national study was conducted by the Civic Education Research Lab at Georgetown University from 2020-2023, during the height of the COVID-19 pandemic. The research employed randomized controlled trials of middle and high school students enrolled in Project Citizen and control group students who took a conventional civics class. The study confirmed the efficacy of project-based learning conveying civic skills and orientations conducive to civic engagement. Project Citizen students' problem-solving and civic expression skills improved significantly after the intervention. They reported a greater desire to turn out to vote if given the opportunity and felt better prepared to take part in the civic life of their community. The gains in civic skills and propensity for engagement were greater for Project Citizen students than those in the control group.
Published: 2024

11. Computational quantum transport

Author: Waintal, Xavier, Wimmer, Michael, Akhmerov, Anton, Groth, Christoph, Nikolic, Branislav K., Istas, Mathieu, Rosdahl, Tómas Örn, and Varjas, Daniel
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Computational Physics
Abstract: This review is devoted to the different techniques that have been developed to compute the coherent transport properties of quantum nanoelectronic systems connected to electrodes. Beside a review of the different algorithms proposed in the literature, we provide a comprehensive and pedagogical derivation of the two formalisms on which these techniques are based: the scattering approach and the Green's function approach. We show that the scattering problem can be formulated as a system of linear equations and that different existing algorithms for solving this scattering problem amount to different sequences of Gaussian elimination. We explicitly prove the equivalence of the two formalisms. We discuss the stability and numerical complexity of the existing methods., Comment: 56 pages, 15 pages
Published: 2024

12. Explaining Graph Neural Networks for Node Similarity on Graphs

Author: Daza, Daniel, Chu, Cuong Xuan, Tran, Trung-Kien, Stepanova, Daria, Cochez, Michael, and Groth, Paul
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Similarity search is a fundamental task for exploiting information in various applications dealing with graph data, such as citation networks or knowledge graphs. While this task has been intensively approached from heuristics to graph embeddings and graph neural networks (GNNs), providing explanations for similarity has received less attention. In this work we are concerned with explainable similarity search over graphs, by investigating how GNN-based methods for computing node similarities can be augmented with explanations. Specifically, we evaluate the performance of two prominent approaches towards explanations in GNNs, based on the concepts of mutual information (MI), and gradient-based explanations (GB). We discuss their suitability and empirically validate the properties of their explanations over different popular graph benchmarks. We find that unlike MI explanations, gradient-based explanations have three desirable properties. First, they are actionable: selecting inputs depending on them results in predictable changes in similarity scores. Second, they are consistent: the effect of selecting certain inputs overlaps very little with the effect of discarding them. Third, they can be pruned significantly to obtain sparse explanations that retain the effect on similarity scores.
Published: 2024

13. Vortex-p: a Helmholtz-Hodge and Reynolds decomposition algorithm for particle-based simulations

Author: Vallés-Pérez, David, Planelles, Susana, Quilis, Vicent, Groth, Frederick, Marin-Gilabert, Tirso, and Dolag, Klaus
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Astrophysical turbulent flows display an intrinsically multi-scale nature, making their numerical simulation and the subsequent analyses of simulated data a complex problem. In particular, two fundamental steps in the study of turbulent velocity fields are the Helmholtz-Hodge decomposition (compressive+solenoidal; HHD) and the Reynolds decomposition (bulk+turbulent; RD). These problems are relatively simple to perform numerically for uniformly-sampled data, such as the one emerging from Eulerian, fix-grid simulations; but their computation is remarkably more complex in the case of non-uniformly sampled data, such as the one stemming from particle-based or meshless simulations. In this paper, we describe, implement and test vortex-p, a publicly available tool evolved from the vortex code, to perform both these decompositions upon the velocity fields of particle-based simulations, either from smoothed particle hydrodynamics (SPH), moving-mesh or meshless codes. The algorithm relies on the creation of an ad-hoc adaptive mesh refinement (AMR) set of grids, on which the input velocity field is represented. HHD is then addressed by means of elliptic solvers, while for the RD we adapt an iterative, multi-scale filter. We perform a series of idealised tests to assess the accuracy, convergence and scaling of the code. Finally, we present some applications of the code to various SPH and meshless finite-mass (MFM) simulations of galaxy clusters performed with OpenGadget3, with different resolutions and physics, to showcase the capabilities of the code., Comment: Accepted for publication in Computer Physics Communications. 20 pages, 13 figures + appendices. The code is available in https://github.com/dvallesp/vortex-p and the documentation can be accessed in https://vortex-particles.github.io
Published: 2024
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14. Probing the connection between IceCube neutrinos and MOJAVE AGN

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Corley, R., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Durnford, D., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Guevel, D., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Carrasco, S. Vergara, Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Active Galactic Nuclei (AGN) are prime candidate sources of the high-energy, astrophysical neutrinos detected by IceCube. This is demonstrated by the real-time multi-messenger detection of the blazar TXS 0506+056 and the recent evidence of neutrino emission from NGC 1068 from a separate time-averaged study. However, the production mechanism of the astrophysical neutrinos in AGN is not well established which can be resolved via correlation studies with photon observations. For neutrinos produced due to photohadronic interactions in AGN, in addition to a correlation of neutrinos with high-energy photons, there would also be a correlation of neutrinos with photons emitted at radio wavelengths. In this work, we perform an in-depth stacking study of the correlation between 15 GHz radio observations of AGN reported in the MOJAVE XV catalog, and ten years of neutrino data from IceCube. We also use a time-dependent approach which improves the statistical power of the stacking analysis. No significant correlation was found for both analyses and upper limits are reported. When compared to the IceCube diffuse flux, at 100 TeV and for a spectral index of 2.5, the upper limits derived are $\sim3\%$ and $\sim9\%$ for the time-averaged and time-dependent case, respectively., Comment: 14 Pages 7 Figures
Published: 2024
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15. Search for a light sterile neutrino with 7.5 years of IceCube DeepCore data

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Corley, R., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Durnford, D., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Guevel, D., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Carrasco, S. Vergara, Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: High Energy Physics - Experiment
Abstract: We present a search for an eV-scale sterile neutrino using 7.5 years of data from the IceCube DeepCore detector. The analysis uses a sample of 21,914 events with energies between 5 and 150 GeV to search for sterile neutrinos through atmospheric muon neutrino disappearance. Improvements in event selection and treatment of systematic uncertainties provide greater statistical power compared to previous DeepCore sterile neutrino searches. Our results are compatible with the absence of mixing between active and sterile neutrino states, and we place constraints on the mixing matrix elements $|U_{\mu 4}|^2 < 0.0534$ and $|U_{\tau 4}|^2 < 0.0574$ at 90% CL under the assumption that $\Delta m^2_{41}\geq 1\;\mathrm{eV^2}$. These null results add to the growing tension between anomalous appearance results and constraints from disappearance searches in the 3+1 sterile neutrino landscape., Comment: 11 pages, 5 figures. Version accepted by Physical Review D for publication
Published: 2024
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16. IceCube Search for Neutrino Emission from X-ray Bright Seyfert Galaxies

