326,235 results on '"A. CHOU"'
Search Results
2. ALMA/SCUBA-2 COSMOS Survey: Properties of X-ray- and SED-selected AGNs in Bright Submillimeter Galaxies
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Uematsu, Ryosuke, Ueda, Yoshihiro, Alexander, David M., Swinbank, A. M., Smail, Ian, Andonie, Carolina, Chen, Chian-Chou, Dudzeviciute, Ugne, Ikarashi, Soh, Kohno, Kotaro, Matsuda, Yuichi, Puglisi, Annagrazia, Umehata, Hideki, and Wang, Wei-Hao
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Astrophysics - Astrophysics of Galaxies - Abstract
We investigate the properties of active galactic nuclei (AGNs) in the brightest submillimeter galaxies (SMGs) in the COSMOS field. We utilize the bright sample of ALMA/SCUBA-2 COSMOS Survey (AS2COSMOS), which consists of 260 SMGs with $S_{\mathrm{870}\, \mu \mathrm{m}}=0.7\text{--}19.2\,\mathrm{mJy}$ at $z=0\text{--}6$. We perform optical to millimeter spectral energy distribution (SED) modeling for the whole sample. We identify 24 AGN-host galaxies from the SEDs. Supplemented by 23 X-ray detected AGNs (X-ray AGNs), we construct an overall sample of 40 AGN-host galaxies. The X-ray luminosity upper bounds indicate that the X-ray undetected SED-identified AGNs are likely to be nearly Compton thick or have unusually suppressed X-ray emission. From visual classification, we identify $25^{+6}_{-5}$\% of the SMGs without AGNs as major merger candidates. This fraction is almost consistent with the general galaxy population at $z\sim2$, suggesting that major mergers are not necessarily required for the enhanced star formation in SMGs. We also identify $47^{+16}_{-15}$\% of the AGN hosts as major merger candidates, which is about twice as high as that in the SMGs without AGNs. This suggests that major mergers play a key role in triggering AGN activity in bright SMGs., Comment: 37 pages, 21 figures, accepted for The Astrophysical Journal
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- 2024
3. Behind the dust veil: A panchromatic view of an optically dark galaxy at z=4.82
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Sillassen, Nikolaj B., Jin, Shuowen, Magdis, Georgios E., Hodge, Jacqueline, Gobat, Raphael, Daddi, Emanuele, Knudsen, Kirsten, Finoguenov, Alexis, Schinnerer, Eva, Wang, Wei-Hao, Gao, Zhen-Kai, Weaver, John R., Algera, Hiddo, Andika, Irham T., Brinch, Malte, Chen, Chian-Chou, Cochrane, Rachel, Enia, Andrea, Faisst, Andreas, Gillman, Steven, Gomez-Guijarro, Carlos, Gozaliasl, Ghassem, Hayward, Chris, Kokorev, Vasily, Merchant, Maya, Rizzo, Francesca, Talia, Margherita, Valentino, Francesco, Blánquez-Sesé, David, Koekemoer, Anton M., Magnelli, Benjamin, Rich, Michael, and Shuntov, Marko
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Astrophysics - Astrophysics of Galaxies - Abstract
Optically dark dusty star-forming galaxies (DSFGs) play an essential role in massive galaxy formation at early cosmic time, however their nature remains elusive. Here we present a detailed case study of all the baryonic components of a $z=4.821$ DSFG, XS55. Selected from the ultra-deep COSMOS-XS 3GHz map with a red SCUBA-2 450$\mu$m/850$\mu$m colour, XS55 was followed up with ALMA 3mm line scans and spectroscopically confirmed to be at $z=4.821$ via detections of the CO(5-4) and [CI](1-0) lines. JWST/NIRCam imaging reveals that XS55 is a F150W-dropout with red F277W/F444W colour, and a complex morphology: a compact central component embedded in an extended structure with a likely companion. XS55 is tentatively detected in X-rays with both Chandra and XMM-Newton, suggesting an active galactic nucleus (AGN) nature. By fitting a panchromatic SED spanning NIR to radio wavelengths, we revealed that XS55 is a massive main-sequence galaxy with a stellar mass of $M_\ast=(5\pm1)\times10^{10}\,{\rm M_\odot}$ and a star formation rate of ${\rm SFR}=540\pm177~{\rm M_\odot\,yr^{-1}}$. The dust of XS55 is optically thick in the far infrared (FIR) with a surprisingly cold dust temperature of $T_{\rm dust}=33\pm2\,{\rm K}$, making XS55 one of the coldest DSFGs at $z>4$ known to date. This work unveils the nature of a radio-selected F150W-dropout, suggesting the existence of a population of DSFGs hosting active black holes embedded in optically thick dust., Comment: 11 pages, 7 figures, accepted in Astronomy & Astrophysics
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- 2024
4. VisionArena: 230K Real World User-VLM Conversations with Preference Labels
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Chou, Christopher, Dunlap, Lisa, Mashita, Koki, Mandal, Krishna, Darrell, Trevor, Stoica, Ion, Gonzalez, Joseph E., and Chiang, Wei-Lin
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Computer Science - Computer Vision and Pattern Recognition - Abstract
With the growing adoption and capabilities of vision-language models (VLMs) comes the need for benchmarks that capture authentic user-VLM interactions. In response, we create VisionArena, a dataset of 230K real-world conversations between users and VLMs. Collected from Chatbot Arena - an open-source platform where users interact with VLMs and submit preference votes - VisionArena spans 73K unique users, 45 VLMs, and 138 languages. Our dataset contains three subsets: VisionArena-Chat, 200k single and multi-turn conversations between a user and a VLM; VisionArena-Battle, 30K conversations comparing two anonymous VLMs with user preference votes; and VisionArena-Bench, an automatic benchmark of 500 diverse user prompts that efficiently approximate the live Chatbot Arena model rankings. Additionally, we highlight the types of question asked by users, the influence of response style on preference, and areas where models often fail. We find open-ended tasks like captioning and humor are highly style-dependent, and current VLMs struggle with spatial reasoning and planning tasks. Lastly, we show finetuning the same base model on VisionArena-Chat outperforms Llava-Instruct-158K, with a 17-point gain on MMMU and a 46-point gain on the WildVision benchmark. Dataset at https://huggingface.co/lmarena-ai
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- 2024
5. Electrokinetic nanofluidic sensing of DNA nanostar condensate
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Chou, Kuang-Hua, Eden, Alex, Huber, David, Pennathur, Sumita, and Fygenson, Deborah Kuchnir
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Condensed Matter - Soft Condensed Matter - Abstract
We demonstrate electronic sensing of DNA nanostar (NS) condensate. Specifically, we use electrokinetic nanofluidics to observe and interpret how temperature-induced NS condensation affects nanochannel current. The increase in current upon filling a nanochannel with NS condensate indicates that its electrophoretic mobility is about half that of a single NS and its effective ionic strength is $\sim35$\% greater than that of 150mM NaCl in phosphate buffer. $\zeta$-potential measurements before and after exposure to NS show that condensate binds the silica walls of a nanochannel more strongly than individual NS do under identical conditions. This binding increases electroosmotic flow, possibly enough to completely balance, or even exceed, the electrophoretic velocity of NS condensate. Although the current through a flat nanochannel is erratic in the presence of NS condensate, tilting the nanochannel to accumulate NS condensate at one entrance (and away from the other) results in a robust electronic signature of the NS phase transition at temperatures $T_c$ = $f$([NaCl]) that agree with those obtained by other methods. Electrokinetic nanofluidic detection and measurement of NS condensate thus provides a foundation for novel biosensing technologies based on liquid-liquid phase separation.
