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20242026
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quant-ph2026

Classical simulation of noisy quantum circuits via locally entanglement-optimal unravelings

Simon Cichy, Paul K. Faehrmann, Lennart Bittel +2

Classical simulations of noisy quantum circuits are instrumental to our understanding of the behavior of real-world quantum systems and the identification of regimes where one expe…

quant-ph2025

Streaming quantum state purification for general mixed states

Daniel Grier, Debbie Leung, Zhi Li +2

Given multiple copies of a mixed quantum state with an unknown, nondegenerate principal eigenspace, quantum state purification is the task of recovering a quantum state that is clo…

quant-ph2024

Shallow shadows: Expectation estimation using low-depth random Clifford circuits

Christian Bertoni, Jonas Haferkamp, Marcel Hinsche +3

We provide practical and powerful schemes for learning many properties of an unknown n-qubit quantum state using a sparing number of copies of the state. Specifically, we present a…

quant-ph2024

On the Trainability and Classical Simulability of Learning Matrix Product States Variationally

Afrad Basheer, Yuan Feng, Christopher Ferrie +2

We prove that using global observables to train the matrix product state ansatz results in the vanishing of all partial derivatives, also known as barren plateaus, while using loca…

quant-ph2024

Principal eigenstate classical shadows

Daniel Grier, Hakop Pashayan, Luke Schaeffer

Given many copies of an unknown quantum state , we consider the task of learning a classical description of its principal eigenstate. Namely, assuming that has an eigensta…

quant-ph2024

Sample-optimal classical shadows for pure states

Daniel Grier, Hakop Pashayan, Luke Schaeffer

We consider the classical shadows task for pure states in the setting of both joint and independent measurements. The task is to measure few copies of an unknown pure state in…