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10,980 results on '"Caruso, P."'

1. Automating grapevine LAI features estimation with UAV imagery and machine learning

Author

Akram, Muhammad Waseem, Vannucci, Marco, Buttazzo, Giorgio, Colla, Valentina, Roccella, Stefano, Vannini, Andrea, Caruso, Giovanni, Nesi, Simone, Francini, Alessandra, and Sebastiani, Luca

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Emerging Technologies, Computer Science - Machine Learning
Abstract

The leaf area index determines crop health and growth. Traditional methods for calculating it are time-consuming, destructive, costly, and limited to a scale. In this study, we automate the index estimation method using drone image data of grapevine plants and a machine learning model. Traditional feature extraction and deep learning methods are used to obtain helpful information from the data and enhance the performance of the different machine learning models employed for the leaf area index prediction. The results showed that deep learning based feature extraction is more effective than traditional methods. The new approach is a significant improvement over old methods, offering a faster, non-destructive, and cost-effective leaf area index calculation, which enhances precision agriculture practices., Comment: Accepted in 2024 IEEE INTERNATIONAL WORKSHOP ON Metrology for Agriculture and Forestry

Published
2024

2. Connecting dust and outflows in AGN: the intriguing case of NGC 6860

Author

Psaradaki, Ioanna, Mehdipour, Missagh, Rogantini, Daniele, Costantini, Elisa, Schulz, Norbert, Zeegers, Sascha, and Caruso, Eleonora

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Cosmic dust plays a crucial role in the evolution of galaxies, significantly influencing star formation and the interstellar medium. However, in active galactic nuclei (AGN), the role and origin of dust remain poorly understood. High-resolution X-ray spectroscopy is a powerful tool for probing the properties of dust in AGN. NGC 6860, an X-ray bright type-1 quasar, is an ideal target for investigating the connection between dust and winds in AGN. It exhibits reddening and X-ray absorption by both dust and winds. By modeling high-resolution X-ray spectra from XMM-Newton and Chandra observations, we determine the properties of dust and outflows in this AGN. Our analysis finds four photoionized components, outflowing with velocities of 50-300 km/s. The first two are relatively highly ionized with logxi = 3.4 and logxi = 2.9. The results of our photoionization modeling suggest that these two components are thermally unstable. The third component is ionized, with logxi = 2.3 and is located further away from the central black hole. The fourth component is less ionized, and is possibly located in the host galaxy. The application of dust models enables us to probe the abundance and location of the dust in NGC 6860. Our findings suggest that dust absorption and reddening originates from the extended narrow-line region and its host galaxy., Comment: Submitted to Astrophysical Journal (ApJ)

Published
2024

3. Did somebody say 'Gest-IT'? A pilot exploration of multimodal data management

Author

Pannitto, Ludovica, Albanesi, Lorenzo, Marion, Laura, Martines, Federica Maria, Caruso, Carmelo, Bianchini, Claudia S., Masini, Francesca, and Mauri, Caterina

Subjects
Computer Science - Computation and Language
Abstract

The paper presents a pilot exploration of the construction, management and analysis of a multimodal corpus. Through a three-layer annotation that provides orthographic, prosodic, and gestural transcriptions, the Gest-IT resource allows to investigate the variation of gesture-making patterns in conversations between sighted people and people with visual impairment. After discussing the transcription methods and technical procedures employed in our study, we propose a unified CoNLL-U corpus and indicate our future steps

Published
2024

4. Selfdual skew cyclic codes

Author

Caruso, Xavier and Drain, Fabrice

Subjects
Computer Science - Information Theory
Abstract

Given a finite extension $K/F$ of degree $r$ of a finite field $F$, we enumerate all selfdual skew cyclic codes in the Ore quotient ring $K[X;\text{Frob}]/(X^{rk}-1)$ for any positive integer $k$ coprime to the characteristic $p$ (separable case). We also provide an enumeration algorithm when $k$ is a power of $p$ (purely inseparable case), at the cost of some redundancies. Our approach is based on an explicit bijection between skew cyclic codes, on the one hand, and certain families of $F$-linear subspaces of some extensions of $K$. Finally, we report on an implementation in SageMath.

Published
2024

5. Classification and Spatiotemporal Correlation of Dominant Fluctuations in Complex Dynamical Systems

Author

Caruso, Cristina, Crippa, Martina, Cardellini, Annalisa, Cioni, Matteo, Perrone, Mattia, Piane, Massimo Delle, and Pavan, Giovanni M.

Subjects
Physics - Chemical Physics
Abstract

The behavior of many complex systems, from nanostructured materials to animal colonies, is governed by local transitions that, while involving a restricted number of interacting units, may generate collective cascade phenomena. Tracking such local events and understanding how they emerge and propagate throughout these systems represent often a challenge. Common strategies monitor specific parameters, tailored ad hoc to describe certain systems, over time. However, such approaches typically require prior knowledge of the underpinning physics and are poorly transferable to different systems. Here we present LEAP, a general, transferable, agnostic analysis approach that can reveal precious information on the physics of a variety of complex dynamical systems simply starting from the trajectory of their constitutive units. Built on a bivariate combination of two abstract descriptors, LENS and {\tau}SOAP, the LEAP analysis allows (i) detecting the emergence of local fluctuations in simulation or experimentally-acquired trajectories of any type of multicomponent system, (ii) classifying fluctuations into categories, and (iii) correlating them in space and time. We demonstrate how LEAP, just building on the abstract concepts of local fluctuations and their spatiotemporal correlation, efficiently reveals precious insights on the emergence and propagation of local and collective phenomena in a variety of complex dynamical systems ranging from the atomic- to the microscopic-scale. Given its abstract character, we expect that LEAP will offer an important tool to understand and predict the behavior of systems whose physics is unknown a priori, as well as to revisit a variety of known complex physical phenomena under a new perspective.

Published
2024

6. Slowly Scaling Per-Record Differential Privacy

Author

Finley, Brian, Caruso, Anthony M, Doty, Justin C, Machanavajjhala, Ashwin, Meyer, Mikaela R, Pujol, David, Sexton, William, and Terner, Zachary

Subjects
Computer Science - Cryptography and Security, Statistics - Methodology
Abstract

We develop formal privacy mechanisms for releasing statistics from data with many outlying values, such as income data. These mechanisms ensure that a per-record differential privacy guarantee degrades slowly in the protected records' influence on the statistics being released. Formal privacy mechanisms generally add randomness, or "noise," to published statistics. If a noisy statistic's distribution changes little with the addition or deletion of a single record in the underlying dataset, an attacker looking at this statistic will find it plausible that any particular record was present or absent, preserving the records' privacy. More influential records -- those whose addition or deletion would change the statistics' distribution more -- typically suffer greater privacy loss. The per-record differential privacy framework quantifies these record-specific privacy guarantees, but existing mechanisms let these guarantees degrade rapidly (linearly or quadratically) with influence. While this may be acceptable in cases with some moderately influential records, it results in unacceptably high privacy losses when records' influence varies widely, as is common in economic data. We develop mechanisms with privacy guarantees that instead degrade as slowly as logarithmically with influence. These mechanisms allow for the accurate, unbiased release of statistics, while providing meaningful protection for highly influential records. As an example, we consider the private release of sums of unbounded establishment data such as payroll, where our mechanisms extend meaningful privacy protection even to very large establishments. We evaluate these mechanisms empirically and demonstrate their utility.

Published
2024

7. Phonon-mediated renormalization of exciton energies and absorption spectra in polar semiconductors

Author

Schebek, Maximilian, Pavone, Pasquale, Draxl, Claudia, and Caruso, Fabio

Subjects
Condensed Matter - Materials Science
Abstract

We investigate the influence of vibrational screening on the excitonic and optical properties of solids based on first-principles electronic-structure calculations. We solve the Bethe-Salpeter equation - the state-of-the-art description of excitons - by explicitly accounting for phonon-assisted screening effects in the screened Coulomb interaction. In the examples of the polar semiconductors ZnS, MgO, and GaN, the exciton binding energies at the absorption onset are found to be renormalized by a few tens of meV. Similar effects are also found for higher-lying unbound electron-hole pairs, leading to red-shifts of the absorption peaks by up to 50 meV. Our analysis reveals that vibrational screening is dictated by long-range Fr\"ohlich coupling involving polar longitudinal optical phonons, whereas the remaining vibrational degrees of freedom are negligible. Overall, by elucidating the influence of phonon screening on the excitonic states and absorption spectra of these selected ionic semiconductors, this study contributes to advancing the ab initio methodology and the fundamental understanding of exciton-phonon coupling in solids.

