The NANOGrav 15 yr Data Set: Harmonic Analysis of the Pulsar Angular Correlations

Autor: Agazie, Gabriella, Baier, Jeremy G., Baker, Paul T., Becsy, Bence, Blecha, Laura, Boddy, Kimberly K., Brazier, Adam, Brook, Paul R., Burke-Spolaor, Sarah, Burnette, Rand, Casey-Clyde, J. Andrew, Charisi, Maria, Chatterjee, Shami, Cohen, Tyler, Cordes, James M., Cornish, Neil J., Crawford, Fronefield, Cromartie, H. Thankful, DeCesar, Megan E., Demorest, Paul B., Deng, Heling, Dey, Lankeswar, Dolch, Timothy, Ferrara, Elizabeth C., Fiore, William, Fonseca, Emmanuel, Freedman, Gabriel E., Gardiner, Emiko C., Gersbach, Kyle A., Glaser, Joseph, Good, Deborah C., Gultekin, Kayhan, Hazboun, Jeffrey S., Jennings, Ross J., Johnson, Aaron D., Kaplan, David L., Kelley, Luke Zoltan, Key, Joey S., Laal, Nima, Lam, Michael T., Lamb, William G., Larsen, Bjorn, Lazio, T. Joseph W., Lewandowska, Natalia, Liu, Tingting, Luo, Jing, Lynch, Ryan S., Ma, Chung-Pei, Madison, Dustin R., McEwen, Alexander, McKee, James W., McLaughlin, Maura A., Meyers, Patrick M., Mingarelli, Chiara M. F., Mitridate, Andrea, Nay, Jonathan, Nice, David J., Ocker, Stella Koch, Olum, Ken D., Pennucci, Timothy T., Petrov, Polina, Pol, Nihan S., Radovan, Henri A., Ransom, Scott M., Ray, Paul S., Runnoe, Jessie C., Saffer, Alexander, Sardesai, Shashwat C., Schmitz, Kai, Siemens, Xavier, Simon, Joseph, Siwek, Magdalena S., Smith, Tristan L., Fiscella, Sophia V. Sosa, Stairs, Ingrid H., Stinebring, Daniel R., Susobhanan, Abhimanyu, Swiggum, Joseph K., Taylor, Jacob, Taylor, Stephen R., Turner, Jacob E., Unal, Caner, Vallisneri, Michele, van Haasteren, Rutger, Verbiest, Joris, Vigeland, Sarah J., Witt, Caitlin A., Wright, David, Young, Olivia

Pulsar timing array observations have found evidence for an isotropic gravitational wave background with the Hellings-Downs angular correlations, expected from general relativity. This interpretation hinges on the measured shape of the angular correl