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glauch, T., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Q. R., Liu, Y. T., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Experiment
Abstract: The recent IceCube detection of TeV neutrino emission from the nearby active galaxy NGC 1068 suggests that active galactic nuclei (AGN) could make a sizable contribution to the diffuse flux of astrophysical neutrinos. The absence of TeV $\gamma$-rays from NGC 1068 indicates neutrino production in the vicinity of the supermassive black hole, where the high radiation density leads to $\gamma$-ray attenuation. Therefore, any potential neutrino emission from similar sources is not expected to correlate with high-energy $\gamma$-rays. Disk-corona models predict neutrino emission from Seyfert galaxies to correlate with keV X-rays, as they are tracers of coronal activity. Using through-going track events from the Northern Sky recorded by IceCube between 2011 and 2021, we report results from a search for individual and aggregated neutrino signals from 27 additional Seyfert galaxies that are contained in the BAT AGN Spectroscopic Survey (BASS). Besides the generic single power-law, we evaluate the spectra predicted by the disk-corona model. Assuming all sources to be intrinsically similar to NGC 1068, our findings constrain the collective neutrino emission from X-ray bright Seyfert galaxies in the Northern Hemisphere, but, at the same time, show excesses of neutrinos that could be associated with the objects NGC 4151 and CGCG 420-015. These excesses result in a 2.7$\sigma$ significance with respect to background expectations., Comment: 17 pages, 9 figures
Published: 2024

17. Search for neutrino emission from hard X-ray AGN with IceCube

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Privon, G. C., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Active Galactic Nuclei (AGN) are promising candidate sources of high-energy astrophysical neutrinos since they provide environments rich in matter and photon targets where cosmic ray interactions may lead to the production of gamma rays and neutrinos. We searched for high-energy neutrino emission from AGN using the $\textit{Swift}$-BAT Spectroscopic Survey (BASS) catalog of hard X-ray sources and 12 years of IceCube muon track data. First, upon performing a stacked search, no significant emission was found. Second, we searched for neutrinos from a list of 43 candidate sources and found an excess from the direction of two sources, Seyfert galaxies NGC 1068 and NGC 4151. We observed NGC 1068 at flux $\phi_{\nu_{\mu}+\bar{\nu}_{\mu}}$ = $4.02_{-1.52}^{+1.58} \times 10^{-11}$ TeV$^{-1}$ cm$^{-2}$ s$^{-1}$ normalized at 1 TeV, with power-law spectral index, $\gamma$ = 3.10$^{+0.26}_{-0.22}$, consistent with previous IceCube results. The observation of a neutrino excess from the direction of NGC 4151 is at a post-trial significance of 2.9$\sigma$. If interpreted as an astrophysical signal, the excess observed from NGC 4151 corresponds to a flux $\phi_{\nu_{\mu}+\bar{\nu}_{\mu}}$ = $1.51_{-0.81}^{+0.99} \times 10^{-11}$ TeV$^{-1}$ cm$^{-2}$ s$^{-1}$ normalized at 1 TeV and $\gamma$ = 2.83$^{+0.35}_{-0.28}$.
Published: 2024

18. Exploration of mass splitting and muon/tau mixing parameters for an eV-scale sterile neutrino with IceCube

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: High Energy Physics - Experiment
Abstract: We present the first three-parameter fit to a 3+1 sterile neutrino model using 7.634 years of data from the IceCube Neutrino Observatory on $\nu_\mu+\overline{\nu}_\mu$ charged-current interactions in the energy range 500--9976 GeV. Our analysis is sensitive to the mass-squared splitting between the heaviest and lightest mass state ($\Delta m_{41}^2$), the mixing matrix element connecting muon flavor to the fourth mass state ($|U_{\mu4}|^2$), and the element connecting tau flavor to the fourth mass state ($|U_{\tau4}|^2$). Predicted propagation effects in matter enhance the signature through a resonance as atmospheric neutrinos from the Northern Hemisphere traverse the Earth to the IceCube detector at the South Pole. The remaining sterile neutrino matrix elements are left fixed, with $|U_{e4}|^2= 0$ and $\delta_{14}=0$, as they have a negligible effect, and $\delta_{24}=\pi$ is set to give the most conservative limits. The result is consistent with the no-sterile neutrino hypothesis with a probability of 4.3%. Profiling the likelihood of each parameter yields the 90\% confidence levels: $ 2.4\,\mathrm{eV}^{2} < \Delta m_{41}^2 <9.6\,\mathrm{eV}^{2} $ , $0.0081 < |U_{\mu4}|^2 < 0.10$ , and $|U_{\tau4}|^2< 0.035$, which narrows the allowed parameter-space for $|U_{\tau4}|^2$. However, the primary result of this analysis is the first map of the 3+1 parameter space exploring the interdependence of $\Delta m_{41}^2$, $|U_{\mu4}|^2$, and $|U_{\tau4}|^2$., Comment: 14 pages, 8 figures. Published in PLB
Published: 2024
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19. Euclid. I. Overview of the Euclid mission