Published
2024

8. Machine-learning based high-bandwidth magnetic sensing

Author

Haim, Galya, Martina, Stefano, Howell, John, Bar-Gill, Nir, and Caruso, Filippo

Subjects
Quantum Physics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Physics - Applied Physics, Physics - Computational Physics, 68T07 (Primary) 68T10, 81-08, 81-05, 81-10, 81-11, 81V10 (Secondary), I.2.6, I.5.4, J.2, I.6.3
Abstract

Recent years have seen significant growth of quantum technologies, and specifically quantum sensing, both in terms of the capabilities of advanced platforms and their applications. One of the leading platforms in this context is nitrogen-vacancy (NV) color centers in diamond, providing versatile, high-sensitivity, and high-resolution magnetic sensing. Nevertheless, current schemes for spin resonance magnetic sensing (as applied by NV quantum sensing) suffer from tradeoffs associated with sensitivity, dynamic range, and bandwidth. Here we address this issue, and implement machine learning tools to enhance NV magnetic sensing in terms of the sensitivity/bandwidth tradeoff in large dynamic range scenarios. We experimentally demonstrate this new approach, reaching an improvement in the relevant figure of merit by a factor of up to 5. Our results promote quantum machine learning protocols for sensing applications towards more feasible and efficient quantum technologies., Comment: 12 pages including supplementary, 6 figures

Published
2024

9. QUBO-based SVM for credit card fraud detection on a real QPU

Author

Canonici, Ettore and Caruso, Filippo

Subjects
Quantum Physics, 81V45 (Primary) 81P68 (Secondary), I.2.0, J.2, I.5.0
Abstract

Among all the physical platforms for the realization of a Quantum Processing Unit (QPU), neutral atom devices are emerging as one of the main players. Their scalability, long coherence times, and the absence of manufacturing errors make them a viable candidate.. Here, we use a binary classifier model whose training is reformulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem and implemented on a neutral atom QPU. In particular, we test it on a Credit Card Fraud (CCF) dataset. We propose several versions of the model, including exploiting the model in ensemble learning schemes. We show that one of our proposed versions seems to achieve higher performance and lower errors, validating our claims by comparing the most popular Machine Learning (ML) models with QUBO SVM models trained with ideal, noisy simulations and even via a real QPU. In addition, the data obtained via real QPU extend up to 24 atoms, confirming the model's noise robustness. We also show, by means of numerical simulations, how a certain amount of noise leads surprisingly to enhanced results. Our results represent a further step towards new quantum ML algorithms running on neutral atom QPUs for cybersecurity applications., Comment: 28 pages, 9 figures, 1 table

Published
2024

10. A response-adaptive multi-arm design for continuous endpoints based on a weighted information measure

Author

Caruso, Gianmarco and Mozgunov, Pavel

Subjects
Statistics - Methodology, Computer Science - Information Theory, Statistics - Applications
Abstract

Multi-arm trials are gaining interest in practice given the statistical and logistical advantages that they can offer. The standard approach is to use a fixed (throughout the trial) allocation ratio, but there is a call for making it adaptive and skewing the allocation of patients towards better performing arms. However, among other challenges, it is well-known that these approaches might suffer from lower statistical power. We present a response-adaptive design for continuous endpoints which explicitly allows to control the trade-off between the number of patients allocated to the 'optimal' arm and the statistical power. Such a balance is achieved through the calibration of a tuning parameter, and we explore various strategies to effectively select it. The proposed criterion is based on a context-dependent information measure which gives a greater weight to those treatment arms which have characteristics close to a pre-specified clinical target. We also introduce a simulation-based hypothesis testing procedure which focuses on selecting the target arm, discussing strategies to effectively control the type-I error rate. The potential advantage of the proposed criterion over currently used alternatives is evaluated in simulations, and its practical implementation is illustrated in the context of early Phase IIa proof-of-concept oncology clinical trials.

Published
2024

11. Dynamic Label Injection for Imbalanced Industrial Defect Segmentation

Author

Caruso, Emanuele, Pelosin, Francesco, Simoni, Alessandro, and Boschetti, Marco

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In this work, we propose a simple yet effective method to tackle the problem of imbalanced multi-class semantic segmentation in deep learning systems. One of the key properties for a good training set is the balancing among the classes. When the input distribution is heavily imbalanced in the number of instances, the learning process could be hindered or difficult to carry on. To this end, we propose a Dynamic Label Injection (DLI) algorithm to impose a uniform distribution in the input batch. Our algorithm computes the current batch defect distribution and re-balances it by transferring defects using a combination of Poisson-based seamless image cloning and cut-paste techniques. A thorough experimental section on the Magnetic Tiles dataset shows better results of DLI compared to other balancing loss approaches also in the challenging weakly-supervised setup. The code is available at https://github.com/covisionlab/dynamic-label-injection.git, Comment: ECCV 2024 VISION Workshop

Published
2024

12. Large-scale cosmic ray anisotropies with 19 years of data from the Pierre Auger Observatory

Author

The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Ambrosone, A., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Bellido, J. A., Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Freitas, M., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Ghia, P. L., Giaccari, U., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kubatova, M., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lundquist, J. P., Payeras, A. Machado, Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Sampathkumar, P., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Weitz, M., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Results are presented for the measurement of large-scale anisotropies in the arrival directions of ultra-high-energy cosmic rays detected at the Pierre Auger Observatory during 19 years of operation, prior to AugerPrime, the upgrade of the Observatory. The 3D dipole amplitude and direction are reconstructed above $4\,$EeV in four energy bins. Besides the established dipolar anisotropy in right ascension above $8\,$EeV, the Fourier amplitude of the $8$ to $16\,$EeV energy bin is now also above the $5\sigma$ discovery level. No time variation of the dipole moment above $8\,$EeV is found, setting an upper limit to the rate of change of such variations of $0.3\%$ per year at the $95\%$ confidence level. Additionally, the results for the angular power spectrum are shown, demonstrating no other statistically significant multipoles. The results for the equatorial dipole component down to $0.03\,$EeV are presented, using for the first time a data set obtained with a trigger that has been optimized for lower energies. Finally, model predictions are discussed and compared with observations, based on two source emission scenarios obtained in the combined fit of spectrum and composition above $0.6\,$EeV., Comment: Minor modifications, accepted for publication in Astrophysical Journal

Published
2024

13. A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications

Author

Guarrasi, Valerio, Aksu, Fatih, Caruso, Camillo Maria, Di Feola, Francesco, Rofena, Aurora, Ruffini, Filippo, and Soda, Paolo

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Deep learning has revolutionized biomedical research by providing sophisticated methods to handle complex, high-dimensional data. Multimodal deep learning (MDL) further enhances this capability by integrating diverse data types such as imaging, textual data, and genetic information, leading to more robust and accurate predictive models. In MDL, differently from early and late fusion methods, intermediate fusion stands out for its ability to effectively combine modality-specific features during the learning process. This systematic review aims to comprehensively analyze and formalize current intermediate fusion methods in biomedical applications. We investigate the techniques employed, the challenges faced, and potential future directions for advancing intermediate fusion methods. Additionally, we introduce a structured notation to enhance the understanding and application of these methods beyond the biomedical domain. Our findings are intended to support researchers, healthcare professionals, and the broader deep learning community in developing more sophisticated and insightful multimodal models. Through this review, we aim to provide a foundational framework for future research and practical applications in the dynamic field of MDL.

Published
2024

14. Coherent Phonons and Quasiparticle Renormalization in Semimetals from First Principles

Author

Emeis, C., Jauernik, S., Dahiya, S., Pan, Y., Jensen, C. E., Hein, P., Bauer, M., and Caruso, F.

