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pro vyhledávání: '"So Aaron"'
Autor:
Chen, Kai-Feng, Wilensky, Michael J., Liu, Adrian, Dillon, Joshua S., Hewitt, Jacqueline N., Adams, Tyrone, Aguirre, James E., Baartman, Rushelle, Beardsley, Adam P., Berkhout, Lindsay M., Bernardi, Gianni, Billings, Tashalee S., Bowman, Judd D., Bull, Philip, Burba, Jacob, Byrne, Ruby, Carey, Steven, Choudhuri, Samir, Cox, Tyler, DeBoer, David R., Dexter, Matt, Eksteen, Nico, Ely, John, Ewall-Wice, Aaron, Furlanetto, Steven R., Gale-Sides, Kingsley, Garsden, Hugh, Gehlot, Bharat Kumar, Gorce, Adélie, Gorthi, Deepthi, Halday, Ziyaad, Hazelton, Bryna J., Hickish, Jack, Jacobs, Daniel C., Josaitis, Alec, Kern, Nicholas S., Kerrigan, Joshua, Kittiwisit, Piyanat, Kolopanis, Matthew, La Plante, Paul, Lanman, Adam, Ma, Yin-Zhe, MacMahon, David H. E., Malan, Lourence, Malgas, Cresshim, Malgas, Keith, Marero, Bradley, Martinot, Zachary E., McBride, Lisa, Mesinger, Andrei, Mohamed-Hinds, Nicel, Molewa, Mathakane, Morales, Miguel F., Murray, Steven G., Nuwegeld, Hans, Parsons, Aaron R., Pascua, Robert, Qin, Yuxiang, Rath, Eleanor, Razavi-Ghods, Nima, Robnett, James, Santos, Mario G., Sims, Peter, Singh, Saurabh, Storer, Dara, Swarts, Hilton, Tan, Jianrong, van Wyngaarden, Pieter, Zheng, Haoxuan
The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency i
Externí odkaz:
http://arxiv.org/abs/2411.10529
We consider the foundational problem of maintaining a $(1-\varepsilon)$-approximate maximum weight matching (MWM) in an $n$-node dynamic graph undergoing edge insertions and deletions. We provide a general reduction that reduces the problem on graphs
Externí odkaz:
http://arxiv.org/abs/2410.18936
Autor:
Gyawali, Gaurav, Cochran, Tyler, Lensky, Yuri, Rosenberg, Eliott, Karamlou, Amir H., Kechedzhi, Kostyantyn, Berndtsson, Julia, Westerhout, Tom, Asfaw, Abraham, Abanin, Dmitry, Acharya, Rajeev, Beni, Laleh Aghababaie, Andersen, Trond I., Ansmann, Markus, Arute, Frank, Arya, Kunal, Astrakhantsev, Nikita, Atalaya, Juan, Babbush, Ryan, Ballard, Brian, Bardin, Joseph C., Bengtsson, Andreas, Bilmes, Alexander, Bortoli, Gina, Bourassa, Alexandre, Bovaird, Jenna, Brill, Leon, Broughton, Michael, Browne, David A., Buchea, Brett, Buckley, Bob B., Buell, David A., Burger, Tim, Burkett, Brian, Bushnell, Nicholas, Cabrera, Anthony, Campero, Juan, Chang, Hung-Shen, Chen, Zijun, Chiaro, Ben, Claes, Jahan, Cleland, Agnetta Y., Cogan, Josh, Collins, Roberto, Conner, Paul, Courtney, William, Crook, Alexander L., Das, Sayan, Debroy, Dripto M., De Lorenzo, Laura, Barba, Alexander Del Toro, Demura, Sean, Di Paolo, Agustin, Donohoe, Paul, Drozdov, Ilya, Dunsworth, Andrew, Earle, Clint, Eickbusch, Alec, Elbag, Aviv Moshe, Elzouka, Mahmoud, Erickson, Catherine, Faoro, Lara, Fatemi, Reza, Ferreira, Vinicius S., Burgos, Leslie Flores, Forati, Ebrahim, Fowler, Austin G., Foxen, Brooks, Ganjam, Suhas, Gasca, Robert, Giang, William, Gidney, Craig, Gilboa, Dar, Gosula, Raja, Dau, Alejandro Grajales, Graumann, Dietrich, Greene, Alex, Gross, Jonathan A., Habegger, Steve, Hamilton, Michael C., Hansen, Monica, Harrigan, Matthew P., Harrington, Sean D., Heslin, Stephen, Heu, Paula, Hill, Gordon, Hilton, Jeremy, Hoffmann, Markus R., Huang, Hsin-Yuan, Huff, Ashley, Huggins, William J., Ioffe, Lev B., Isakov, Sergei V., Jeffrey, Evan, Jiang, Zhang, Jones, Cody, Jordan, Stephen, Joshi, Chaitali, Juhas, Pavol, Kafri, Dvir, Kang, Hui, Khaire, Trupti, Khattar, Tanuj, Khezri, Mostafa, Kieferová, Mária, Kim, Seon, Klimov, Paul V., Klots, Andrey R., Kobrin, Bryce, Korotkov, Alexander N., Kostritsa, Fedor, Kreikebaum, John Mark, Kurilovich, Vladislav D., Landhuis, David, Lange-Dei, Tiano, Langley, Brandon W., Laptev, Pavel, Lau, Kim-Ming, Guevel, Loïck Le, Ledford, Justin, Lee, Joonho, Lee, Kenny, Lester, Brian J., Li, Wing Yan, Lill, Alexander T., Liu, Wayne, Livingston, William P., Locharla, Aditya, Lundahl, Daniel, Lunt, Aaron, Madhuk, Sid, Maloney, Ashley, Mandrà, Salvatore, Martin, Leigh S., Martin, Steven, Martin, Orion, Maxfield, Cameron, McClean, Jarrod R., McEwen, Matt, Meeks, Seneca, Megrant, Anthony, Mi, Xiao, Miao, Kevin C., Mieszala, Amanda, Molina, Sebastian, Montazeri, Shirin, Morvan, Alexis, Movassagh, Ramis, Neill, Charles, Nersisyan, Ani, Newman, Michael, Nguyen, Anthony, Nguyen, Murray, Ni, Chia-Hung, Niu, Murphy