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We present a new approximation technique for quantum field theory. The standard one-loop result is used as a seed for a recursive formula that gives a sequence of improved Gaussian approximations for the generating functional. In a…

High Energy Physics - Theory · Physics 2011-08-08 Antun Balaz , Aleksandar Belic , Aleksandar Bogojevic

We discuss the recently developed method of refined absorption and how it is used to provide a new proof of the Existence Conjecture for combinatorial designs. This method can also be applied to resolve open problems in extremal and…

Combinatorics · Mathematics 2025-10-24 Luke Postle

By merging algorithmic Matsubara integration with discrete pole representations we present a procedure to generate fully analytic closed form results for impurity problems at fixed perturbation order. To demonstrate the utility of this…

Strongly Correlated Electrons · Physics 2024-07-02 Daria Gazizova , Lei Zhang , Emanuel Gull , J. P. F. LeBlanc

We introduce a symbolic method for the evaluation of definite integrals containing combinations of various functions, including exponentials, logarithm and products of Bessel functions of different types. The method we develop is naturally…

Classical Analysis and ODEs · Mathematics 2011-11-04 D. Babusci , G. Dattoli

In recent years enormous progress has been made in perturbative quantum field theory by applying methods of algebraic geometry to parametric Feynman integrals for scalar theories. The transition to gauge theories is complicated not only by…

Mathematical Physics · Physics 2017-09-14 Marcel Golz

In view synthesis, a neural radiance field approximates underlying density and radiance fields based on a sparse set of scene pictures. To generate a pixel of a novel view, it marches a ray through the pixel and computes a weighted sum of…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Nikita Morozov , Denis Rakitin , Oleg Desheulin , Dmitry Vetrov , Kirill Struminsky

Existing factual consistency evaluation approaches for text summarization provide binary predictions and limited insights into the weakness of summarization systems. Therefore, we propose the task of fine-grained inconsistency detection,…

Computation and Language · Computer Science 2023-05-25 Hou Pong Chan , Qi Zeng , Heng Ji

We give a detailed exposition of the formalism of Kinetic Field Theory (KFT) with emphasis on the perturbative determination of observables. KFT is a statistical non-equilibrium classical field theory based on the path integral formulation…

High Energy Physics - Theory · Physics 2022-10-05 Lavinia Heisenberg , Shayan Hemmatyar , Stefan Zentarra

Partition refinement is a method for minimizing automata and transition systems of various types. Recently, a new partition refinement algorithm and associated tool CoPaR were developed that are generic in the transition type of the input…

Data Structures and Algorithms · Computer Science 2022-04-14 Fabian Birkmann , Hans-Peter Deifel , Stefan Milius

An autonomous variational inference algorithm for arbitrary graphical models requires the ability to optimize variational approximations over the space of model parameters as well as over the choice of tractable families used for the…

Machine Learning · Computer Science 2012-07-19 Eric P. Xing , Michael I. Jordan , Stuart Russell

A new formulation of field theory is presented, based on a pseudo-complex description. An extended group structure is introduced, implying a minimal scalar length, rendering the theory regularized a la Pauli-Villars. Cross sections are…

High Energy Physics - Theory · Physics 2008-11-26 Peter O. Hess , Walter Greiner

We use the homological perturbation lemma to produce explicit formulas computing the class in the twisted de Rham complex represented by an arbitrary polynomial. This is a non-asymptotic version of the method of Feynman diagrams. In…

Mathematical Physics · Physics 2019-11-05 Theo Johnson-Freyd

We present a method derived from Laplace transform theory that enables the evaluation of fractional integrals. This method is adapted and extended in a variety of ways to demonstrate its utility in deriving alternative representations for…

Classical Analysis and ODEs · Mathematics 2009-09-25 M. Lawrence Glasser , Victor Kowalenko

We demonstrate that a Meijer-G-function-based resummation approach can be successfully applied to approximate the Borel sum of divergent series, and thus to approximate the Borel-\'Ecalle summation of resurgent transseries in quantum field…

High Energy Physics - Theory · Physics 2018-06-06 Hector Mera , Thomas G. Pedersen , Branislav K. Nikolic

Over the last year significant progress was made in the understanding of the computation of Feynman integrals using differential equations. These lectures give a review of these developments, while not assuming any prior knowledge of the…

High Energy Physics - Phenomenology · Physics 2015-06-23 Johannes M. Henn

A natural procedure is introduced to replace the traditional, perturbatively generated counter terms to yield a formulation of covariant, self-interacting, nonrenormalizable scalar quantum field theories that has the added virtue of…

High Energy Physics - Theory · Physics 2008-11-26 John R. Klauder

The recent hardware trend towards reduced precision computing has reignited the interest in numerical techniques that can be used to enhance the accuracy of floating point operations beyond what is natively supported for basic arithmetic…

Numerical Analysis · Mathematics 2026-02-24 Longfei Gao , Frimpong Baidoo

In this paper, we consider a "compensated" random sum that arises from numerical approximation of stochastic integrations and differential equations. We show that the compensated sum exhibits some surprising cancellations among its…

Probability · Mathematics 2024-01-30 Yanghui Liu

A new powerful method to calculate Feynman diagrams is proposed. It consists in setting up a Taylor series expansion in the external momenta squared (in general multivariable). The Taylor coefficients are obtained from the original diagram…

High Energy Physics - Phenomenology · Physics 2011-08-17 J. Fleischer , O. V. Tarasov

The Symbolic Regression (SR) problem, where the goal is to find a regression function that does not have a pre-specified form but is any function that can be composed of a list of operators, is a hard problem in machine learning, both…

Machine Learning · Computer Science 2020-06-15 Vernon Austel , Cristina Cornelio , Sanjeeb Dash , Joao Goncalves , Lior Horesh , Tyler Josephson , Nimrod Megiddo