Subjects
Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract

Coherent phonons, light-induced coherent lattice vibrations in solids, provide a powerful route to engineer structural and electronic degrees of freedom using light. In this manuscript, we formulate an ab initio theory of the displacive excitation of coherent phonons (DECP), the primary mechanism for light-induced structural control in semimetals. Our study - based on the ab initio simulations of the ultrafast electron and coherent-phonon dynamics in presence of electron-phonon interactions - establishes a predictive computational framework for describing the emergence of light-induced structural changes and the ensuing transient band-structure renormalization arising from the DECP mechanism. We validate this framework via a combined theoretical and experimental investigation of coherent phonons in the elemental semimetal antimony. Via a Fourier analysis of time- and angle-resolved photoemission spectroscopy (tr-ARPES) measurements, we retrieve information about transient spectral features and quasiparticle renormalization arising from the coherent A1g phonon as a function of momentum, energy, time, and fluence. The qualitative and quantitative agreement between experiment and theory corroborates the first-principles approach formulated in this study. Besides advancing the fundamental understanding of electron-phonon interactions mediated by coherent phonons, this study opens new opportunities for predictively engineering structural and electronic degrees of freedom in semimetals via the DECP mechanism.

Published
2024

15. Not Another Imputation Method: A Transformer-based Model for Missing Values in Tabular Datasets

Author

Caruso, Camillo Maria, Soda, Paolo, and Guarrasi, Valerio

Subjects
Computer Science - Machine Learning
Abstract

Handling missing values in tabular datasets presents a significant challenge in training and testing artificial intelligence models, an issue usually addressed using imputation techniques. Here we introduce "Not Another Imputation Method" (NAIM), a novel transformer-based model specifically designed to address this issue without the need for traditional imputation techniques. NAIM employs feature-specific embeddings and a masked self-attention mechanism that effectively learns from available data, thus avoiding the necessity to impute missing values. Additionally, a novel regularization technique is introduced to enhance the model's generalization capability from incomplete data. We extensively evaluated NAIM on 5 publicly available tabular datasets, demonstrating its superior performance over 6 state-of-the-art machine learning models and 4 deep learning models, each paired with 3 different imputation techniques when necessary. The results highlight the efficacy of NAIM in improving predictive performance and resilience in the presence of missing data. To facilitate further research and practical application in handling missing data without traditional imputation methods, we made the code for NAIM available at https://github.com/cosbidev/NAIM., Comment: 12 pages, 8 figures

Published
2024

16. The flux of ultra-high-energy cosmic rays along the supergalactic plane measured at the Pierre Auger Observatory

Author

The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Bellido, J. A., Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Ghia, P. L., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reininghaus, M., Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., de Carvalho, W. Rodrigues, Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Savina, P., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Smau, R., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Ultra-high-energy cosmic rays are known to be mainly of extragalactic origin, and their propagation is limited by energy losses, so their arrival directions are expected to correlate with the large-scale structure of the local Universe. In this work, we investigate the possible presence of intermediate-scale excesses in the flux of the most energetic cosmic rays from the direction of the supergalactic plane region using events with energies above 20 EeV recorded with the surface detector array of the Pierre Auger Observatory up to 31 December 2022, with a total exposure of 135,000 km^2 sr yr. The strongest indication for an excess that we find, with a post-trial significance of 3.1{\sigma}, is in the Centaurus region, as in our previous reports, and it extends down to lower energies than previously studied. We do not find any strong hints of excesses from any other region of the supergalactic plane at the same angular scale. In particular, our results do not confirm the reports by the Telescope Array collaboration of excesses from two regions in the Northern Hemisphere at the edge of the field of view of the Pierre Auger Observatory. With a comparable exposure, our results in those regions are in good agreement with the expectations from an isotropic distribution., Comment: submitted to ApJ

Published
2024

17. Is time one-dimensional?

Author

Caruso, Francisco

Subjects
Physics - History and Philosophy of Physics
Abstract

In the History of Ideas, a succession of philosophical and scientific achievements, concerning the concept of space and its dimensionality, were essential to contribute, after a long period, to the theoretical possibility of thinking physical time with more than one dimension. Meanwhile, such a progress brought with it the expectation that one can either understand the role of dimensionality in the World or disclose how certain physical phenomena depend on it. Some of these issues are sketched throughout the text, as well as those remarkable moments in the History of Science where important contributions were made in order to give a satisfactory answer to the following inescapable question: -- How many dimensions does time have?, Comment: 22 pp. arXiv admin note: substantial text overlap with arXiv:2101.12167

Published
2024

18. What's in the Sound? Common and Language-Specific Patterns in Brain Activation and Functional Connectivity for Phonological Awareness in Spanish-English Bilinguals

Author

Nia Nickerson, Xin Sun, Valeria Caruso, Kehui Zhang, Chi-Lin Yu, Rachel Eggleston, Natasha Chaku, Xiaosu Hu, Teresa Satterfield, and Ioulia Kovelman

Abstract

Phonological awareness is the stepping-stone to learning to read as it helps children map language sounds onto letters. Theories of bilingualism posit that phonological awareness is a language-common literacy skill. However, bilingual learners are also thought to build language-specific representations. To illuminate common and specific dual-language processes, we asked bilingual Spanish-English heritage language speakers (N = 60, M[subscript age] = 8.2) to complete a phonological sound-matching task in Spanish and English during functional Near Infrared Neuroimaging (fNIRS). The left perisylvian activation was common across bilinguals' two languages, including similar active regions and functional connections. The findings further revealed language-specific modulation of the system with more robust engagement of the temporal networks for Spanish and frontal networks for English. We interpret the results in the context of analytically demanding reading experiences in English and more informal home-based Spanish language experiences typical of heritage language speakers.

Published
2024
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19. Lexical Morphology as a Source of Risk and Resilience for Learning to Read with Dyslexia: An fNIRS Investigation

Author

Rachel L. Eggleston, Rebecca A. Marks, Xin Sun, Chi-Lin Yu, Kehui Zhang, Nia Nickerson, Xiaosu Hu, Valeria Caruso, and Ioulia Kovelman

Abstract

Purpose: We examined the neurocognitive bases of lexical morphology in children of varied reading abilities to understand the role of meaning-based skills in learning to read with dyslexia. Method: Children completed auditory morphological and phonological awareness tasks during functional near-infrared spectroscopy neuroimaging. We first examined the relation between lexical morphology and phonological processes in typically developing readers (Study 1, N = 66, M[subscript age] = 8.39), followed by a more focal inquiry into lexical morphology processes in dyslexia (Study 2, N = 50, M[subscript age] = 8.62). Results: Typical readers exhibited stronger engagement of language neurocircuitry during the morphology task relative to the phonology task, suggesting that morphological analyses involve synthesizing multiple components of sublexical processing. This effect was stronger for more analytically complex derivational affixes ("like + ly") than more semantically transparent free base morphemes ("snow + man"). In contrast, children with dyslexia exhibited stronger activation during the free base condition relative to derivational affix condition. Taken together, the findings suggest that although children with dyslexia may struggle with derivational morphology, they may also use free base morphemes' semantic information to boost word recognition. Conclusion: This study informs literacy theories by identifying an interaction between reading ability, word structure, and how the developing brain learns to recognize words in speech and print.

Published
2024
Full Text
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20. Ocean weather, biological rates, and unexplained global ecological patterns.

Author

Li Shing Hiung, Darren, Schuster, Jasmin, Duncan, Murray, Payne, Nicholas, Helmuth, Brian, Chu, Jackson, Baum, Julia, Brambilla, Viviana, Bruno, John, Davies, Sarah, Dornelas, Maria, Gagnon, Patrick, Guy-Haim, Tamar, Jackson, Jennifer, Leichter, James, Madin, Joshua, Monteith, Zachary, Queirós, Ana, Schneider, Eric, Starko, Samuel, Talwar, Brendan, Wyatt, Alex, Aichelman, Hannah, Bensoussan, Nathaniel, Caruso, Carlo, Castillo, Karl, Choi, Francis, Dong, Yun-Wei, Garrabou, Joaquim, Guillemain, Dorian, Higgs, Nicholas, Jiang, Yuwu, Kersting, Diego, Kushner, David, Longo, Guilherme, Neufeld, Christopher, Peirache, Marion, Smyth, Tim, Sprague, Joshua, Urvoy, Gaëlle, Zuberer, Frederic, and Bates, Amanda

Subjects
biological rate, climate variability hypothesis, high frequency, in situ, ocean temperature
Abstract

As on land, oceans exhibit high temporal and spatial temperature variation. This ocean weather contributes to the physiological and ecological processes that ultimately determine the patterns of species distribution and abundance, yet is often unrecognized, especially in tropical oceans. Here, we tested the paradigm of temperature stability in shallow waters (

Published
2024

21. Search for photons above 10$^{18}$ eV by simultaneously measuring the atmospheric depth and the muon content of air showers at the Pierre Auger Observatory

