Zobrazeno 1 - 10
of 11 778
pro vyhledávání: '"Verma A. K"'
Heat transport in highly turbulent convection is not well understood. In this paper, we simulate compressible convection in a box of aspect ratio 4 using computationally-efficient MacCormack-TVD finite difference method on single and multi-GPUs, and
Externí odkaz:
http://arxiv.org/abs/2411.10372
In this paper, using \textit{hydrodynamic entropy} we quantify the multiscale disorder in Euler and hydrodynamic turbulence. These examples illustrate that the hydrodynamic entropy is not extensive because it is not proportional to the system size. C
Externí odkaz:
http://arxiv.org/abs/2411.03135
Autor:
Verma, Mahendra K.
Hydrodynamic turbulence exhibits nonequilibrium behaviour with $k^{-5/3}$ energy spectrum, and equilibrium behaviour with $k^{d-1}$ energy spectrum and zero viscosity, where $d$ is the space dimension. Using recursive renormalization group {in Craya-
Externí odkaz:
http://arxiv.org/abs/2408.07573
This paper introduces nonlinear fractional Lane-Emden equations of the form, $$ D^{\alpha} y(x) + \frac{\lambda}{x^\beta}~ D^{\beta} y(x) + f(y) =0, ~ ~1 < \alpha \leq 2, ~~ 0< \beta \leq 1, ~~ 0 < x < 1,$$ subject to boundary conditions, $$ y'(0) =\
Externí odkaz:
http://arxiv.org/abs/2408.10212
Despite the rapid advancement in the field of image recognition, the processing of high-resolution imagery remains a computational challenge. However, this processing is pivotal for extracting detailed object insights in areas ranging from autonomous
Externí odkaz:
http://arxiv.org/abs/2405.07166
Autor:
Bhat, Meghana, Dubey, Saipriya, Masuti, Shreedevi K., Okuma, Tomohiro, Verma, Jugal K., Watanabe, Kei-ichi, Yoshida, Ken-ichi
Let $(A, \mathfrak{m})$ be a Gorenstein local ring, and $\mathcal{F} =\{F_n \}_{n\in \mathbb{Z}}$ a Hilbert filtration. In this paper, we give a criterion for Gorensteinness of the associated graded ring of $\mathcal{F}$ in terms of the Hilbert coeff
Externí odkaz:
http://arxiv.org/abs/2404.14189
Continual Learning (CL) enables machine learning models to learn from continuously shifting new training data in absence of data from old tasks. Recently, pretrained vision transformers combined with prompt tuning have shown promise for overcoming ca
Externí odkaz:
http://arxiv.org/abs/2403.20317
This article investigates the computational aspects of the $\varepsilon$-multiplicity. Primarily, we show that the $\varepsilon$-multiplicity of a homogeneous ideal $I$ in a two-dimensional standard graded domain of finite type over an algebraically
Externí odkaz:
http://arxiv.org/abs/2402.11935
Autor:
Maurya, Seetaram, Verma, Nishchal K.
Various methods for designing input features have been proposed for fault recognition in rotating machines using one-dimensional raw sensor data. The available methods are complex, rely on empirical approaches, and may differ depending on the conditi
Externí odkaz:
http://arxiv.org/abs/2402.09957
Autor:
Gupta, Bivek, Verma, Amit K.
This comprehensive review paper delves into the intricacies of advanced Fourier type integral transforms and their mathematical properties, with a particular focus on fractional Fourier transform (FrFT), linear canonical transform (LCT), quadratic ph
Externí odkaz:
http://arxiv.org/abs/2402.06645