English
Related papers

Related papers: Mode-sum regularization of $\left\langle \phi^{2} …

200 papers

Calculating cost-effective solutions to particle dynamics in viscous flows is an important problem in many areas of industry and nature. We implement a second-order symmetric splitting method on the governing equations for a rigid…

Computational Physics · Physics 2018-04-09 Benjamin Tapley , Elena Celledoni , Brynjulf Owren , Helge I. Andersson

We propose a second renormalization group method to handle the tensor-network states or models. This method reduces dramatically the truncation error of the tensor renormalization group. It allows physical quantities of classical…

Strongly Correlated Electrons · Physics 2024-06-26 Z. Y. Xie , H. C. Jiang , Q. N. Chen , Z. Y. Weng , T. Xiang

In this paper, we study a fractional-order variant of the asymptotical regularization method, called {\it Fractional Asymptotical Regularization (FAR)}, for solving linear ill-posed operator equations in a Hilbert space setting. We assign…

Numerical Analysis · Mathematics 2019-07-16 Ye Zhang , Bernd Hofmann

The angular power spectrum is a gauge-independent observable that is in principle the natural tool for analysing galaxy number counts. In practice, the problem is that the computational requirements for next-generation spectroscopic surveys…

Cosmology and Nongalactic Astrophysics · Physics 2019-03-12 Stefano Camera , José Fonseca , Roy Maartens , Mário G. Santos

The renormalization of entanglement entropy of quantum field theories is investigated in the simplest setting with a $\lambda \phi^4$ scalar field theory. The 3+1 dimensional spacetime is separated into two regions by an infinitely flat…

High Energy Physics - Theory · Physics 2017-09-19 Jiunn-Wei Chen , Jin-Yi Pang

We propose a scalable tensorization framework for neural network compression based on slice-wise feature distillation. Unlike conventional tensor decomposition methods that rely on costly global finetuning, our approach decomposes the…

Machine Learning · Computer Science 2026-05-20 Safa Hamreras , Sukhbinder Singh , Román Orús

A tensor network renormalization algorithm with global optimization based on the corner transfer matrix is proposed. Since the environment is updated by the corner transfer matrix renormalization group method, the forward-backward iteration…

Statistical Mechanics · Physics 2021-01-26 Satoshi Morita , Naoki Kawashima

In this thesis, we present a novel method combining energy-based finite-size scaling with tensor network renormalization (TNR) to study phase transitions in lattice models. This approach effectively calculates running coupling constants and…

Statistical Mechanics · Physics 2024-02-01 Atsushi Ueda

We calculate the renormalized vacuum polarization and stress tensor for a massless, arbitrarily coupled scalar field in the Hartle-Hawking vacuum state on the horizon of a Schwarzschild black hole threaded by an infinte straight cosmic…

General Relativity and Quantum Cosmology · Physics 2011-01-27 Adrian C. Ottewill , Peter Taylor

We present a method to accelerate the numerical evaluation of spatial integrals of Feynman diagrams when expressed on the real frequency axis. This can be realized through use of a renormalized perturbation expansion with a constant but…

Strongly Correlated Electrons · Physics 2023-04-05 M. D. Burke , Maxence Grandadam , J. P. F. LeBlanc

We extend our previous symmetrized path-integral molecular dynamics approach to calculate tunneling splittings of molecules in rotationally excited states. In this new formalism, the system is rigorously projected onto selected rotational…

Chemical Physics · Physics 2026-04-15 Lea Zupan , Yu-Chen Wang , Jeremy O. Richardson

The point-splitting regularization technique for composite operators is discussed in connection with anomaly calculation. We present a pedagogical and self-contained review of the topic with an emphasis on the technical details. We also…

High Energy Physics - Theory · Physics 2015-06-26 J. Novotny , M. Schnabl

We present a new finite element method, called $\phi$-FEM, to solve numerically elliptic partial differential equations with natural (Neumann or Robin) boundary conditions using simple computational grids, not fitted to the boundary of the…

Numerical Analysis · Mathematics 2020-12-08 Michel Duprez , Vanessa Lleras , Alexei Lozinski

In this thesis, a new class of algorithms based on Sums of Squares Programming is developed. These allow to reduce a degree-$d$ homogeneous polynomial $T = \sum_{i = 1}^m \langle a_i, X \rangle^d $ to a quadratic form being close to a…

Numerical Analysis · Mathematics 2018-12-14 Alexander Taveira Blomenhofer

We construct a pseudospectral method for the solution of time-dependent, non-linear partial differential equations on a three-dimensional spherical shell. The problem we address is the treatment of tensor fields on the sphere. As a test…

Computational Physics · Physics 2015-05-27 Bernd Bruegmann

To reconstruct a mixed or pure quantum state of a spin s is possible through coherent states: its density matrix is fixed by the probabilities to measure the value s along 4s(s+1) appropriately chosen directions in space. Thus, after…

Quantum Physics · Physics 2007-05-23 Stefan Weigert

We study the stress-energy tensor of a massless, conformally coupled, quantum scalar field in a rigidly-rotating thermal state on three- and four-dimensional anti-de Sitter space-time. We first find the stress-energy tensor using…

High Energy Physics - Theory · Physics 2025-08-08 Jacob C. Thompson , Elizabeth Winstanley

We combine the multigrid (MG) method with state-of-the-art concepts from the variational formulation of the numerical renormalization group. The resulting MG renormalization (MGR) method is a natural generalization of the MG method for…

Computational Physics · Physics 2018-07-17 Michael Lubasch , Pierre Moinier , Dieter Jaksch

Tensor networks have proven to be a valuable tool, for instance, in the classical simulation of (strongly correlated) quantum systems. As the size of the systems increases, contracting larger tensor networks becomes computationally…

Quantum Physics · Physics 2025-07-29 Manuel Geiger , Qunsheng Huang , Christian B. Mendl

We propose a numerical method for kinetic plasma simulation in which the phase-space distribution function is represented by a low-rank tensor network with an adaptive level of compression. The Vlasov-Poisson system is advanced using Strang…

Computational Physics · Physics 2026-02-16 Erik M. Åsgrim , Luca Pennati , Marco Pasquale , Stefano Markidis
‹ Prev 1 4 5 6 7 8 10 Next ›