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- 2024
6. Multiprobe Cosmology from the Abundance of SPT Clusters and DES Galaxy Clustering and Weak Lensing
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Bocquet, S., Grandis, S., Krause, E., To, C., Bleem, L. E., Klein, M., Mohr, J. J., Schrabback, T., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Baxter, E. J., Bechtol, K., Becker, M. R., Bernstein, G. M., Blazek, J., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Choi, A., Cordero, J., Crocce, M., Davis, C., DeRose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elsner, F., Elvin-Poole, J., Everett, S., Fang, X., Ferté, A., Fosalba, P., Friedrich, O., Frieman, J., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huang, H., Huff, E. M., Huterer, D., Jarvis, M., Kuropatkin, N., Leget, P. -F., Lemos, P., Liddle, A. R., MacCrann, N., McCullough, J., Muir, J., Myles, J., Navarro-Alsina, A., Pandey, S., Park, Y., Porredon, A., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Rosenfeld, R., Rykoff, E. S., Sánchez, C., Sanchez, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Weaverdyck, N., Wechsler, R. H., Wu, H. -Y., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Ade, P. A. R., Aguena, M., Allam, S., Allen, S. W., Anderson, A. J., Ansarinejad, B., Austermann, J. E., Bayliss, M., Beall, J. A., Bender, A. N., Benson, B. A., Bianchini, F., Brodwin, M., Brooks, D., Bryant, L., Burke, D. L., Canning, R. E. A., Carlstrom, J. E., Carretero, J., Castander, F. J., Chang, C. L., Chaubal, P., Chiang, H. C., Chou, T-L., Citron, R., Moran, C. Corbett, Costanzi, M., Crawford, T. M., Crites, A. T., da Costa, L. N., Pereira, M. E. S., Davis, T. M., de Haan, T., Dobbs, M. A., Doel, P., Everett, W., Farahi, A., Flaugher, B., Flores, A. M., Floyd, B., Gallicchio, J., Gaztanaga, E., George, E. M., Gladders, M. D., Gupta, N., Gutierrez, G., Halverson, N. W., Hinton, S. R., Hlavacek-Larrondo, J., Holder, G. P., Hollowood, D. L., Holzapfel, W. L., Hrubes, J. D., Huang, N., Hubmayr, J., Irwin, K. D., James, D. J., Kéruzoré, F., Khullar, G., Kim, K., Knox, L., Kraft, R., Kuehn, K., Lahav, O., Lee, A. T., Lee, S., Li, D., Lidman, C., Lima, M., Lowitz, A., Mahler, G., Mantz, A., Marshall, J. L., McDonald, M., McMahon, J. J., Mena-Fernández, J., Meyer, S. S., Miquel, R., Montgomery, J., Natoli, T., Nibarger, J. P., Noble, G. I., Novosad, V., Ogando, R. L. C., Padin, S., Paschos, P., Patil, S., Malagón, A. A. Plazas, Pryke, C., Reichardt, C. L., Roberson, J., Romer, A. K., Romero, C., Ruhl, J. E., Saliwanchik, B. R., Salvati, L., Samuroff, S., Sanchez, E., Santiago, B., Sarkar, A., Saro, A., Schaffer, K. K., Sharon, K., Sievers, C., Smecher, G., Smith, M., Somboonpanyakul, T., Sommer, M., Stalder, B., Stark, A. A., Stephen, J., Strazzullo, V., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, C., Tucker, D. L., Veach, T., Vieira, J. D., von der Linden, A., Wang, G., Whitehorn, N., Wu, W. L. K., Yefremenko, V., Young, M., Zebrowski, J. A., Zohren, H., Collaboration, DES, and Collaboration, SPT
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the auto- and cross-correlation of galaxy position and weak lensing measurements (3$\times$2pt) in the Dark Energy Survey (DES). We consider the cosmological correlation between the different tracers and we account for the systematic uncertainties that are shared between the large-scale lensing correlation functions and the small-scale lensing-based cluster mass calibration. Marginalized over the remaining $\Lambda$CDM parameters (including the sum of neutrino masses) and 52 astrophysical modeling parameters, we measure $\Omega_\mathrm{m}=0.300\pm0.017$ and $\sigma_8=0.797\pm0.026$. Compared to constraints from Planck primary CMB anisotropies, our constraints are only 15% wider with a probability to exceed of 0.22 ($1.2\sigma$) for the two-parameter difference. We further obtain $S_8\equiv\sigma_8(\Omega_\mathrm{m}/0.3)^{0.5}=0.796\pm0.013$ which is lower than the Planck measurement at the $1.6\sigma$ level. The combined SPT cluster, DES 3$\times$2pt, and Planck datasets mildly prefer a non-zero positive neutrino mass, with a 95% upper limit $\sum m_\nu<0.25~\mathrm{eV}$ on the sum of neutrino masses. Assuming a $w$CDM model, we constrain the dark energy equation of state parameter $w=-1.15^{+0.23}_{-0.17}$ and when combining with Planck primary CMB anisotropies, we recover $w=-1.20^{+0.15}_{-0.09}$, a $1.7\sigma$ difference with a cosmological constant. The precision of our results highlights the benefits of multiwavelength multiprobe cosmology., Comment: Submitted to Phys. Rev. D
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- 2024
7. Efficient 3D Recognition with Event-driven Spike Sparse Convolution
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Qiu, Xuerui, Yao, Man, Zhang, Jieyuan, Chou, Yuhong, Qiao, Ning, Zhou, Shibo, Xu, Bo, and Li, Guoqi
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. Point clouds are sparse 3D spatial data, which suggests that SNNs should be well-suited for processing them. However, when applying SNNs to point clouds, they often exhibit limited performance and fewer application scenarios. We attribute this to inappropriate preprocessing and feature extraction methods. To address this issue, we first introduce the Spike Voxel Coding (SVC) scheme, which encodes the 3D point clouds into a sparse spike train space, reducing the storage requirements and saving time on point cloud preprocessing. Then, we propose a Spike Sparse Convolution (SSC) model for efficiently extracting 3D sparse point cloud features. Combining SVC and SSC, we design an efficient 3D SNN backbone (E-3DSNN), which is friendly with neuromorphic hardware. For instance, SSC can be implemented on neuromorphic chips with only minor modifications to the addressing function of vanilla spike convolution. Experiments on ModelNet40, KITTI, and Semantic KITTI datasets demonstrate that E-3DSNN achieves state-of-the-art (SOTA) results with remarkable efficiency. Notably, our E-3DSNN (1.87M) obtained 91.7\% top-1 accuracy on ModelNet40, surpassing the current best SNN baselines (14.3M) by 3.0\%. To our best knowledge, it is the first direct training 3D SNN backbone that can simultaneously handle various 3D computer vision tasks (e.g., classification, detection, and segmentation) with an event-driven nature. Code is available: https://github.com/bollossom/E-3DSNN/., Comment: Accepted by AAAI 2025
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- 2024
8. Unveiling the Role of Lewis Base Strength in Small-Molecule Passivation of Defect Perovskites
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Wu, Yi-Chen and Chou, Hsien-Hsin
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Physics - Chemical Physics ,Condensed Matter - Materials Science - Abstract
Perovskite materials are highly promising for a range of optoelectronic applications including energy conversion technologies, owing to their high charge-carrier mobilities, adaptability of bandgap tuning, and exceptional light-harvesting capabilities. Yet, defects that arise during manufacturing often lead to performance limitations such as hindered efficiency and stability. This is primarily due to significant deviations in crystal geometry and band structure elements such as the Fermi level, work function, and density of states, compared to pristine perovskite. To mitigate these issues, this study explored the passivation of surface iodide-vacancy defect in perovskite using small-molecule Lewis bases, an approach aims to counteract these detrimental effects. Among the examined N-, P- and O-coordinated benzyl derivatives, those featuring a phosphonic acid group as a passivator for the undercoordinated Pb(II) sites demonstrated outstanding electronic structure properties. This was notably achieved by lowering the Fermi level, increasing the work function, and suppressing surface trap states. The effective restoration of electronic properties achieved by targeted small molecule passivation provides crucial insights into enhanced functionality and efficiency for defect perovskite materials.
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- 2024
9. Macroscopic magnetization of primordial plasma by virial shocks
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Keshet, Uri and Hou, Kuan-Chou
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Astrophysics - High Energy Astrophysical Phenomena ,Physics - Plasma Physics - Abstract
Galaxy-cluster virial (structure-formation accretion) shock observations are shown to imply $\gtrsim1\%$ magnetization of a layer extending $\gtrsim10^{16}$ Debye lengths downstream, challenging the modelling of high Alfv\'en-Mach collisionless shocks. Unlike similar shocks in supernova remnants or relativistic shocks in $\gamma$-ray burst afterglows, where macroscopic magnetized layers were detected but purportedly attributed to preexisting or non-resonant cosmic-ray streaming-seeded substructure, the upstream of strong virial shocks is both weakly magnetized and pristine. Hence, some mechanism must generate large-scale and possibly self-similar magnetic sub-structure out of the accreted primordial plasma; such a mechanism may dominate other high-Mach shock systems, too., Comment: 8 pages, 1 figure, comments welcome
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- 2024
10. Supporting Gig Worker Needs and Advancing Policy Through Worker-Centered Data-Sharing
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Hsieh, Jane, Zhang, Angie, Rasetarinera, Mialy, Chou, Erik, Ngo, Daniel, Lightman, Karen, Lee, Min Kyung, and Zhu, Haiyi
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Computer Science - Computers and Society - Abstract
The proliferating adoption of platform-based gig work increasingly raises concerns for worker conditions. Past studies documented how platforms leveraged design to exploit labor, withheld information to generate power asymmetries, and left workers alone to manage logistical overheads as well as social isolation. However, researchers also called attention to the potential of helping workers overcome such costs via worker-led datasharing, which can enable collective actions and mutual aid among workers, while offering advocates, lawmakers and regulatory bodies insights for improving work conditions. To understand stakeholders' desiderata for a data-sharing system (i.e. functionality and policy initiatives that it can serve), we interviewed 11 policy domain experts in the U.S. and conducted co-design workshops with 14 active gig workers across four domains. Our results outline policymakers' prioritized initiatives, information needs, and (mis)alignments with workers' concerns and desires around data collectives. We offer design recommendations for data-sharing systems that support worker needs while bringing us closer to legislation that promote more thriving and equitable gig work futures.
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- 2024
11. Stability condition on a singular surface and its resolution
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Chou, Tzu-Yang
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Mathematics - Algebraic Geometry ,14F08 (Primary) 14J17, 18E40, 18G80 (Secondary) - Abstract
Let $X$ be a surface with an ADE-singularity and let $\widetilde{X}$ be its crepant resolution. In this paper, we show that there exists a Bridgeland stability condition $\sigma_X$ on ${\rm D}^b(X)$ and a weak stability condition $\sigma_{\widetilde{X}}$ on the derived category of the desingularisation ${\rm D}^b(\widetilde{X})$, such that pushforward of $\sigma_{\widetilde{X}}$-semistable objects are $\sigma_X$-semistable We first construct Bridgeland stability conditions on ${\rm D}^b(\widetilde{X})$ associated to the contraction $\widetilde{X} \longrightarrow X$, generalizing the results of Tramel and Xia in \cite{TX22}, Then we deform it to a weak stability condition $\sigma_{\widetilde{X}}$ and show that it descends to ${\rm D}^b(X)$, producing the stability condition $\sigma_X$., Comment: 33 pages
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- 2024
12. Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Training
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Yao, Man, Qiu, Xuerui, Hu, Tianxiang, Hu, Jiakui, Chou, Yuhong, Tian, Keyu, Liao, Jianxing, Leng, Luziwei, Xu, Bo, and Li, Guoqi
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Computer Science - Computer Vision and Pattern Recognition - Abstract
The ambition of brain-inspired Spiking Neural Networks (SNNs) is to become a low-power alternative to traditional Artificial Neural Networks (ANNs). This work addresses two major challenges in realizing this vision: the performance gap between SNNs and ANNs, and the high training costs of SNNs. We identify intrinsic flaws in spiking neurons caused by binary firing mechanisms and propose a Spike Firing Approximation (SFA) method using integer training and spike-driven inference. This optimizes the spike firing pattern of spiking neurons, enhancing efficient training, reducing power consumption, improving performance, enabling easier scaling, and better utilizing neuromorphic chips. We also develop an efficient spike-driven Transformer architecture and a spike-masked autoencoder to prevent performance degradation during SNN scaling. On ImageNet-1k, we achieve state-of-the-art top-1 accuracy of 78.5\%, 79.8\%, 84.0\%, and 86.2\% with models containing 10M, 19M, 83M, and 173M parameters, respectively. For instance, the 10M model outperforms the best existing SNN by 7.2\% on ImageNet, with training time acceleration and inference energy efficiency improved by 4.5$\times$ and 3.9$\times$, respectively. We validate the effectiveness and efficiency of the proposed method across various tasks, including object detection, semantic segmentation, and neuromorphic vision tasks. This work enables SNNs to match ANN performance while maintaining the low-power advantage, marking a significant step towards SNNs as a general visual backbone. Code is available at https://github.com/BICLab/Spike-Driven-Transformer-V3.
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- 2024
13. Deterministic multi-phonon entanglement between two mechanical resonators on separate substrates
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Chou, Ming-Han, Qiao, Hong, Yan, Haoxiong, Andersson, Gustav, Conner, Christopher R., Grebel, Joel, Joshi, Yash J., Miller, Jacob M., Povey, Rhys G., Wu, Xuntao, and Cleland, Andrew N.