Author: Euclid Collaboration, Mellier, Y., Abdurro'uf, Barroso, J. A. Acevedo, Achúcarro, A., Adamek, J., Adam, R., Addison, G. E., Aghanim, N., Aguena, M., Ajani, V., Akrami, Y., Al-Bahlawan, A., Alavi, A., Albuquerque, I. S., Alestas, G., Alguero, G., Allaoui, A., Allen, S. W., Allevato, V., Alonso-Tetilla, A. V., Altieri, B., Alvarez-Candal, A., Alvi, S., Amara, A., Amendola, L., Amiaux, J., Andika, I. T., Andreon, S., Andrews, A., Angora, G., Angulo, R. E., Annibali, F., Anselmi, A., Anselmi, S., Arcari, S., Archidiacono, M., Aricò, G., Arnaud, M., Arnouts, S., Asgari, M., Asorey, J., Atayde, L., Atek, H., Atrio-Barandela, F., Aubert, M., Aubourg, E., Auphan, T., Auricchio, N., Aussel, B., Aussel, H., Avelino, P. P., Avgoustidis, A., Avila, S., Awan, S., Azzollini, R., Baccigalupi, C., Bachelet, E., Bacon, D., Baes, M., Bagley, M. B., Bahr-Kalus, B., Balaguera-Antolinez, A., Balbinot, E., Balcells, M., Baldi, M., Baldry, I., Balestra, A., Ballardini, M., Ballester, O., Balogh, M., Bañados, E., Barbier, R., Bardelli, S., Baron, M., Barreiro, T., Barrena, R., Barriere, J. -C., Barros, B. J., Barthelemy, A., Bartolo, N., Basset, A., Battaglia, P., Battisti, A. J., Baugh, C. M., Baumont, L., Bazzanini, L., Beaulieu, J. -P., Beckmann, V., Belikov, A. N., Bel, J., Bellagamba, F., Bella, M., Bellini, E., Benabed, K., Bender, R., Benevento, G., Bennett, C. L., Benson, K., Bergamini, P., Bermejo-Climent, J. R., Bernardeau, F., Bertacca, D., Berthe, M., Berthier, J., Bethermin, M., Beutler, F., Bevillon, C., Bhargava, S., Bhatawdekar, R., Bianchi, D., Bisigello, L., Biviano, A., Blake, R. P., Blanchard, A., Blazek, J., Blot, L., Bosco, A., Bodendorf, C., Boenke, T., Böhringer, H., Boldrini, P., Bolzonella, M., Bonchi, A., Bonici, M., Bonino, D., Bonino, L., Bonvin, C., Bon, W., Booth, J. T., Borgani, S., Borlaff, A. S., Borsato, E., Bose, B., Botticella, M. T., Boucaud, A., Bouche, F., Boucher, J. S., Boutigny, D., Bouvard, T., Bouwens, R., Bouy, H., Bowler, R. A. A., Bozza, V., Bozzo, E., Branchini, E., Brando, G., Brau-Nogue, S., Brekke, P., Bremer, M. N., Brescia, M., Breton, M. -A., Brinchmann, J., Brinckmann, T., Brockley-Blatt, C., Brodwin, M., Brouard, L., Brown, M. L., Bruton, S., Bucko, J., Buddelmeijer, H., Buenadicha, G., Buitrago, F., Burger, P., Burigana, C., Busillo, V., Busonero, D., Cabanac, R., Cabayol-Garcia, L., Cagliari, M. S., Caillat, A., Caillat, L., Calabrese, M., Calabro, A., Calderone, G., Calura, F., Quevedo, B. Camacho, Camera, S., Campos, L., Canas-Herrera, G., Candini, G. P., Cantiello, M., Capobianco, V., Cappellaro, E., Cappelluti, N., Cappi, A., Caputi, K. I., Cara, C., Carbone, C., Cardone, V. F., Carella, E., Carlberg, R. G., Carle, M., Carminati, L., Caro, F., Carrasco, J. M., Carretero, J., Carrilho, P., Duque, J. Carron, Carry, B., Carvalho, A., Carvalho, C. S., Casas, R., Casas, S., Casenove, P., Casey, C. M., Cassata, P., Castander, F. J., Castelao, D., Castellano, M., Castiblanco, L., Castignani, G., Castro, T., Cavet, C., Cavuoti, S., Chabaud, P. -Y., Chambers, K. C., Charles, Y., Charlot, S., Chartab, N., Chary, R., Chaumeil, F., Cho, H., Chon, G., Ciancetta, E., Ciliegi, P., Cimatti, A., Cimino, M., Cioni, M. -R. L., Claydon, R., Cleland, C., Clément, B., Clements, D. L., Clerc, N., Clesse, S., Codis, S., Cogato, F., Colbert, J., Cole, R. E., Coles, P., Collett, T. E., Collins, R. S., Colodro-Conde, C., Colombo, C., Combes, F., Conforti, V., Congedo, G., Conseil, S., Conselice, C. J., Contarini, S., Contini, T., Conversi, L., Cooray, A. R., Copin, Y., Corasaniti, P. -S., Corcho-Caballero, P., Corcione, L., Cordes, O., Corpace, O., Correnti, M., Costanzi, M., Costille, A., Courbin, F., Mifsud, L. Courcoult, Courtois, H. 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W., Prezelus, S., Prieto, E., Pugno, A., Quai, S., Quilley, L., Racca, G. D., Raccanelli, A., Rácz, G., Radinović, S., Radovich, M., Ragagnin, A., Ragnit, U., Raison, F., Ramos-Chernenko, N., Ranc, C., Rasera, Y., Raylet, N., Rebolo, R., Refregier, A., Reimberg, P., Reiprich, T. H., Renk, F., Renzi, A., Retre, J., Revaz, Y., Reylé, C., Reynolds, L., Rhodes, J., Ricci, F., Ricci, M., Riccio, G., Ricken, S. O., Rissanen, S., Risso, I., Rix, H. -W., Robin, A. C., Rocca-Volmerange, B., Rocci, P. -F., Rodenhuis, M., Rodighiero, G., Monroy, M. Rodriguez, Rollins, R. P., Romanello, M., Roman, J., Romelli, E., Romero-Gomez, M., Roncarelli, M., Rosati, P., Rosset, C., Rossetti, E., Roster, W., Rottgering, H. J. A., Rozas-Fernández, A., Ruane, K., Rubino-Martin, J. A., Rudolph, A., Ruppin, F., Rusholme, B., Sacquegna, S., Sáez-Casares, I., Saga, S., Saglia, R., Sahlén, M., Saifollahi, T., Sakr, Z., Salvalaggio, J., Salvaterra, R., Salvati, L., Salvato, M., Salvignol, J. -C., Sánchez, A. G., Sanchez, E., Sanders, D. B., Sapone, D., Saponara, M., Sarpa, E., Sarron, F., Sartori, S., Sartoris, B., Sassolas, B., Sauniere, L., Sauvage, M., Sawicki, M., Scaramella, R., Scarlata, C., Scharré, L., Schaye, J., Schewtschenko, J. A., Schindler, J. -T., Schinnerer, E., Schirmer, M., Schmidt, F., Schmidt, M., Schneider, A., Schneider, M., Schneider, P., Schöneberg, N., Schrabback, T., Schultheis, M., Schulz, S., Schuster, N., Schwartz, J., Sciotti, D., Scodeggio, M., Scognamiglio, D., Scott, D., Scottez, V., Secroun, A., Sefusatti, E., Seidel, G., Seiffert, M., Sellentin, E., Selwood, M., Semboloni, E., Sereno, M., Serjeant, S., Serrano, S., Setnikar, G., Shankar, F., Sharples, R. M., Short, A., Shulevski, A., Shuntov, M., Sias, M., Sikkema, G., Silvestri, A., Simon, P., Sirignano, C., Sirri, G., Skottfelt, J., Slezak, E., Sluse, D., Smith, G. P., Smith, L. C., Smith, R. E., Smit, S. J. A., Soldano, F., Solheim, B. G. B., Sorce, J. G., Sorrenti, F., Soubrie, E., Spinoglio, L., Mancini, A. Spurio, Stadel, J., Stagnaro, L., Stanco, L., Stanford, S. A., Starck, J. -L., Stassi, P., Steinwagner, J., Stern, D., Stone, C., Strada, P., Strafella, F., Stramaccioni, D., Surace, C., Sureau, F., Suyu, S. H., Swindells, I., Szafraniec, M., Szapudi, I., Taamoli, S., Talia, M., Tallada-Crespí, P., Tanidis, K., Tao, C., Tarrío, P., Tavagnacco, D., Taylor, A. N., Taylor, J. E., Taylor, P. L., Teixeira, E. M., Tenti, M., Idiago, P. Teodoro, Teplitz, H. I., Tereno, I., Tessore, N., Testa, V., Testera, G., Tewes, M., Teyssier, R., Theret, N., Thizy, C., Thomas, P. D., Toba, Y., Toft, S., Toledo-Moreo, R., Tolstoy, E., Tommasi, E., Torbaniuk, O., Torradeflot, F., Tortora, C., Tosi, S., Tosti, S., Trifoglio, M., Troja, A., Trombetti, T., Tronconi, A., Tsedrik, M., Tsyganov, A., Tucci, M., Tutusaus, I., Uhlemann, C., Ulivi, L., Urbano, M., Vacher, L., Vaillon, L., Valageas, P., Valdes, I., Valentijn, E. A., Valenziano, L., Valieri, C., Valiviita, J., Broeck, M. Van den, Vassallo, T., Vavrek, R., Vega-Ferrero, J., Venemans, B., Venhola, A., Ventura, S., Kleijn, G. Verdoes, Vergani, D., Verma, A., Vernizzi, F., Veropalumbo, A., Verza, G., Vescovi, C., Vibert, D., Viel, M., Vielzeuf, P., Viglione, C., Viitanen, A., Villaescusa-Navarro, F., Vinciguerra, S., Visticot, F., Voggel, K., von Wietersheim-Kramsta, M., Vriend, W. J., Wachter, S., Walmsley, M., Walth, G., Walton, D. M., Walton, N. A., Wander, M., Wang, L., Wang, Y., Weaver, J. R., Weller, J., Wetzstein, M., Whalen, D. J., Whittam, I. H., Widmer, A., Wiesmann, M., Wilde, J., Williams, O. R., Winther, H. -A., Wittje, A., Wong, J. H. W., Wright, A. H., Yankelevich, V., Yeung, H. W., Yoon, M., Youles, S., Yung, L. Y. A., Zacchei, A., Zalesky, L., Zamorani, G., Vitorelli, A. Zamorano, Marc, M. Zanoni, Zennaro, M., Zerbi, F. M., Zinchenko, I. A., Zoubian, J., Zucca, E., and Zumalacarregui, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'
Published: 2024

