Zobrazeno 1 - 10
of 3 432
pro vyhledávání: '"Semon A"'
Autor:
Cotler, Jordan, Rezchikov, Semon
We study the computational complexity theory of smooth, finite-dimensional dynamical systems. Building off of previous work, we give definitions for what it means for a smooth dynamical system to simulate a Turing machine. We then show that 'chaotic'
Externí odkaz:
http://arxiv.org/abs/2409.12179
Understanding the similarities and differences between adding or removing electrons from a charge-transfer insulator may provide insights about the origin of the electron-hole asymmetry found in cuprates. Here we study with cellular dynamical mean-fi
Externí odkaz:
http://arxiv.org/abs/2407.19545
Autor:
Rezchikov, Semon
We extend the Cohen-Jones-Segal construction of stable homotopy types associated to flow categories of Morse-Smale functions $f$ to the setting where $f$ is equivariant under a finite group action and is Morse but no longer Morse-Smale. This setting
Externí odkaz:
http://arxiv.org/abs/2405.18370
Informally, a model is calibrated if its predictions are correct with a probability that matches the confidence of the prediction. By far the most common method in the literature for measuring calibration is the expected calibration error (ECE). Rece
Externí odkaz:
http://arxiv.org/abs/2402.10046
ComDMFT is a parallel computational package designed to study the electronic structure of correlated quantum materials from first principles. Our approach is based on the combination of first-principles methods and dynamical mean field theories. In v
Externí odkaz:
http://arxiv.org/abs/2310.04613
Currently, a large number of stored tissue samples are unavailable for spectroscopic study without the time consuming and destructive process of paraffin removal. Instead, a structurally sensitive technique, sum frequency generation, and a chemically
Externí odkaz:
http://arxiv.org/abs/2310.00460
Autor:
Cotler, Jordan, Rezchikov, Semon
We explain how to use diffusion models to learn inverse renormalization group flows of statistical and quantum field theories. Diffusion models are a class of machine learning models which have been used to generate samples from complex distributions
Externí odkaz:
http://arxiv.org/abs/2308.12355
Autor:
Victor D. Thompson, Matthew Sanger, Karen Y. Smith, Carey J. Garland, Matthew D. Howland, C. Fred T. Andrus, Isabelle Holland-Lulewicz, Carla Hadden, Clark Alexander, Rachel Cajigas, Elliot Blair, Anna Semon, David Hurst Thomas
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Shell ring archaeological sites are one of the most visible site types along the lower South Atlantic Coast of the United States. These cultural sites are large, circular to arcuate piles of mollusk shells with some reaching over three meter
Externí odkaz:
https://doaj.org/article/fe7a12ec68f64696854f493af020c764
Publikováno v:
Phys. Rev. B 108, 075163 (2023)
Doping a Mott insulator gives rise to unconventional superconducting correlations. Here we address the interplay between d-wave superconductivity and Mott physics using the two-dimensional Hubbard model with cellular dynamical mean-field theory on a
Externí odkaz:
http://arxiv.org/abs/2307.02681
Autor:
Tewari, Ayush, Yin, Tianwei, Cazenavette, George, Rezchikov, Semon, Tenenbaum, Joshua B., Durand, Frédo, Freeman, William T., Sitzmann, Vincent
Denoising diffusion models are a powerful type of generative models used to capture complex distributions of real-world signals. However, their applicability is limited to scenarios where training samples are readily available, which is not always th
Externí odkaz:
http://arxiv.org/abs/2306.11719