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Quantum Physics - Abstract
Mechanical systems have emerged as a compelling platform for applications in quantum information, leveraging recent advances in the control of phonons, the quanta of mechanical vibrations. Several experiments have demonstrated control and measurement of phonon states in mechanical resonators integrated with superconducting qubits, and while entanglement of two mechanical resonators has been demonstrated in some approaches, a full exploitation of the bosonic nature of phonons, such as multi-phonon entanglement, remains a challenge. Here, we describe a modular platform capable of rapid multi-phonon entanglement generation and subsequent tomographic analysis, using two surface acoustic wave resonators on separate substrates, each connected to a superconducting qubit. We generate a mechanical Bell state between the two mechanical resonators, achieving a fidelity of $\mathcal{F} = 0.872\pm 0.002$, and further demonstrate the creation of a multi-phonon entangled state (N=2 N00N state), shared between the two resonators, with fidelity $\mathcal{F} = 0.748\pm 0.008$. This approach promises the generation and manipulation of more complex phonon states, with potential future applications in bosonic quantum computing in mechanical systems. The compactness, modularity, and scalability of our platform further promises advances in both fundamental science and advanced quantum protocols, including quantum random access memory and quantum error correction., Comment: 25 pages, 9 figures
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- 2024
14. The properties of the interstellar medium in dusty, star-forming galaxies at $z \sim 2-4$: The shape of the CO spectral line energy distributions
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Taylor, Dominic J., Swinbank, A. M., Smail, Ian, Puglisi, Annagrazia, Birkin, Jack E., Dudzeviciute, Ugne, Chen, Chian-Chou, Ikarashi, S., Castillo, Marta Frias, Weiss, Axel, Li, Zefeng, Chapman, Scott C., Jansen, Jasper, Jimenez-Andrade, E. F., Morabito, Leah K., Murphy, Eric J., Rybak, Matus, and van der Werf, P. P.
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Astrophysics - Astrophysics of Galaxies ,Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
The molecular gas in the interstellar medium (ISM) of star-forming galaxy populations exhibits diverse physical properties. We investigate the $^{12}$CO excitation of twelve dusty, luminous star-forming galaxies at $z \sim 2-4$ by combining observations of the $^{12}$CO from $J_{\rm up} = 1$ to $J_{\rm up} = 8$. The spectral line energy distribution (SLED) has a similar shape to NGC 253, M82, and local ULIRGs, with much stronger excitation than the Milky Way inner disc. By combining with resolved dust continuum sizes from high-resolution $870$-$\mu$m ALMA observations and dust mass measurements determined from multi-wavelength SED fitting, we measure the relationship between the $^{12}$CO SLED and probable physical drivers of excitation: star-formation efficiency, the average intensity of the radiation field $\langle U\rangle$, and the star-formation rate surface density. The primary driver of high-$J_{\rm up}$ $^{12}$CO excitation in star-forming galaxies is star-formation rate surface density. We use the ratio of the CO($3-2$) and CO($6-5$) line fluxes to infer the CO excitation in each source and find that the average ratios for our sample are elevated compared to observations of low-redshift, less actively star-forming galaxies and agree well with predictions from numerical models that relate the ISM excitation to the star-formation rate surface density. The significant scatter in the line ratios of a factor $\approx 3$ within our sample likely reflects intrinsic variations in the ISM properties which may be caused by other effects on the excitation of the molecular gas, such as cosmic ray ionization rates and mechanical heating through turbulence dissipation., Comment: Accepted for publication in MNRAS; 17 pages, 7 figures
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- 2024
15. Maximizing Quantum Enhancement in Axion Dark Matter Experiments
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Kuo, Chao-Lin, Bartram, Chelsea L., Chou, Aaron S., Dyson, Taj A., Kurinsky, Noah A., Rybka, Gray, Wen, Osmond, Withers, Matthew O., Yi, Andrew K., and Zhang, Cheng
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High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
We provide a comprehensive comparison of linear amplifiers and microwave photon-counters in axion dark matter experiments. The study is done assuming a range of realistic operating conditions and detector parameters, over the frequency range between 1--30 GHz. As expected, photon counters are found to be advantageous under low background, at high frequencies ($\nu>$ 5 GHz), {\em if} they can be implemented with robust wide-frequency tuning or a very low dark count rate. Additional noteworthy observations emerging from this study include: (1) an expanded applicability of off-resonance photon background reduction, including the single-quadrature state squeezing, for scan rate enhancements; (2) a much broader appeal for operating the haloscope resonators in the over-coupling regime, up to $\beta\sim 10$; (3) the need for a detailed investigation into the cryogenic and electromagnetic conditions inside haloscope cavities to lower the photon temperature for future experiments; (4) the necessity to develop a distributed network of coupling ports in high-volume axion haloscopes to utilize these potential gains in the scan rate.
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- 2024
16. The Fast and the Furious: Tracking the Effect of the Tomoa Skip on Speed Climbing
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Chou, Caleb and Kaplan, Andee
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Statistics - Applications - Abstract
Sport climbing is an athletic discipline comprised of three sub-disciplines -- lead climbing, bouldering, and speed climbing. These three sub-disciplines have distinct goals, resulting in specialization of athletes into one of the three events. The year 2020 marked the first inclusion of sport climbing in the Olympic Games. While this decision was met with excitement from the climbing community, it was not without controversy. The International Olympic Committee had allocated one set of medals for the entire sport, necessitating the combination of sub-disciplines into one competition. As a result, athletes who specialized in lead and bouldering were forced to train and compete in speed for the first time in their careers. One such athlete was Tomoa Narasaki, a World Champion boulderer, who introduced a new method of approaching the speed event. This approach, deemed the Tomoa Skip (TS), was subsequently adopted by many of the top speed climbers. Concurrently, speed records fell rapidly (from 5.48s in 2017 to 4.90s in 2023). Speed climbing involves ascending a 15m wall containing the same pattern of obstacles. Thus, records can be compared across time. In this paper we investigate the effect of the TS on speed climbing by answering two questions: (1) Did the TS result in a decrease in speed times? and (2) Do climbers who utilize the TS show less consistency? The success of the TS highlights the potential of collaboration between different disciplines of sport, showing athletes of diverse backgrounds may contribute to the evolution of competition., Comment: 15 pages, 6 figures. Accepted at Chance Magazine
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- 2024
17. Generating 3D-Consistent Videos from Unposed Internet Photos
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Chou, Gene, Zhang, Kai, Bi, Sai, Tan, Hao, Xu, Zexiang, Luan, Fujun, Hariharan, Bharath, and Snavely, Noah
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We address the problem of generating videos from unposed internet photos. A handful of input images serve as keyframes, and our model interpolates between them to simulate a path moving between the cameras. Given random images, a model's ability to capture underlying geometry, recognize scene identity, and relate frames in terms of camera position and orientation reflects a fundamental understanding of 3D structure and scene layout. However, existing video models such as Luma Dream Machine fail at this task. We design a self-supervised method that takes advantage of the consistency of videos and variability of multiview internet photos to train a scalable, 3D-aware video model without any 3D annotations such as camera parameters. We validate that our method outperforms all baselines in terms of geometric and appearance consistency. We also show our model benefits applications that enable camera control, such as 3D Gaussian Splatting. Our results suggest that we can scale up scene-level 3D learning using only 2D data such as videos and multiview internet photos.
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- 2024
18. MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map
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Chou, Yuhong, Yao, Man, Wang, Kexin, Pan, Yuqi, Zhu, Ruijie, Zhong, Yiran, Qiao, Yu, Wu, Jibin, Xu, Bo, and Li, Guoqi
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Various linear complexity models, such as Linear Transformer (LinFormer), State Space Model (SSM), and Linear RNN (LinRNN), have been proposed to replace the conventional softmax attention in Transformer structures. However, the optimal design of these linear models is still an open question. In this work, we attempt to answer this question by finding the best linear approximation to softmax attention from a theoretical perspective. We start by unifying existing linear complexity models as the linear attention form and then identify three conditions for the optimal linear attention design: 1) Dynamic memory ability; 2) Static approximation ability; 3) Least parameter approximation. We find that none of the current linear models meet all three conditions, resulting in suboptimal performance. Instead, we propose Meta Linear Attention (MetaLA) as a solution that satisfies these conditions. Our experiments on Multi-Query Associative Recall (MQAR) task, language modeling, image classification, and Long-Range Arena (LRA) benchmark demonstrate that MetaLA is more effective than the existing linear models.
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- 2024
19. BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery
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John, Peter St., Lin, Dejun, Binder, Polina, Greaves, Malcolm, Shah, Vega, John, John St., Lange, Adrian, Hsu, Patrick, Illango, Rajesh, Ramanathan, Arvind, Anandkumar, Anima, Brookes, David H, Busia, Akosua, Mahajan, Abhishaike, Malina, Stephen, Prasad, Neha, Sinai, Sam, Edwards, Lindsay, Gaudelet, Thomas, Regep, Cristian, Steinegger, Martin, Rost, Burkhard, Brace, Alexander, Hippe, Kyle, Naef, Luca, Kamata, Keisuke, Armstrong, George, Boyd, Kevin, Cao, Zhonglin, Chou, Han-Yi, Chu, Simon, Costa, Allan dos Santos, Darabi, Sajad, Dawson, Eric, Didi, Kieran, Fu, Cong, Geiger, Mario, Gill, Michelle, Hsu, Darren, Kaushik, Gagan, Korshunova, Maria, Kothen-Hill, Steven, Lee, Youhan, Liu, Meng, Livne, Micha, McClure, Zachary, Mitchell, Jonathan, Moradzadeh, Alireza, Mosafi, Ohad, Nashed, Youssef, Paliwal, Saee, Peng, Yuxing, Rabhi, Sara, Ramezanghorbani, Farhad, Reidenbach, Danny, Ricketts, Camir, Roland, Brian, Shah, Kushal, Shimko, Tyler, Sirelkhatim, Hassan, Srinivasan, Savitha, Stern, Abraham C, Toczydlowska, Dorota, Veccham, Srimukh Prasad, Venanzi, Niccolò Alberto Elia, Vorontsov, Anton, Wilber, Jared, Wilkinson, Isabel, Wong, Wei Jing, Xue, Eva, Ye, Cory, Yu, Xin, Zhang, Yang, Zhou, Guoqing, Zandstein, Becca, Dallago, Christian, Trentini, Bruno, Kucukbenli, Emine, Rvachov, Timur, Calleja, Eddie, Israeli, Johnny, Clifford, Harry, Haukioja, Risto, Haemel, Nicholas, Tretina, Kyle, Tadimeti, Neha, and Costa, Anthony B
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Computer Science - Machine Learning ,Quantitative Biology - Biomolecules - Abstract
Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increasingly relies on computational scale, with recent protein language models (pLM) training on hundreds of graphical processing units (GPUs). We introduce the BioNeMo Framework to facilitate the training of computational biology and chemistry AI models across hundreds of GPUs. Its modular design allows the integration of individual components, such as data loaders, into existing workflows and is open to community contributions. We detail technical features of the BioNeMo Framework through use cases such as pLM pre-training and fine-tuning. On 256 NVIDIA A100s, BioNeMo Framework trains a three billion parameter BERT-based pLM on over one trillion tokens in 4.2 days. The BioNeMo Framework is open-source and free for everyone to use.