20. Cost-Benefit Analysis using Modular Dynamic Fault Tree Analysis and Monte Carlo Simulations for Condition-based Maintenance of Unmanned Systems

Author: Southgate, Joseph M., Groth, Katrina, Sandborn, Peter, and Azarm, Shapour
Subjects: Quantitative Finance - Computational Finance
Abstract: Recent developments in condition-based maintenance (CBM) have helped make it a promising approach to maintenance cost avoidance in engineering systems. By performing maintenance based on conditions of the component with regards to failure or time, there is potential to avoid the large costs of system shutdown and maintenance delays. However, CBM requires a large investment cost compared to other available maintenance strategies. The investment cost is required for research, development, and implementation. Despite the potential to avoid significant maintenance costs, the large investment cost of CBM makes decision makers hesitant to implement. This study is the first in the literature that attempts to address the problem of conducting a cost-benefit analysis (CBA) for implementing CBM concepts for unmanned systems. This paper proposes a method for conducting a CBA to determine the return on investment (ROI) of potential CBM strategies. The CBA seeks to compare different CBM strategies based on the differences in the various maintenance requirements associated with maintaining a multi-component, unmanned system. The proposed method uses modular dynamic fault tree analysis (MDFTA) with Monte Carlo simulations (MCS) to assess the various maintenance requirements. The proposed method is demonstrated on an unmanned surface vessel (USV) example taken from the literature that consists of 5 subsystems and 71 components. Following this USV example, it is found that selecting different combinations of components for a CBM strategy can have a significant impact on maintenance requirements and ROI by impacting cost avoidances and investment costs., Comment: 18 pages, 9 figures, 4 tables
Published: 2024

21. Methods and stability tests associated with the sterile neutrino search using improved high-energy $\nu_\mu$ event reconstruction in IceCube

Author: IceCube Collaboration, Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Sponsler, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract: We provide supporting details for the search for a 3+1 sterile neutrino using data collected over eleven years at the IceCube Neutrino Observatory. The analysis uses atmospheric muon-flavored neutrinos from 0.5 to 100\, TeV that traverse the Earth to reach the IceCube detector, and finds a best-fit point at $\sin^2(2\theta_{24}) = 0.16$ and $\Delta m^{2}_{41} = 3.5$ eV$^2$ with a goodness-of-fit p-value of 12\% and consistency with the null hypothesis of no oscillations to sterile neutrinos with a p-value of 3.1\%. Several improvements were made over past analyses, which are reviewed in this article, including upgrades to the reconstruction and the study of sources of systematic uncertainty. We provide details of the fit quality and discuss stability tests that split the data for separate samples, comparing results. We find that the fits are consistent between split data sets., Comment: 19 pages, 19 figures, 2 tables. This long-form paper is a companion to the letter "A search for an eV-scale sterile neutrino using improved high-energy {\nu}{\mu} event reconstruction in IceCube." Matches published version
Published: 2024
Full Text: View/download PDF

22. A search for an eV-scale sterile neutrino using improved high-energy $\nu_\mu$ event reconstruction in IceCube

Author: IceCube Collaboration, Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Sponsler, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract: This Letter presents the result of a 3+1 sterile neutrino search using 10.7 years of IceCube data. We analyze atmospheric muon neutrinos that traverse the Earth with energies ranging from 0.5 to 100 TeV, incorporating significant improvements in modeling neutrino flux and detector response compared to earlier studies. Notably, for the first time, we categorize data into starting and through-going events, distinguishing neutrino interactions with vertices inside or outside the instrumented volume, to improve energy resolution. The best-fit point for a 3+1 model is found to be at $\sin^2(2\theta_{24}) = 0.16$ and $\Delta m^{2}_{41} = 3.5$ eV$^2$, which agrees with previous iterations of this study. The result is consistent with the null hypothesis of no sterile neutrinos with a p-value of 3.1\%., Comment: 10 pages, 4 figures. This letter is supported by the long-form paper "Methods and stability tests associated with the sterile neutrino search using improved high-energy $\nu_\mu$ event reconstruction in IceCube," also appearing on arXiv. Matches published version
Published: 2024
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23. Search for joint multimessenger signals from potential Galactic PeVatrons with HAWC and IceCube

