27 citations · 61 across the 16 of their papers we have counts for
5 papers · 1 filter
Quantum-stabilized patterns in a vector Hopfield network
Richard D. Barney, Sharba Bhattacharjee, Victor Galitski +2
We introduce the quantum vector Hopfield network, in which patterns are formed by orientations of quantum vector spins; quantum dynamics arise intrinsically from the non-commutativ…
Learning quantum ground states in the space of measurement outcomes
Kartiek Agarwal
We investigate variational learning of quantum many-body ground states directly in measurement space using autoregressive neural networks. In particular, we represent quantum state…
Learning shadows to predict quantum ground state correlations
Pierre-Gabriel Rozon, Kartiek Agarwal
We introduce a variational scheme inspired by classical shadow tomography to compute ground state correlations of quantum spin Hamiltonians. Shadow tomography allows for efficient…
Spatiotemporal Quenches for Efficient Critical Ground State Preparation in Two-Dimensional Quantum Systems
Simon Bernier, Kartiek Agarwal
Quantum simulators have the potential to shed light on the study of quantum many-body systems and materials, offering unique insights into various quantum phenomena. While adiabati…
Optimal twirling depths for shadow tomography in the presence of noise
Pierre-Gabriel Rozon, Ning Bao, Kartiek Agarwal
The classical shadows protocol is an efficient strategy for estimating properties of an unknown state using a small number of state copies and measurements. In its original for…