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20242026
most citedMachine learning of measurement schemes for efficient quantum observable estimation

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

collaborators

5 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-ph2025

Fast quantum algorithm for differential equations

Mohsen Bagherimehrab, Kouhei Nakaji, Nathan Wiebe +3

Partial differential equations (PDEs) are ubiquitous in science and engineering. Prior quantum algorithms for solving the system of linear algebraic equations obtained from discret…

cs.LG2025

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Xuan Zhang, Limei Wang, Jacob Helwig +60

Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…

quant-ph2025

Information flow in parameterized quantum circuits

Abhinav Anand, Lasse Bjørn Kristensen, Felix Frohnert +2

In this work, we introduce a new way to quantify information flow in quantum systems, especially for parameterized quantum circuits. We use a graph representation of the circuits a…

cs.LG2024

Waveflow: boundary-conditioned normalizing flows applied to fermionic wavefunctions

Luca Thiede, Chong Sun, Alán Aspuru-Guzik

An efficient and expressive wavefunction ansatz is key to scalable solutions for complex many-body electronic structures. While Slater determinants are predominantly used for const…