Author: Alfaro, R., Alvarez, C., Arteaga-Velázquez, J. C., Rojas, D. Avila, Solares, H. A. Ayala, Babu, R., Belmont-Moreno, E., Caballero-Mora, K. S., Capistrán, T., Carramiñana, A., Casanova, S., Cotti, U., Cotzomi, J., de León, S. Coutiño, De la Fuente, E., Depaoli, D., Di Lalla, N., Hernandez, R. Diaz, Díaz-Vélez, J. C., Engel, K., Ergin, T., Fan, K. L., Fang, K., Fraija, N., Fraija, S., García-González, J. A., Garfias, F., González, M. M., Goodman, J. A., Groetsch, S., Harding, J. P., Hernández-Cadena, S., Herzog, I., Huang, D., Hueyotl-Zahuantitla, F., Hüntemeyer, P., Iriarte, A., Kaufmann, S., Lee, J., Vargas, H. León, Longinotti, A. L., Luis-Raya, G., Malone, K., Martínez-Castro, J., Matthews, J. A., Miranda-Romagnoli, P., Montes, J. A., Moreno, E., Mostafá, M., Nellen, L., Omodei, N., Osorio, M., Araujo, Y. Pérez, Pérez-Pérez, E. G., Rho, C. D., Rosa-González, D., Salazar, H., Salazar-Gallegos, D., Sandoval, A., Schneider, M., Serna-Franco, J., Smith, A. J., Son, Y., Tibolla, O., Tollefson, K., Torres, I., Torres-Escobedo, R., Turner, R., Ureña-Mena, F., Wang, X., Watson, I. J., Whitaker, K., Willox, E., Wu, H., Yun-Cárcamo, S., Zhou, H., de León, C., Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Galactic PeVatrons are sources that can accelerate cosmic rays to PeV energies. The high-energy cosmic rays are expected to interact with the surrounding ambient material or radiation, resulting in the production of gamma rays and neutrinos. To optimize for the detection of such associated production of gamma rays and neutrinos for a given source morphology and spectrum, a multi-messenger analysis that combines gamma rays and neutrinos is required. In this study, we use the Multi-Mission Maximum Likelihood framework (3ML) with IceCube Maximum Likelihood Analysis software (i3mla) and HAWC Accelerated Likelihood (HAL) to search for a correlation between 22 known gamma-ray sources from the third HAWC gamma-ray catalog and 14 years of IceCube track-like data. No significant neutrino emission from the direction of the HAWC sources was found. We report the best-fit gamma-ray model and 90% CL neutrino flux limit from the 22 sources. From the neutrino flux limit, we conclude that the gamma-ray emission from five of the sources can not be produced purely from hadronic interactions. We report the limit for the fraction of gamma rays produced by hadronic interactions for these five sources.
Published: 2024

24. Gene regulation by convergent promoters

Author: Wiechens, Elina, Vigliotti, Flavia, Siniuk, Kanstantsin, Schwarz, Robert, Schwab, Katjana, Riege, Konstantin, van Bömmel, Alena, Görlich, Ivonne, Bens, Martin, Sahm, Arne, Groth, Marco, Sammons, Morgan A., Loewer, Alexander, Hoffmann, Steve, and Fischer, Martin
Published: 2025
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25. Medikamenteninduzierte Todesfälle bei Niereninsuffizienz: Retrospektive Studie des Instituts für Rechtsmedizin München

Author: Groth, Olwen, Roider, Gabriele, and Graw, Matthias
Published: 2025
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26. Volatile hydrocarbon exposures and immune-related illnesses among Deepwater Horizon oil spill workers

Author: Patel, Opal P., Lawrence, Kaitlyn G., Parks, Christine G., Stewart, Patricia A., Stenzel, Mark R., Groth, Caroline P., Ramachandran, Gurumurthy, Banerjee, Sudipto, Huynh, Tran B., Jackson, Braxton, Sandler, Dale P., and Engel, Lawrence S.
Published: 2024
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27. Training and education of operating room nurses in robot-assisted surgery: a systematic review

Author: Møller, Louise, Olsen, Rikke Groth, Jørgensen, Lone, Hertz, Peter, Petersson, Jane, Røder, Andreas, Konge, Lars, and Bjerrum, Flemming
Published: 2024
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28. 3D monitors improve performance on the HUGO™ RAS system: a randomised trial

Author: Østdal, Theresa Bruun, Tang, Diana Hai Yen, Olsen, Rikke Groth, Olsen, Louise Møller, Konge, Lars, and Bjerrum, Flemming
Published: 2024
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29. Cross-Correlation of Interconnection Technologies—A Case Study of Reduced Wire Bond Quality after Ultrasonic Welding

Author: Groth, A. and Hempel, M.
Published: 2024
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30. Todesursache: Medikamenteninduzierte Verlängerung des QT-Intervalls

Author: Groth, Olwen, Roider, Gabriele, and Graw, Matthias
Published: 2024
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31. Acceptance Tests of more than 10 000 Photomultiplier Tubes for the multi-PMT Digital Optical Modules of the IceCube Upgrade

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Joppe, R., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Kossatz, M., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sulanke, K. H., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: More than 10,000 photomultiplier tubes (PMTs) with a diameter of 80 mm will be installed in multi-PMT Digital Optical Modules (mDOMs) of the IceCube Upgrade. These have been tested and pre-calibrated at two sites. A throughput of more than 1000 PMTs per week with both sites was achieved with a modular design of the testing facilities and highly automated testing procedures. The testing facilities can easily be adapted to other PMTs, such that they can, e.g., be re-used for testing the PMTs for IceCube-Gen2. Single photoelectron response, high voltage dependence, time resolution, prepulse, late pulse, afterpulse probabilities, and dark rates were measured for each PMT. We describe the design of the testing facilities, the testing procedures, and the results of the acceptance tests., Comment: 24 pages, 19 figures, 2 tables, submitted to JINST
Published: 2024

32. Towards Interactively Improving ML Data Preparation Code via 'Shadow Pipelines'

Author: Grafberger, Stefan, Groth, Paul, and Schelter, Sebastian
Subjects: Computer Science - Databases, Computer Science - Machine Learning, Computer Science - Software Engineering, H.2, H.2.8, H.4, D.2.6, I.2
Abstract: Data scientists develop ML pipelines in an iterative manner: they repeatedly screen a pipeline for potential issues, debug it, and then revise and improve its code according to their findings. However, this manual process is tedious and error-prone. Therefore, we propose to support data scientists during this development cycle with automatically derived interactive suggestions for pipeline improvements. We discuss our vision to generate these suggestions with so-called shadow pipelines, hidden variants of the original pipeline that modify it to auto-detect potential issues, try out modifications for improvements, and suggest and explain these modifications to the user. We envision to apply incremental view maintenance-based optimisations to ensure low-latency computation and maintenance of the shadow pipelines. We conduct preliminary experiments to showcase the feasibility of our envisioned approach and the potential benefits of our proposed optimisations.
Published: 2024
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33. Evaluating Class Membership Relations in Knowledge Graphs using Large Language Models

