English
Related papers

Related papers: Analytic continuation by averaging Pad\'e approxim…

200 papers

We develop a framework for extracting non-polynomial analytic functions of density matrices in randomized measurement experiments by a method of analytical continuation. A central advantage of this approach, dubbed stabilized analytic…

Quantum Physics · Physics 2026-01-29 Akash Vijay , Ayush Raj , Jonah Kudler-Flam , Benoît Vermersch , Andreas Elben , Laimei Nie

We initiate a systematic study of utilizing predictions to improve over approximation guarantees of classic algorithms, without increasing the running time. We propose a systematic method for a wide class of optimization problems that ask…

Data Structures and Algorithms · Computer Science 2024-11-26 Antonios Antoniadis , Marek Eliáš , Adam Polak , Moritz Venzin

An analytical Green's function is developed to study the acoustic scattering by a flat plate with a serrated edge. The scattered pressure is solved using the Wiener-Hopf technique in conjunction with the adjoint technique. It is shown that…

Fluid Dynamics · Physics 2023-05-10 Benshuai Lyu

We present a method for analytic continuation of retarded Green functions, including Euclidean Green functions computed using lattice QCD. The method is based on conformal maps and construction of an interpolation function which is analytic…

High Energy Physics - Lattice · Physics 2023-06-14 Thomas Bergamaschi , William I. Jay , Patrick R. Oare

We consider the numerical approximation of the mild solution to a semilinear stochastic wave equation driven by additive noise. For the spatial approximation we consider a standard finite element method and for the temporal approximation, a…

Numerical Analysis · Mathematics 2023-12-06 Mihály Kovács , Annika Lang , Andreas Petersson

During the past three decades, the advantageous concept of the Green's function has been extended from linear systems to nonlinear ones. At that, there exist a rigorous and an approximate extensions. The rigorous extension introduces the…

Mathematical Physics · Physics 2018-03-28 Asatur Khurshudyan

We compare and discuss the respective efficiency of three methods (with two variants for each of them), based respectively on Taylor (Maclaurin) series, Pad\'{e} approximants and conformal mappings, for solving quasi-analytically a…

Mathematical Physics · Physics 2011-09-09 S. Abbasbandy , C. Bervillier

In this work we present a numerical method to solve the set of Dyson-like equations arising the context of non-equilibrium Green's functions. The technique is based on the self-consistent solution of the Dyson equations for the interacting…

Strongly Correlated Electrons · Physics 2019-09-04 N. W. Talarico , S. Maniscalco , N. Lo Gullo

In the framework of the many-electron s-d exchange model and Hubbard model, self-consistent equations are derived for the one-particle retarded Green's function in the many-electron Hubbard X-operator representation. We analyze the general…

Strongly Correlated Electrons · Physics 2015-06-03 A. O. Anokhin , A. V. Zarubin , V. Yu. Irkhin

Given a locally consistent set of reduced density matrices, we construct approximate density matrices which are globally consistent with the local density matrices we started from when the trial density matrix has a tree structure. We…

Disordered Systems and Neural Networks · Physics 2015-06-18 I. Biazzo , A. Ramezanpour

Entropy is ubiquitous in machine learning, but it is in general intractable to compute the entropy of the distribution of an arbitrary continuous random variable. In this paper, we propose the amortized residual denoising autoencoder…

Machine Learning · Computer Science 2020-06-11 Jae Hyun Lim , Aaron Courville , Christopher Pal , Chin-Wei Huang

Asymptotically exact results are obtained for the average Green function and density of states of a disordered system for a renormalizable class of models (as opposed to the lattice models examined previously [Zh. Eksp. Teor. Fiz. 106…

Disordered Systems and Neural Networks · Physics 2007-05-23 I. M. Suslov

Solving the Anderson impurity model typically involves a two-step process, where one first calculates the ground state of the Hamiltonian, and then computes its dynamical properties to obtain the Green's function. Here we propose a hybrid…

The inspiral of two compact objects in gravitational wave astronomy is described by a post-Newtonian expansion in powers of $(v/c)$. In most cases, it is believed that the post-Newtonian expansion is asymptotically divergent. A standard…

General Relativity and Quantum Cosmology · Physics 2011-12-15 Jérôme Carré , Edward K. Porter

A method based on separated integration to estimate anharmonic corrections to energy and vibration of molecules in a second-order diagrammatic vibrational many-body Green's function formalism has already been presented. A severe bottleneck…

Chemical Physics · Physics 2019-09-17 Prashant Rai , Khachik Sargsyan , Habib Najm , So Hirata

We propose a message-passing algorithm to compute the Hamiltonian expectation with respect to an appropriate class of trial wave functions for an interacting system of fermions. To this end, we connect the quantum expectations to average…

Statistical Mechanics · Physics 2015-06-11 A. Ramezanpour , R. Zecchina

Green's functions with continuum spectra are a way of avoiding the strong bounds on new physics from the absence of new narrow resonances in experimental data. We model such a situation with a five-dimensional model with two branes along…

High Energy Physics - Phenomenology · Physics 2021-10-13 Eugenio Megias , Mariano Quiros

We develop a method for calculating the self-energy of a quantum impurity coupled to a continuous bath by stochastically generating a distribution of finite Anderson models that are solved by exact diagonalization, using the noninteracting…

Strongly Correlated Electrons · Physics 2012-09-13 Mats Granath , Hugo U. R. Strand

Variational inference in probabilistic graphical models aims to approximate fundamental quantities such as marginal distributions and the partition function. Popular approaches are the Bethe approximation, tree-reweighted, and other types…

Machine Learning · Statistics 2025-02-06 Harald Leisenberger , Franz Pernkopf

A canonical feature of the constraint satisfaction problems in NP is approximation hardness, where in the worst case, finding sufficient-quality approximate solutions is exponentially hard for all known methods. Fundamentally, the lack of…