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Detecting multipartite entanglement in many qubit systems is measurement-intensive, motivating protocols that estimate only selected observables with provable efficiency. In this work we use the classical shadow protocol to study the sample…

Quantum Physics · Physics 2026-01-06 Ziran Zhang

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 depth-modulated randomized measurement scheme that…

Classical shadows are a powerful method for learning many properties of quantum states in a sample-efficient manner, by making use of randomized measurements. Here we study the sample complexity of learning the expectation value of Pauli…

Quantum Physics · Physics 2023-06-13 Matteo Ippoliti , Yaodong Li , Tibor Rakovszky , Vedika Khemani

Accurately estimating expectation values of quantum observables with as few measurements as possible is crucial to many quantum computing applications. We introduce a framework that covers many of existing measurement strategies and…

Efficiently learning expectation values of unknown quantum states via classical shadows has become an important primitive in both theoretical and experimental aspects of quantum computation. Typically, classical shadow protocols involve…

Quantum Physics · Physics 2026-05-08 Rebecca Chang , Maureen Krumtünger , Martin Larocca , Maxwell West

We show that entangled measurements provide an exponential advantage in sample complexity for Pauli channel estimation, which is both a fundamental problem and a practically important subroutine for benchmarking near-term quantum devices.…

Quantum Physics · Physics 2022-03-23 Senrui Chen , Sisi Zhou , Alireza Seif , Liang Jiang

Extracting information efficiently from quantum systems is a major component of quantum information processing tasks. Randomized measurements, or classical shadows, enable predicting many properties of arbitrary quantum states using few…

Shadow tomography protocols have recently emerged as powerful tools for efficient quantum state learning, aiming to reconstruct expectation values of observables with fewer resources than traditional quantum state tomography. For the…

Quantum Physics · Physics 2026-01-27 Viet T. Tran , Richard Kueng

Classical shadow tomography is a powerful randomized measurement protocol for predicting many properties of a quantum state with few measurements. Two classical shadow protocols have been extensively studied in the literature: the…

Quantum Physics · Physics 2023-06-07 Ahmed A. Akhtar , Hong-Ye Hu , Yi-Zhuang You

The classical shadow estimation protocol is a noise-resilient and sample-efficient quantum algorithm for learning the properties of quantum systems. Its performance depends on the choice of a unitary ensemble, which must be chosen by a user…

Quantum Physics · Physics 2024-01-10 Kaifeng Bu , Dax Enshan Koh , Roy J. Garcia , Arthur Jaffe

Given copies of a quantum state $\rho$, a shadow tomography protocol aims to learn all expectation values from a fixed set of observables, to within a given precision $\epsilon$. We say that a shadow tomography protocol is triply efficient…

Quantum Physics · Physics 2025-03-28 Robbie King , David Gosset , Robin Kothari , Ryan Babbush

Classical shadows provide a versatile framework for estimating many properties of quantum states from repeated, randomly chosen measurements without requiring full quantum state tomography. When prior information is available, such as…

Quantum Physics · Physics 2026-05-27 Jacob Bringewatt , Henry Froland , Andreas Elben , Niklas Mueller

Randomized measurement protocols, including classical shadows, entanglement tomography, and randomized benchmarking are powerful techniques to estimate observables, perform state tomography, or extract the entanglement properties of quantum…

Quantum Physics · Physics 2024-04-03 Jacob Bringewatt , Jonathan Kunjummen , Niklas Mueller

Efficiently learning expectation values of a quantum state using classical shadow tomography has become a fundamental task in quantum information theory. In a classical shadows protocol, one measures a state in a chosen basis W after it has…

Quantum Physics · Physics 2025-06-04 Maxwell West , Antonio Anna Mele , Martin Larocca , M. Cerezo

We introduce a Pauli-measurement-based algorithm to certify the Schmidt number of $n$-qubit pure states. Our protocol achieves an average-case sample complexity of $\caO(\mathrm{poly}(n)\chi^2)$, a substantial improvement over the $\caO(2^n…

Quantum Physics · Physics 2026-01-19 Changhao Yi

We revisit the problem of Pauli shadow tomography: given copies of an unknown $n$-qubit quantum state $\rho$, estimate $\text{tr}(P\rho)$ for some set of Pauli operators $P$ to within additive error $\epsilon$. This has been a popular…

Quantum Physics · Physics 2024-11-18 Sitan Chen , Weiyuan Gong , Qi Ye

We introduce "holographic shadows", a new class of randomized measurement schemes for classical shadow tomography that achieves the optimal scaling of sample complexity for learning geometrically local Pauli operators at any length scale,…

Quantum Physics · Physics 2025-12-30 Shuhan Zhang , Xiaozhou Feng , Matteo Ippoliti , Yi-Zhuang You

A constant number of random Clifford measurements allows the classical shadow protocol to perform direct fidelity estimation (DFE) with high precision. However, estimating properties of an unknown quantum state is expected to be more…

Quantum Physics · Physics 2025-09-17 Hyunho Cha , Jungwoo Lee

We experimentally demonstrate local robust shadows on a trapped-ion quantum computing system, a protocol developed to counteract measurement errors. We alternate between a calibration stage and the shadow estimation stage and also introduce…

While the structure of entangled quantum states is relatively well understood, the characterization of entangled measurements, especially in multipartite and high-dimensional settings, remains far less developed. In this work, we introduce…

Quantum Physics · Physics 2026-05-28 Jef Pauwels , Cyril Branciard , Alejandro Pozas-Kerstjens , Nicolas Gisin
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