Author: Allen, Bradley P. and Groth, Paul T.
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, I.2.7, I.2.4
Abstract: A backbone of knowledge graphs are their class membership relations, which assign entities to a given class. As part of the knowledge engineering process, we propose a new method for evaluating the quality of these relations by processing descriptions of a given entity and class using a zero-shot chain-of-thought classifier that uses a natural language intensional definition of a class. We evaluate the method using two publicly available knowledge graphs, Wikidata and CaLiGraph, and 7 large language models. Using the gpt-4-0125-preview large language model, the method's classification performance achieves a macro-averaged F1-score of 0.830 on data from Wikidata and 0.893 on data from CaLiGraph. Moreover, a manual analysis of the classification errors shows that 40.9% of errors were due to the knowledge graphs, with 16.0% due to missing relations and 24.9% due to incorrectly asserted relations. These results show how large language models can assist knowledge engineers in the process of knowledge graph refinement. The code and data are available on Github., Comment: 11 pages, 1 figure, 2 tables, accepted at the European Semantic Web Conference Special Track on Large Language Models for Knowledge Engineering, Hersonissos, Crete, GR, May 2024, for associated code and data, see https://github.com/bradleypallen/evaluating-kg-class-memberships-using-llms
Published: 2024

34. Fast single atom imaging for optical lattice arrays

Author: Su, Lin, Douglas, Alexander, Szurek, Michal, Hebert, Anne H., Krahn, Aaron, Groth, Robin, Phelps, Gregory A., Markovic, Ognjen, and Greiner, Markus
Subjects: Condensed Matter - Quantum Gases, Physics - Atomic Physics, Quantum Physics
Abstract: High-resolution fluorescence imaging of ultracold atoms and molecules is paramount to performing quantum simulation and computation in optical lattices and tweezers. Imaging durations in these experiments typically range from a millisecond to a second, significantly limiting the cycle time. In this work, we present fast, 2.4 microseconds single-atom imaging in lattices, with 99.4% fidelity - pushing the readout duration of neutral atom quantum platforms to be close to that of superconducting qubit platforms. Additionally, we thoroughly study the performance of accordion lattices. We also demonstrate number-resolved imaging without parity projection, which will facilitate experiments such as the exploration of high-filling phases in the extended Bose-Hubbard models, multi-band or SU(N) Fermi-Hubbard models, and quantum link models.
Published: 2024

35. Kermut: Composite kernel regression for protein variant effects

Author: Groth, Peter Mørch, Kerrn, Mads Herbert, Olsen, Lars, Salomon, Jesper, and Boomsma, Wouter
Subjects: Quantitative Biology - Biomolecules, Computer Science - Machine Learning
Abstract: Reliable prediction of protein variant effects is crucial for both protein optimization and for advancing biological understanding. For practical use in protein engineering, it is important that we can also provide reliable uncertainty estimates for our predictions, and while prediction accuracy has seen much progress in recent years, uncertainty metrics are rarely reported. We here provide a Gaussian process regression model, Kermut, with a novel composite kernel for modeling mutation similarity, which obtains state-of-the-art performance for supervised protein variant effect prediction while also offering estimates of uncertainty through its posterior. An analysis of the quality of the uncertainty estimates demonstrates that our model provides meaningful levels of overall calibration, but that instance-specific uncertainty calibration remains more challenging., Comment: Accepted to NeurIPS 2024 as Spotlight
Published: 2024

36. SHROOM-INDElab at SemEval-2024 Task 6: Zero- and Few-Shot LLM-Based Classification for Hallucination Detection

Author: Allen, Bradley P., Polat, Fina, and Groth, Paul
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: We describe the University of Amsterdam Intelligent Data Engineering Lab team's entry for the SemEval-2024 Task 6 competition. The SHROOM-INDElab system builds on previous work on using prompt programming and in-context learning with large language models (LLMs) to build classifiers for hallucination detection, and extends that work through the incorporation of context-specific definition of task, role, and target concept, and automated generation of examples for use in a few-shot prompting approach. The resulting system achieved fourth-best and sixth-best performance in the model-agnostic track and model-aware tracks for Task 6, respectively, and evaluation using the validation sets showed that the system's classification decisions were consistent with those of the crowd-sourced human labellers. We further found that a zero-shot approach provided better accuracy than a few-shot approach using automatically generated examples. Code for the system described in this paper is available on Github., Comment: 6 pages, 6 figures, 4 tables, camera-ready copy, accepted to the 18th International Workshop on Semantic Evaluation (SemEval-2024), for associated code and data see https://github.com/bradleypallen/shroom
Published: 2024

37. AE SemRL: Learning Semantic Association Rules with Autoencoders

Author: Karabulut, Erkan, Degeler, Victoria, and Groth, Paul
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Association Rule Mining (ARM) is the task of learning associations among data features in the form of logical rules. Mining association rules from high-dimensional numerical data, for example, time series data from a large number of sensors in a smart environment, is a computationally intensive task. In this study, we propose an Autoencoder-based approach to learn and extract association rules from time series data (AE SemRL). Moreover, we argue that in the presence of semantic information related to time series data sources, semantics can facilitate learning generalizable and explainable association rules. Despite enriching time series data with additional semantic features, AE SemRL makes learning association rules from high-dimensional data feasible. Our experiments show that semantic association rules can be extracted from a latent representation created by an Autoencoder and this method has in the order of hundreds of times faster execution time than state-of-the-art ARM approaches in many scenarios. We believe that this study advances a new way of extracting associations from representations and has the potential to inspire more research in this field.
Published: 2024

38. Observation of Seven Astrophysical Tau Neutrino Candidates with IceCube

Author: IceCube Collaboration, Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Bourbeau, E., Braun, J., Brinson, B., Brostean-Kaiser, J., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Classen, L., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Feigl, N., Fiedlschuster, S., Fienberg, A. T., Fischer, L., Fox, D., Franckowiak, A., Fritz, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Goehlke, N., Gonzalez, J. G., Goswami, S., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Helbing, K., Hellrung, J., Henningsen, F., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Q. R., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oehler, M., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Pankova, D. V., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Renzi, G., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwefer, G., Sclafani, S., Seckel, D., Seikh, M., Seunarine, S., Shah, R., Sharma, A., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Ty, B., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Willey, N., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, F., Yu, S., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Experiment
Abstract: We report on a measurement of astrophysical tau neutrinos with 9.7 years of IceCube data. Using convolutional neural networks trained on images derived from simulated events, seven candidate $\nu_\tau$ events were found with visible energies ranging from roughly 20 TeV to 1 PeV and a median expected parent $\nu_\tau$ energy of about 200 TeV. Considering backgrounds from astrophysical and atmospheric neutrinos, and muons from $\pi^\pm/K^\pm$ decays in atmospheric air showers, we obtain a total estimated background of about 0.5 events, dominated by non-$\nu_\tau$ astrophysical neutrinos. Thus, we rule out the absence of astrophysical $\nu_\tau$ at the $5\sigma$ level. The measured astrophysical $\nu_\tau$ flux is consistent with expectations based on previously published IceCube astrophysical neutrino flux measurements and neutrino oscillations., Comment: Accepted for publication in Physical Review Letters. This version includes full author list metadata
Published: 2024
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39. Improved modeling of in-ice particle showers for IceCube event reconstruction

