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20202025
most citedCorrelator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data

56 citations · 237 across the 8 of their papers we have counts for

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5 papers · 1 filter

cond-mat.str-el2022★ 33 cited

Langevin dynamics of generalized spins as SU() coherent states

David Dahlbom, Cole Miles, Hao Zhang +2

Classical models of spin systems traditionally retain only the dipole moments, but a quantum spin state will frequently have additional structure. Spins of magnitude have $N=2S…

cond-mat.str-el2022★ 35 cited

Geometric integration of classical spin dynamics via a mean-field Schrödinger equation

David Dahlbom, Hao Zhang, Cole Miles +3

The Landau-Lifshitz equation describes the time-evolution of magnetic dipoles, and can be derived by taking the classical limit of a quantum mechanical spin Hamiltonian. To take th…

cond-mat.str-el2022★ 33 cited

Fast and scalable quantum Monte Carlo simulations of electron-phonon models

Benjamin Cohen-Stead, Owen Bradley, Cole Miles +3

We introduce methodologies for highly scalable quantum Monte Carlo simulations of electron-phonon models, and report benchmark results for the Holstein model on the square lattice.…

cond-mat.str-el2021★ 18 cited

Machine learning of Kondo physics using variational autoencoders and symbolic regression

Cole Miles, Matthew R. Carbone, Erica J. Sturm +4

We employ variational autoencoders to extract physical insight from a dataset of one-particle Anderson impurity model spectral functions. Autoencoders are trained to find a low-dim…

cond-mat.str-el2020★ 56 cited

Correlator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data

Cole Miles, Annabelle Bohrdt, Ruihan Wu +7

Machine learning models are a powerful theoretical tool for analyzing data from quantum simulators, in which results of experiments are sets of snapshots of many-body states. Recen…