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20162026
most citedParameterized quantum circuits as machine learning models

1.1k citations · 1.2k across the 11 of their papers we have counts for

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quant-ph2026

Reducing entanglement with a Hamiltonian derived Clifford transformation

James Brown, Erika Lloyd, Alexandre Fleury +2

Recently (Physica Scripta, 100(10):105401, 2025), an algorithm was introduced that deterministically generates a Clifford transformation from the Qubit Coupled Cluster (QCC) algori…

quant-ph2025

Offline recovery of magic and entanglement from noisy Pauli product states

Erika Lloyd, Alexandre Fleury, Marc P. Coons +2

The dependence of quantum algorithms on state fidelity is difficult to characterize analytically and is best explored experimentally as hardware scales and noisy simulations become…

quant-ph2024★ 2 cited

Non-unitary Coupled Cluster Enabled by Mid-circuit Measurements on Quantum Computers

Alexandre Fleury, James Brown, Erika Lloyd +2

Many quantum algorithms rely on a quality initial state for optimal performance. Preparing an initial state for specific applications can considerably reduce the cost of probabilis…

quant-ph2022

Iterative Qubit Coupled Cluster using only Clifford circuits

James Brown, Marc P. Coons, Erika Lloyd +4

The performance of quantum algorithms for ground-state energy estimation is directly impacted by the quality of the initial state, where quality is traditionally defined in terms o…

quant-ph2022★ 5 cited

Tangelo: An Open-source Python Package for End-to-end Chemistry Workflows on Quantum Computers

Valentin Senicourt, James Brown, Alexandre Fleury +10

Tangelo [link: https://github.com/goodchemistryco/Tangelo] is an open-source Python software package for the development of end-to-end chemistry workflows on quantum computers, rel…

quant-ph2021★ 3 cited

Optimizing Electronic Structure Simulations on a Trapped-ion Quantum Computer using Problem Decomposition

Yukio Kawashima, Erika Lloyd, Marc P. Coons +12

Quantum computers have the potential to advance material design and drug discovery by performing costly electronic structure calculations. A critical aspect of this application req…

quant-ph2019★ 1.1k cited

Parameterized quantum circuits as machine learning models

Marcello Benedetti, Erika Lloyd, Stefan Sack +1

Hybrid quantum-classical systems make it possible to utilize existing quantum computers to their fullest extent. Within this framework, parameterized quantum circuits can be regard…