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- 2024
20. A generalization of the martingale property of entropy production in stochastic systems
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Li, Xiangting and Chou, Tom
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Condensed Matter - Statistical Mechanics ,Mathematical Physics ,Mathematics - Probability ,60H30 - Abstract
By decoupling forward and backward stochastic trajectories, we develop a family of martingales and work theorems for the same stochastic process. We achieve this by introducing an alternative work theorem derivation that uses tools from stochastic calculus instead of path integrals. Our derivation applies to both overdamped and underdamped Langevin dynamics and generalizes work theorems so that they connect new quantities in stochastic processes, potentially revealing new applications in dissipative systems.
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- 2024
21. Receiver Noise in Axion Haloscopes
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Guzzetti, M., Zhang, D., Goodman, C., Hanretty, C., Sinnis, J., Rosenberg, L. J, Rybka, G., Clarke, John, Siddiqi, I., Chou, A. S., Hollister, M., Knirck, S., Sonnenschein, A., Caligiure, T. J., Gleason, J. R., Hipp, A. T., Sikivie, P., Solano, M. E., Sullivan, N. S., Tanner, D. B., Khatiwada, R., Carosi, G., Du, N., Cisneros, C., Robertson, N., Woollett, N., Duffy, L. D., Boutan, C., Braine, T., Oblath, N. S., Taubman, M. S., Lentz, E., Daw, E. J., Mostyn, C., Perry, M. G., Bartram, C., Dyson, T. A., Kuo, C. L., Ruppert, S., Withers, M. O., Yi, A. K., McAllister, B. T., Buckley, J. H., Gaikwad, C., Hoffman, J., Murch, K., Russell, J., Goryachev, M., Hartman, E., Quiskamp, A., and Tobar, M. E.
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High Energy Physics - Experiment - Abstract
Axions are a well-motivated candidate for dark matter. The preeminent method to search for axion dark matter is known as the axion haloscope, which makes use of the conversion of axions to photons in a large magnetic field. Due to the weak coupling of axions to photons however, the expected signal strength is exceptionally small. To increase signal strength, many haloscopes make use of resonant enhancement and high gain amplifiers, while also taking measures to keep receiver noise as low as possible such as the use of dilution refrigerators and ultra low-noise electronics. In this paper we derive the theoretical noise model based on the sources of noise found within a typical axion haloscope receiver chain, using the Axion Dark Matter eXperiment (ADMX) as a case study. We present examples of different noise calibration measurements at 1280~MHz using a variable temperature stage with ADMX during its most recent data taking run. The consistency between the measurements and the detailed model provide suggestions for future improvements within ADMX and other axion haloscopes to reach a lower noise temperature and to simplify the receiver chain design.
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- 2024
22. Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data
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Ge, F., Millea, M., Camphuis, E., Daley, C., Huang, N., Omori, Y., Quan, W., Anderes, E., Anderson, A. J., Ansarinejad, B., Archipley, M., Balkenhol, L., Benabed, K., Bender, A. N., Benson, B. A., Bianchini, F., Bleem, L. E., Bouchet, F. R., Bryant, L., Carlstrom, J. E., Chang, C. L., Chaubal, P., Chen, G., Chichura, P. M., Chokshi, A., Chou, T. -L., Coerver, A., Crawford, T. M., de Haan, T., Dibert, K. R., Dobbs, M. A., Doohan, M., Doussot, A., Dutcher, D., Everett, W., Feng, C., Ferguson, K. R., Fichman, K., Foster, A., Galli, S., Gambrel, A. E., Gardner, R. W., Goeckner-Wald, N., Gualtieri, R., Guidi, F., Guns, S., Halverson, N. W., Hivon, E., Holder, G. P., Holzapfel, W. L., Hood, J. C., Howe, D., Hryciuk, A., Kéruzoré, F., Khalife, A. R., Knox, L., Korman, M., Kornoelje, K., Kuo, C. -L., Lee, A. T., Levy, K., Lowitz, A. E., Lu, C., Maniyar, A., Martsen, E. S., Menanteau, F., Montgomery, J., Nakato, Y., Natoli, T., Noble, G. I., Pan, Z., Paschos, P., Phadke, K. A., Pollak, A. W., Prabhu, K., Rahimi, M., Rahlin, A., Reichardt, C. L., Riebel, D., Rouble, M., Ruhl, J. E., Schiappucci, E., Sobrin, J. A., Stark, A. A., Stephen, J., Tandoi, C., Thorne, B., Trendafilova, C., Umilta, C., Vieira, J. D., Vitrier, A., Wan, Y., Whitehorn, N., Wu, W. L. K., Young, M. R., and Zebrowski, J. A.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
From CMB polarization data alone we reconstruct the CMB lensing power spectrum, comparable in overall constraining power to previous temperature-based reconstructions, and an unlensed E-mode power spectrum. The observations, taken in 2019 and 2020 with the South Pole Telescope (SPT) and the SPT-3G camera, cover 1500 deg$^2$ at 95, 150, and 220 GHz with arcminute resolution and roughly 4.9$\mu$K-arcmin coadded noise in polarization. The power spectrum estimates, together with systematic parameter estimates and a joint covariance matrix, follow from a Bayesian analysis using the Marginal Unbiased Score Expansion (MUSE) method. The E-mode spectrum at $\ell>2000$ and lensing spectrum at $L>350$ are the most precise to date. Assuming the $\Lambda$CDM model, and using only these SPT data and priors on $\tau$ and absolute calibration from Planck, we find $H_0=66.81\pm0.81$ km/s/Mpc, comparable in precision to the Planck determination and in 5.4$\sigma$ tension with the most precise $H_0$ inference derived via the distance ladder. We also find $S_8=0.850\pm0.017$, providing further independent evidence of a slight tension with low-redshift structure probes. The $\Lambda$CDM model provides a good simultaneous fit to the combined Planck, ACT, and SPT data, and thus passes a powerful test. Combining these CMB datasets with BAO observations, we find that the effective number of neutrino species, spatial curvature, and primordial helium fraction are consistent with standard model values, and that the 95% confidence upper limit on the neutrino mass sum is 0.075 eV. The SPT data are consistent with the somewhat weak preference for excess lensing power seen in Planck and ACT data relative to predictions of the $\Lambda$CDM model. We also detect at greater than 3$\sigma$ the influence of non-linear evolution in the CMB lensing power spectrum and discuss it in the context of the $S_8$ tension.(abridged), Comment: 28 pages, 21 figures + appendices
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- 2024
23. Multiuser Commitment over Noisy Channels
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Chou, Remi A. and Bloch, Matthieu R.
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Computer Science - Information Theory ,Computer Science - Cryptography and Security - Abstract
We consider multi-user commitment models that capture the problem of enabling multiple bidders to simultaneously submit auctions to verifiers while ensuring that i) verifiers do not obtain information on the auctions until bidders reveal them at a later stage; and, ii) bidders cannot change their auction once committed. Specifically, we assume that bidders and verifiers have access to a noiseless channel as well as a noisy multiple-access channel or broadcast channel, where inputs are controlled by the bidders and outputs are observed by verifiers. In the case of multiple bidders and a single verifier connected by a non-redundant multiple-access channel, we characterize the commitment capacity region when bidders are not colluding. When the bidders are colluding, we derive an achievable region and a tight converse for the sum rate. In both cases our proposed achievable commitment schemes are constructive. In the case of a single bidder and multiple verifiers connected by a non-redundant broadcast channel, in which verifiers could drop out of the network after auctions are committed, we also characterize the commitment capacity. Our results demonstrate how commitment schemes can benefit from multi-user protocols, and develop resilience when some verifiers may become unavailable.
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- 2024
24. Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
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Bassi, Pedro R. A. S., Li, Wenxuan, Tang, Yucheng, Isensee, Fabian, Wang, Zifu, Chen, Jieneng, Chou, Yu-Cheng, Kirchhoff, Yannick, Rokuss, Maximilian, Huang, Ziyan, Ye, Jin, He, Junjun, Wald, Tassilo, Ulrich, Constantin, Baumgartner, Michael, Roy, Saikat, Maier-Hein, Klaus H., Jaeger, Paul, Ye, Yiwen, Xie, Yutong, Zhang, Jianpeng, Chen, Ziyang, Xia, Yong, Xing, Zhaohu, Zhu, Lei, Sadegheih, Yousef, Bozorgpour, Afshin, Kumari, Pratibha, Azad, Reza, Merhof, Dorit, Shi, Pengcheng, Ma, Ting, Du, Yuxin, Bai, Fan, Huang, Tiejun, Zhao, Bo, Wang, Haonan, Li, Xiaomeng, Gu, Hanxue, Dong, Haoyu, Yang, Jichen, Mazurowski, Maciej A., Gupta, Saumya, Wu, Linshan, Zhuang, Jiaxin, Chen, Hao, Roth, Holger, Xu, Daguang, Blaschko, Matthew B., Decherchi, Sergio, Cavalli, Andrea, Yuille, Alan L., and Zhou, Zongwei
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified metrics, unfair comparisons, and short-term outcome pressure. As a consequence, good performance on standard benchmarks does not guarantee success in real-world scenarios. To address these problems, we present Touchstone, a large-scale collaborative segmentation benchmark of 9 types of abdominal organs. This benchmark is based on 5,195 training CT scans from 76 hospitals around the world and 5,903 testing CT scans from 11 additional hospitals. This diverse test set enhances the statistical significance of benchmark results and rigorously evaluates AI algorithms across various out-of-distribution scenarios. We invited 14 inventors of 19 AI algorithms to train their algorithms, while our team, as a third party, independently evaluated these algorithms on three test sets. In addition, we also evaluated pre-existing AI frameworks--which, differing from algorithms, are more flexible and can support different algorithms--including MONAI from NVIDIA, nnU-Net from DKFZ, and numerous other open-source frameworks. We are committed to expanding this benchmark to encourage more innovation of AI algorithms for the medical domain., Comment: Accepted to NeurIPS-2024
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- 2024
25. Detection of Thermal Emission at Millimeter Wavelengths from Low-Earth Orbit Satellites
- Author
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Foster, A., Chokshi, A., Anderson, A. J., Ansarinejad, B., Archipley, M., Balkenhol, L., Benabed, K., Bender, A. N., Barron, D. R., Benson, B. A., Bianchini, F., Bleem, L. E., Bouchet, F. R., Bryant, L., Camphuis, E., Carlstrom, J. E., Chang, C. L., Chaubal, P., Chichura, P. M., Chou, T. -L., Coerver, A., Crawford, T. M., Daley, C., de Haan, T., Dibert, K. R., Dobbs, M. A., Doussot, A., Dutcher, D., Everett, W., Feng, C., Ferguson, K. R., Fichman, K., Galli, S., Gambrel, A. E., Gardner, R. W., Ge, F., Goeckner-Wald, N., Gualtieri, R., Guidi, F., Guns, S., Halverson, N. W., Hivon, E., Holder, G. P., Holzapfel, W. L., Hood, J. C., Hryciuk, A., Huang, N., Kéruzoré, F., Khalife, A. R., Knox, L., Korman, M., Kornoelje, K., Kuo, C. -L., Levy, K., Lowitz, A. E., Lu, C., Maniyar, A., Martsen, E. S., Menanteau, F., Millea, M., Montgomery, J., Nakato, Y., Natoli, T., Noble, G. I., Omori, Y., Pan, Z., Paschos, P., Phadke, K. A., Pollak, A. W., Prabhu, K., Quan, W., Raghunathan, S., Rahimi, M., Rahlin, A., Reichardt, C. L., Rouble, M., Ruhl, J. E., Schiappucci, E., Sobrin, J. A., Stark, A. A., Stephen, J., Tandoi, C., Thorne, B., Trendafilova, C., Umilta, C., Vieira, J. D., Vitrier, A., Wan, Y., Whitehorn, N., Wu, W. L. K., Young, M. R., and Zebrowski, J. A.
