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Related papers: Generative Flow Networks in Covariant Loop Quantum…

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Generative Flow Networks (GFNs) have emerged as a powerful tool for sampling discrete objects from unnormalized distributions, offering a scalable alternative to Markov Chain Monte Carlo (MCMC) methods. While GFNs draw inspiration from…

Machine Learning · Computer Science 2025-02-24 Sobhan Mohammadpour , Emmanuel Bengio , Emma Frejinger , Pierre-Luc Bacon

The first computation of a spin foam dynamics that provides a test of the quantum equations of motions of gravity is presented. Specifically, a triangulation that includes an inner edge is treated. The computation leverages the recently…

General Relativity and Quantum Cosmology · Physics 2021-07-07 Seth K. Asante , Bianca Dittrich , Hal M. Haggard

The present paper aims to demonstrate the usage of Convolutional Neural Networks as a generative model for stochastic processes, enabling researchers from a wide range of fields (such as quantitative finance and physics) to develop a…

Machine Learning · Statistics 2018-01-12 Fernando Fernandes Neto

Spinfoams provide a framework for the dynamics of loop quantum gravity that is manifestly covariant under the full four-dimensional diffeomorphism symmetry group of general relativity. In this way they complete the ideal of…

General Relativity and Quantum Cosmology · Physics 2023-11-01 Jonathan Engle , Simone Speziale

One of the most pressing issues for loop quantum gravity and spin foams is the construction of the continuum limit. In this paper, we propose a systematic coarse-graining scheme for three-dimensional lattice gauge models including spin…

General Relativity and Quantum Cosmology · Physics 2017-11-22 Clement Delcamp , Bianca Dittrich

Spin Foam Models (SFMs) are covariant formulations of Loop Quantum Gravity (LQG) in 4 dimensions. This work studies the perturbations of SFMs on a flat background. It demonstrates for the first time that smooth curved spacetime geometries…

General Relativity and Quantum Cosmology · Physics 2019-08-07 Muxin Han , Zichang Huang , Antonia Zipfel

Generative flow networks utilize a flow-matching loss to learn a stochastic policy for generating objects from a sequence of actions, such that the probability of generating a pattern can be proportional to the corresponding given reward.…

Machine Learning · Computer Science 2025-09-26 Leo Maxime Brunswic , Haozhi Wang , Shuang Luo , Jianye Hao , Amir Rasouli , Yinchuan Li

Diffusion and flow-based generative models have achieved remarkable success in domains such as image synthesis, video generation, and natural language modeling. In this work, we extend these advances to weight space learning by leveraging…

Machine Learning · Computer Science 2025-10-17 Daniel Saragih , Deyu Cao , Tejas Balaji

Quantum geometric maps, which relate SU(2) spin networks and Lorentz covariant projected spin networks, are an important ingredient of spin foam models (and tensorial group field theories) for 4-dimensional quantum gravity. We give a…

General Relativity and Quantum Cosmology · Physics 2020-12-22 Marco Finocchiaro , Yoobin Jeong , Daniele Oriti

Spin foams are models of quantum gravity and therefore quantum space time. A key open issue is to determine the possible continuum phases of these models. Progress on this issue has been prohibited by the complexity of the full…

General Relativity and Quantum Cosmology · Physics 2015-02-16 Bianca Dittrich , Mercedes Martín-Benito , Erik Schnetter

The decoherent histories formalism, developed by Griffiths, Gell-Mann, and Hartle is a general framework in which to formulate a timeless, `generalised' quantum theory and extract predictions from it. Recent advances in spin foam models…

General Relativity and Quantum Cosmology · Physics 2013-02-08 David P. B. Schroeren

This paper is about the problem of learning a stochastic policy for generating an object (like a molecular graph) from a sequence of actions, such that the probability of generating an object is proportional to a given positive reward for…

Machine Learning · Computer Science 2021-11-22 Emmanuel Bengio , Moksh Jain , Maksym Korablyov , Doina Precup , Yoshua Bengio

The canonical ``loop'' formulation of quantum gravity is a mathematically well defined, background independent, non perturbative standard quantization of Einstein's theory of General Relativity. Some among the most meaningful results of the…

General Relativity and Quantum Cosmology · Physics 2012-06-12 R. De Pietri

In this article we review the present status of the spin foam formulation of non-perturbative (background independent) quantum gravity. The article is divided in two parts. In the first part we present a general introduction to the main…

General Relativity and Quantum Cosmology · Physics 2017-08-23 Alejandro Perez

The Generative Flow Network is a probabilistic framework where an agent learns a stochastic policy for object generation, such that the probability of generating an object is proportional to a given reward function. Its effectiveness has…

Machine Learning · Computer Science 2022-10-10 Ling Pan , Dinghuai Zhang , Aaron Courville , Longbo Huang , Yoshua Bengio

We undertake first steps in making a class of discrete models of quantum gravity, spin foams, accessible to a large scale analysis by numerical and computational methods. In particular, we apply Migdal-Kadanoff and Tensor Network…

General Relativity and Quantum Cosmology · Physics 2015-10-19 Bianca Dittrich , Frank C. Eckert , Mercedes Martin-Benito

Vertex amplitudes are elementary contributions to the transition amplitudes in the spin foam models of quantum gravity. The purpose of this article is make the first step towards computing vertex amplitudes with the use of quantum…

General Relativity and Quantum Cosmology · Physics 2019-06-20 Jakub Mielczarek

In the quest of a physical theory of quantum gravity, spin foam models, or in short spinfoams, propose a well-defined path integral summing over quantized discrete space-time geometries. At the crossroad of topological quantum field theory,…

General Relativity and Quantum Cosmology · Physics 2025-01-08 Etera R. Livine

We give a general definition of spin foam models, and then of models of 4d quantum gravity based on constraining BF theory. We highlight the construction and quantization ambiguities entering model building, among which the choice of…

General Relativity and Quantum Cosmology · Physics 2019-06-19 Marco Finocchiaro , Daniele Oriti

We give a very brief introduction to the group field theory approach to quantum gravity, a generalisation of matrix models for 2-dimensional quantum gravity to higher dimension, that has emerged recently from research in spin foam models.

General Relativity and Quantum Cosmology · Physics 2015-06-25 Daniele Oriti