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20212026
most citedImproved machine learning algorithm for predicting ground state properties

39 citations · 67 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph2026

Equivalence Between Average-Case Hardness of Learning and Cryptography for Mixed Quantum States

Alexandru Cojocaru, Laura Lewis

The relationship between cryptography and learning theory has long been a central theme in the foundations of theoretical computer science: cryptographic primitives can imply hardn…

quant-ph2024★ 2 cited

Agnostic Process Tomography

Chirag Wadhwa, Laura Lewis, Elham Kashefi +1

Characterizing a quantum system by learning its state or evolution is a fundamental problem in quantum physics and learning theory with a myriad of applications. Recently, as a new…

quant-ph2023★ 39 cited

Improved machine learning algorithm for predicting ground state properties

Laura Lewis, Hsin-Yuan Huang, Viet T. Tran +3

Finding the ground state of a quantum many-body system is a fundamental problem in quantum physics. In this work, we give a classical machine learning (ML) algorithm for predicting…

quant-ph2022★ 3 cited

Experimental Implementation of an Efficient Test of Quantumness

Laura Lewis, Daiwei Zhu, Alexandru Gheorghiu +11

A test of quantumness is a protocol where a classical user issues challenges to a quantum device to determine if it exhibits non-classical behavior, under certain cryptographic ass…

quant-ph2021★ 23 cited

Interactive Protocols for Classically-Verifiable Quantum Advantage

Daiwei Zhu, Gregory D. Kahanamoku-Meyer, Laura Lewis +15

Achieving quantum computational advantage requires solving a classically intractable problem on a quantum device. Natural proposals rely upon the intrinsic hardness of classically…