activity
20172024
most citedMachine learning non-Markovian quantum dynamics

101 citations · 240 across the 18 of their papers we have counts for

collaborators

19 papers

physics.optics2024★ 2 cited

Multifrequency-resolved Hanbury Brown-Twiss Effect

Joseph Ferrantini, Jesse Crawford, Sergei Kulkov +14

The Hanbury Brown-Twiss (HBT) effect holds a pivotal place in intensity interferometry and gave a seminal contribution to the development of quantum optics. To observe such an effe…

quant-ph2023★ 5 cited

Fast data-driven spectrometer with direct measurement of time and frequency for multiple single photons

Jakub Jirsa, Sergei Kulkov, Raphael A. Abrahao +9

We present a single-photon-sensitive spectrometer, based on a linear array of 512 single-photon avalanche diode detectors, with 0.04 nm spectral and 40 ps temporal resolutions. We…

astro-ph.IM2023★ 11 cited

Towards Quantum Telescopes: Demonstration of a Two-Photon Interferometer for Quantum-Assisted Astronomy

Jesse Crawford, Denis Dolzhenko, Michael Keach +6

Classical optical interferometery requires maintaining live, phase-stable links between telescope stations. This requirement greatly adds to the cost of extending to long baseline…

quant-ph2022★ 23 cited

Classification of four-qubit entangled states via Machine Learning

S. V. Vintskevich, N. Bao, A. Nomerotski +2

We apply the support vector machine (SVM) algorithm to derive a set of entanglement witnesses (EW) to identify entanglement patterns in families of four-qubit states. The effective…

astro-ph.IM2022★ 13 cited

Astrometry in two-photon interferometry using Earth rotation fringe scan

Zhi Chen, Andrei Nomerotski, Anže Slosar +2

Optical interferometers may not require a phase-stable optical link between the stations if instead sources of quantum-mechanically entangled pairs could be provided to them, enabl…

quant-ph2022

Computing with two quantum reservoirs connected via optimized two-qubit nonselective measurements

Stephen Vintskevich, Dmitry Grigoriev

Currently, quantum reservoir computing is one of the most promising and experimentally accessible techniques for hybrid, quantum-classical machine learning. However, its applicatio…