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20112022
most citedQuantum circuits with many photons on a programmable nanophotonic chip

551 citations · 696 across the 7 of their papers we have counts for

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19 papers · 1 filter

quant-ph20221 cited

Implicit differentiation of variational quantum algorithms

Shahnawaz Ahmed, Nathan Killoran, Juan Felipe Carrasquilla Álvarez

Several quantities important in condensed matter physics, quantum information, and quantum chemistry, as well as quantities required in meta-optimization of machine learning algori…

quant-ph20221 cited

Quantum computing with differentiable quantum transforms

Olivia Di Matteo, Josh Izaac, Tom Bromley +6

We present a framework for differentiable quantum transforms. Such transforms are metaprograms capable of manipulating quantum programs in a way that preserves their differentiabil…

quant-ph2021551 cited

Quantum circuits with many photons on a programmable nanophotonic chip

J. M. Arrazola, V. Bergholm, K. Brádler +36

Growing interest in quantum computing for practical applications has led to a surge in the availability of programmable machines for executing quantum algorithms. Present day photo…

quant-ph2020

Estimating the gradient and higher-order derivatives on quantum hardware

Andrea Mari, Thomas R. Bromley, Nathan Killoran

For a large class of variational quantum circuits, we show how arbitrary-order derivatives can be analytically evaluated in terms of simple parameter-shift rules, i.e., by running…

quant-ph2019

Applications of Near-Term Photonic Quantum Computers: Software and Algorithms

Thomas R. Bromley, Juan Miguel Arrazola, Soran Jahangiri +7

Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based pr…

quant-ph2019

Transfer learning in hybrid classical-quantum neural networks

Andrea Mari, Thomas R. Bromley, Josh Izaac +2

We extend the concept of transfer learning, widely applied in modern machine learning algorithms, to the emerging context of hybrid neural networks composed of classical and quantu…