Zobrazeno 1 - 10
of 11 104
pro vyhledávání: '"Luo, Jing"'
Autor:
Dey, Lankeswar, McLaughlin, Maura A., Wahl, Haley M., Demorest, Paul B., Arzoumanian, Zaven, Blumer, Harsha, Brook, Paul R., Burke-Spolaor, Sarah, Cromartie, H. Thankful, DeCesar, Megan E., Dolch, Timothy, Ellis, Justin A., Ferdman, Robert D., Ferrara, Elizabeth C., Fiore, William, Fonseca, Emmanuel, Garver-Daniels, Nate, Gentile, Peter A., Glaser, Joseph, Good, Deborah C., Jennings, Ross J., Jones, Megan L., Lam, Michael T., Lorimer, Duncan R., Luo, Jing, Lynch, Ryan S., Ng, Cherry, Nice, David J., Pennucci, Timothy T., Pol, Nihan S., Ransom, Scott M., Spiewak, Renée, Stairs, Ingrid H., Stovall, Kevin, Swiggum, Joseph K.
Pulsar timing array experiments have recently uncovered evidence for a nanohertz gravitational wave background by precisely timing an ensemble of millisecond pulsars. The next significant milestones for these experiments include characterizing the de
Externí odkaz:
http://arxiv.org/abs/2406.13463
Autor:
Guo, Zijie, Lyu, Pumeng, Ling, Fenghua, Luo, Jing-Jia, Boers, Niklas, Ouyang, Wanli, Bai, Lei
Ocean dynamics plays a crucial role in driving global weather and climate patterns. Accurate and efficient modeling of ocean dynamics is essential for improved understanding of complex ocean circulation and processes, for predicting climate variation
Externí odkaz:
http://arxiv.org/abs/2405.15412
Autor:
Larsen, Bjorn, Mingarelli, Chiara M. F., Hazboun, Jeffrey S., Chalumeau, Aurelien, Good, Deborah C., Simon, Joseph, Agazie, Gabriella, Anumarlapudi, Akash, Archibald, Anne M., Arzoumanian, Zaven, Baker, Paul T., Brook, Paul R., Cromartie, H. Thankful, Crowter, Kathryn, DeCesar, Megan E., Demorest, Paul B., Dolch, Timothy, Ferrara, Elizabeth C., Fiore, William, Fonseca, Emmanuel, Freedman, Gabriel E., Garver-Daniels, Nate, Gentile, Peter A., Glaser, Joseph, Jennings, Ross J., Jones, Megan L., Kaplan, David L., Kerr, Matthew, Lam, Michael T., Lorimer, Duncan R., Luo, Jing, Lynch, Ryan S., McEwen, Alexander, McLaughlin, Maura A., McMann, Natasha, Meyers, Bradley W., Ng, Cherry, Nice, David J., Pennucci, Timothy T., Perera, Benetge B. P., Pol, Nihan S., Radovan, Henri A., Ransom, Scott M., Ray, Paul S., Schmiedekamp, Ann, Schmiedekamp, Carl, Shapiro-Albert, Brent J., Stairs, Ingrid H., Stovall, Kevin, Susobhanan, Abhimanyu, Swiggum, Joseph K., Wahl, Haley M., Champion, David J., Cognard, Ismael, Guillemot, Lucas, Hu, Huanchen, Keith, Michael J., Liu, Kuo, McKee, James W., Parthasarathy, Aditya, Perrodin, Delphine, Possenti, Andrea, Shaifullah, Golam M., Theureau, Gilles
Pulsar timing arrays (PTAs) are designed to detect low-frequency gravitational waves (GWs). GWs induce achromatic signals in PTA data, meaning that the timing delays do not depend on radio-frequency. However, pulse arrival times are also affected by
Externí odkaz:
http://arxiv.org/abs/2405.14941
Autor:
Zhong, Xiaohui, Chen, Lei, Li, Hao, Liu, Jun, Fan, Xu, Feng, Jie, Dai, Kan, Luo, Jing-Jia, Wu, Jie, Qi, Yuan, Lu, Bo
Ensemble forecasting is crucial for improving weather predictions, especially for forecasts of extreme events. Constructing an ensemble prediction system (EPS) based on conventional NWP models is highly computationally expensive. ML models have emerg
Externí odkaz:
http://arxiv.org/abs/2405.05925
Autor:
Susobhanan, Abhimanyu, Kaplan, David, Archibald, Anne, Luo, Jing, Ray, Paul, Pennucci, Timothy, Ransom, Scott, Agazie, Gabriella, Fiore, William, Larsen, Bjorn, O'Neill, Patrick, van Haasteren, Rutger, Anumarlapudi, Akash, Bachetti, Matteo, Bhakta, Deven, Champagne, Chloe, Cromartie, H. Thankful, Demorest, Paul, Jennings, Ross, Kerr, Matthew, Levina, Sasha, McEwen, Alexander, Shapiro-Albert, Brent, Swiggum, Joseph
PINT is a pure-Python framework for high-precision pulsar timing developed on top of widely used and well-tested Python libraries, supporting both interactive and programmatic data analysis workflows. We present a new frequentist framework within PIN
Externí odkaz:
http://arxiv.org/abs/2405.01977
Autor:
Agazie, Gabriella, Baker, Paul T., Bécsy, Bence, Blecha, Laura, Brazier, Adam, Brook, Paul R., Brown, Lucas, Burke-Spolaor, Sarah, 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, Dolch, Timothy, Ferrara, Elizabeth C., Fiore, William, Fonseca, Emmanuel, Freedman, Gabriel E., Garver-Daniels, Nate, Glaser, Joseph, Good, Deborah C., Gültekin, Kayhan, Hazboun, Jeffrey S., Jennings, Ross J., Johnson, Aaron D., Jones, Megan L., Kaiser, Andrew R., 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, Natarajan, Priyamvada, Nice, David J., Ocker, Stella Koch, Olum, Ken D., Pennucci, Timothy T., Pol, Nihan S., Radovan, Henri A., Ransom, Scott M., Ray, Paul S., Romano, Joseph D., Runnoe, Jessie C., Sardesai, Shashwat C., Schmitz, Kai, Siemens, Xavier, Simon, Joseph, Siwek, Magdalena S., Fiscella, Sophia V. Sosa, Stairs, Ingrid H., Stinebring, Daniel R., Susobhanan, Abhimanyu, Swiggum, Joseph K., Taylor, Stephen R., Turner, Jacob E., Unal, Caner, Vallisneri, Michele, Vigeland, Sarah J., Wahl, Haley M., Willson, London, Witt, Caitlin A., Young, Olivia
The cosmic merger history of supermassive black hole binaries (SMBHBs) is expected to produce a low-frequency gravitational wave background (GWB). Here we investigate how signs of the discrete nature of this GWB can manifest in pulsar timing arrays t
Externí odkaz:
http://arxiv.org/abs/2404.07020
This study aims to address the pervasive challenge of quantifying uncertainty in large language models (LLMs) without logit-access. Conformal Prediction (CP), known for its model-agnostic and distribution-free features, is a desired approach for vari
Externí odkaz:
http://arxiv.org/abs/2403.01216
Autor:
Ling, Fenghua, Lu, Zeyu, Luo, Jing-Jia, Bai, Lei, Behera, Swadhin K., Jin, Dachao, Pan, Baoxiang, Jiang, Huidong, Yamagata, Toshio
As our planet is entering into the "global boiling" era, understanding regional climate change becomes imperative. Effective downscaling methods that provide localized insights are crucial for this target. Traditional approaches, including computatio
Externí odkaz:
http://arxiv.org/abs/2402.06646
Autor:
Ling, Fenghua, Ouyang, Lin, Larbi, Boufeniza Redouane, Luo, Jing-Jia, Han, Tao, Zhong, Xiaohui, Bai, Lei
The rapid advancement of artificial intelligence technologies, particularly in recent years, has led to the emergence of several large parameter artificial intelligence weather forecast models. These models represent a significant breakthrough, overc
Externí odkaz:
http://arxiv.org/abs/2401.16669
Autor:
Chen, Kun, Bai, Lei, Ling, Fenghua, Ye, Peng, Chen, Tao, Luo, Jing-Jia, Chen, Hao, Xiao, Yi, Chen, Kang, Han, Tao, Ouyang, Wanli
The weather forecasting system is important for science and society, and significant achievements have been made in applying artificial intelligence (AI) to medium-range weather forecasting. However, existing AI-based weather forecasting models rely
Externí odkaz:
http://arxiv.org/abs/2312.12462