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Data Analysis, Statistics and Probability
Abstract: The IceCube Neutrino Observatory relies on an array of photomultiplier tubes to detect Cherenkov light produced by charged particles in the South Pole ice. IceCube data analyses depend on an in-depth characterization of the glacial ice, and on novel approaches in event reconstruction that utilize fast approximations of photoelectron yields. Here, a more accurate model is derived for event reconstruction that better captures our current knowledge of ice optical properties. When evaluated on a Monte Carlo simulation set, the median angular resolution for in-ice particle showers improves by over a factor of three compared to a reconstruction based on a simplified model of the ice. The most substantial improvement is obtained when including effects of birefringence due to the polycrystalline structure of the ice. When evaluated on data classified as particle showers in the high-energy starting events sample, a significantly improved description of the events is observed., Comment: 28 pages, 18 figures, 1 table, submitted to JINST, updated to account for comments received
Published: 2024
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40. Characterization of the Astrophysical Diffuse Neutrino Flux using Starting Track Events in IceCube

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: A measurement of the diffuse astrophysical neutrino spectrum is presented using IceCube data collected from 2011-2022 (10.3 years). We developed novel detection techniques to search for events with a contained vertex and exiting track induced by muon neutrinos undergoing a charged-current interaction. Searching for these starting track events allows us to not only more effectively reject atmospheric muons but also atmospheric neutrino backgrounds in the southern sky, opening a new window to the sub-100 TeV astrophysical neutrino sky. The event selection is constructed using a dynamic starting track veto and machine learning algorithms. We use this data to measure the astrophysical diffuse flux as a single power law flux (SPL) with a best-fit spectral index of $\gamma = 2.58 ^{+0.10}_{-0.09}$ and per-flavor normalization of $\phi^{\mathrm{Astro}}_{\mathrm{per-flavor}} = 1.68 ^{+0.19}_{-0.22} \times 10^{-18} \times \mathrm{GeV}^{-1} \mathrm{cm}^{-2} \mathrm{s}^{-1} \mathrm{sr}^{-1}$ (at 100 TeV). The sensitive energy range for this dataset is 3 - 550 TeV under the SPL assumption. This data was also used to measure the flux under a broken power law, however we did not find any evidence of a low energy cutoff., Comment: 27 pages, 28 figures
Published: 2024
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41. Offline Actor-Critic Reinforcement Learning Scales to Large Models

Author: Springenberg, Jost Tobias, Abdolmaleki, Abbas, Zhang, Jingwei, Groth, Oliver, Bloesch, Michael, Lampe, Thomas, Brakel, Philemon, Bechtle, Sarah, Kapturowski, Steven, Hafner, Roland, Heess, Nicolas, and Riedmiller, Martin
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Robotics
Abstract: We show that offline actor-critic reinforcement learning can scale to large models - such as transformers - and follows similar scaling laws as supervised learning. We find that offline actor-critic algorithms can outperform strong, supervised, behavioral cloning baselines for multi-task training on a large dataset containing both sub-optimal and expert behavior on 132 continuous control tasks. We introduce a Perceiver-based actor-critic model and elucidate the key model features needed to make offline RL work with self- and cross-attention modules. Overall, we find that: i) simple offline actor critic algorithms are a natural choice for gradually moving away from the currently predominant paradigm of behavioral cloning, and ii) via offline RL it is possible to learn multi-task policies that master many domains simultaneously, including real robotics tasks, from sub-optimal demonstrations or self-generated data.
Published: 2024

42. From Data Creator to Data Reuser: Distance Matters

Author: Borgman, Christine L. and Groth, Paul T.
Subjects: Computer Science - Human-Computer Interaction, Computer Science - Computers and Society, Computer Science - Digital Libraries, Computer Science - Information Retrieval
Abstract: Sharing research data is necessary, but not sufficient, for data reuse. Open science policies focus more heavily on data sharing than on reuse, yet both are complex, labor-intensive, expensive, and require infrastructure investments by multiple stakeholders. The value of data reuse lies in relationships between creators and reusers. By addressing knowledge exchange, rather than mere transactions between stakeholders, investments in data management and knowledge infrastructures can be made more wisely. Drawing upon empirical studies of data sharing and reuse, we develop the theoretical construct of distance between data creator and data reuser, identifying six distance dimensions that influence the ability to transfer knowledge effectively: domain, methods, collaboration, curation, purposes, and time and temporality. We address the social and socio-technical aspects of these dimensions, exploring ways in which they may decrease -- or increase -- distances between creators and reusers. Our theoretical framing of the distance between data creators and prospective reusers leads to recommendations to four categories of stakeholders on how to make data sharing and reuse more effective: data creators, data reusers, data archivists, and funding agencies. 'It takes a village' to share research data -- and a village to reuse data. Our aim is to provoke new research questions, new research, and new investments in effective and efficient circulation of research data; and to identify criteria for investments at each stage of data and research life cycles., Comment: 74 pages, double-spaced, consisting of Table of Contents, Abstract, 45 page narrative, 1 box, 1 figure, 1 table, 27 pages references. Original work
Published: 2024

43. Theory-Based Evaluation of Lesson Study Professional Development: Challenges, Opportunities, and Lessons Learned

Author: D. Jake Follmer, Randall Groth, Jennifer Bergner, and Starlin Weaver
Abstract: "Lesson study" has garnered considerable attention from educational researchers and practitioners as a promising method for improving instruction. At its core, lesson study reflects a collaborative inquiry process, grounded in cycles of planning, enacting, and reflecting, that promotes teacher learning through active engagement in lesson refinement. In this article, we leverage lesson study as an exemplar case to foreground an examination and application of theory-based evaluation. We overview a novel evaluation framework contextualized to this multidimensional instructional program and draw out the contributions of theory-based evaluation to the study of program effects. To ground the description of this framework, we summarize representative findings from our ongoing evaluation of a lesson study-based instructional program and discuss processes for selecting, using, and managing evidence sources as well as determining causal strands supporting program outcomes. We conclude by discussing lessons learned and implications for theory-based evaluation of complex programs.
Published: 2024
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44. Nachwuchsförderung in der AIO – die AIO-Studienakademie: Junge Nachwuchsforscher berichten über ihre Teilnahme an einem 6-tägigen Workshop zur Entwicklung ihrer Studienideen