- Subjects
Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
The detection of satellite thermal emission at millimeter wavelengths is presented using data from the 3rd-Generation receiver on the South Pole Telescope (SPT-3G). This represents the first reported detection of thermal emission from artificial satellites at millimeter wavelengths. Satellite thermal emission is shown to be detectable at high signal-to-noise on timescales as short as a few tens of milliseconds. An algorithm for downloading orbital information and tracking known satellites given observer constraints and time-ordered observatory pointing is described. Consequences for cosmological surveys and short-duration transient searches are discussed, revealing that the integrated thermal emission from all large satellites does not contribute significantly to the SPT-3G survey intensity map. Measured satellite positions are found to be discrepant from their two-line element (TLE) derived ephemerides up to several arcminutes which may present a difficulty in cross-checking or masking satellites from short-duration transient searches.
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- 2024
26. Semantic Knowledge Distillation for Onboard Satellite Earth Observation Image Classification
- Author
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Le, Thanh-Dung, Ha, Vu Nguyen, Nguyen, Ti Ti, Eappen, Geoffrey, Thiruvasagam, Prabhu, Chou, Hong-fu, Tran, Duc-Dung, Garces-Socarras, Luis M., Gonzalez-Rios, Jorge L., Merlano-Duncan, Juan Carlos, and Chatzinotas, Symeon
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Signal Processing - Abstract
This study presents an innovative dynamic weighting knowledge distillation (KD) framework tailored for efficient Earth observation (EO) image classification (IC) in resource-constrained settings. Utilizing EfficientViT and MobileViT as teacher models, this framework enables lightweight student models, particularly ResNet8 and ResNet16, to surpass 90% in accuracy, precision, and recall, adhering to the stringent confidence thresholds necessary for reliable classification tasks. Unlike conventional KD methods that rely on static weight distribution, our adaptive weighting mechanism responds to each teacher model's confidence, allowing student models to prioritize more credible sources of knowledge dynamically. Remarkably, ResNet8 delivers substantial efficiency gains, achieving a 97.5% reduction in parameters, a 96.7% decrease in FLOPs, an 86.2% cut in power consumption, and a 63.5% increase in inference speed over MobileViT. This significant optimization of complexity and resource demands establishes ResNet8 as an optimal candidate for EO tasks, combining robust performance with feasibility in deployment. The confidence-based, adaptable KD approach underscores the potential of dynamic distillation strategies to yield high-performing, resource-efficient models tailored for satellite-based EO applications. The reproducible code is accessible on our GitHub repository., Comment: Under revisions
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- 2024
27. Accelerated AI Inference via Dynamic Execution Methods
- Author
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Barad, Haim, Achterberg, Jascha, Chou, Tien Pei, and Yu, Jean
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
In this paper, we focus on Dynamic Execution techniques that optimize the computation flow based on input. This aims to identify simpler problems that can be solved using fewer resources, similar to human cognition. The techniques discussed include early exit from deep networks, speculative sampling for language models, and adaptive steps for diffusion models. Experimental results demonstrate that these dynamic approaches can significantly improve latency and throughput without compromising quality. When combined with model-based optimizations, such as quantization, dynamic execution provides a powerful multi-pronged strategy to optimize AI inference. Generative AI requires a large amount of compute resources. This is expected to grow, and demand for resources in data centers through to the edge is expected to continue to increase at high rates. We take advantage of existing research and provide additional innovations for some generative optimizations. In the case of LLMs, we provide more efficient sampling methods that depend on the complexity of the data. In the case of diffusion model generation, we provide a new method that also leverages the difficulty of the input prompt to predict an optimal early stopping point. Therefore, dynamic execution methods are relevant because they add another dimension of performance optimizations. Performance is critical from a competitive point of view, but increasing capacity can result in significant power savings and cost savings. We have provided several integrations of these techniques into several Intel performance libraries and Huggingface Optimum. These integrations will make them easier to use and increase the adoption of these techniques.
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- 2024
28. Cognitive Semantic Augmentation LEO Satellite Networks for Earth Observation
- Author
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Chou, Hong-fu, Ha, Vu Nguyen, Thiruvasagam, Prabhu, Le, Thanh-Dung, Eappen, Geoffrey, Nguyen, Ti Ti, Tran, Duc Dung, Garces-Socarras, Luis M., Merlano-Duncan, Juan Carlos, and Chatzinotas, Symeon
- Subjects
Computer Science - Networking and Internet Architecture - Abstract
Earth observation (EO) systems are essential for mapping, catastrophe monitoring, and resource management, but they have trouble processing and sending large amounts of EO data efficiently, especially for specialized applications like agriculture and real-time disaster response. This paper presents a novel framework for semantic communication in EO satellite networks, aimed at enhancing data transmission efficiency and system performance through cognitive processing techniques. The proposed system leverages Discrete Task-Oriented Joint Source-Channel Coding (DT-JSCC) and Semantic Data Augmentation (SA) integrate cognitive semantic processing with inter-satellite links, enabling efficient analysis and transmission of multispectral imagery for improved object detection, pattern recognition, and real-time decision-making. Cognitive Semantic Augmentation (CSA) is introduced to enhance a system's capability to process and transmit semantic information, improving feature prioritization, consistency, and adaptation to changing communication and application needs. The end-to-end architecture is designed for next-generation satellite networks, such as those supporting 6G, demonstrating significant improvements in fewer communication rounds and better accuracy over federated learning., Comment: 8 Pages, 5 figures, Magazine. arXiv admin note: substantial text overlap with arXiv:2409.15246
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- 2024
29. Orbital Topology of Chiral Crystals for Orbitronics
- Author
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Hagiwara, Kenta, Chen, Ying-Jiun, Go, Dongwook, Tan, Xin Liang, Grytsiuk, Sergii, Yang, Kui-Hon Ou, Shu, Guo-Jiun, Chien, Jing, Shen, Yi-Hsin, Huang, Xiang-Lin, Chou, Fang-Cheng, Cojocariu, Iulia, Feyer, Vitaliy, Lin, Minn-Tsong, Blügel, Stefan, Schneider, Claus Michael, Mokrousov, Yuriy, and Tusche, Christian
- Subjects
Condensed Matter - Mesoscale and Nanoscale Physics ,Condensed Matter - Materials Science - Abstract
Chirality is ubiquitous in nature and manifests in a wide range of phenomena including chemical reactions, biological processes, and quantum transport of electrons. In quantum materials, the chirality of fermions, given by the relative directions between the electron spin and momentum, is connected to the band topology of electronic states. Here, we show that in structurally chiral materials like CoSi, the orbital angular momentum (OAM) serves as the main driver of a nontrivial band topology in this new class of unconventional topological semimetals, even when spin-orbit coupling is negligible. A nontrivial orbital-momentum locking of multifold chiral fermions in the bulk leads to a pronounced OAM texture of the helicoid Fermi arcs at the surface. Our findings highlight the pivotal role of the orbital degree of freedom for the chirality and topology of electron states, in general, and pave the way towards the application of topological chiral semimetals in orbitronic devices.
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- 2024
30. Search for gravitational waves emitted from SN 2023ixf
- Author
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The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. 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W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singh, S., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Smith, W. J., Soldateschi, J., Somiya, K., Song, I., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Sotani, H., Soulard, R., Southgate, A., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Spoon, J. B., Sprague, C. A., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Suleiman, L., Sullivan, K. D., Sun, L., Sunil, S., Suresh, J., Sutton, P. J., Suzuki, T., Suzuki, Y., Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takase, T., Takatani, K., Takeda, H., Takeshita, K., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, P., Tiwari, S., Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trapananti, A., Travasso, F., Traylor, G., Trevor, M., Tringali, M. C., Tripathee, A., Troian, G., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Uchikata, N., Uchiyama, T., Udall, R. P., Uehara, T., Uematsu, M., Ueno, K., Ueno, S., Undheim, V., Ushiba, T., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Van Hove, P., VanKeuren, M., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varghese, J. J., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vives, A., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Wajid, A., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B. R., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Wilkin, A. T., Willadsen, D. J., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Winterflood, J., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wuchner, E., Wysocki, D. M., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, Y., Yarbrough, Z., Yasui, H., Yeh, S. -W., Yelikar, A. B., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuan, S., Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, X. -J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
- Subjects
Astrophysics - High Energy Astrophysical Phenomena - Abstract
We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered $\sim 14\%$ of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave emission mechanism of core-collapse supernovae across a broad frequency spectrum, ranging from 50 Hz to 2 kHz where we assume the GW emission occurred when coincident data are available in the on-source window. Considering an ellipsoid model for a rotating proto-neutron star, our search is sensitive to gravitational-wave energy $1 \times 10^{-5} M_{\odot} c^2$ and luminosity $4 \times 10^{-5} M_{\odot} c^2/\text{s}$ for a source emitting at 50 Hz. These constraints are around an order of magnitude more stringent than those obtained so far with gravitational-wave data. The constraint on the ellipticity of the proto-neutron star that is formed is as low as $1.04$, at frequencies above $1200$ Hz, surpassing results from SN 2019ejj., Comment: Main paper: 6 pages, 4 figures and 1 table. Total with appendices: 20 pages, 4 figures, and 1 table
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- 2024
31. Large Language Models for Energy-Efficient Code: Emerging Results and Future Directions
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Peng, Huiyun, Gupte, Arjun, Eliopoulos, Nicholas John, Ho, Chien Chou, Mantri, Rishi, Deng, Leo, Jiang, Wenxin, Lu, Yung-Hsiang, Läufer, Konstantin, Thiruvathukal, George K., and Davis, James C.
