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One of the primary applications of classical Boltzmann machines is generative modeling, wherein the goal is to tune the parameters of a model distribution so that it closely approximates a target distribution. Training relies on estimating…

Quantum Physics · Physics 2025-12-24 Mark M. Wilde

This contribution, to be published in Imagine Math 8 to celebrate Michele Emmer's 75th birthday, can be seen as the second part of my previous considerations on the relationships between topology and physics (Mouchet, 2018). Nevertheless,…

History and Philosophy of Physics · Physics 2021-11-08 Amaury Mouchet

Stochastic mechanics---the study of classical stochastic systems governed by things like master equations and Fokker-Planck equations---exhibits striking mathematical parallels to quantum mechanics. In this article, we make those parallels…

Statistical Mechanics · Physics 2019-10-01 John J. Vastola , William R. Holmes

Many interesting physical theories have analytic classical actions. We show how Feynman's path integral may be defined non-perturbatively, for such theories, without a Wick rotation to imaginary time. We start by introducing a class of…

High Energy Physics - Theory · Physics 2023-05-17 Job Feldbrugge , Neil Turok

Many computational problems are unchanged under some symmetry operation. In classical machine learning, this can be reflected with the layer structure of the neural network. In quantum machine learning, the ansatz can be tuned to correspond…

We develop a constructive approach to generate artificial neural networks representing the exact ground states of a large class of many-body lattice Hamiltonians. It is based on the deep Boltzmann machine architecture, in which two layers…

Disordered Systems and Neural Networks · Physics 2018-12-18 Giuseppe Carleo , Yusuke Nomura , Masatoshi Imada

Quantum Boltzmann machines are natural quantum generalizations of Boltzmann machines that are expected to be more expressive than their classical counterparts, as evidenced both numerically for small systems and asymptotically under various…

Quantum Physics · Physics 2019-03-05 Eric R. Anschuetz , Yudong Cao

These lectures are intended as an introduction to the technique of path integrals and their applications in physics. The audience is mainly first-year graduate students, and it is assumed that the reader has a good foundation in quantum…

Quantum Physics · Physics 2007-05-23 Richard MacKenzie

We review equivariant localization techniques for the evaluation of Feynman path integrals. We develop systematic geometric methods for studying the semi-classical properties of phase space path integrals for dynamical systems, emphasizing…

High Energy Physics - Theory · Physics 2007-05-23 Richard J. Szabo

Attempts to apply Neural Networks (NN) to a wide range of research problems have been ubiquitous and plentiful in recent literature. Particularly, the use of deep NNs for understanding complex physical and chemical phenomena has opened a…

Machine Learning · Computer Science 2021-12-01 Arijit Sehanobish , Hector H. Corzo , Onur Kara , David van Dijk

Complex (semi-)classical paths, or instantons, form an integral part of our understanding of quantum physics. Whereas real classical paths describe classically allowed transitions in the real-time Feynman path integral, classically…

Quantum Physics · Physics 2025-08-26 Job Feldbrugge , Ue-Li Pen

The saddle points of a conventional Feynman path integral are not entangled, since they comprise a sequence of classical field configurations. We combine insights from field theory and tensor networks by constructing a Feynman path integral…

Strongly Correlated Electrons · Physics 2016-07-08 A. G. Green , C. A. Hooley , J. Keeling , S. H. Simon

Feynman's path integral formulation arose from his attempt to incorporate the Lagrangian framework into quantum mechanics, offering what he regarded as a more fundamental perspective than the Hamiltonian approach, particularly in the…

Quantum Physics · Physics 2025-09-23 Bernat Frangi , Héctor López

The path integral approach to quantum mechanics requires a substantial generalisation to describe the dynamics of systems confined to bounded domains. Non-local boundary conditions can be introduced in Feynman's approach by means of…

Quantum Physics · Physics 2008-11-26 M. Asorey , J. Clemente-Gallardo , J. M. Munoz-Castaneda

We present a representation for linguistic structure that we call a Fock-space representation, which allows us to embed problems in language processing into small quantum devices. We further develop a formalism for understanding both…

Quantum Physics · Physics 2019-02-15 Nathan Wiebe , Alex Bocharov , Paul Smolensky , Matthias Troyer , Krysta M Svore

Efforts at understanding the computational processes in the brain have met with limited success, despite their importance and potential uses in building intelligent machines. We propose a simple new model which draws on recent findings in…

Neural and Evolutionary Computing · Computer Science 2016-09-14 Eric Laukien , Richard Crowder , Fergal Byrne

We give two novel proofs that the path integral and stochastic quantizations of generic scalar Euclidean quantum field theories are equivalent. Our proofs rely on Taylor interpolations indexed by forests, in the fashion of constructive…

Mathematical Physics · Physics 2026-04-09 Dario Benedetti , Ilya Chevyrev , Razvan Gurau

Our previous work on quantum mechanics in Hilbert spaces of finite dimensions N is applied to elucidate the deep meaning of Feynman's path integral pointed out by G. Svetlichny. He speculated that the secret of the Feynman path integral may…

Quantum Physics · Physics 2009-08-05 J Tolar , G Chadzitaskos

The process of data interpretation is always based on the implicit introduction of equivalence relations on the set of walks over the database. Every equivalence relation on the set of walks specifies a Markov chain describing the…

Physics and Society · Physics 2015-12-15 D. Volchenkov

We propose a novel quantum model for the restricted Boltzmann machine (RBM), in which the visible units remain classical whereas the hidden units are quantized as noninteracting fermions. The free motion of the fermions is parametrically…

Disordered Systems and Neural Networks · Physics 2021-02-15 Ya. S. Lyakhova , E. A. Polyakov , A. N. Rubtsov