English
Related papers

Related papers: Improved Gaussian Approximation

200 papers

In this paper, a quantum algorithm based on gaussian process regression model is proposed. The proposed quantum algorithm consists of three sub-algorithms. One is the first quantum subalgorithm to efficiently generate mean predictor. The…

Quantum Physics · Physics 2022-07-20 Menghan Chen , Gongde Guo , Song Lin , Jing Li

This paper investigates the approximation of Gaussian random variables in Banach spaces, focusing on the high-probability bounds for the approximation of Gaussian random variables using finitely many observations. We derive non-asymptotic…

Statistics Theory · Mathematics 2025-08-28 Daniel Winkle , Ingo Steinwart , Bernard Haasdonk

Dimensional regularization of Euclidean momentum space integrals is a highly successful technique in renormalization of quantum field theories. While it yields a straightforward algorithmic method, with which to evaluate diagrams beyond…

Mathematical Physics · Physics 2020-09-03 Juuso Österman

Gaussian states hold a fundamental place in quantum mechanics, quantum information, and quantum computing. Many subfields, including quantum simulation of continuous-variable systems, quantum chemistry, and quantum machine learning, rely on…

Quantum Physics · Physics 2026-05-13 Yichen Xie , Nadav Ben-Ami

We develop an unambiguous and practical method to calculate one-loop quantum corrections to the energies of classical time-independent field configurations in renormalizable field theories. We show that the standard perturbative…

High Energy Physics - Theory · Physics 2009-10-31 Edward Farhi , Noah Graham , Peter E. Haagensen , Robert L. Jaffe

In this paper, we use some standard numerical techniques to approximate the hypergeometric function $$ {}_2F_1[a,b;c;x]=1+\frac{ab}{c}x+\frac{a(a+1)b(b+1)}{c(c+1)}\frac{x^2}{2!}+\cdots $$ for a range of parameter triples $(a,b,c)$ on the…

Numerical Analysis · Mathematics 2017-07-26 Hina Manoj Arora , Swadesh Kumar Sahoo

Although Bayesian methods are robust and principled, their application in practice could be limited since they typically rely on computationally intensive Markov Chain Monte Carlo algorithms for their implementation. One possible solution…

Computation · Statistics 2015-10-06 Tian Chen , Jeffrey Streets , Babak Shahbaba

We present the beta functions of gauge and Yukawa couplings in general four-dimensional quantum field theory, at four and three loops, respectively. The essence of our approach is fixing unknown coefficients in the most general ansatz for…

High Energy Physics - Phenomenology · Physics 2021-07-28 Alexander Bednyakov , Andrey Pikelner

We introduce a new scalable approximation for Gaussian processes with provable guarantees which hold simultaneously over its entire parameter space. Our approximation is obtained from an improved sample complexity analysis for sparse…

Machine Learning · Computer Science 2020-11-18 Quang Minh Hoang , Trong Nghia Hoang , Hai Pham , David P. Woodruff

Generalized Fourier series with orthogonal polynomial bases have useful applications in several fields, including differential equations, pattern recognition, and image and signal processing. However, computing the generalized Fourier…

Numerical Analysis · Mathematics 2015-02-09 Ashley Prater

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical…

Machine Learning · Computer Science 2024-07-18 Hwanwoo Kim , Daniel Sanz-Alonso

We outline, test, and apply a new scheme for nonpertubative analyses of quantized field systems in contact with dynamical gravity. While gravity is treated classically in the present paper, the approach lends itself for a generalization to…

General Relativity and Quantum Cosmology · Physics 2020-12-30 Maximilian Becker , Martin Reuter

Generalized matrix approximation plays a fundamental role in many machine learning problems, such as CUR decomposition, kernel approximation, and matrix low rank approximation. Especially with today's applications involved in larger and…

Numerical Analysis · Computer Science 2016-09-09 Haishan Ye , Qiaoming Ye , Zhihua Zhang

The quantisation of scalar field theory and Einstein gravity is investigated using a fully covariant background field formalism, including Vilkovisky-DeWitt corrections. The one-loop divergences, which are relevant for the consistency of…

High Energy Physics - Theory · Physics 2014-09-17 Ian G. Moss

We derive the quantum effective action up to second order in gradients and up to two-loop order for an interacting scalar field theory. This expansion of the effective action is useful to study problems in cosmological settings where…

High Energy Physics - Theory · Physics 2024-09-17 Sofia Canevarolo , Tomislav Prokopec

In this work, we mainly study the one-loop effective action for real scalar theories in non-homogeneous backgrounds in odd dimensions. It is shown that through the method studied in Ref. [1], it is possible to obtain a unified result for…

High Energy Physics - Theory · Physics 2011-04-06 Burak Tevfik Kaynak

Gaussian processes are a powerful framework for uncertainty-aware function approximation and sequential decision-making. Unfortunately, their classical formulation does not scale gracefully to large amounts of data and modern hardware for…

Machine Learning · Computer Science 2025-07-10 Jihao Andreas Lin

The process of equilibration in phi^4 theory is investigated for a homogeneous system in 3+1 dimensions and a variety of out-of-equilibrium initial conditions, both in the symmetric and broken phase, by means of the 2PI effective action.…

High Energy Physics - Phenomenology · Physics 2009-11-11 Alejandro Arrizabalaga , Jan Smit , Anders Tranberg

We develop a general, functional calculus approach to approximation of $C_0$-semigroups on Banach spaces by bounded completely monotone functions of their generators. The approach comprises most of well-known approximation formulas, yields…

Functional Analysis · Mathematics 2018-07-10 A. Gomilko , S. Kosowicz , Yu. Tomilov

A number of improvements have been added to the existing analytical model of hysteresis loop defined in parametric form. In particular, three phase shifts are included in the model, which permits to tilt the hysteresis loop smoothly by the…

Optimization and Control · Mathematics 2020-06-11 Rostislav V. Lapshin