Externí odkaz: http://arxiv.org/abs/2411.13472

Neutrinoless Double Beta Decay Sensitivity of the XLZD Rare Event Observatory

Autor: XLZD Collaboration, Aalbers, J., Abe, K., Adrover, M., Maouloud, S. Ahmed, Akerib, D. S., Musalhi, A. K. Al, Alder, F., Althueser, L., Amaral, D. W. P., Amarasinghe, C. S., Ames, A., Andrieu, B., Angelides, N., Angelino, E., Antunovic, B., Aprile, E., Araújo, H. M., Armstrong, J. E., Arthurs, M., Babicz, M., Bajpai, D., Baker, A., Balzer, M., Bang, J., Barberio, E., Bargemann, J. W., Barillier, E., Basharina-Freshville, A., Baudis, L., Bauer, D., Bazyk, M., Beattie, K., Beaupere, N., Bell, N. F., Bellagamba, L., Benson, T., Bhatti, A., Biesiadzinski, T. P., Biondi, R., Biondi, Y., Birch, H. J., Bishop, E., Bismark, A., Boehm, C., Boese, K., Bolotnikov, A., Brás, P., Braun, R., Breskin, A., Brew, C. A. J., Brommer, S., Brown, A., Bruni, G., Budnik, R., Burdin, S., Cai, C., Capelli, C., Carini, G., Carmona-Benitez, M. C., Carter, M., Chauvin, A., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Chavez, A. P. Cimental, Clark, K., Colijn, A. P., Colling, D. J., Conrad, J., Converse, M. V., Coronel, R., Costanzo, D., Cottle, A., Cox, G., Cuenca-García, J. J., Curran, D., Cussans, D., D'Andrea, V., Garcia, L. C. Daniel, Darlington, I., Dave, S., David, A., Davies, G. J., Decowski, M. P., Deisting, A., Delgaudio, J., Dey, S., Di Donato, C., Di Felice, L., Di Gangi, P., Diglio, S., Ding, C., Dobson, J. E. Y., Doerenkamp, M., Drexlin, G., Druszkiewicz, E., Dunbar, C. L., Eitel, K., Elykov, A., Engel, R., Eriksen, S. R., Fayer, S., Fearon, N. M., Ferella, A. D., Ferrari, C., Fieldhouse, N., Fischer, H., Flaecher, H., Flehmke, T., Flierman, M., Fraser, E. D., Fruth, T. M. A., Fujikawa, K., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Gaitskell, R. J., Gallice, N., Galloway, M., Gao, F., Garroum, N., Geffre, A., Genovesi, J., Ghag, C., Ghosh, S., Giacomobono, R., Gibbons, R., Girard, F., Glade-Beucke, R., Glück, F., Gokhale, S., Grandi, L., Green, J., Grigat, J., van der Grinten, M. G. D., Größle, R., Guan, H., Guida, M., Gyorgy, P., Haiston, J. J., Hall, C. R., Hall, T., Hammann, R., Hannen, V., Hansmann-Menzemer, S., Hargittai, N., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M., Hertel, S. A., Higuera, A., Hils, C., Hiraoka, K., Hoetzsch, L., Hoferichter, M., Homenides, G. J., Hood, N. F., Horn, M., Huang, D. Q., Hughes, S., Hunt, D., Iacovacci, M., Itow, Y., Jacquet, E., Jakob, J., James, R. S., Joerg, F., Jones, S., Kaboth, A. C., Kahlert, F., Kamaha, A. C., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Keller, M., Kemp-Russell, P., Khaitan, D., Kharbanda, P., Kilminster, B., Kim, J., Kirk, R., Kleifges, M., Klute, M., Kobayashi, M., Kodroff, D., Koke, D., Kopec, A., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., von Krosigk, B., Kudryavtsev, V. A., Kuger, F., Kurita, N., Landsman, H., Lang, R. F., Lawes, C., Lee, J., Lehnert, B., Leonard, D. S., Lesko, K. T., Levinson, L., Li, A., Li, I., Li, S., Liang, S., Liang, Z., Lin, J., Lin, Y. -T., Lindemann, S., Linden, S., Lindner, M., Lindote, A., Lippincott, W. H., Liu, K., Loizeau, J., Lombardi, F., Lopes, J. A. M., Lopes, M. I., Lorenzon, W., Loutit, M., Lu, C., Lucchetti, G. M., Luce, T., Luitz, S., Ma, Y., Macolino, C., Mahlstedt, J., Maier, B., Majewski, P. A., Manalaysay, A., Mancuso, A., Manenti, L., Mannino, R. L., Marignetti, F., Marley, T., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Maupin, C., McCabe, C., McCarthy, M. E., McKinsey, D. N., McLaughlin, J. B., Melchiorre, A., Menéndez, J., Messina, M., Miller, E. H., Milosovic, B., Milutinovic, S., Miuchi, K., Miyata, R., Mizrachi, E., Molinario, A., Monteiro, C. M. B., Monzani, M. E., Morå, K., Moriyama, S., Morrison, E., Morteau, E., Mosbacher, Y., Mount, B. J., Müller, J., Murdy, M., Murphy, A. St. J., Murra, M., Naylor, A., Nelson, H. N., Neves, F., Newstead, J. L., Nguyen, A., Ni, K., O'Hare, C., Oberlack, U., Obradovic, M., Olcina, I., Oliver-Mallory, K. C., Gann, G. D. Orebi, Orpwood, J., Ostrowskiy, I., Ouahada, S., Oyulmaz, K., Paetsch, B., Palladino, K. J., Palmer, J., Pan, Y., Pandurovic, M., Pannifer, N. J., Paramesvaran, S., Patton, S. J., Pellegrini, Q., Penning, B., Pereira, G., Peres, R., Perry, E., Pershing, T., Piastra, F., Pienaar, J., Piepke, A., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qiao, K., Qie, Y., Qin, J., Radeka, S., Radeka, V., Rajado, M., García, D. Ramírez, Ravindran, A., Razeto, A., Reichenbacher, J., Rhyne, C. A., Richards, A., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Roy, A., Rushton, T., Rynders, D., Saakyan, R., Sanchez, L., Sanchez-Lucas, P., Santone, D., Santos, J. M. F. dos, Sartorelli, G., Sazzad, A. B. M. R., Scaffidi, A., Schnee, R. W., Schreiner, J., Schulte, P., Schulze, H., Eißing, Schumann, M., Schwenck, A., Schwenk, A., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Sharma, S., Shaw, S., Shen, W., Sherman, L., Shi, S., Shi, S. Y., Shimada, T., Shutt, T., Silk, J. J., Silva, C., Simgen, H., Sinev, G., Singh, R., Siniscalco, J., Solmaz, M., Solovov, V. N., Song, Z., Sorensen, P., Soria, J., Stanley, O., Steidl, M., Stenhouse, T., Stevens, A., Stifter, K., Sumner, T. J., Takeda, A., Tan, P. -L., Taylor, D. J., Taylor, W. C., Thers, D., Thümmler, T., Tiedt, D. R., Tönnies, F., Tong, Z., Toschi, F., Tovey, D. R., Tranter, J., Trask, M., Trinchero, G., Tripathi, M., Tronstad, D. R., Trotta, R., Tunnell, C. D., Urquijo, P., Usón, A., Utoyama, M., Vaitkus, A. C., Valentino, O., Valerius, K., Vecchi, S., Velan, V., Vetter, S., de Viveiros, L., Volta, G., Vorkapic, D., Wang, A., Wang, J. J., Wang, W., Wang, Y., Waters, D., Weerman, K. M., Weinheimer, C., Weiss, M., Wenz, D., Whitis, T. J., Wild, K., Williams, M., Wilson, M., Wilson, S. T., Wittweg, C., Wolf, J., Wolfs, F. L. H., Woodford, S., Woodward, D., Worcester, M., Wright, C. J., Wu, V. H. S., üstling, S. W, Wurm, M., Xia, Q., Xing, Y., Xu, D., Xu, J., Xu, Y., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yeh, M., Yu, B., Zavattini, G., Zha, W., Zhong, M., Zuber, K.

