3 citations · 6 across the 13 of their papers we have counts for
4 papers · 1 filter
Efficient Learning of Lattice Gauge Theories with Fermions
Shreya Shukla, Yukari Yamauchi, Andrey Y. Lokhov +2
We introduce a learning method for recovering action parameters in lattice field theories. Our method is based on the minimization of a convex loss function constructed using the S…
Learning of Statistical Field Theories
Shreya Shukla, Abhijith Jayakumar, Andrey Y. Lokhov
Recovering microscopic couplings directly from data provides a route to solving the inverse problem in statistical field theories, one that complements the traditional-often comput…
Autoregressive pairwise Graphical Models efficiently find ground state representations of stoquastic Hamiltonians
Yuchen Pang, Abhijith Jayakumar, Evan McKinney +3
We introduce Autoregressive Graphical Models (AGMs) as an Ansatz for modeling the ground states of stoquastic Hamiltonians. Exact learning of these models for smaller systems show…
Learning response functions of analog quantum computers: analysis of neutral-atom and superconducting platforms
Cenk Tüysüz, Abhijith Jayakumar, Carleton Coffrin +2
Analog quantum computation is an attractive paradigm for the simulation of time-dependent quantum systems. Programmable analog quantum computers have been realized in hardware usin…