- Subjects
Computer Science - Software Engineering - Abstract
Energy-efficient software helps improve mobile device experiences and reduce the carbon footprint of data centers. However, energy goals are often de-prioritized in order to meet other requirements. We take inspiration from recent work exploring the use of large language models (LLMs) for different software engineering activities. We propose a novel application of LLMs: as code optimizers for energy efficiency. We describe and evaluate a prototype, finding that over 6 small programs our system can improve energy efficiency in 3 of them, up to 2x better than compiler optimizations alone. From our experience, we identify some of the challenges of energy-efficient LLM code optimization and propose a research agenda.
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- 2024
32. Search for non-virialized axions with 3.3-4.2 $\mu$eV mass at selected resolving powers
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Hipp, A. T., Quiskamp, A., Caligiure, T. J., Gleason, J. R., Han, Y., Jois, S., Sikivie, P., Solano, M. E., Sullivan, N. S., Tanner, D. B., Goryachev, M., Hartman, E., Tobar, M. E., McAllister, B. T., Duffy, L. D., Braine, T., Burns, E., Cervantes, R., Crisosto, N., Goodman, C., Guzzetti, M., Hanretty, C., Lee, S., Korandla, H., Leum, G., Mohapatra, P., Nitta, T., Rosenberg, L. J, Rybka, G., Sinnis, J., Zhang, D., Bartram, C., Dyson, T. A., Kuo, C. L., Ruppert, S., Withers, M. O., Awida, M. H., Bowring, D., Chou, A. S., Hollister, M., Knirck, S., Sonnenschein, A., Wester, W., Brodsky, J., Carosi, G., Du, N., Roberston, N., Woollett, N., Boutan, C., Jones, A. M., LaRoque, B. H., Lentz, E., Man, N. E., Oblath, N. S., Taubman, M. S., Yang, J., Khatiwada, R., Clarke, John, Siddiqi, I., Agrawal, A., Dixit, A. V., Daw, E. J., Perry, M. G., Buckley, J. H., Gaikwad, C., Hoffman, J., Murch, K. W., and Russell, J.
- Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
The Axion Dark Matter eXperiment is sensitive to narrow axion flows, given axions compose a fraction of the dark matter with a non-negligible local density. Detecting these low-velocity dispersion flows requires a high spectral resolution and careful attention to the expected signal modulation due to Earth's motion. We report an exclusion on the local axion dark matter density in narrow flows of $\rho_a \gtrsim 0.03\,\mathrm{GeV/cm^3}$ and $\rho_a \gtrsim 0.004\,\mathrm{GeV/cm^3}$ for Dine-Fischler-Srednicki-Zhitnitski and Kim-Shifman-Vainshtein-Zakharov axion-photon couplings, respectively, over the mass range $3.3-4.2\,\mu\text{eV}$. Measurements were made at selected resolving powers to allow for a range of possible velocity dispersions., Comment: 7 pages, 3 figures
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- 2024
33. A search using GEO600 for gravitational waves coincident with fast radio bursts from SGR 1935+2154
- Author
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The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Azrad, D., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R. ., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghonge, S., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. 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- Subjects
Astrophysics - High Energy Astrophysical Phenomena - Abstract
The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by CHIME/FRB, as well as X-ray glitches and X-ray bursts detected by NICER and NuSTAR close to the time of one of the FRBs. We do not detect any significant GW emission from any of the events. Instead, using a short-duration GW search (for bursts $\leq$ 1 s) we derive 50\% (90\%) upper limits of $10^{48}$ ($10^{49}$) erg for GWs at 300 Hz and $10^{49}$ ($10^{50}$) erg at 2 kHz, and constrain the GW-to-radio energy ratio to $\leq 10^{14} - 10^{16}$. We also derive upper limits from a long-duration search for bursts with durations between 1 and 10 s. These represent the strictest upper limits on concurrent GW emission from FRBs., Comment: 15 pages of text including references, 4 figures, 5 tables
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- 2024
34. Bots can Snoop: Uncovering and Mitigating Privacy Risks of Bots in Group Chats
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Chou, Kai-Hsiang, Lin, Yi-Min, Wang, Yi-An, Li, Jonathan Weiping, Kim, Tiffany Hyun-Jin, and Hsiao, Hsu-Chun
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Computer Science - Cryptography and Security - Abstract
New privacy concerns arise with chatbots on group messaging platforms. Chatbots may access information beyond their intended functionalities, such as messages unintended for chatbots or sender's identities. Chatbot operators may exploit such information to infer personal information and link users across groups, potentially leading to personal data breaches, pervasive tracking, and targeted advertising. Our analysis of conversation datasets shows that (1) chatbots often access far more messages than needed, and (2) when a user joins a new group with chatbots, there is a 3.4% chance that at least one of the chatbots can recognize and associate the user with their previous interactions in other groups. Although state-of-the-art group messaging protocols provide robust end-to-end security and some platforms have implemented policies to limit chatbot access, no platforms successfully combine these features. This paper introduces SnoopGuard, a secure group messaging protocol that ensures user privacy against chatbots while maintaining strong end-to-end security. Our method offers selective message access, preventing chatbots from accessing unrelated messages, and ensures sender anonymity within the group. SnoopGuard achieves $O(\log n + m)$ message-sending complexity for a group of $n$ users and $m$ chatbots, compared to $O(\log(n + m))$ in state-of-the-art protocols, with acceptable overhead for enhanced privacy. Our prototype implementation shows that sending a message in a group of 50 users and 10 chatbots takes about 30 milliseconds when integrated with Message Layer Security (MLS)., Comment: 18 pages, 5 figures
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- 2024
35. MM-R$^3$: On (In-)Consistency of Multi-modal Large Language Models (MLLMs)
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Chou, Shih-Han, Chandhok, Shivam, Little, James J., and Sigal, Leonid
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Computer Science - Computer Vision and Pattern Recognition - Abstract
With the advent of Large Language Models (LLMs) and Multimodal (Visio-lingual) LLMs, a flurry of research has emerged, analyzing the performance of such models across a diverse array of tasks. While most studies focus on evaluating the capabilities of state-of-the-art (SoTA) MLLM models through task accuracy (e.g., Visual Question Answering, grounding) across various datasets, our work explores the related but complementary aspect of consistency - the ability of an MLLM model to produce semantically similar or identical responses to semantically similar queries. We note that consistency is a fundamental prerequisite (necessary but not sufficient condition) for robustness and trust in MLLMs. Humans, in particular, are known to be highly consistent (even if not always accurate) in their responses, and consistency is inherently expected from AI systems. Armed with this perspective, we propose the MM-R$^3$ benchmark, which analyses the performance in terms of consistency and accuracy in SoTA MLLMs with three tasks: Question Rephrasing, Image Restyling, and Context Reasoning. Our analysis reveals that consistency does not always align with accuracy, indicating that models with higher accuracy are not necessarily more consistent, and vice versa. Furthermore, we propose a simple yet effective mitigation strategy in the form of an adapter module trained to minimize inconsistency across prompts. With our proposed strategy, we are able to achieve absolute improvements of 5.7% and 12.5%, on average on widely used MLLMs such as BLIP-2 and LLaVa 1.5M in terms of consistency over their existing counterparts.
