Zobrazeno 1 - 10
of 1 214
pro vyhledávání: '"Shah, Parth A"'
Publikováno v:
Int.J.Geom.Meth.Mod.Phys. 20 (2023) 03, 2350042
We explore an autonomous system analysis of dark energy models with interactions between dark energy and cold dark matter in a general systematic approach to cosmological fluids. We investigate two types of models such as local and non-local ones. In
Externí odkaz:
http://arxiv.org/abs/2403.08263
Distributing entanglement between remote sites is integral to quantum networks. Here, we demonstrate the autonomous stabilization of remote entanglement between a pair of non-interacting superconducting qubits connected by an open waveguide on a chip
Externí odkaz:
http://arxiv.org/abs/2402.15701
Autor:
Vishwakarma, Pooja, Shah, Parth
Publikováno v:
Eur. Phys. J. C 84, 159 (2024)
The higher-curvature gravity with boundary terms i.e the $f(Q)$ theories, grounded on non-metricity as a fundamental geometric quantity, exhibit remarkable efficacy in portraying late-time universe phenomena. The aim is to delineate constraints on tw
Externí odkaz:
http://arxiv.org/abs/2402.07951
Autor:
Vishwakarma, Pooja, Shah, Parth
Publikováno v:
Int.J.Mod.Phys.D 32 (2023) 11, 2350071
In recent years, the modified theory of gravity known as $f(Q)$ gravity has drawn interest as a potential alternative to general relativity. According to this theory, the gravitational force is determined by a function of the so-called ``non-metricit
Externí odkaz:
http://arxiv.org/abs/2401.09004
Cosmological dynamics are investigated in detail through systematic procedures by using the autonomous system analyses of gravitational field equations in $ f(Q) $ gravity. The explicit analyses of the late-time cosmic evolutions are demonstrated for
Externí odkaz:
http://arxiv.org/abs/2401.05455
In this paper we show an effective means of integrating data driven frameworks to sampling based optimal control to vastly reduce the compute time for easy adoption and adaptation to real time applications such as on-road autonomous driving in the pr
Externí odkaz:
http://arxiv.org/abs/2310.13077
Large Language Models (LLMs) have seen widespread deployment in various real-world applications. Understanding these biases is crucial to comprehend the potential downstream consequences when using LLMs to make decisions, particularly for historicall
Externí odkaz:
http://arxiv.org/abs/2308.02053
Autor:
Bhunia, Ayan Kumar, Sain, Aneeshan, Shah, Parth, Gupta, Animesh, Chowdhury, Pinaki Nath, Xiang, Tao, Song, Yi-Zhe
The recent focus on Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) has shifted towards generalising a model to new categories without any training data from them. In real-world applications, however, a trained FG-SBIR model is often applied to b
Externí odkaz:
http://arxiv.org/abs/2207.01723
Autor:
Kim, Juhyeon, Shah, Parth, Bhavsar, Raj, Lim, Dongbin, Seo, Sojin, Hyung, Jisung, Park, Sangmin, Kwon, Joseph Sang-Il
Publikováno v:
In Chemical Engineering Journal 1 November 2024 499
Autor:
Cleary, Colin M., Adajian, Allison, Gifford, Edward D., Orosco, Emily, Li, Ya-Huei, Healy, Laura, Dawiczyk, Stephania, Bozeman, Patricia, Guerin, Elizabeth, Farrell, Hannah, Shah, Parth
Publikováno v:
In Journal of Vascular Surgery September 2024 80(3):821-830