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Incorporating symmetries into the numerical solution of differential equations has been a mainstay of research over the last 40 years, however, one aspect is less known and under-utilised: discretisations of partial differential equations…

Numerical Analysis · Mathematics 2025-10-16 Sheehan Olver

The worldvolume tempered Lefschetz thimble method (WV-TLTM) is an algorithm towards solving the sign problem, where hybrid Monte Carlo updates are performed on a continuous accumulation of flowed surfaces foliated by the anti-holomorphic…

High Energy Physics - Lattice · Physics 2021-11-30 Masafumi Fukuma , Nobuyuki Matsumoto , Yusuke Namekawa

We studied integration contour deformations in the chiral random matrix theory of Stephanov with the goal of alleviating the finite-density sign problem. We considered simple ans\"atze for the deformed integration contours, and optimized…

High Energy Physics - Lattice · Physics 2023-01-31 Matteo Giordano , Attila Pasztor , David Pesznyak , Zoltan Tulipant

I formulate a deformation of the dimensional-regularization technique that is useful for theories where the common dimensional regularization does not apply. The Dirac algebra is not dimensionally continued, to avoid inconsistencies with…

High Energy Physics - Theory · Physics 2009-11-10 Damiano Anselmi

This paper introduces a new functional expansion framework that extends classical ideas beyond the Taylor series. Unlike traditional Taylor expansions based on local polynomial approximations, the proposed approach arises from exact…

Numerical Analysis · Mathematics 2026-02-03 Junping Wang

We study three dimensional $\mathcal{N}=2$ supersymmetric abelian gauge theories with various matter contents living on a squashed sphere. In particular we focus on two problems: firstly we perform a Picard-Lefschetz decomposition of the…

High Energy Physics - Theory · Physics 2020-01-29 Daniele Dorigoni , Philip Glass

A new transform-based approach is presented that can be used to solve mixed boundary value problems for Laplace's equation in non-convex and other planar domains, specifically the so-called Lipschitz domains. This work complements Crowdy…

Complex Variables · Mathematics 2025-07-30 Jesse J. Hulse , Loredana Lanzani , Stefan G. Llewellyn Smith , Elena Luca

A fruitful approach for solving signal deconvolution problems consists of resorting to a frame-based convex variational formulation. In this context, parallel proximal algorithms and related alternating direction methods of multipliers have…

Other Computer Science · Computer Science 2015-05-28 Nelly Pustelnik , Jean-Christophe Pesquet , Caroline Chaux

A matrix formalism is proposed for computations based on Picard--Lefschetz theory in a 2D case. The formalism is essentially equivalent to the computation of the intersection indices necessary for the Picard--Lefschetz formula and enables…

Mathematical Physics · Physics 2025-12-22 A. V. Shanin , A. I. Korolkov , N. M. Artemov , R. C. Assier

We consider the problem of single-source domain generalization. Existing methods typically rely on extensive augmentations to synthetically cover diverse domains during training. However, they struggle with semantic shifts (e.g., background…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Aishwarya Agarwal , Srikrishna Karanam , Vineet Gandhi

Many physical systems are well described on domains which are relatively large in some directions but relatively thin in other directions. In this scenario we typically expect the system to have emergent structures that vary slowly over the…

Dynamical Systems · Mathematics 2016-12-15 A. J. Roberts , J. E. Bunder

A summation framework is developed that enhances Karr's difference field approach. It covers not only indefinite nested sums and products in terms of transcendental extensions, but it can treat, e.g., nested products defined over roots of…

Symbolic Computation · Computer Science 2015-02-04 Carsten Schneider

In the present paper we consider the problem of Laplace deconvolution with noisy discrete non-equally spaced observations on a finite time interval. We propose a new method for Laplace deconvolution which is based on expansions of the…

Methodology · Statistics 2015-03-17 Fabienne Comte , Charles-A. Cuenod , Marianna Pensky , Yves Rozenholc

The method of self-consistent expansions is a powerful tool for handling strong coupling problems that might otherwise be beyond the reach of perturbation theory, providing surprisingly accurate approximations even at low order. First…

Statistical Mechanics · Physics 2025-01-15 Minhui Zhu , Nigel Goldenfeld

Discontinuity with respect to data perturbations is common in algebraic computation where solutions are often highly sensitive. Such problems can be modeled as solving systems of equations at given data parameters. By appending auxiliary…

Numerical Analysis · Mathematics 2021-02-17 Zhonggang Zeng

We discuss two problems in complexified auxiliary fields in fermionic effective models, the auxiliary sign problem associated with the repulsive vector-field and the choice of the cut for the scalar field appearing from the logarithmic…

High Energy Physics - Lattice · Physics 2018-04-18 Yuto Mori , Kouji Kashiwa , Akira Ohnishi

Based on the Taylor expansion, we propose a renormalization method for asymptotic analysis. The standard renormalization group (RG) method for asymptotic analysis can be derived out from this new method, and hence the mathematical essence…

Mathematical Physics · Physics 2016-05-11 Cheng-shi Liu

A regularization procedure developed in [1] for the integral curvature invariants on manifolds with conical singularities is generalized to the case of squashed cones. In general, the squashed conical singularities do not have rotational…

High Energy Physics - Theory · Physics 2015-06-16 Dmitri V. Fursaev , Alexander Patrushev , Sergey N. Solodukhin

This note is about promoting singularity subtraction as a helpful tool in the discretization of singular integral operators on curved surfaces. Singular and nearly singular kernels are expanded in series whose terms are integrated on…

Numerical Analysis · Mathematics 2013-01-31 Johan Helsing

Nonlinear dimensionality reduction methods provide a valuable means to visualize and interpret high-dimensional data. However, many popular methods can fail dramatically, even on simple two-dimensional manifolds, due to problems such as…

Machine Learning · Statistics 2020-07-08 Daniel Ting , Michael I. Jordan