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We introduce the problem of *shadow tomography*: given an unknown $D$-dimensional quantum mixed state $\rho$, as well as known two-outcome measurements $E_{1},\ldots,E_{M}$, estimate the probability that $E_{i}$ accepts $\rho$, to within…

Quantum Physics · Physics 2018-11-14 Scott Aaronson

We investigate the estimation technique called quantum state smoothing introduced by Guevara and Wiseman [Phys.~Rev.~Lett.~{\bf 115}, 180407 (2015)], which offers a valid quantum state estimate for a partially monitored system, conditioned…

Quantum Physics · Physics 2020-04-23 Areeya Chantasri , Ivonne Guevara , Howard M. Wiseman

Calculating the properties of Gibbs states is an important task in Quantum Chemistry and Quantum Machine Learning. Previous work has proposed a quantum algorithm which predicts Gibbs state expectation values for $M$ observables from only…

Quantum Physics · Physics 2024-09-10 Arnav Sharma , Kevin Obenland

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

We introduce Sketch Tomography, an efficient procedure for quantum state tomography based on the classical shadow protocol used for quantum observable estimations. The procedure applies to the case where the ground truth quantum state is a…

Quantum Physics · Physics 2026-05-27 Xun Tang , Haoxuan Chen , Yuehaw Khoo , Lexing Ying

Mixed states of a quantum system, represented by density operators, can be decomposed as a statistical mixture of pure states in a number of ways where each decomposition can be viewed as a different preparation recipe. However the fact…

Quantum Physics · Physics 2016-01-26 Sandeep K Goyal , Rajeev Singh , Sibasish Ghosh

Given a quantum state in the finite-dimensional Hilbert space $ \C^n $, the range of possible values of a quantum observable is usually identified with the discrete spectrum of eigenvalues of a corresponding Hermitian matrix. Here any such…

Quantum Physics · Physics 2025-09-29 Peter J. Hammond

The well-known algorithm for quantum phase estimation requires that the considered unitary is available as a conditional transformation depending on the quantum state of an ancilla register. We present an algorithm converting an unknown…

Quantum Physics · Physics 2007-05-23 Dominik Janzing

Quantum estimation theory is a reformulation of random statistical theory with the modern language of quantum mechanics. In fact, the density operator plays a role similar to that of probability distribution functions in classical…

Quantum Physics · Physics 2022-11-15 Bakmou Lahcen , Daoud Mohammed

Estimating the expectation value of an operator corresponding to an observable is a fundamental task in quantum computation. It is often impossible to obtain such estimates directly, as the computer is restricted to measuring in a fixed…

Accurate control of quantum states is crucial for quantum computing and other quantum technologies. In the basic scenario, the task is to steer a quantum system towards a target state through a sequence of control operations. Determining…

Quantum Physics · Physics 2024-06-14 Yan Zhu , Tailong Xiao , Guihua Zeng , Giulio Chiribella , Ya-Dong Wu

Quantum state tomography is a technique in quantum information science used to reconstruct the density matrix of an unknown quantum state, providing complete information about the quantum state. It is of significant importance in fields…

Quantum Physics · Physics 2025-07-23 Wenlong Zhao , Da Zhang , Huili Zhang , Haifeng Yu , Zhang-qi Yin

We introduce a hierarchical algorithm for identifying the largest Pauli coefficients of an unknown $n$-qubit quantum state. The algorithm traverses a prefix-based tree whose nodes represent partial sums of squared Pauli coefficients, always…

Efficiently estimating large numbers of non-commuting observables is an important subroutine of many quantum science tasks. We present the derandomized shallow shadows (DSS) algorithm for efficiently learning a large set of non-commuting…

Reducing the number of measurements required to estimate the expectation value of an observable is crucial for the variational quantum eigensolver to become competitive with state-of-the-art classical algorithms. To measure complicated…

Quantum Physics · Physics 2023-01-09 Seonghoon Choi , Tzu-Ching Yen , Artur F. Izmaylov

Quantum tomography is a procedure to determine the quantum state of a physical system, or equivalently, to estimate the expectation value of any operator. It consists in appropriately averaging the outcomes of the measurement results of…

Quantum Physics · Physics 2025-04-02 G. M. D'Ariano , L. Maccone , M. F. Sacchi

We introduce a variational scheme inspired by classical shadow tomography to compute ground state correlations of quantum spin Hamiltonians. Shadow tomography allows for efficient reconstruction of expectation values of arbitrary…

Quantum Physics · Physics 2025-08-04 Pierre-Gabriel Rozon , Kartiek Agarwal

If an experimentalist observes a sequence of emitted quantum states via either projective or positive-operator-valued measurements, the outcomes form a time series. Individual time series are realizations of a stochastic process over the…

Quantum Physics · Physics 2023-06-14 A. Venegas-Li , J. P. Crutchfield

A novel operational method for estimating the efficiency of quantum state tomography protocols is suggested. It is based on a-priori estimation of the quality of an arbitrary protocol by means of universal asymptotic fidelity distribution…

Quantum Physics · Physics 2015-05-18 Yu. I. Bogdanov , G. Brida , M. Genovese , S. P. Kulik , E. V. Moreva , A. P. Shurupov

In quantum mechanics, predictions are made by way of calculating expectation values of observables, which take the form of Hermitian operators. It is far less common to exploit non-Hermitian operators to perform measurements. Here, we show…

Quantum Physics · Physics 2015-11-04 Eliot Bolduc , Genevieve Gariepy , Jonathan Leach