Author

The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., do, J. A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Ghia, P. L., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reininghaus, M., Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., de Carvalho, W. Rodrigues, Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Savina, P., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Smau, R., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Pierre Auger Observatory is the most sensitive instrument to detect photons with energies above $10^{17}$ eV. It measures extensive air showers generated by ultra high energy cosmic rays using a hybrid technique that exploits the combination of a fluorescence detector with a ground array of particle detectors. The signatures of a photon-induced air shower are a larger atmospheric depth of the shower maximum ($X_{max}$) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced cascades. In this work, a new analysis technique in the energy interval between 1 and 30 EeV (1 EeV = $10^{18}$ eV) has been developed by combining the fluorescence detector-based measurement of $X_{max}$ with the specific features of the surface detector signal through a parameter related to the air shower muon content, derived from the universality of the air shower development. No evidence of a statistically significant signal due to photon primaries was found using data collected in about 12 years of operation. Thus, upper bounds to the integral photon flux have been set using a detailed calculation of the detector exposure, in combination with a data-driven background estimation. The derived 95% confidence level upper limits are 0.0403, 0.01113, 0.0035, 0.0023, and 0.0021 km$^{-2}$ sr$^{-1}$ yr$^{-1}$ above 1, 2, 3, 5, and 10 EeV, respectively, leading to the most stringent upper limits on the photon flux in the EeV range. Compared with past results, the upper limits were improved by about 40% for the lowest energy threshold and by a factor 3 above 3 EeV, where no candidates were found and the expected background is negligible. The presented limits can be used to probe the assumptions on chemical composition of ultra-high energy cosmic rays and allow for the constraint of the mass and lifetime phase space of super-heavy dark matter particles., Comment: 19 pages, 22 figures

Published
2024

22. Measurement of the Depth of Maximum of Air-Shower Profiles with energies between $\mathbf{10^{18.5}}$ and $\mathbf{10^{20}}$ eV using the Surface Detector of the Pierre Auger Observatory and Deep Learning

Author

The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., do, J. A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Ghia, P. L., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reininghaus, M., Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., de Carvalho, W. Rodrigues, Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Savina, P., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Smau, R., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV (1 EeV=$10^{18}$ eV) using the distributions of the depth of shower maximum $X_\mathrm{max}$. The analysis relies on ${\sim}50,000$ events recorded by the Surface Detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the data set offers a 10-fold increase in statistics with respect to fluorescence measurements at the Observatory. After cross-calibration using the Fluorescence Detector, this enables the first measurement of the evolution of the mean and the standard deviation of the $X_\mathrm{max}$ distributions up to 100 EeV. Our findings are threefold: (1.) The evolution of the mean logarithmic mass towards a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (2.) The evolution of the fluctuations of $X_\mathrm{max}$ towards a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in $X_\mathrm{max}$ at the highest energies. (3.) We find indications for a characteristic structure beyond a constant change in the mean logarithmic mass, featuring three breaks that are observed in proximity to the ankle, instep, and suppression features in the energy spectrum., Comment: submitted to Phys. Rev. D, 28 pages, 18 figures, 5 tables

Published
2024

23. Inference of the Mass Composition of Cosmic Rays with energies from $\mathbf{10^{18.5}}$ to $\mathbf{10^{20}}$ eV using the Pierre Auger Observatory and Deep Learning

Author

The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., do, J. A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Ghia, P. L., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reininghaus, M., Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., de Carvalho, W. Rodrigues, Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Savina, P., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Smau, R., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

We present measurements of the atmospheric depth of the shower maximum $X_\mathrm{max}$, inferred for the first time on an event-by-event level using the Surface Detector of the Pierre Auger Observatory. Using deep learning, we were able to extend measurements of the $X_\mathrm{max}$ distributions up to energies of 100 EeV ($10^{20}$ eV), not yet revealed by current measurements, providing new insights into the mass composition of cosmic rays at extreme energies. Gaining a 10-fold increase in statistics compared to the Fluorescence Detector data, we find evidence that the rate of change of the average $X_\mathrm{max}$ with the logarithm of energy features three breaks at $6.5\pm0.6~(\mathrm{stat})\pm1~(\mathrm{sys})$ EeV, $11\pm 2~(\mathrm{stat})\pm1~(\mathrm{sys})$ EeV, and $31\pm5~(\mathrm{stat})\pm3~(\mathrm{sys})$ EeV, in the vicinity to the three prominent features (ankle, instep, suppression) of the cosmic-ray flux. The energy evolution of the mean and standard deviation of the measured $X_\mathrm{max}$ distributions indicates that the mass composition becomes increasingly heavier and purer, thus being incompatible with a large fraction of light nuclei between 50 EeV and 100 EeV., Comment: submitted to Phys. Rev. Lett., 10 pages, 3 figures, 1 table

Published
2024

24. Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector

Author

Gavrikov, A., Cerrone, V., Serafini, A., Brugnera, R., Garfagnini, A., Grassi, M., Jelmini, B., Lastrucci, L., Aiello, S., Andronico, G., Antonelli, V., Barresi, A., Basilico, D., Beretta, M., Bergnoli, A., Borghesi, M., Brigatti, A., Bruno, R., Budano, A., Caccianiga, B., Cammi, A., Caruso, R., Chiesa, D., Clementi, C., Dusini, S., Fabbri, A., Felici, G., Ferraro, F., Giammarchi, M. G., Giudice, N., Guizzetti, R. M., Guardone, N., Landini, C., Lippi, I., Loffredo, S., Loi, L., Lombardi, P., Lombardo, C., Mantovani, F., Mari, S. M., Martini, A., Miramonti, L., Montuschi, M., Nastasi, M., Orestano, D., Ortica, F., Paoloni, A., Percalli, E., Petrucci, F., Previtali, E., Ranucci, G., Re, A. C., Redchuck, M., Ricci, B., Romani, A., Saggese, P., Sava, G., Sirignano, C., Sisti, M., Stanco, L., Farilla, E. Stanescu, Strati, V., Torri, M. D. C., Triossi, A., Tuvé, C., Venettacci, C., Verde, G., and Votano, L.

Subjects
Physics - Instrumentation and Detectors, Computer Science - Machine Learning, High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract

Several neutrino detectors, KamLAND, Daya Bay, Double Chooz, RENO, and the forthcoming large-scale JUNO, rely on liquid scintillator to detect reactor antineutrino interactions. In this context, inverse beta decay represents the golden channel for antineutrino detection, providing a pair of correlated events, thus a strong experimental signature to distinguish the signal from a variety of backgrounds. However, given the low cross-section of antineutrino interactions, the development of a powerful event selection algorithm becomes imperative to achieve effective discrimination between signal and backgrounds. In this study, we introduce a machine learning (ML) model to achieve this goal: a fully connected neural network as a powerful signal-background discriminator for a large liquid scintillator detector. We demonstrate, using the JUNO detector as an example, that, despite the already high efficiency of a cut-based approach, the presented ML model can further improve the overall event selection efficiency. Moreover, it allows for the retention of signal events at the detector edges that would otherwise be rejected because of the overwhelming amount of background events in that region. We also present the first interpretable analysis of the ML approach for event selection in reactor neutrino experiments. This method provides insights into the decision-making process of the model and offers valuable information for improving and updating traditional event selection approaches., Comment: This is a post-peer-review, pre-copyedit version of an article published in Phys. Lett. B. The final published version is available online: https://www.sciencedirect.com/science/article/pii/S0370269324006993

Published
2024
Full Text
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25. Open problems and perspectives on solving Friedrichs systems by Krylov approximation

Author

Caruso, Noe Angelo and Michelangeli, Alessandro

Subjects
Mathematics - Functional Analysis, Mathematics - Analysis of PDEs, Mathematics - Numerical Analysis
Abstract

We set up, at the abstract Hilbert space setting, the general question on when an inverse linear problem induced by an operator of Friedrichs type admits solutions belonging to (the closure of) the Krylov subspace associated to such operator. Such Krylov solvability of abstract Friedrichs systems allows to predict when, for concrete differential inverse problems, truncation algorithms can or cannot reproduce the exact solutions in terms of approximants from the Krylov subspace., Comment: To appear in Springer INdAM Series "Singularities, Asymptotics, and Limiting Models" (2024)