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- 2024
36. ScriptViz: A Visualization Tool to Aid Scriptwriting based on a Large Movie Database
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Rao, Anyi, Chou, Jean-Peïc, and Agrawala, Maneesh
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Computer Science - Human-Computer Interaction ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Graphics - Abstract
Scriptwriters usually rely on their mental visualization to create a vivid story by using their imagination to see, feel, and experience the scenes they are writing. Besides mental visualization, they often refer to existing images or scenes in movies and analyze the visual elements to create a certain mood or atmosphere. In this paper, we develop ScriptViz to provide external visualization based on a large movie database for the screenwriting process. It retrieves reference visuals on the fly based on scripts' text and dialogue from a large movie database. The tool provides two types of control on visual elements that enable writers to 1) see exactly what they want with fixed visual elements and 2) see variances in uncertain elements. User evaluation among 15 scriptwriters shows that ScriptViz is able to present scriptwriters with consistent yet diverse visual possibilities, aligning closely with their scripts and helping their creation., Comment: Accepted in the 37th Annual ACM Symposium on User Interface Software and Technology (UIST'24). Webpage: https://virtualfilmstudio.github.io/projects/scriptviz
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- 2024
37. FAIR Universe HiggsML Uncertainty Challenge Competition
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Bhimji, Wahid, Calafiura, Paolo, Chakkappai, Ragansu, Chou, Yuan-Tang, Diefenbacher, Sascha, Dudley, Jordan, Farrell, Steven, Ghosh, Aishik, Guyon, Isabelle, Harris, Chris, Hsu, Shih-Chieh, Khoda, Elham E, Lyscar, Rémy, Michon, Alexandre, Nachman, Benjamin, Nugent, Peter, Reymond, Mathis, Rousseau, David, Sluijter, Benjamin, Thorne, Benjamin, Ullah, Ihsan, and Zhang, Yulei
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High Energy Physics - Phenomenology ,Computer Science - Machine Learning ,High Energy Physics - Experiment ,Physics - Data Analysis, Statistics and Probability - Abstract
The FAIR Universe -- HiggsML Uncertainty Challenge focuses on measuring the physics properties of elementary particles with imperfect simulators due to differences in modelling systematic errors. Additionally, the challenge is leveraging a large-compute-scale AI platform for sharing datasets, training models, and hosting machine learning competitions. Our challenge brings together the physics and machine learning communities to advance our understanding and methodologies in handling systematic (epistemic) uncertainties within AI techniques., Comment: Whitepaper for the FAIR Universe HiggsML Uncertainty Challenge Competition, available : https://fair-universe.lbl.gov
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- 2024
38. Constraining cosmology with N-body simulations for future spectroscopic galaxy surveys at $2\leq z\leq 3$
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Pu, Sy-Yun, Okumura, Teppei, Chen, Chian-Chou, Nishimichi, Takahiro, and Akitsu, Kazuyuki
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Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - Astrophysics of Galaxies - Abstract
Determining the spatial curvature ($\Omega_k$) independent of cosmic microwave background observations plays a key role in revealing the physics of the early universe. The Hubble tension is one of the most serious issues in modern cosmology. We investigate halo catalogs identified from $N$-body simulations at $z=2$ and 3, mimicking high-redshift galaxy surveys. We measure redshift-space correlation functions of halos from the two snapshots. We detect clear features of baryon acoustic oscillations and redshift-space distortions. We find that we can obtain a few percent constraints on both the geometric distances and growth of structure at the distant universe in future surveys. By taking into account the information of the underlying matter power spectrum, we demonstrate that we can also achieve constraint on the Hubble constant $H_0$ with a few percent as well as the spatial curvature with $|\Omega_k|\lesssim 0.1$ by observing galaxies with the number density with $\bar{n}_{\rm g}\simeq 10^{-4} (~h^3{\rm ~Mpc}^{-3})$. Our analysis provides a timely forecast for the upcoming spectroscopic surveys, which target emission line galaxy or dusty star-forming galaxy samples., Comment: 8 pages, 4 figures, 3 tables; references and results updated; typos corrected
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- 2024
39. Equivariant cohomology of Grassmannian spanning lines
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Chou, Raymond, Matsumura, Tomoo, and Rhoades, Brendon
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Mathematics - Combinatorics ,Mathematics - Algebraic Geometry - Abstract
Given integers $n \geq k \geq d$, let $X_{n,k,d}$ be the moduli space of $n$-tuples of lines $(\ell_1, \dots, \ell_n)$ in $\mathbb{C}^k$ such that $\ell_1 + \cdots + \ell_n$ has dimension $d$. We give a quotient presentation of the torus-equivariant cohomology of $X_{n,k,d}$. The form of this presentation, and in particular the torus parameters appearing therein, will arise from the orbit harmonics method of combinatorial deformation theory., Comment: 30 pages
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- 2024
40. Examining Key Determinants of Social Presence and Satisfaction in Online Learning: An Exploration with Undergraduate Student
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Sandrotua Bali, Ming-Chou Liu, and Harmita Sari
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The increasing popularity of online learning and its associated technology in higher education, particularly due to the COVID-19 pandemic, has garnered significant attention worldwide. This study focuses on investigating and developing the construct of social presence and its relationship with satisfaction in computerized learning environments. The study explores various dimensions of social presence, including social respect, social sharing, open communication, and social navigation, and their impact on satisfaction in online learning. The findings demonstrate that social presence plays a significant role in influencing satisfaction, and a statistically significant correlation exists among the observed variables. The implications of these results are important for higher education institutions, instructional designers, instructors, and learners. This study also provides valuable theoretical foundations for further discussions on social presence and satisfaction in online learning. To effectively meet learners' expectations and enhance social presence and satisfaction, higher education institutions offering online programs should understand their learners' needs. Instructors can contribute to learners' engagement and success by strategically incorporating instructional course designs, arranging materials, and generating clear learning activities that enhance social presence. By providing a high level of social presence in online learning environments, instructors can promote student satisfaction and facilitate effective comprehension of learning materials.
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- 2024
41. Live-Streaming Performance in Inquiry-Based Science Learning with Action: Teachers' Perspectives
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Jon-Chao Hong, Huei-Ying Ho, Ming-Chou Liu, and Kai-Hsin Tai
- Abstract
Online teaching has become an imperative approach in today's society. However, as an essential approach, using live streaming to teach students in small groups, particularly rural primary school students, has not been extensively studied. To address this gap, an inquiry-based model, predict-do/observe-quiz/discuss-explain-transfer (P-D/O-Q/D-E-T), was adopted for live streaming with action, and its performance was analysed. Reflection by teachers can lead them to a deeper understanding to capture the profound impact of an educational program. In the present study, eight teachers who had experience assisting rural students in this experiment were invited to rate their points of view on immersion, social interactivity, humanness, and value perception. Examining the consistency of teachers' viewpoints using the hermeneutic method, the results showed that they highly supported viewing these four constructs using live streaming to conduct inquiry-based science learning with action. As expected, using live streaming to deliver teaching with the P-D/O-Q/D-E-T approach can enrich other online science teaching.
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- 2024
42. The Effects of Live-Streaming Presence and Extraneous Cognitive Load on Learning Performance in P-D/O-Q/D-E-T Inquiry
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Jon-Chao Hong, Ming-Chou Liu, Huei-Ying Ho, Chi-Ruei Tsai, and Kai-Hsin Tai
- Abstract
By using information technology, science learning can be widely disseminated, including, for example, to rural schools. However, the implementation of inquiry-based science learning with action-to-ground science concepts for rural learners needs to be explored. To address this purpose, the present study adopted "live stream" technology with a science inquiry model for rural students to learn four science concepts. Using different science knowledge representations, the predict-do/observe-quiz/discuss-explain-transform (P-D/O-Q/D-E-T) inquiry model was designed to be implemented via live streaming with local teachers' facilitation. Drawing on the cognitive-affective theory of multimedia learning and triadic reciprocal determinism, the present study focused on exploring how the live-streaming presence and external cognitive load can predict participants' flow and learning performance. A total of 45 participants completed the questionnaire, pre-test, and post-test, and structural equation modeling was adopted to test the hypotheses of this study. The results showed that live-streaming presence could positively predict flow, but external cognitive load can negatively predict flow, while flow can positively predict learning performance. This live-streaming method uses inexpensive and affordable educational technology that can be implemented at any rural elementary school to enable rural students to learn science remotely.
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- 2024
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43. Contrasting Patterns of Population Genomic Structure Between Broadcast-Spawning and Brooding Corals in Southeast Asia
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Afiq-Rosli, Lutfi, Wainwright, Benjamin J., Lee, Jen Nie, Waheed, Zarinah, Chou, Loke Ming, and Huang, Danwei
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- 2024
44. Patients Can Administer Mobile Audio Recordings to Increase Knowledge in Advanced Prostate Cancer.
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Kwon, Daniel, Trihy, Lauren, Darvish, Nika, Hearst, Eliza, Sumra, Saffanat, Borno, Hala, Bose, Rohit, Chou, Jonathan, de Kouchkovsky, Ivan, Desai, Arpita, Ekstrand, Brad, Friedlander, Terence, Kaur, Gurleen, Koshkin, Vadim, Nesheiwat, Samantha, Sepucha, Karen, Small, Eric, Aggarwal, Rahul, and Belkora, Jeffrey
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implementation science ,palliative care ,patient education ,patient knowledge ,prostate cancer ,recordings ,shared decision‐making ,Aged ,Humans ,Male ,Appointments and Schedules ,Decision Making ,Docetaxel ,Health Knowledge ,Attitudes ,Practice ,Mobile Applications ,Patient Education as Topic ,Prostatic Neoplasms ,Surveys and Questionnaires ,Tape Recording ,Aged ,80 and over - Abstract
INTRODUCTION: Consultation audio recordings improve patient decision-making but are underutilized. Patient-administered recording apps on mobile devices may increase access, but implementation has not been evaluated. METHODS: We conducted a single-arm study delivering education, coaching, and reminders for patients to record their appointment using a mobile recording app. Patients had progressive, advanced prostate cancer and an upcoming appointment where the option of docetaxel would be discussed. We used the RE-AIM framework for evaluation. Reach was the proportion of patients who participated. Effectiveness was change in informed decision-making pre- vs. post-appointment. We used a questionnaire evaluating patient knowledge about docetaxel (0%-100% correct) and the decisional conflict scale-informed subscale (0 = feels extremely uninformed to 100 = extremely informed) to compare means using the paired t-test. Adoption was the proportion of providers agreeing to be recorded. Implementation was coordinator adherence to intervention delivery. We conducted semistructured interviews with patients, caregivers, and providers to assess barriers, facilitators, and suggestions for recording implementation. RESULTS: Of 102 patients approached, 50 (49%) patients participated. Mean age was 75 years, 38 (76%) were Non-Hispanic White, and 43 (86%) had telehealth appointments. Knowledge increased from 44.7% to 49.5% (p = 0.019), particularly about palliative care (42% answering correctly to 60%, p = 0.035). Decisional conflict-informed subscale increased from 48.9 to 70.9 (p
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- 2024
45. Platelet releasates mitigate the endotheliopathy of trauma.
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Gallagher, Lauren, LaCroix, Ian, Fields, Alexander, Mitra, Sanchayita, Argabright, Amy, DAlessandro, Angelo, Erickson, Christopher, Nunez-Garcia, Brenda, Herrera-Rodriguez, Kimberly, Chou, Yu, Stocker, Benjamin, Ramser, Benjamin, Thielen, Otto, Hallas, William, Silliman, Christopher, Kornblith, Lucy, and Cohen, Mitchell
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Humans ,Blood Platelets ,Wounds and Injuries ,Male ,Adult ,Female ,Platelet Activation ,Endothelium ,Vascular ,Metabolomics ,Endothelial Cells - Abstract
BACKGROUND: Platelets are well known for their roles in hemostasis, but they also play a key role in thromboinflammatory pathways by regulating endothelial health, stimulating angiogenesis, and mediating host defense through both contact dependent and independent signaling. When activated, platelets degranulate releasing multiple active substances. We hypothesized that the soluble environment formed by trauma platelet releasates (TPR) attenuates thromboinflammation via mitigation of trauma induced endothelial permeability and metabolomic reprogramming. METHODS: Blood was collected from injured and healthy patients to generate platelet releasates and plasma in parallel. Permeability of endothelial cells when exposed to TPR and plasma (TP) was assessed via resistance measurement by electric cell-substrate impedance sensing (ECIS). Endothelial cells treated with TPR and TP were subjected to mass spectrometry-based metabolomics. RESULTS: TP increased endothelial permeability, whereas TPR decreased endothelial permeability when compared with untreated cells. When TP and TPR were mixed ex vivo, TPR mitigated TP-induced permeability, with significant increase in AUC compared with TP alone. Metabolomics of TPR and TP demonstrated disrupted redox reactions and anti-inflammatory mechanisms. CONCLUSION: Trauma platelet releasates provide endothelial barrier protection against TP-induced endothelial permeability. Our findings highlight a potential beneficial action of activated platelets on the endothelium in injured patients through disrupted redox reactions and increased antioxidants. Our findings support that soluble signaling from platelet degranulation may mitigate the endotheliopathy of trauma. The clinical implications of this are that activated platelets may prove a promising therapeutic target in the complex integration of thrombosis, endotheliopathy, and inflammation in trauma.