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60 to 80 t capable of probing the remaining WIMP-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that,

Externí odkaz: http://arxiv.org/abs/2410.19016

Short-term Streamflow and Flood Forecasting based on Graph Convolutional Recurrent Neural Network and Residual Error Learning

Autor: Pan, Xiyu, Mohammadi, Neda, Taylor, John E.

Accurate short-term streamflow and flood forecasting are critical for mitigating river flood impacts, especially given the increasing climate variability. Machine learning-based streamflow forecasting relies on large streamflow datasets derived from

Externí odkaz: http://arxiv.org/abs/2412.04764

Beta delayed neutron emission of $N=84$ $^{132}$Cd

Autor: Madurga, M., Xu, Z. Y., Grzywacz, 1 R., Andreyev, A., Benzoni, G., Borge, M. J. G., Costache, C., Cox, I., Dimitrov, B., Van Duppen, P., Fraile, L. M., Franchoo, S., Fynbo, H., Gonsalves, B., Gottardo, A., Greenless, P. T., Gross, C. J., Harkness-Brennan, L. J., Hyuse, M., Judson, D. S., Kisyov, S., Kolos, K., Konki, J., Kurzewicz, J., Lazarus, I., Lica, R., Lynch, L., Lund, M., Marginean, N., Marginean, R., Mihai, C., Marroquin, I., Mazzocchi, C., Mengoni, D., Morales, A. I., Nacher, E., Negret, A., Page, R. D., Pascu, S., Paulauskas, S. V., Perea, A., Piersa-Silkowska, M., Pucknell, V., Rahkila, P., Rapisarda, E., Rotaru, F., Sotty, C., Taylor, S., Tengblad, O., Vedia, V., Verney, D., Wadsworth, R., Warr, N., de Witte, H.

Using the time-of-flight technique, we measured the beta-delayed neutron emission of $^{132}$Cd. From our large-scale shell model (LSSM) calculation using the N$^3$LO interaction [Z.Y. Xu et al., Phys. Rev. Lett. 131, 022501 (2023)], we suggest the d

Externí odkaz: http://arxiv.org/abs/2412.04333

PBP: Post-training Backdoor Purification for Malware Classifiers

Autor: Nguyen, Dung Thuy, Tran, Ngoc N., Johnson, Taylor T., Leach, Kevin

In recent years, the rise of machine learning (ML) in cybersecurity has brought new challenges, including the increasing threat of backdoor poisoning attacks on ML malware classifiers. For instance, adversaries could inject malicious samples into pub

Externí odkaz: http://arxiv.org/abs/2412.03441