1.1k citations · 2.4k across the 13 of their papers we have counts for
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Machine learning logical gates for quantum error correction
Hongxiang Chen, Michael Vasmer, Nikolas P. Breuckmann +1
Quantum error correcting codes protect quantum computation from errors caused by decoherence and other noise. Here we study the problem of designing logical operations for quantum…
Cost function embedding and dataset encoding for machine learning with parameterized quantum circuits
Shuxiang Cao, Leonard Wossnig, Brian Vlastakis +2
Machine learning is seen as a promising application of quantum computation. For near-term noisy intermediate-scale quantum (NISQ) devices, parametrized quantum circuits (PQCs) have…
Dynamical mean field theory algorithm and experiment on quantum computers
I. Rungger, N. Fitzpatrick, H. Chen +12
The developments of quantum computing algorithms and experiments for atomic scale simulations have largely focused on quantum chemistry for molecules, while their application in co…
Structure optimization for parameterized quantum circuits
Mateusz Ostaszewski, Edward Grant, Marcello Benedetti
We propose an efficient method for simultaneously optimizing both the structure and parameter values of quantum circuits with only a small computational overhead. Shallow circuits…
An initialization strategy for addressing barren plateaus in parametrized quantum circuits
Edward Grant, Leonard Wossnig, Mateusz Ostaszewski +1
Parametrized quantum circuits initialized with random initial parameter values are characterized by barren plateaus where the gradient becomes exponentially small in the number of…