Published
2024

26. Distillation and Stripping purification plants for JUNO liquid scintillator

Author

Landini, C., Beretta, M., Lombardi, P., Brigatti, A., Montuschi, M., Parmeggiano, S., Ranucci, G., Antonelli, V., Basilico, D., Caccianiga, B., Giammarchi, M. G., Miramonti, L., Percalli, E., Re, A. C., Saggese, P., Torri, M. D. C., Aiello, S., Andronico, G., Barresi, A., Bergnoli, A., Borghesi, M., Brugnera, R., Bruno, R., Budano, A., Cammi, A., Cerrone, V., Caruso, R., Chiesa, D., Clementi, C., Dusini, S., Fabbri, A., Felici, G., Garfagnini, A., Giudice, N., Gavrikov, A., Grassi, M., Guizzetti, R. M., Guardone, N., Jelmini, B., Lastrucci, L., Lippi, I., Loi, L., Lombardo, C., Mantovani, F., Mari, S. M., Martini, A., Nastasi, M., Orestano, D., Ortica, F., Paoloni, A., Petrucci, F., Previtali, E., Redchuck, M., Ricci, B., Romani, A., Sava, G., Serafini, A., Sirignano, C., Sisti, M., Stanco, L., Farilla, E. Stanescu, Strati, V., Triossi, A., Tuvè, C., Venettacci, C., Verde, G., and Votano, L.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

The optical and radiochemical purification of the scintillating liquid, which will fill the central detector of the JUNO experiment, plays a crucial role in achieving its scientific goals. Given its gigantic mass and dimensions and an unprecedented target value of about 3% @ 1 MeV in energy resolution, JUNO has set severe requirements on the parameters of its scintillator, such as attenuation length (Lat>20 m at 430 nm), transparency, light yield, and content of radioactive contaminants (238U,232Th<10-15 g/g). To accomplish these needs, the scintillator will be processed using several purification methods, including distillation in partial vacuum and gas stripping, which are performed in two large scale plants installed at the JUNO site. In this paper, layout, operating principles, and technical aspects which have driven the design and construction of the distil- lation and gas stripping plants are reviewed. The distillation is effective in enhancing the optical properties and removing heavy radio-impurities (238U,232Th, 40K), while the stripping process exploits pure water steam and high-purity nitrogen to extract gaseous contaminants (222Rn, 39Ar, 85Kr, O2) from the scintillator. The plant operating parameters have been tuned during the recent com- missioning phase at the JUNO site and several QA/QC measurements and tests have been performed to evaluate the performances of the plants. Some preliminary results on the efficiency of these purification processes will be shown., Comment: 11 pages, 7 figures

Published
2024

27. On the covariance of the d'Alembert equation: the cases of sound and light

Author

Caruso, Francisco and Oguri, Vitor

Subjects
Physics - Classical Physics
Abstract

The covariance of the d'Alembert equation for acoustic phenomena, described by mechanical waves in one or three spatial dimensions, under Galilean transformations, is demonstrated without the need to abandon the hypothesis that time is absolute in Classical Mechanics. This is true only if and only if the phase velocity of sound depends on the velocity of the observer. On the other hand, it is also shown that the same d'Alembert equation is covariant under Lorentz transformations if and only if the phase velocity of light does not depend on the observer., Comment: 11 pages, in Portuguese

Published
2024

28. Refractive index in the JUNO liquid scintillator

Author

Zhang, H. S., Beretta, M., Cialdi, S., Yang, C. X., Huang, J. H., Ferraro, F., Cao, G. F., Reina, G., Deng, Z. Y., Suerra, E., Altilia, S., Antonelli, V., Basilico, D., Brigatti, A., Caccianiga, B., Giammarchi, M. G., Landini, C., Lombardi, P., Miramonti, L., Percalli, E., Ranucci, G., Re, A. C., Saggese, P., Torri, M. D. C., Aiello, S., Andronico, G., Barresi, A., Bergnoli, A., Borghesi, M., Brugnera, R., Bruno, R., Budano, A., Cammi, A., Cerrone, V., Caruso, R., Chiesa, D., Clementi, C., Dusini, S., Fabbri, A., Felici, G., Garfagnini, A., Giudice, N., Gavrikov, A., Grassi, M., Guizzetti, R. M., Guardone, N., Jelmini, B., Lastrucci, L., Lippi, I., Loi, L., Lombardo, C., Mantovani, F., Mari, S. M., Martini, A., Montuschi, M., Nastasi, M., Orestano, D., Ortica, F., Paoloni, A., Petrucci, F., Previtali, E., Redchuck, M., Ricci, B., Romani, A., Sava, G., Serafini, A., Sirignano, C., Sisti, M., Stanco, L., Farilla, E. Stanescu, Strati, V., Triossi, A., Tuvé, C., Venettacci, C., Verde, G., and Votano, L.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

In the field of rare event physics, it is common to have huge masses of organic liquid scintillator as detection medium. In particular, they are widely used to study neutrino properties or astrophysical neutrinos. Thanks to its safety properties (such as low toxicity and high flash point) and easy scalability, linear alkyl benzene is the most common solvent used to produce liquid scintillators for large mass experiments. The knowledge of the refractive index is a pivotal point to understand the detector response, as this quantity (and its wavelength dependence) affects the Cherenkov radiation and photon propagation in the medium. In this paper, we report the measurement of the refractive index of the JUNO liquid scintillator between 260-1064 nm performed with two different methods (an ellipsometer and a refractometer), with a sub percent level precision. In addition, we used an interferometer to measure the group velocity in the JUNO liquid scintillator and verify the expected value derived from the refractive index measurements., Comment: 6 pages, 9 figures