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- 2024
46. CDK12 loss drives prostate cancer progression, transcription-replication conflicts, and synthetic lethality with paralog CDK13.
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Tien, Jean, Luo, Jie, Chang, Yu, Zhang, Yuping, Cheng, Yunhui, Wang, Xiaoju, Yang, Jianzhang, Mannan, Rahul, Mahapatra, Somnath, Shah, Palak, Wang, Xiao-Ming, Todd, Abigail, Eyunni, Sanjana, Cheng, Caleb, Rebernick, Ryan, Xiao, Lanbo, Bao, Yi, Neiswender, James, Brough, Rachel, Pettitt, Stephen, Cao, Xuhong, Miner, Stephanie, Zhou, Licheng, Wu, Yi-Mi, Labanca, Estefania, Wang, Yuzhuo, Parolia, Abhijit, Cieslik, Marcin, Robinson, Dan, Wang, Zhen, Feng, Felix, Chou, Jonathan, Lord, Christopher, Ding, Ke, and Chinnaiyan, Arul
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CDK12 ,CDK13 ,Cdk12 knockout ,R-loops ,paralog-based synthetic lethality ,prostate cancer ,transcription-replication conflicts ,Male ,Animals ,Humans ,Cyclin-Dependent Kinases ,Mice ,Synthetic Lethal Mutations ,Prostatic Neoplasms ,Tumor Suppressor Protein p53 ,Disease Progression ,PTEN Phosphohydrolase ,Genomic Instability ,Transcription ,Genetic ,Organoids ,Prostatic Neoplasms ,Castration-Resistant ,Cell Proliferation ,DNA Replication ,Mice ,Knockout ,Cell Line ,Tumor ,Mice ,Inbred C57BL ,CDC2 Protein Kinase - Abstract
Biallelic loss of cyclin-dependent kinase 12 (CDK12) defines a metastatic castration-resistant prostate cancer (mCRPC) subtype. It remains unclear, however, whether CDK12 loss drives prostate cancer (PCa) development or uncovers pharmacologic vulnerabilities. Here, we show Cdk12 ablation in murine prostate epithelium is sufficient to induce preneoplastic lesions with lymphocytic infiltration. In allograft-based CRISPR screening, Cdk12 loss associates positively with Trp53 inactivation but negatively with Pten inactivation. Moreover, concurrent Cdk12/Trp53 ablation promotes proliferation of prostate-derived organoids, while Cdk12 knockout in Pten-null mice abrogates prostate tumor growth. In syngeneic systems, Cdk12/Trp53-null allografts exhibit luminal morphology and immune checkpoint blockade sensitivity. Mechanistically, Cdk12 inactivation mediates genomic instability by inducing transcription-replication conflicts. Strikingly, CDK12-mutant organoids and patient-derived xenografts are sensitive to inhibition or degradation of the paralog kinase, CDK13. We therein establish CDK12 as a bona fide tumor suppressor, mechanistically define how CDK12 inactivation causes genomic instability, and advance a therapeutic strategy for CDK12-mutant mCRPC.
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- 2024
47. 1.7-micron Optical Coherence Tomography Angiography for diagnosis and monitoring of Hereditary Hemorrhagic Telangiectasia - A pilot study
- Author
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Murthy, Raksha Sreeramachandra, Elsanadi, Rachel, Soliman, John, Li, Yan, Chou, Li-Dek, Sprecher, Dennis, Kelly, Kristen M, and Chen, Zhongping
- Subjects
Engineering ,Biomedical Engineering ,Information and Computing Sciences ,Electronics ,Sensors and Digital Hardware ,Computer Vision and Multimedia Computation ,Rare Diseases ,Biomedical Imaging ,Clinical Research ,Hematology ,Bioengineering ,4.2 Evaluation of markers and technologies ,Artificial Intelligence and Image Processing ,Electrical and Electronic Engineering ,Biomedical engineering ,Electronics ,sensors and digital hardware ,Computer vision and multimedia computation - Abstract
ObjectiveDevelop a multi-functional imaging system that combines 1.7μm optical coherence tomography/angiography (OCT/OCTA) to accurately interrogate Hereditary Hemorrhagic Telangiectasia (HHT) skin lesions.MethodsThe study involved imaging HHT skin lesions on five subjects including lips, hands, and chest. We assessed the attributes of both HHT lesions and the healthy vasculature around them in these individuals, employing quantifiable measures such as vascular density and diameter. Additionally, we performed scans on an HHT patient who had undergone anti-angiogenic therapy, allowing us to observe changes in vasculature before and after treatment.ResultsThe results from this pilot study demonstrate the feasibility of evaluating the HHT lesion using this novel methodology and suggest the potential of OCTA to noninvasively track HHT lesions over time. The average percentage change in density between HHT patients' lesions and control was 37%. The percentage increase in vessel diameter between lesion and control vessels in HHT patients was 23.21%.ConclusionIn this study, we demonstrated that OCTA, as a functional extension of OCT, can non-invasively scan HHT lesions in vivo. We scanned five subjects with HHT lesions in various areas (lip, ear, finger, and palm) and quantified vascular density and diameter in both the lesions and adjacent healthy tissue. This non-invasive method will permit a more comprehensive examination of HHT lesions.SignificanceThis method of non-invasive imaging could offer new insights into the physiology, management, and therapeutics of HHT-associated lesion development and bleeding.
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- 2024
48. Low-energy spin excitations in field-induced phases of the spin-ladder antiferromagnet BiCu$_2$PO$_6$
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Pilch, Patrick, Amelin, Kirill, Schmiedinghoff, Gary, Reinold, Anneke, Zhu, Changqing, Povarov, Kirill Yu., Zvyagin, Sergei, Engelkamp, Hans, Lan, Yin-Ping, Shu, Guo-Jiun, Chou, Fang-Cheng, Nagel, Urmas, Rõõm, Toomas, Uhrig, Götz S., Fauseweh, Benedikt, and Wang, Zhe
- Subjects
Condensed Matter - Strongly Correlated Electrons - Abstract
We report on terahertz spectroscopic measurements of quantum spin dynamics on single crystals of a spin-1/2 frustrated spin-ladder antiferromagnet BiCu$_2$PO$_6$ as a function of temperature, polarization, and applied external magnetic fields. Spin triplon excitations are observed at zero field and split in applied magnetic fields. For magnetic fields applied along the crystallographic $a$ axis, a quantum phase transition at $B_{c1}=21.4$~T is featured by a low-energy excitation mode emerging above $B_{c1}$ which indicates a gap reopening. For fields along the $b$ axis and the $c$ axis, different field dependencies are observed for the spin triplon excitations, whereas no low-lying modes could be resolved at field-induced phase transitions. We perform a theoretical analysis of the magnetic field dependence of the spin triplon modes by using continuous unitary transformations to determine an effective low energy Hamiltonian. Through an exhaustive parameter search we find numerically optimized parameters to very well describe the experimentally observed modes, which corroborate the importance of significant magnetic anisotropy in the system., Comment: 12 pages, 9 figures
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- 2024
49. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models
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Deitke, Matt, Clark, Christopher, Lee, Sangho, Tripathi, Rohun, Yang, Yue, Park, Jae Sung, Salehi, Mohammadreza, Muennighoff, Niklas, Lo, Kyle, Soldaini, Luca, Lu, Jiasen, Anderson, Taira, Bransom, Erin, Ehsani, Kiana, Ngo, Huong, Chen, YenSung, Patel, Ajay, Yatskar, Mark, Callison-Burch, Chris, Head, Andrew, Hendrix, Rose, Bastani, Favyen, VanderBilt, Eli, Lambert, Nathan, Chou, Yvonne, Chheda, Arnavi, Sparks, Jenna, Skjonsberg, Sam, Schmitz, Michael, Sarnat, Aaron, Bischoff, Byron, Walsh, Pete, Newell, Chris, Wolters, Piper, Gupta, Tanmay, Zeng, Kuo-Hao, Borchardt, Jon, Groeneveld, Dirk, Nam, Crystal, Lebrecht, Sophie, Wittlif, Caitlin, Schoenick, Carissa, Michel, Oscar, Krishna, Ranjay, Weihs, Luca, Smith, Noah A., Hajishirzi, Hannaneh, Girshick, Ross, Farhadi, Ali, and Kembhavi, Aniruddha
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Computation and Language ,Computer Science - Machine Learning - Abstract
Today's most advanced vision-language models (VLMs) remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good performance, effectively distilling these closed VLMs into open ones. As a result, the community has been missing foundational knowledge about how to build performant VLMs from scratch. We present Molmo, a new family of VLMs that are state-of-the-art in their class of openness. Our key contribution is a collection of new datasets called PixMo, including a dataset of highly detailed image captions for pre-training, a free-form image Q&A dataset for fine-tuning, and an innovative 2D pointing dataset, all collected without the use of external VLMs. The success of our approach relies on careful modeling choices, a well-tuned training pipeline, and, most critically, the quality of our newly collected datasets. Our best-in-class 72B model not only outperforms others in the class of open weight and data models, but also outperforms larger proprietary models including Claude 3.5 Sonnet, and Gemini 1.5 Pro and Flash, second only to GPT-4o based on both academic benchmarks and on a large human evaluation. Our model weights, new datasets, and source code are available at https://molmo.allenai.org/blog., Comment: Updated with ablations and more technical details
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- 2024
50. Aggregating multiple test results to improve medical decision-making
- Author
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Böttcher, Lucas, D'Orsogna, Maria R., and Chou, Tom
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Statistics - Applications ,Quantitative Biology - Quantitative Methods - Abstract
Gathering observational data for medical decision-making often involves uncertainties arising from both type I (false positive)and type II (false negative) errors. In this work, we develop a statistical model to study how medical decision-making can be improved by repeating diagnostic and screening tests, and aggregating their results. This approach is relevant not only in clinical settings, such as medical imaging, but also in public health, as highlighted by the need for rapid, cost-effective testing methods during the SARS-CoV-2pandemic. Our model enables the development of testing protocols with an arbitrary number of tests, which can be customized to meet requirements for type I and type II errors. This allows us to adjust sensitivity and specificity according to application-specific needs. Additionally, we derive generalized Rogan--Gladen estimates for estimating disease prevalence, accounting for an arbitrary number of tests with potentially different type I and type II errors. We also provide the corresponding uncertainty quantification., Comment: 24 pages, 6 figures, 2 tables
- Published
- 2024
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