most citedMachine learning of measurement schemes for efficient quantum observable estimation

1 citations · 1 across the 1 of their papers we have counts for

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10 papers

quant-ph20261 cited

Machine learning of measurement schemes for efficient quantum observable estimation

Zi-Jian Zhang, Kouhei Nakaji, Matthew Choi +1

Estimation of the expectation value of observables is a key subroutine in quantum computing and is also the bottleneck of the performance of many near-term quantum algorithms. Many…

quant-ph2026

Generative Circuit Design for Quantum-Selected Configuration Interaction

Ryota Kemmoku, Qi Gao, Shu Kanno +4

Quantum-selected configuration interaction (QSCI) has emerged as a feasible approach for approximating electronic ground states on noisy quantum devices toward large-system demonst…

quant-ph2026

Auger Spectroscopy via Generative Quantum Eigensolver: A Quantum Approach to Molecular Excitations

Kimberlee Keithley, Shunsuke Yamamoto, Ryota Kenmoku +16

Auger electron spectroscopy, a way of characterizing electronic structure through core-level decay processes, is widely used in materials characterization; however direct calculati…

cs.LG2026

Coupled Cluster con MōLe: Molecular Orbital Learning for Neural Wavefunctions

Luca Thiede, Abdulrahman Aldossary, Andreas Burger +9

Density functional theory (DFT) is the most widely used method for calculating molecular properties; however, its accuracy is often insufficient for quantitative predictions. Coupl…

quant-ph2025

Artificial Intelligence for Quantum Computing

Yuri Alexeev, Marwa H. Farag, Taylor L. Patti +25

Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extend…

quant-ph2025

Quantum Transformer: Accelerating model inference via quantum linear algebra

Naixu Guo, Zhan Yu, Matthew Choi +5

Powerful generative artificial intelligence from large language models (LLMs) harnesses extensive computational resources for inference. In this work, we investigate the transforme…