Published
2024

29. JUNO Sensitivity to Invisible Decay Modes of Neutrons

Author

JUNO Collaboration, Abusleme, Angel, Adam, Thomas, Adamowicz, Kai, Ahmad, Shakeel, Ahmed, Rizwan, Aiello, Sebastiano, An, Fengpeng, An, Qi, Andronico, Giuseppe, Anfimov, Nikolay, Antonelli, Vito, Antoshkina, Tatiana, de André, João Pedro Athayde Marcondes, Auguste, Didier, Bai, Weidong, Balashov, Nikita, Baldini, Wander, Barresi, Andrea, Basilico, Davide, Baussan, Eric, Bellato, Marco, Beretta, Marco, Bergnoli, Antonio, Bick, Daniel, Bieger, Lukas, Biktemerova, Svetlana, Birkenfeld, Thilo, Blake, Iwan, Blyth, Simon, Bolshakova, Anastasia, Bongrand, Mathieu, Breton, Dominique, Brigatti, Augusto, Brugnera, Riccardo, Bruno, Riccardo, Budano, Antonio, Busto, Jose, Cabrera, Anatael, Caccianiga, Barbara, Cai, Hao, Cai, Xiao, Cai, Yanke, Cai, Zhiyan, Callier, Stéphane, Calvez, Steven, Cammi, Antonio, Campeny, Agustin, Cao, Chuanya, Cao, Guofu, Cao, Jun, Caruso, Rossella, Cerna, Cédric, Cerrone, Vanessa, Chang, Jinfan, Chang, Yun, Chatrabhuti, Auttakit, Chen, Chao, Chen, Guoming, Chen, Pingping, Chen, Shaomin, Chen, Xin, Chen, Yiming, Chen, Yixue, Chen, Yu, Chen, Zelin, Chen, Zhangming, Chen, Zhiyuan, Chen, Zikang, Cheng, Jie, Cheng, Yaping, Cheng, Yu Chin, Chepurnov, Alexander, Chetverikov, Alexey, Chiesa, Davide, Chimenti, Pietro, Chin, Yen-Ting, Chou, Po-Lin, Chu, Ziliang, Chukanov, Artem, Claverie, Gérard, Clementi, Catia, Clerbaux, Barbara, Molla, Marta Colomer, Di Lorenzo, Selma Conforti, Coppi, Alberto, Corti, Daniele, Csakli, Simon, Cui, Chenyang, Corso, Flavio Dal, Dalager, Olivia, Datta, Jaydeep, De La Taille, Christophe, Deng, Zhi, Deng, Ziyan, Ding, Xiaoyu, Ding, Xuefeng, Ding, Yayun, Dirgantara, Bayu, Dittrich, Carsten, Dmitrievsky, Sergey, Dohnal, Tadeas, Dolzhikov, Dmitry, Donchenko, Georgy, Dong, Jianmeng, Doroshkevich, Evgeny, Dou, Wei, Dracos, Marcos, Druillole, Frédéric, Du, Ran, Du, Shuxian, Duan, Yujie, Dugas, Katherine, Dusini, Stefano, Duyang, Hongyue, Eck, Jessica, Enqvist, Timo, Fabbri, Andrea, Fahrendholz, Ulrike, Fan, Lei, Fang, Jian, Fang, Wenxing, Fedoseev, Dmitry, Feng, Li-Cheng, Feng, Qichun, Ferraro, Federico, Fournier, Amélie, Fritsch, Fritsch, Gan, Haonan, Gao, Feng, Garfagnini, Alberto, Gavrikov, Arsenii, Giammarchi, Marco, Giudice, Nunzio, Gonchar, Maxim, Gong, Guanghua, Gong, Hui, Gornushkin, Yuri, Grassi, Marco, Gromov, Maxim, Gromov, Vasily, Gu, Minghao, Gu, Xiaofei, Gu, Yu, Guan, Mengyun, Guan, Yuduo, Guardone, Nunzio, Guizzetti, Rosa Maria, Guo, Cong, Guo, Wanlei, Hagner, Caren, Han, Hechong, Han, Ran, Han, Yang, He, Jinhong, He, Miao, He, Wei, He, Xinhai, Heinz, Tobias, Hellmuth, Patrick, Heng, Yuekun, Herrera, Rafael, Hor, YuenKeung, Hou, Shaojing, Hsiung, Yee, Hu, Bei-Zhen, Hu, Hang, Hu, Jun, Hu, Peng, Hu, Shouyang, Hu, Tao, Hu, Yuxiang, Hu, Zhuojun, Huang, Guihong, Huang, Hanxiong, Huang, Jinhao, Huang, Junting, Huang, Kaixuan, Huang, Shengheng, Huang, Wenhao, Huang, Xin, Huang, Xingtao, Huang, Yongbo, Hui, Jiaqi, Huo, Lei, Huo, Wenju, Huss, Cédric, Hussain, Safeer, Imbert, Leonard, Ioannisian, Ara, Isocrate, Roberto, Jafar, Arshak, Jelmini, Beatrice, Jeria, Ignacio, Ji, Xiaolu, Jia, Huihui, Jia, Junji, Jian, Siyu, Jiang, Cailian, Jiang, Di, Jiang, Guangzheng, Jiang, Wei, Jiang, Xiaoshan, Jiang, Xiaozhao, Jiang, Yixuan, Jing, Xiaoping, Jollet, Cécile, Kang, Li, Karaparabil, Rebin, Kazarian, Narine, Khan, Ali, Khatun, Amina, Khosonthongkee, Khanchai, Korablev, Denis, Kouzakov, Konstantin, Krasnoperov, Alexey, Kuleshov, Sergey, Kumaran, Sindhujha, Kutovskiy, Nikolay, Labit, Loïc, Lachenmaier, Tobias, Lai, Haojing, Landini, Cecilia, Leblanc, Sébastien, Lefevre, Frederic, Lei, Ruiting, Leitner, Rupert, Leung, Jason, Li, Demin, Li, Fei, Li, Fule, Li, Gaosong, Li, Hongjian, Li, Huang, Li, Jiajun, Li, Min, Li, Nan, Li, Qingjiang, Li, Ruhui, Li, Rui, Li, Shanfeng, Li, Shuo, Li, Tao, Li, Teng, Li, Weidong, Li, Weiguo, Li, Xiaomei, Li, Xiaonan, Li, Xinglong, Li, Yi, Li, Yichen, Li, Yufeng, Li, Zhaohan, Li, Zhibing, Li, Ziyuan, Li, Zonghai, Liang, An-An, Liang, Hao, Liao, Jiajun, Liao, Yilin, Liao, Yuzhong, Limphirat, Ayut, Lin, Guey-Lin, Lin, Shengxin, Lin, Tao, Ling, Jiajie, Ling, Xin, Lippi, Ivano, Liu, Caimei, Liu, Fang, Liu, Fengcheng, Liu, Haidong, Liu, Haotian, Liu, Hongbang, Liu, Hongjuan, Liu, Hongtao, Liu, Hongyang, Liu, Jianglai, Liu, Jiaxi, Liu, Jinchang, Liu, Min, Liu, Qian, Liu, Qin, Liu, Runxuan, Liu, Shenghui, Liu, Shubin, Liu, Shulin, Liu, Xiaowei, Liu, Xiwen, Liu, Xuewei, Liu, Yankai, Liu, Zhen, Loi, Lorenzo, Lokhov, Alexey, Lombardi, Paolo, Lombardo, Claudio, Loo, Kai, Lu, Chuan, Lu, Haoqi, Lu, Jingbin, Lu, Junguang, Lu, Meishu, Lu, Peizhi, Lu, Shuxiang, Lu, Xianguo, Lubsandorzhiev, Bayarto, Lubsandorzhiev, Sultim, Ludhova, Livia, Lukanov, Arslan, Luo, Fengjiao, Luo, Guang, Luo, Jianyi, Luo, Shu, Luo, Wuming, Luo, Xiaojie, Lyashuk, Vladimir, Ma, Bangzheng, Ma, Bing, Ma, Qiumei, Ma, Si, Ma, Xiaoyan, Ma, Xubo, Maalmi, Jihane, Mai, Jingyu, Malabarba, Marco, Malyshkin, Yury, Mandujano, Roberto Carlos, Mantovani, Fabio, Mao, Xin, Mao, Yajun, Mari, Stefano M., Marini, Filippo, Martini, Agnese, Mayer, Matthias, Mayilyan, Davit, Mednieks, Ints, Meng, Yue, Meraviglia, Anita, Meregaglia, Anselmo, Meroni, Emanuela, Miramonti, Lino, Mohan, Nikhil, Montuschi, Michele, Reveco, Cristobal Morales, Nastasi, Massimiliano, Naumov, Dmitry V., Naumova, Elena, Navas-Nicolas, Diana, Nemchenok, Igor, Thi, Minh Thuan Nguyen, Nikolaev, Alexey, Ning, Feipeng, Ning, Zhe, Nunokawa, Hiroshi, Oberauer, Lothar, Ochoa-Ricoux, Juan Pedro, Olshevskiy, Alexander, Orestano, Domizia, Ortica, Fausto, Othegraven, Rainer, Paoloni, Alessandro, Parker, George, Parmeggiano, Sergio, Patsias, Achilleas, Pei, Yatian, Pelicci, Luca, Peng, Anguo, Peng, Haiping, Peng, Yu, Peng, Zhaoyuan, Percalli, Elisa, Perrin, Willy, Perrot, Frédéric, Petitjean, Pierre-Alexandre, Petrucci, Fabrizio, Pilarczyk, Oliver, Rico, Luis Felipe Piñeres, Popov, Artyom, Poussot, Pascal, Previtali, Ezio, Qi, Fazhi, Qi, Ming, Qi, Xiaohui, Qian, Sen, Qian, Xiaohui, Qian, Zhen, Qiao, Hao, Qin, Zhonghua, Qiu, Shoukang, Qu, Manhao, Qu, Zhenning, Ranucci, Gioacchino, Re, Alessandra, Rebii, Abdel, Redchuk, Mariia, Reina, Gioele, Ren, Bin, Ren, Jie, Ren, Yuhan, Ricci, Barbara, Rientong, Komkrit, Rifai, Mariam, Roche, Mathieu, Rodphai, Narongkiat, Romani, Aldo, Roskovec, Bedřich, Ruan, Xichao, Rybnikov, Arseniy, Sadovsky, Andrey, Saggese, Paolo, Sandanayake, Deshan, Sangka, Anut, Sava, Giuseppe, Sawangwit, Utane, Schever, Michaela, Schwab, Cédric, Schweizer, Konstantin, Selyunin, Alexandr, Serafini, Andrea, Settimo, Mariangela, Shao, Junyu, Sharov, Vladislav, Shi, Hexi, Shi, Jingyan, Shi, Yanan, Shutov, Vitaly, Sidorenkov, Andrey, Šimkovic, Fedor, Singhal, Apeksha, Sirignano, Chiara, Siripak, Jaruchit, Sisti, Monica, Smirnov, Mikhail, Smirnov, Oleg, Sokolov, Sergey, Songwadhana, Julanan, Soonthornthum, Boonrucksar, Sotnikov, Albert, Sreethawong, Warintorn, Stahl, Achim, Stanco, Luca, Stankevich, Konstantin, Steiger, Hans, Steinmann, Jochen, Sterr, Tobias, Stock, Matthias Raphael, Strati, Virginia, Strizh, Michail, Studenikin, Alexander, Su, Aoqi, Su, Jun, Sun, Guangbao, Sun, Shifeng, Sun, Xilei, Sun, Yongjie, Sun, Yongzhao, Sun, Zhengyang, Suwonjandee, Narumon, Takenaka, Akira, Tan, Xiaohan, Tang, Jian, Tang, Jingzhe, Tang, Qiang, Tang, Quan, Tang, Xiao, Hariharan, Vidhya Thara, Tkachev, Igor, Tmej, Tomas, Torri, Marco Danilo Claudio, Triossi, Andrea, Trzaska, Wladyslaw, Tung, Yu-Chen, Tuve, Cristina, Ushakov, Nikita, Vedin, Vadim, Venettacci, Carlo, Verde, Giuseppe, Vialkov, Maxim, Viaud, Benoit, Vollbrecht, Cornelius Moritz, von Sturm, Katharina, Vorobel, Vit, Voronin, Dmitriy, Votano, Lucia, Walker, Pablo, Wang, Caishen, Wang, Chung-Hsiang, Wang, En, Wang, Guoli, Wang, Hanwen, Wang, Jian, Wang, Jun, Wang, Li, Wang, Lu, Wang, Meng, Wang, Mingyuan, Wang, Qianchuan, Wang, Ruiguang, Wang, Sibo, Wang, Siguang, Wang, Wei, Wang, Wenshuai, Wang, Xi, Wang, Xiangyue, Wang, Yangfu, Wang, Yaoguang, Wang, Yi, Wang, Yifang, Wang, Yuanqing, Wang, Yuyi, Wang, Zhe, Wang, Zheng, Wang, Zhimin, Watcharangkool, Apimook, Wei, Wei, Wei, Wenlu, Wei, Yadong, Wei, Yuehuan, Wen, Liangjian, Weng, Jun, Wiebusch, Christopher, Wirth, Rosmarie, Wu, Chengxin, Wu, Diru, Wu, Qun, Wu, Yinhui, Wu, Yiyang, Wu, Zhi, Wurm, Michael, Wurtz, Jacques, Wysotzki, Christian, Xi, Yufei, Xia, Dongmei, Xian, Shishen, Xiang, Ziqian, Xiao, Fei, Xiao, Xiang, Xie, Xiaochuan, Xie, Yijun, Xie, Yuguang, Xin, Zhao, Xing, Zhizhong, Xu, Benda, Xu, Cheng, Xu, Donglian, Xu, Fanrong, Xu, Hangkun, Xu, Jiayang, Xu, Jilei, Xu, Jing, Xu, Jinghuan, Xu, Meihang, Xu, Xunjie, Xu, Yin, Xu, Yu, Yan, Baojun, Yan, Qiyu, Yan, Taylor, Yan, Xiongbo, Yan, Yupeng, Yang, Changgen, Yang, Chengfeng, Yang, Fengfan, Yang, Jie, Yang, Lei, Yang, Pengfei, Yang, Xiaoyu, Yang, Yifan, Yang, Yixiang, Yang, Zekun, Yao, Haifeng, Ye, Jiaxuan, Ye, Mei, Ye, Ziping, Yermia, Frédéric, You, Zhengyun, Yu, Boxiang, Yu, Chiye, Yu, Chunxu, Yu, Guojun, Yu, Hongzhao, Yu, Miao, Yu, Xianghui, Yu, Zeyuan, Yu, Zezhong, Yuan, Cenxi, Yuan, Chengzhuo, Yuan, Ying, Yuan, Zhenxiong, Yue, Baobiao, Zafar, Noman, Zamogilnyi, Kirill, Zavadskyi, Vitalii, Zeng, Fanrui, Zeng, Shan, Zeng, Tingxuan, Zeng, Yuda, Zhan, Liang, Zhang, Aiqiang, Zhang, Bin, Zhang, Binting, Zhang, Feiyang, Zhang, Hangchang, Zhang, Haosen, Zhang, Honghao, Zhang, Jialiang, Zhang, Jiawen, Zhang, Jie, Zhang, Jingbo, Zhang, Jinnan, Zhang, Junwei, Zhang, Lei, Zhang, Peng, Zhang, Ping, Zhang, Qingmin, Zhang, Shiqi, Zhang, Shu, Zhang, Shuihan, Zhang, Siyuan, Zhang, Tao, Zhang, Xiaomei, Zhang, Xin, Zhang, Xuantong, Zhang, Yibing, Zhang, Yinhong, Zhang, Yiyu, Zhang, Yongpeng, Zhang, Yu, Zhang, Yuanyuan, Zhang, Yumei, Zhang, Zhenyu, Zhang, Zhijian, Zhao, Jie, Zhao, Rong, Zhao, Runze, Zhao, Shujun, Zhao, Tianhao, Zheng, Hua, Zheng, Yangheng, Zhou, Jing, Zhou, Li, Zhou, Nan, Zhou, Shun, Zhou, Tong, Zhou, Xiang, Zhou, Xing, Zhu, Jingsen, Zhu, Kangfu, Zhu, Kejun, Zhu, Zhihang, Zhuang, Bo, Zhuang, Honglin, Zong, Liang, and Zou, Jiaheng

