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Related papers: Computation Kernel for Feynman Diagrams

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A derivation is given of the Feynman rules to be used in the perturbative computation of the Green's functions of a generic quantum many-body theory when the action which is being perturbed is not necessarily quadratic. Some applications…

High Energy Physics - Theory · Physics 2008-11-26 M. J. de la Plata , L. L. Salcedo

We present a formalism for computing arbitrary multi-loop Feynman graphs in curved spacetime using the heat kernel approach. To this end, we compute the off-diagonal components of the heat kernel in Riemann normal coordinates up to second…

High Energy Physics - Theory · Physics 2024-08-09 Igor Carneiro , Gero von Gersdorff

The use of kernel functions is a common technique to extract important features from data sets. A quantum computer can be used to estimate kernel entries as transition amplitudes of unitary circuits. Quantum kernels exist that, subject to…

We propose a representation of graph as a functional object derived from the power iteration of the underlying adjacency matrix. The proposed functional representation is a graph invariant, i.e., the functional remains unchanged under any…

Machine Learning · Computer Science 2014-04-22 Anshumali Shrivastava , Ping Li

We present a simple numerical scheme for perturbation theory (PT) calculations of large-scale structure. Solving the evolution equations for perturbations numerically, we construct the PT kernels as building blocks of statistical…

Cosmology and Nongalactic Astrophysics · Physics 2016-07-13 Atsushi Taruya

The many-body problem is usually approached from one of two perspectives: the first originates from an action and is based on Feynman diagrams, the second is centered around a Hamiltonian and deals with quantum states and operators. The…

Strongly Correlated Electrons · Physics 2021-10-15 Fabian B. Kugler , Seung-Sup B. Lee , Jan von Delft

Feynman's diagrammatic series is a common language for a formally exact theoretical description of systems of infinitely-many interacting quantum particles, as well as a foundation for precision computational techniques. Here we introduce a…

Strongly Correlated Electrons · Physics 2024-09-12 Evgeny Kozik

Symmetry-breaking considerations play an important role in allowing reliable and accurate predictions of complex systems in quantum many-body simulations. The general theory of perturbations in symmetry-breaking phases is nonetheless…

Nuclear Theory · Physics 2025-07-09 M. Drissi , A. Rios , C. Barbieri

We use tensor network techniques to obtain high order perturbative diagrammatic expansions for the quantum many-body problem at very high precision. The approach is based on a tensor train parsimonious representation of the sum of all…

We present results for many-body perturbation theory for the one-body Green's function at finite temperatures using the Matsubara formalism. Our method relies on the accurate representation of the single-particle states in standard Gaussian…

Strongly Correlated Electrons · Physics 2018-04-04 Michael Schüler , Yaroslav Pavlyukh

Accurate simulations of atomistic systems from first principles are limited by computational cost. In high-throughput settings, machine learning can reduce these costs significantly by accurately interpolating between reference…

Chemical Physics · Physics 2022-11-28 Haoyan Huo , Matthias Rupp

In this talk we discuss mathematical structures associated to Feynman graphs. Feynman graphs are the backbone of calculations in perturbative quantum field theory. The mathematical structures -- apart from being of interest in their own…

Mathematical Physics · Physics 2009-12-23 Christian Bogner , Stefan Weinzierl

The kernel method is a potential approach to analyzing structured data such as sequences, trees, and graphs; however, unordered trees have not been investigated extensively. Kimura et al. (2011) proposed a kernel function for unordered…

Data Structures and Algorithms · Computer Science 2012-06-22 Daisuke Kimura , Hisashi Kashima

In the univariate setting, using the kernel spectral representation is an appealing approach for generating stationary covariance functions. However, performing the same task for multiple-output Gaussian processes is substantially more…

Machine Learning · Statistics 2021-03-15 Fergus Simpson , Alexis Boukouvalas , Vaclav Cadek , Elvijs Sarkans , Nicolas Durrande

Inspired by the work of Feynman, Deutsch, We formally propose the theory of physical computability and accordingly, the physical complexity theory. To achieve this, a framework that can evaluate almost all forms of computation using various…

Computational Physics · Physics 2011-12-06 Huimin Zheng , HaiXing Hu , Nan Wu , Fangmin Song

We present a geometric algorithm to compute the geometric kernel of a generic polyhedron. The geometric kernel (or simply kernel) is definedas the set of points from which the whole polyhedron is visible. Whilst the computation of the…

Computational Geometry · Computer Science 2021-10-28 Tommaso Sorgente , Silvia Biasotti , Michela Spagnuolo

The nonequilibrium Green's function formalism provides a versatile and powerful framework for numerical studies of nonequilibrium phenomena in correlated many-body systems. For calculations starting from an equilibrium initial state, a…

Strongly Correlated Electrons · Physics 2024-07-11 Matthias Murray , Hiroshi Shinaoka , Philipp Werner

QAssemble is a pure-Python package for the quantum many-body problem. It implements various functional approaches, such as tight-binding, Hartree-Fock, and GW approximations within a unified object-oriented architecture. Each physical…

Strongly Correlated Electrons · Physics 2026-04-27 Seongjun Mo , Dongming Li , Mancheon Han , Johan Jönsson , Byungkyun Kang , Hoonkyung Lee , Gabriel Kotliar , Sangkook Choi

We prove in full generality the thermal operator representation for Matsubara sums in a relativistic field theory of scalar and fermionic particles. It states that the full result of performing the Matsubara sum associated to any given…

High Energy Physics - Phenomenology · Physics 2011-07-19 Olivier Espinosa

The algorithm to calculate the generating function for the number of ``skeleton'' diagrams for the irreducible self-energy and vertex parts is derived for the problems with Gaussian random fields. We find an exact recurrence relation…

Disordered Systems and Neural Networks · Physics 2009-10-30 E. Z. Kuchinskii , M. V. Sadovskii
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