Results 21 to 30 of about 1,437,304 (362)
Diffusion Models as Stochastic Quantization in Lattice Field Theory [PDF]
Journal of High Energy Physics, 2023 In this work, we establish a direct connection between generative diffusion models (DMs) and stochastic quantization (SQ). The DM is realized by approximating the reversal of a stochastic process dictated by the Langevin equation, generating samples from
L. Wang, Gert Aarts, Kai Zhou
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Quantum mean estimation for lattice field theory [PDF]
Quantum mean estimation for lattice field theory, 2023 We demonstrate the quantum mean estimation algorithm on Euclidean lattice field theories. This shows a quadratic advantage over Monte Carlo methods which persists even in presence of a sign problem, and is insensitive to critical slowing down.
Erik J. Gustafson +2 more
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Stochastic normalizing flows for lattice field theory [PDF]
Proceedings of The 39th International Symposium on Lattice Field Theory — PoS(LATTICE2022), 2022 Stochastic normalizing flows are a class of deep generative models that combine normalizing flows with Monte Carlo updates and can be used in lattice field theory to sample from Boltzmann distributions.
M. Caselle +3 more
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A chaotic lattice field theory in one dimension [PDF]
Journal of Physics A: Mathematical and Theoretical, 2022 Motivated by Gutzwiller’s semiclassical quantization, in which unstable periodic orbits of low-dimensional deterministic dynamics serve as a WKB ‘skeleton’ for chaotic quantum mechanics, we construct the corresponding deterministic skeleton for infinite ...
Han Liang, P. Cvitanovic
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Bayesian model averaging for analysis of lattice field theory results [PDF]
Physical Review D, 2020 Statistical modeling is a key component in the extraction of physical results from lattice field theory calculations. Although the general models used are often strongly motivated by physics, their precise form is typically ill-determined, and many model
W. Jay, E. Neil
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Entanglement Hamiltonians: From Field Theory to Lattice Models and Experiments [PDF]
Annals of Physics, 2022 Results about entanglement (or modular) Hamiltonians of quantum many‐body systems in field theory and statistical mechanics models, and recent applications in the context of quantum information and quantum simulation, are reviewed.
M. Dalmonte +3 more
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Real-time spin systems from lattice field theory
Journal of High Energy Physics, 2023 We construct a lattice field theory method for computing the real-time dynamics of spin systems in a thermal bath. This is done by building on previous work of Takano with Schwinger-Keldysh and functional differentiation techniques. We derive a Schwinger-
Neill C. Warrington
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Tensor lattice field theory for renormalization and quantum computing [PDF]
Reviews of Modern Physics, 2020 We discuss the successes and limitations of statistical sampling for a sequence of models studied in the context of lattice QCD and emphasize the need for new methods to deal with finite-density and real-time evolution.
Y. Meurice, Ryo Sakai, J. Unmuth-Yockey
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Quantum algorithms for open lattice field theory [PDF]
Physical Review A, 2020 Certain aspects of some unitary quantum systems are well-described by evolution via a non-Hermitian effective Hamiltonian, as in the Wigner-Weisskopf theory for spontaneous decay. Conversely, any non-Hermitian Hamiltonian evolution can be accommodated in
J. Hubisz +2 more
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Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning [PDF]
Physical Review D, 2020 Machine learning has the potential to aid our understanding of phase structures in lattice quantum field theories through the statistical analysis of Monte Carlo samples. Available algorithms, in particular those based on deep learning, often demonstrate
Stefan Blücher +4 more
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