Tootfinder

Replaced article(s) found for math.PR. https://arxiv.org/list/math.PR/new
[1/1]:
- The high-dimensional asymptotics of first order methods with random data
Michael Celentano, Chen Cheng, Andrea Montanari

This https://arxiv.org/abs/2112.06300 has been replaced.
link: https://scholar.google.com/scholar?q=a

Time of Impact Dataset for Continuous Collision Detection and a Scalable Conservative Algorithm
We introduce a large-scale benchmark for broad- and narrow-phase continuous collision detection (CCD) over linearized trajectories with exact time of impacts and use it to evaluate the accuracy, correctness, and efficiency of 13 state-of-the-art CCD algorithms. Our analysis shows that several methods exhibit problems either in efficiency or accuracy. To overcome these limitations, we introduce an algorithm for CCD designed to be scalable on modern parallel architectures and provably correct w…

Replaced article(s) found for math.AP. https://arxiv.org/list/math.AP/new
[1/1]:
- Orlicz-Sobolev versus H\"older local minimizer for nonlinear Robin problems
Anouar Bahrouni, Hlel Missaoui, Hichem Ounaies, Vicentiu Radulescu

This https://arxiv.org/abs/2112.04700 has been replaced.
link: https://scholar.google.com/scholar?q=a

Asymptotic stability of sharp fronts: Analysis and rigorous computation
We investigate the stability of traveling front solutions to nonlinear diffusive-dispersive equations of Burgers type, with a primary focus on the Korteweg-de Vries-Burgers (KdVB) equation, although our analytical findings extend more broadly. Manipulating the temporal modulation of the translation parameter of the front and employing the energy method, we establish asymptotic, nonlinear, and orbital stability, provided that an auxiliary Schrödinger equation possesses precisely one bound state…