Subjects
High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract

We explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$., Comment: 28 pages, 7 figures, 4 tables

Published
2024

30. Strain-induced activation of chiral-phonon emission in monolayer WS$_2$

Author

Pan, Yiming and Caruso, Fabio

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract

We report a theoretical investigation of the ultrafast dynamics of electrons and phonons in strained monolayer WS$_2$ following photoexcitation. We show that strain substantially modifies the phase space for electron-phonon scattering, unlocking new relaxation pathways that are unavailable in the pristine monolayer. In particular, strain triggers a transition between distinct dynamical regimes of the non-equilibrium lattice dynamics characterized by the emission of chiral phonons under high strain and linearly-polarized phonons under low strain. For valley-polarized electronic excitations, this mechanism can be exploited to selectively activate the emission of chiral phonons -- phonons carrying a net angular momentum. Our simulations are based on state-of-the-art ab-initio methods and focus exclusively on realistic excitation and strain conditions that have already been achieved in recent experimental studies. Overall, strain emerges as a powerful tool for controlling chiral phonons emission and relaxation pathways in multivalley quantum materials.

Published
2024

31. Reed-Muller codes in the sum-rank metric

Author

Berardini, Elena and Caruso, Xavier

Subjects
Computer Science - Information Theory
Abstract

We introduce the sum-rank metric analogue of Reed-Muller codes, which we called linearized Reed-Muller codes, using multivariate Ore polynomials. We study the parameters of these codes, compute their dimension and give a lower bound for their minimum distance. Our codes exhibit quite good parameters, respecting a similar bound to Reed-Muller codes in the Hamming metric. Finally, we also show that many of the newly introduced linearized Reed--Muller codes can be embedded in some linearized Algebraic Geometry codes, a property which could turn out to be useful in light of decoding.

