Zobrazeno 1 - 10
of 14 016
pro vyhledávání: '"Kini, AS"'
Autor:
Denton, Peter B., Kini, Yves
A nearby supernova will carry an unprecedented wealth of information about astrophysics, nuclear physics, and particle physics. Because supernova are fundamentally neutrino driven phenomenon, our knowledge about neutrinos -- particles that remain qui
Externí odkaz:
http://arxiv.org/abs/2411.13634
Autor:
Salmi, Tuomo, Deneva, Julia S., Ray, Paul S., Watts, Anna L., Choudhury, Devarshi, Kini, Yves, Vinciguerra, Serena, Cromartie, H. Thankful, Wolff, Michael T., Arzoumanian, Zaven, Bogdanov, Slavko, Gendreau, Keith, Guillot, Sebastien, Ho, Wynn C. G., Morsink, Sharon M., Cognard, Ismaël, Guillemot, Lucas, Theureau, Gilles, Kerr, Matthew
Publikováno v:
ApJ 976 58 (2024)
Recent constraints on neutron star mass and radius have advanced our understanding of the equation of state (EOS) of cold dense matter. Some of them have been obtained by modeling the pulses of three millisecond X-ray pulsars observed by the Neutron
Externí odkaz:
http://arxiv.org/abs/2409.14923
Autor:
Dorsman, Bas, Salmi, Tuomo, Watts, Anna L., Ng, Mason, Kamath, Satish, Bobrikova, Anna, Poutanen, Juri, Loktev, Vladislav, Kini, Yves, Choudhury, Devarshi, Vinciguerra, Serena, Bogdanov, Slavko, Chakrabarty, Deepto
Pulse profile modelling (PPM) is a technique for inferring mass, radius and hotspot properties of millisecond pulsars. PPM is now regularly used for analysis of rotation-powered millisecond pulsars (RMPs) with data from the Neutron Star Interior Comp
Externí odkaz:
http://arxiv.org/abs/2409.07908
Autor:
Choudhury, Devarshi, Salmi, Tuomo, Vinciguerra, Serena, Riley, Thomas E., Kini, Yves, Watts, Anna L., Dorsman, Bas, Bogdanov, Slavko, Guillot, Sebastien, Ray, Paul S., Reardon, Daniel J., Remillard, Ronald A., Bilous, Anna V., Huppenkothen, Daniela, Lattimer, James M., Rutherford, Nathan, Arzoumanian, Zaven, Gendreau, Keith C., Morsink, Sharon M., Ho, Wynn C. G.
We report Bayesian inference of the mass, radius and hot X-ray emitting region properties - using data from the Neutron Star Interior Composition ExploreR (NICER) - for the brightest rotation-powered millisecond X-ray pulsar PSR J0437$\unicode{x2013}
Externí odkaz:
http://arxiv.org/abs/2407.06789
Autor:
Salmi, Tuomo, Choudhury, Devarshi, Kini, Yves, Riley, Thomas E., Vinciguerra, Serena, Watts, Anna L., Wolff, Michael T., Arzoumanian, Zaven, Bogdanov, Slavko, Chakrabarty, Deepto, Gendreau, Keith, Guillot, Sebastien, Ho, Wynn C. G., Huppenkothen, Daniela, Ludlam, Renee M., Morsink, Sharon M., Ray, Paul S.
Publikováno v:
ApJ 974 294 (2024)
We report an updated analysis of the radius, mass, and heated surface regions of the massive pulsar PSR J0740+6620 using Neutron Star Interior Composition Explorer (NICER) data from 2018 September 21 to 2022 April 21, a substantial increase in data s
Externí odkaz:
http://arxiv.org/abs/2406.14466
In real-life scenarios, humans seek out objects in the 3D world to fulfill their daily needs or intentions. This inspires us to introduce 3D intention grounding, a new task in 3D object detection employing RGB-D, based on human intention, such as "I
Externí odkaz:
http://arxiv.org/abs/2405.18295
Autor:
Kini, Yves, Salmi, Tuomo, Vinciguerra, Serena, Watts, Anna L., Bilous, Anna, Galloway, Duncan K., van der Wateren, Emma, Khalsa, Guru Partap, Bogdanov, Slavko, Buchner, Johannes, Suleimanov, Valery
Pulse profile modelling (PPM) is a comprehensive relativistic ray-tracing technique employed to determine the properties of neutron stars. In this study, we apply this technique to the Type I X-ray burster and accretion-powered millisecond pulsar XTE
Externí odkaz:
http://arxiv.org/abs/2405.10717
FastCAR is a novel task consolidation approach in Multi-Task Learning (MTL) for a classification and a regression task, despite task heterogeneity with only subtle correlation. It addresses object classification and continuous property variable regre
Externí odkaz:
http://arxiv.org/abs/2403.17926
Learning from preference-based feedback has recently gained traction as a promising approach to align language models with human interests. While these aligned generative models have demonstrated impressive capabilities across various tasks, their de
Externí odkaz:
http://arxiv.org/abs/2403.00409
Autor:
Wang, Hanbing, Liu, Xiaorui, Fan, Wenqi, Zhao, Xiangyu, Kini, Venkataramana, Yadav, Devendra, Wang, Fei, Wen, Zhen, Tang, Jiliang, Liu, Hui
Recently, sequential recommendation has been adapted to the LLM paradigm to enjoy the power of LLMs. LLM-based methods usually formulate recommendation information into natural language and the model is trained to predict the next item in an auto-reg
Externí odkaz:
http://arxiv.org/abs/2402.09543