72 citations · 542 across the 65 of their papers we have counts for
4 papers · 1 filter
Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat
David A. Quiroga, Anastasios Kyrillidis
We propose a non-convex optimization algorithm, based on the Burer-Monteiro (BM) factorization, for the quantum process tomography problem, in order to estimate a low-rank process…
Fast quantum state reconstruction via accelerated non-convex programming
Junhyung Lyle Kim, George Kollias, Amir Kalev +2
We propose a new quantum state reconstruction method that combines ideas from compressed sensing, non-convex optimization, and acceleration methods. The algorithm, called Momentum-…
Validating and Certifying Stabilizer States
Amir Kalev, Anastasios Kyrillidis, Norbert M. Linke
We propose a measurement scheme that validates the preparation of an -qubit stabilizer state. The scheme involves a measurement of Pauli observables, a priori determined fro…
Provable quantum state tomography via non-convex methods
Anastasios Kyrillidis, Amir Kalev, Dohuyng Park +3
With nowadays steadily growing quantum processors, it is required to develop new quantum tomography tools that are tailored for high-dimensional systems. In this work, we describe…