3 citations · 3 across the 3 of their papers we have counts for
3 papers
quant-ph2025
Variational optical phase learning on a continuous-variable quantum compiler
Matthew A. Feldman, Tyler Volkoff, Seongjin Hong +5
Quantum process learning is a fundamental primitive that draws inspiration from machine learning with the goal of better studying the dynamics of quantum systems. One approach to q…
quant-ph2023
Learning linear optical circuits with coherent states
T. J. Volkoff, Andrew T. Sornborger
We analyze the energy and training data requirements for supervised learning of an -mode linear optical circuit by minimizing an empirical risk defined solely from the action of…
quant-ph2021★ 3 cited
Universal compiling and (No-)Free-Lunch theorems for continuous variable quantum learning
Tyler Volkoff, Zoë Holmes, Andrew Sornborger
Quantum compiling, where a parameterized quantum circuit is trained to learn a target unitary, is an important primitive for quantum computing that can be used as a subroutine to o…