31 citations · 79 across the 5 of their papers we have counts for
6 papers
Learning Hamiltonians at Long Times
Constantin Cedillo Vayson de Pradenne, Jordan Cotler, Hsin-Yuan Huang
We study the problem of learning an unknown -qubit Hamiltonian from for a single time , where may be arbitrarily large. For broad families of local Ham…
Learning shallow quantum circuits with many-qubit gates
Francisca Vasconcelos, Hsin-Yuan Huang
We present the first computationally-efficient algorithm for average-case learning of shallow quantum circuits with many-qubit gates. Specifically, we provide a quasi-polynomial ti…
Classically estimating observables of noiseless quantum circuits
Armando Angrisani, Alexander Schmidhuber, Manuel S. Rudolph +3
We present a classical algorithm based on Pauli propagation for estimating expectation values of arbitrary observables on random unstructured quantum circuits across all circuit ar…
Learning shallow quantum circuits
Hsin-Yuan Huang, Yunchao Liu, Michael Broughton +4
Despite fundamental interests in learning quantum circuits, the existence of a computationally efficient algorithm for learning shallow quantum circuits remains an open question. B…
Learning quantum states and unitaries of bounded gate complexity
Haimeng Zhao, Laura Lewis, Ishaan Kannan +3
While quantum state tomography is notoriously hard, most states hold little interest to practically-minded tomographers. Given that states and unitaries appearing in Nature are of…
TensorFlow Quantum: A Software Framework for Quantum Machine Learning
Michael Broughton, Guillaume Verdon, Trevor McCourt +26
We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high…