Published
2024

32. Quantum AI for Alzheimer's disease early screening

Author

Cappiello, Giacomo and Caruso, Filippo

Subjects
Computer Science - Emerging Technologies, Computer Science - Machine Learning, Quantum Physics
Abstract

Quantum machine learning is a new research field combining quantum information science and machine learning. Quantum computing technologies seem to be particularly well suited to solving problems in the health sector in an efficient way, because they may deal with large datasets more efficiently than classical AI. Alzheimer's disease is a neurodegenerative brain disorder that mostly affects elderly people, causing important cognitive impairments. It is the most common cause of dementia and it has an effect on memory, thought, learning abilities and movement control. This type of disease has no cure, consequently an early diagnosis is fundamental for reducing its impact. The analysis of handwriting can be effective for diagnosing, as many researches have conjectured. The DARWIN (Diagnosis AlzheimeR WIth haNdwriting) dataset contains handwriting samples from people affected by Alzheimer's disease and a group of healthy people. Here we apply quantum AI to this use-case. In particular, we use this dataset to test kernel methods for classification task and compare their performances with the ones obtained via quantum machine learning methods. We find that quantum and classical algorithms achieve similar performances and in some cases quantum methods perform even better. Our results pave the way for future new quantum machine learning applications in early-screening diagnostics in the healthcare domain., Comment: 18 pages, 6 figures

Published
2024

33. Structural properties of Krylov subspaces, Krylov solvability, and applications to unbounded self-adjoint operators

Author

Caruso, Noè Angelo

Subjects
Mathematics - Functional Analysis, Mathematics - Spectral Theory, 47B02, 47B15, 47B25, 47B28, 47A60, 47N40, 47N20, 44A60, 46C05, 65J10, 65J22
Abstract

This paper presents a study of the inherent structural properties of Krylov subspaces, in particular for the self-adjoint class of operators, and how they relate with the important phenomenon of `Krylov solvability' of linear inverse problems. Owing to the complexity of the problem in the unbounded setting, recently developed perturbative techniques are used that exploit the use of the weak topology on $\mathcal{H}$. We also make a strong connection between the approximation properties of the Krylov subspace and the famous Hamburger problem of moments, in particular the determinacy condition., Comment: Accepted to the Banach Journal of Mathematical Analysis

Published
2024
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34. Permutation-equivariant quantum convolutional neural networks

Author

Das, Sreetama and Caruso, Filippo

Subjects
Quantum Physics, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

The Symmetric group $S_{n}$ manifests itself in large classes of quantum systems as the invariance of certain characteristics of a quantum state with respect to permuting the qubits. The subgroups of $S_{n}$ arise, among many other contexts, to describe label symmetry of classical images with respect to spatial transformations, e.g. reflection or rotation. Equipped with the formalism of geometric quantum machine learning, in this work we propose the architectures of equivariant quantum convolutional neural networks (EQCNNs) adherent to $S_{n}$ and its subgroups. We demonstrate that a careful choice of pixel-to-qubit embedding order can facilitate easy construction of EQCNNs for small subgroups of $S_{n}$. Our novel EQCNN architecture corresponding to the full permutation group $S_{n}$ is built by applying all possible QCNNs with equal probability, which can also be conceptualized as a dropout strategy in quantum neural networks. For subgroups of $S_{n}$, our numerical results using MNIST datasets show better classification accuracy than non-equivariant QCNNs. The $S_{n}$-equivariant QCNN architecture shows significantly improved training and test performance than non-equivariant QCNN for classification of connected and non-connected graphs. When trained with sufficiently large number of data, the $S_{n}$-equivariant QCNN shows better average performance compared to $S_{n}$-equivariant QNN . These results contribute towards building powerful quantum machine learning architectures in permutation-symmetric systems., Comment: 13 pages, 10 figures

Published
2024
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35. A first passage model of intravitreal drug delivery and residence time, in relation to ocular geometry, individual variability, and injection location

Author

Lamirande, Patricia, Gaffney, Eamonn A., Gertz, Michael, Maini, Philip K., Crawshaw, Jessica R., and Caruso, Antonello

Subjects
Quantitative Biology - Quantitative Methods, Mathematics - Analysis of PDEs
Abstract

Purpose: Standard of care for various retinal diseases involves recurrent intravitreal injections. This motivates mathematical modelling efforts to identify influential factors for drug residence time, aiming to minimise administration frequency. We sought to describe the vitreal diffusion of therapeutics in nonclinical species used during drug development assessments. In human eyes, we investigated the impact of variability in vitreous cavity size and eccentricity, and in injection location, on drug elimination. Methods: Using a first passage time approach, we modelled the transport-controlled distribution of two standard therapeutic protein formats (Fab and IgG) and elimination through anterior and posterior pathways. Detailed anatomical 3D geometries of mouse, rat, rabbit, cynomolgus monkey, and human eyes were constructed using ocular images and biometry datasets. A scaling relationship was derived for comparison with experimental ocular half-lives. Results: Model simulations revealed a dependence of residence time on ocular size and injection location. Delivery to the posterior vitreous resulted in increased vitreal half-life and retinal permeation. Interindividual variability in human eyes had a significant influence on residence time (half-life range of 5-7 days), showing a strong correlation to axial length and vitreal volume. Anterior exit was the predominant route of drug elimination. Contribution of the posterior pathway displayed a small (3%) difference between protein formats, but varied between species (10-30%). Conclusions: The modelling results suggest that experimental variability in ocular half-life is partially attributed to anatomical differences and injection site location. Simulations further suggest a potential role of the posterior pathway permeability in determining species differences in ocular pharmacokinetics.

Published
2024
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36. Impact of the Magnetic Horizon on the Interpretation of the Pierre Auger Observatory Spectrum and Composition Data

Author

The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Bellido, J. A., Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., de Errico, B. P. de Souza, De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janardhana, V., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Armand, J. Perez, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. 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Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The flux of ultra-high energy cosmic rays reaching Earth above the ankle energy (5 EeV) can be described as a mixture of nuclei injected by extragalactic sources with very hard spectra and a low rigidity cutoff. Extragalactic magnetic fields existing between the Earth and the closest sources can affect the observed CR spectrum by reducing the flux of low-rigidity particles reaching Earth. We perform a combined fit of the spectrum and distributions of depth of shower maximum measured with the Pierre Auger Observatory including the effect of this magnetic horizon in the propagation of UHECRs in the intergalactic space. We find that, within a specific range of the various experimental and phenomenological systematics, the magnetic horizon effect can be relevant for turbulent magnetic field strengths in the local neighbourhood of order $B_{\rm rms}\simeq (50-100)\,{\rm nG}\,(20\rm{Mpc}/{d_{\rm s})( 100\,\rm{kpc}/L_{\rm coh}})^{1/2}$, with $d_{\rm s}$ the typical intersource separation and $L_{\rm coh}$ the magnetic field coherence length. When this is the case, the inferred slope of the source spectrum becomes softer and can be closer to the expectations of diffusive shock acceleration, i.e., $\propto E^{-2}$. An additional cosmic-ray population with higher source density and softer spectra, presumably also extragalactic and dominating the cosmic-ray flux at EeV energies, is also required to reproduce the overall spectrum and composition results for all energies down to 0.6~EeV., Comment: Matches published version

Published
2024
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40. The value of ACR, European, Korean, and ATA ultrasound risk stratification systems combined with RAS mutations for detecting thyroid carcinoma in cytologically indeterminate and suspicious for malignancy thyroid nodules

Author

Scappaticcio, Lorenzo, Di Martino, Nicole, Caruso, Paola, Ferrazzano, Pamela, Marino, Federica Zito, Clery, Eduardo, Cioce, Alessandro, Cozzolino, Giovanni, Maiorino, Maria Ida, Docimo, Giovanni, Trimboli, Pierpaolo, Franco, Renato, Esposito, Katherine, and Bellastella, Giuseppe

Published
2024
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47. Cost-effectiveness of robotic vs laparoscopic distal pancreatectomy. Results from the national prospective trial ROBOCOSTES

Author

Guerrero-Ortiz, María Alejandra, Sánchez-Velazquez, Patricia, Burdío, Fernando, Gimeno, Marta, Podda, Mauro, Pellino, Gianluca, Toledano, Miguel, Nuñez, Javier, Bellido, Juan, Acosta-Mérida, María Asunción, Vicente, Emilio, Lopez-Ben, Santiago, Pacheco, David, Pando, Elizabeth, Jorba, Rosa, Trujillo, Juan Pablo Arjona, Ausania, Fabio, Alvarez, Mario, Fernandes, Nair, Castro-Boix, Sandra, Gantxegi, Amaia, Carré, Miquel Kraft-, Pinto-Fuentes, Pilar, Bueno-Cañones, Alejandro, Valdes-Hernandez, Javier, Tresierra, Luis, Caruso, Riccardo, Ferri, Valentina, Tio, Berta, Babiloni-Simon, Sonia, Lacasa-Martin, David, González-Abós, Carolina, Guevara-Martinez, Jenny, Gutierrez-Iscar, Eduardo, Sanchez-Santos, Raquel, Cano-Valderrama, Oscar, Nogueira-Sixto, Manuel, Alvarez-Garrido, Nicolas, Martinez-Cortijo, Sagrario, Lasaia, Manuel Alberto, Linacero, Santiago, Morante, Ana Pilar, Rotellar, Fernando, Arredondo, Jorge, Marti, Pablo, Sabatella, Lucas, Zozaya, Gabriel, and Ielpo, Benedetto

Published
2024
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