Author: Heinzen, Sophie, Kemper, Marcel, Yaghobramzi, Sarvenaz, Klingberg, Jonas, Pixberg, Constantin, Reitnauer, Lea, and Groth, Annika
Published: 2024
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45. Medikamenteninduzierte Todesfälle bei Niereninsuffizienz

Author: Groth, Olwen, Roider, Gabriele, and Graw, Matthias
Published: 2024
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46. Citizen Science for IceCube: Name that Neutrino

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Warrick, E. H. S., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Name that Neutrino is a citizen science project where volunteers aid in classification of events for the IceCube Neutrino Observatory, an immense particle detector at the geographic South Pole. From March 2023 to September 2023, volunteers did classifications of videos produced from simulated data of both neutrino signal and background interactions. Name that Neutrino obtained more than 128,000 classifications by over 1,800 registered volunteers that were compared to results obtained by a deep neural network machine-learning algorithm. Possible improvements for both Name that Neutrino and the deep neural network are discussed.
Published: 2024

47. Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots

Author: Lampe, Thomas, Abdolmaleki, Abbas, Bechtle, Sarah, Huang, Sandy H., Springenberg, Jost Tobias, Bloesch, Michael, Groth, Oliver, Hafner, Roland, Hertweck, Tim, Neunert, Michael, Wulfmeier, Markus, Zhang, Jingwei, Nori, Francesco, Heess, Nicolas, and Riedmiller, Martin
Subjects: Computer Science - Robotics
Abstract: Reinforcement learning solely from an agent's self-generated data is often believed to be infeasible for learning on real robots, due to the amount of data needed. However, if done right, agents learning from real data can be surprisingly efficient through re-using previously collected sub-optimal data. In this paper we demonstrate how the increased understanding of off-policy learning methods and their embedding in an iterative online/offline scheme (``collect and infer'') can drastically improve data-efficiency by using all the collected experience, which empowers learning from real robot experience only. Moreover, the resulting policy improves significantly over the state of the art on a recently proposed real robot manipulation benchmark. Our approach learns end-to-end, directly from pixels, and does not rely on additional human domain knowledge such as a simulator or demonstrations.
Published: 2023

48. Search for 10--1000 GeV neutrinos from Gamma Ray Bursts with IceCube

Author: IceCube Collaboration, Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Gonzalez, J. G., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Y., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seunarine, S., Shah, R., Shefali, S., Shimizu, N., Silva, C., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, Y., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present the results of a search for 10--1,000 GeV neutrinos from 2,268 gamma-ray bursts over 8 years of IceCube-DeepCore data. This work probes burst physics below the photosphere where electromagnetic radiation cannot escape. Neutrinos of tens of GeVs are predicted in sub-photospheric collision of free streaming neutrons with bulk-jet protons. In a first analysis, we searched for the most significant neutrino-GRB coincidence using six overlapping time windows centered on the prompt phase of each GRB. In a second analysis, we conducted a search for a group of GRBs, each individually too weak to be detectable, but potentially significant when combined. No evidence of neutrino emission is found for either analysis. The most significant neutrino coincidence is for Fermi-GBM GRB bn 140807500, with a p-value of 0.097 corrected for all trials. The binomial test used to search for a group of GRBs had a p-value of 0.65 after all trial corrections. The binomial test found a group consisting only of GRB bn 140807500 and no additional GRBs. The neutrino limits of this work complement those obtained by IceCube at TeV to PeV energies. We compare our findings for the large set of GRBs as well as GRB 221009A to the sub-photospheric neutron-proton collision model and find that GRB 221009A provides the most constraining limit on baryon loading. For a jet Lorentz factor of 300 (800), the baryon loading on GRB 221009A is lower than 3.85 (2.13) at a 90% confidence level.
Published: 2023
Full Text: View/download PDF

49. All-Sky Search for Transient Astrophysical Neutrino Emission with 10 Years of IceCube Cascade Events

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Gonzalez, J. G., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Y., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seunarine, S., Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, Y., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Experiment
Abstract: We present the results of a time-dependent search for neutrino flares in data collected by IceCube between May 2011 and 2021. This data set contains cascade-like events originating from charged-current electron neutrino and tau neutrino interactions and all-flavor neutral-current interactions. IceCube's previous all-sky searches for neutrino flares used data sets consisting of track-like events originating from charged-current muon neutrino interactions. The cascade data sets are statistically independent of the track data sets and provide a new opportunity to observe the transient all-sky landscape. This search uses the spatial, temporal, and energy information of the cascade-like events to conduct searches for the most statistically significant neutrino flares in the northern and southern skies. No statistically significant time-dependent neutrino emission was observed. For the most statistically significant location in the northern sky, $p_\mathrm{global} =$ 0.71, and in the southern sky, $p_\mathrm{global} =$ 0.51. These results are compatible with the background hypothesis. Assuming an E$^{-2.53}$ spectrum from the diffuse astrophysical neutrino flux as measured with cascades, these results are used to calculate upper limits at the 90\% confidence level on neutrino flares of varying duration and constrain the contribution of these flares to the diffuse astrophysical neutrino flux. These constraints are independent of a specified class of astrophysical objects and show that multiple unresolved transient sources may contribute to the diffuse astrophysical neutrino flux., Comment: Submitted to The Astrophysical Journal
Published: 2023
Full Text: View/download PDF

50. AdaTyper: Adaptive Semantic Column Type Detection

Author: Hulsebos, Madelon, Groth, Paul, and Demiralp, Çağatay
Subjects: Computer Science - Databases, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract: Understanding the semantics of relational tables is instrumental for automation in data exploration and preparation systems. A key source for understanding a table is the semantics of its columns. With the rise of deep learning, learned table representations are now available, which can be applied for semantic type detection and achieve good performance on benchmarks. Nevertheless, we observe a gap between this performance and its applicability in practice. In this paper, we propose AdaTyper to address one of the most critical deployment challenges: adaptation. AdaTyper uses weak-supervision to adapt a hybrid type predictor towards new semantic types and shifted data distributions at inference time, using minimal human feedback. The hybrid type predictor of AdaTyper combines rule-based methods and a light machine learning model for semantic column type detection. We evaluate the adaptation performance of AdaTyper on real-world database tables hand-annotated with semantic column types through crowdsourcing and find that the f1-score improves for new and existing types. AdaTyper approaches an average precision of 0.6 after only seeing 5 examples, significantly outperforming existing adaptation methods based on human-provided regular expressions or dictionaries., Comment: Submitted to VLDB'24
Published: 2023

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