Zobrazeno 1 - 10
of 6 740
pro vyhledávání: '"P. Buch"'
We prove that Schubert varieties in flag manifolds are uniquely determined by their equivariant cohomology classes, as well as a stronger result that replaces Schubert varieties with closures of Bialynicki-Birula cells under suitable conditions. This
Externí odkaz:
http://arxiv.org/abs/2409.11387
A homology class $d \in H_2(X)$ of a complex flag variety $X = G/P$ is called a line degree if the moduli space $\overline{M}_{0,0}(X,d)$ of 0-pointed stable maps to $X$ of degree $d$ is also a flag variety $G/P'$. We prove a quantum equals classical
Externí odkaz:
http://arxiv.org/abs/2409.09580
Autor:
Wargnier, Antonin, Poch, Olivier, Poggiali, Giovanni, Gautier, Thomas, Doressoundiram, Alain, Beck, Pierre, Nakamura, Tomoki, Miyamoto, Hideaki, Kameda, Shingo, Ruscassier, Nathalie, Buch, Arnaud, Hasselmann, Pedro H., Sultana, Robin, Quirico, Eric, Fornasier, Sonia, Barucci, Antonella
Surface porosity has been found to be an important property for small bodies. Some asteroids and comets can exhibit an extremely high surface porosity in the first millimeter layer. This layer may be produced by various processes and maintained by th
Externí odkaz:
http://arxiv.org/abs/2408.14149
Autor:
Jain, Gagan, Hegde, Nidhi, Kusupati, Aditya, Nagrani, Arsha, Buch, Shyamal, Jain, Prateek, Arnab, Anurag, Paul, Sujoy
The visual medium (images and videos) naturally contains a large amount of information redundancy, thereby providing a great opportunity for leveraging efficiency in processing. While Vision Transformer (ViT) based models scale effectively to large d
Externí odkaz:
http://arxiv.org/abs/2407.19985
Autor:
Aihara, H., Aloisio, A., Auguste, D. P., Aversano, M., Babeluk, M., Bahinipati, S., Banerjee, Sw., Barbero, M., Baudot, J., Beaubien, A., Becherer, F., Bergauer, T., Bernlochner., F. U., Bertacchi, V., Bertolone, G., Bespin, C., Bessner, M., Bettarini, S., Bevan, A. J., Bhuyan, B., Bona, M., Bonis, J. F., Borah, J., Bosi, F., Boudagga, R., Bozek, A., Bračko, M., Branchini, P., Breugnon, P., Browder, T. E., Buch, Y., Budano, A., Campajola, M., Casarosa, G., Cecchi, C., Chen, C., Choudhury, S., Corona, L., de Marino, G., De Nardo, G., De Pietro, G., de Sangro, R., Dey, S., Dingfelder, J. C., Dong, T. V., Dorokhov, A., Dujany, G., Epifanov, D., Federici, L., Ferber, T., Fillinger, T., Finck, Ch., Finocchiaro, G., Forti, F., Frey, A., Friedl, M., Gabrielli, A., Gaioni, L., Gao, Y., Gaudino, G., Gaur, V., Gaz, A., Giordano, R., Giroletti, S., Gobbo, B., Godang, R., Haide, I., Han, Y., Hara, K., Hayasaka, K., Hearty, C., Heidelbach, A., Higuchi, T., Himmi, A., Hoferichter, M., Howgill, D. A., Hu-Guo, C., Iijima, T., Inami, K., Irmler, C., Ishikawa, A., Itoh, R., Iyer, D., Jacobs, W. W., Jaffe, D. E., Jin, Y., Junginger, T., Kandra, J., Kojima, K., Koga, T., Korobov, A. A., Korpar, S., Križan, P., Krüger, H., Kuhr, T., Kumar, A., Kumar, R ., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lacasta, C., Lai, Y. -T., Lalwani, K., Lam, T., Lanceri, L., Lee, M. J., Leonidopoulos, C., Levit, D., Lewis, P. M., Libby, J. F., Liu, Q. Y., Liu, Z. Y., Liventsev, D., Longo, S., Mancinelli, G., Manghisoni, M., Manoni, E., Marinas, C., Martellini, C., Martens, A., Massa, M., Massaccesi, L., Mawas, F., Mazorra, J., Merola, M., Miller, C., Minuti, M., Mizuk, R., Modak, A., Moggi, A., Mohanty, G. B., Moneta, S., Muller, Th., Na, I., Nakamura, K. R., Nakao, M., Natochii, A., Niebuhr, C., Nishida, S., Novosel, A., Pangaud, P., Parker, B., Passeri, A., Pedlar, T. K., Peinaud, Y., Peng, Y., Peschke, R., Pestotnik, R., Pham, T. H., Piccolo, M., Piilonen, L. E., Prell, S., Purohit, M. V., Ratti, L., Re, V., Reuter, L., Riceputi, E., Ripp-Baudot, I., Rizzo, G., Roney, J. M., Russo, A., Sandilya, S., Santelj, L., Savinov, V., Scavino, B., Schall, L., Schnell, G., Schwanda, C., Schwartz, A. J., Schwenker, B., Schwickardi, M., Seljak, A., Serrano, J., Shiu, J. -G., Shwartz, B., Simon, F., Soffer, A., Song, W. M., Starič, M., Stavroulakis, P., Stefkova, S., Stroili, R., Tanaka, S., Taniguchi, N., Teotia, V., Tessema, N., Thalmeier, R., Torassa, E., Trabelsi, K., Trantou, F. F., Traversi, G., Urquijo, P., Vahsen, S. E., Valin, I., Varner, G. S., Varvell, K. E., Vitale, L., Vobbilisetti, V., Wang, X. L., Wessel, C., Wienands, H. U., Won, E., Xu, D., Yamada, S., Yin, J. H., Yoshihara, K., Yuan, C. Z., Zani, L., Zong, Z., Zou, S.
We describe the planned near-term and potential longer-term upgrades of the Belle II detector at the SuperKEKB electron-positron collider operating at the KEK laboratory in Tsukuba, Japan. These upgrades will allow increasingly sensitive searches for
Externí odkaz:
http://arxiv.org/abs/2406.19421
Autor:
Wargnier, Antonin, Gautier, Thomas, Doressoundiram, Alain, Poggiali, Giovanni, Beck, Pierre, Poch, Olivier, Quirico, Eric, Nakamura, Tomoki, Miyamoto, Hideaki, Kameda, Shingo, Hasselmann, Pedro H., Ruscassier, Nathalie, Buch, Arnaud, Fornasier, Sonia, Barucci, Maria Antonietta
Previous observations of Phobos and Deimos, the moons of Mars, have improved our understanding of these small bodies. However, their formation and composition remain poorly constrained. Physical and spectral properties suggest that Phobos may be a we
Externí odkaz:
http://arxiv.org/abs/2405.02999
Publikováno v:
ApJ 971, 79 (2024)
We present Milky Way-est, a suite of 20 cosmological cold-dark-matter-only zoom-in simulations of Milky Way (MW)-like host halos. Milky Way-est hosts are selected such that they (i) are consistent with the MW's measured halo mass and concentration, (
Externí odkaz:
http://arxiv.org/abs/2404.08043
This paper addresses the task of video question answering (videoQA) via a decomposed multi-stage, modular reasoning framework. Previous modular methods have shown promise with a single planning stage ungrounded in visual content. However, through a s
Externí odkaz:
http://arxiv.org/abs/2404.06511
Autor:
Zhou, Xingyi, Arnab, Anurag, Buch, Shyamal, Yan, Shen, Myers, Austin, Xiong, Xuehan, Nagrani, Arsha, Schmid, Cordelia
An ideal model for dense video captioning -- predicting captions localized temporally in a video -- should be able to handle long input videos, predict rich, detailed textual descriptions, and be able to produce outputs before processing the entire v
Externí odkaz:
http://arxiv.org/abs/2404.01297
Maximum entropy (Maxent) models are a class of statistical models that use the maximum entropy principle to estimate probability distributions from data. Due to the size of modern data sets, Maxent models need efficient optimization algorithms to sca
Externí odkaz:
http://arxiv.org/abs/2403.06816