Yuezhen, Oliver, William D., Ottosson, Kristoffer, Pizzuto, Alex, Potter, Rebecca, Pritchard, Orion, Pryadko, Leonid P., Quintana, Chris, Reagor, Matthew J., Rhodes, David M., Roberts, Gabrielle, Rocque, Charles, Rubin, Nicholas C., Saei, Negar, Sankaragomathi, Kannan, Satzinger, Kevin J., Schurkus, Henry F., Schuster, Christopher, Shearn, Michael J., Shorter, Aaron, Shutty, Noah, Shvarts, Vladimir, Sivak, Volodymyr, Skruzny, Jindra, Small, Spencer, Smith, W. Clarke, Springer, Sofia, Sterling, George, Suchard, Jordan, Szalay, Marco, Szasz, Aaron, Sztein, Alex, Thor, Douglas, Torunbalci, M. Mert, Vaishnav, Abeer, Vdovichev, Sergey, Vidal, Guifré, Heidweiller, Catherine Vollgraff, Waltman, Steven, Wang, Shannon X., White, Theodore, Wong, Kristi, Woo, Bryan W. K., Xing, Cheng, Yao, Z. Jamie, Yeh, Ping, Ying, Bicheng, Yoo, Juhwan, Yosri, Noureldin, Young, Grayson, Zalcman, Adam, Zhang, Yaxing, Zhu, Ningfeng, Zobrist, Nicholas, Boixo, Sergio, Kelly, Julian, Lucero, Erik, Chen, Yu, Smelyanskiy, Vadim, Neven, Hartmut, Kovrizhin, Dmitry, Knolle, Johannes, Halimeh, Jad C., Aleiner, Igor, Moessner, Roderich, Roushan, Pedram
One of the most challenging problems in the computational study of localization in quantum manybody systems is to capture the effects of rare events, which requires sampling over exponentially many disorder realizations. We implement an efficient pro
Externí odkaz:
http://arxiv.org/abs/2410.06557
Autor:
Chickles, Emma T., Burdge, Kevin B., Chakraborty, Joheen, Dhillon, Vik S., Draghis, Paul, Hughes, Scott A., Munday, James, Rappaport, Saul A., Tonry, John, Bauer, Evan, Brown, Alex, Castro, Noel, Chakrabarty, Deepto, Dyer, Martin, El-Badry, Kareem, Frebel, Anna, Furesz, Gabor, Garbutt, James, Green, Matthew J., Householder, Aaron, Jarvis, Daniel, Kara, Erin, Kennedy, Mark R., Kerry, Paul, Littlefair, Stuart P, McCormac, James, Mo, Geoffrey, Ng, Mason, Parsons, Steven, Pelisoli, Ingrid, Pike, Eleanor, Prince, Thomas A., Ricker, George R., van Roestel, Jan, Sahman, David, Shen, Ken J., Simcoe, Robert A., Vanderburg, Andrew, Wong, Tin Long Sunny
Type Ia supernovae, critical for studying cosmic expansion, arise from thermonuclear explosions of white dwarfs, but their precise progenitor pathways remain unclear. Growing evidence supports the ``double-degenerate'' scenario, where two white dwarf
Externí odkaz:
http://arxiv.org/abs/2411.19916
Ordinary Differential Equations (ODEs) are widely used in physics, chemistry, and biology to model dynamic systems, including reaction kinetics, population dynamics, and biological processes. In this work, we integrate GPU-accelerated ODE solvers int
Externí odkaz:
http://arxiv.org/abs/2411.19882
We present an efficient reduction that converts any machine learning algorithm into an interactive protocol, enabling collaboration with another party (e.g., a human) to achieve consensus on predictions and improve accuracy. This approach imposes cal
Externí odkaz:
http://arxiv.org/abs/2411.19791
Autor:
Behari, Nikhil, Young, Aaron, Somasundaram, Siddharth, Klinghoffer, Tzofi, Dave, Akshat, Raskar, Ramesh
3D surface reconstruction is essential across applications of virtual reality, robotics, and mobile scanning. However, RGB-based reconstruction often fails in low-texture, low-light, and low-albedo scenes. Handheld LiDARs, now common on mobile device
Externí odkaz:
http://arxiv.org/abs/2411.19474
Autor:
Goertz, Madeleine, Williams, Aaron
We investigate solutions to the new "Ziggu" family of exponential puzzles. These puzzles have $p$ pieces that form $m$ mazes. We encode the puzzle state as an quaternary number (base $4$) with $n=m+1$ digits, where each digit gives the horizontal or
Externí odkaz:
http://arxiv.org/abs/2411.19291
Analyzing large datasets and summarizing it into useful information is the heart of the data mining process. In healthcare, information can be converted into knowledge about patient historical patterns and possible future trends. During the COVID-19
Externí odkaz:
http://arxiv.org/abs/2411.18759
Despite having triggered devastating pandemics in the past, our ability to quantitatively assess the emergence potential of individual strains of animal influenza viruses remains limited. This study introduces Emergenet, a tool to infer a digital twi
Externí odkaz:
http://arxiv.org/abs/2411.17154