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Quantum machine learning seeks a computational advantage in data processing by evaluating functions of quantum states, such as their similarity, that can be classically intractable to compute. For quantum advantage to be possible, however,…

Quantum state tomography is a fundamental tool in quantum information processing. It allows us to estimate the state of a quantum system by measuring different observables on many identically prepared copies of the system. This is, in…

Quantum Physics · Physics 2011-11-28 Carlos A. Riofrío

We address the class of positive operator-valued measures (POVMs) for qubit systems that are obtained by coupling the signal qubit with a probe qubit and then performing a projective measurement on the sole probe system. These POVMs, which…

Quantum Physics · Physics 2015-10-27 Carlo Sparaciari , Matteo G. A. Paris

Quantum coherence is a fundamental feature of quantum physics and plays a significant role in quantum information processing. By generalizing the resource theory of coherence from von Neumann measurements to positive operator-valued…

Quantum Physics · Physics 2023-05-12 Meng-Li Guo , Jin-Min Liang , Bo Li , Shao-Ming Fei , Zhi-Xi Wang

Phase estimation protocols provide a fundamental benchmark for the field of quantum metrology. The latter represents one of the most relevant applications of quantum theory, potentially enabling the capability of measuring unknown physical…

Generalized quantum measurements identifying non-orthogonal states without ambiguity often play an indispensable role in various quantum applications. For such unambiguous state discrimination scenario, we have a finite probability of…

Quantum Physics · Physics 2021-04-16 Shuro Izumi , Jonas S. Neergaard-Nielsen , Ulrik L. Andersen

Recent advances have demonstrated that $\mathcal{O}(\log M)$ measurements suffice to predict $M$ properties of arbitrarily large quantum many-body systems. However, these remarkable findings assume that the properties to be predicted are…

Quantum Physics · Physics 2024-10-22 Jerry Huang , Laura Lewis , Hsin-Yuan Huang , John Preskill

The rapid progress in quantum computing (QC) and machine learning (ML) has attracted growing attention, prompting extensive research into quantum machine learning (QML) algorithms to solve diverse and complex problems. Designing…

Quantum Physics · Physics 2025-01-13 Samuel Yen-Chi Chen , Huan-Hsin Tseng , Hsin-Yi Lin , Shinjae Yoo

We consider measurements, described by a positive-operator-valued measure (POVM), whose outcome probabilities determine an arbitrary pure state of a D-dimensional quantum system. We call such a measurement a pure-state informationally…

Quantum Physics · Physics 2009-11-10 Steven T. Flammia , Andrew Silberfarb , Carlton M. Caves

We report an experimental realization of adaptive Bayesian quantum state tomography for two-qubit states. Our implementation is based on the adaptive experimental design strategy proposed in [F.Husz\'ar and N.M.T.Houlsby, Phys.Rev.A 85,…

Estimation of physical quantities is at the core of most scientific research and the use of quantum devices promises to enhance its performances. In real scenarios, it is fundamental to consider that the resources are limited and Bayesian…

Quantum tomography is a critically important tool to evaluate quantum hardware, making it essential to develop optimized measurement strategies that are both accurate and efficient. We compare a variety of strategies using nearly pure test…

Quantum Physics · Physics 2017-10-18 H. Sosa-Martinez , N. K. Lysne , C. H. Baldwin , A. Kalev , I. H. Deutsch , P. S. Jessen

Quantum state tomography is both a crucial component in the field of quantum information and computation, and a formidable task that requires an incogitably large number of measurement configurations as the system dimension grows. We…

Measurement is a fundamental operation in quantum computing and has many important use cases in quantum algorithms. This article provides a comprehensive overview of the basic measurement operations in quantum computing and represents a…

Adaptive sampling algorithms are modern and efficient methods that dynamically adjust the sample size throughout the optimization process. However, they may encounter difficulties in risk-averse settings, particularly due to the challenge…

Optimization and Control · Mathematics 2025-02-17 Sandra Pieraccini , Tommaso Vanzan

Programmable photonic quantum processors face a critical challenge: despite significant advances in quantum state preparation and manipulation, measurements remain limited to projective techniques. Here, we demonstrate a programmable…

The development of large-scale platforms for quantum information requires new methods for verification and validation of quantum behavior. Quantum tomography (QT) is the standard tool for diagnosing quantum states, process, and readout…

Quantum Physics · Physics 2017-01-10 Charles H. Baldwin

Measuring the state of quantum computers is a highly non-trivial task, with implications for virtually all quantum algorithms. We propose a novel scheme where identical copies of a quantum state are measured jointly so that all Pauli…

Quantum Physics · Physics 2025-09-03 Rick P. A. Simon , Zheng Shi , Charlie Nation , Andrew Jena , Luca Dellantonio

We present the first complete optimization of quantum tomography, for states, POVMs, and various classes of transformations, for arbitrary prior ensemble and arbitrary representation, giving corresponding feasible experimental schemes.

Quantum Physics · Physics 2009-11-13 A. Bisio , G. Chiribella , G. M. D'Ariano , S. Facchini , P. Perinotti

The measurement precision of modern quantum simulators is intrinsically constrained by the limited set of measurements that can be efficiently implemented on hardware. This fundamental limitation is particularly severe for quantum…

Quantum Physics · Physics 2020-07-01 Giacomo Torlai , Guglielmo Mazzola , Giuseppe Carleo , Antonio Mezzacapo