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Quantum states encoded in electromagnetic fields, also known as bosonic states, have been widely applied in quantum sensing, quantum communication, and quantum error correction. Accurate characterization is therefore essential yet difficult…

Quantum computation has been growing rapidly in both theory and experiments. In particular, quantum computing devices with a large number of qubits have been developed by IBM, Google, IonQ, and others. The current quantum computing devices…

Quantum Physics · Physics 2021-02-10 Rishabh Gupta , Rongxin Xia , Raphael D. Levine , Sabre Kais

Quantum state tomography (QST) aims at reconstructing the state of a quantum system. However in conventional QST the number of measurements scales exponentially with the number of qubits. Here we propose a QST protocol, in which the…

Quantum Physics · Physics 2024-08-23 Daniele Binosi , Giovanni Garberoglio , Diego Maragnano , Maurizio Dapor , Marco Liscidini

Quantum tomography is a fundamental technique for characterizing, benchmarking, and verifying quantum states and devices. It plays a crucial role in advancing quantum technologies and deepening our understanding of quantum mechanics.…

Quantum state estimation aims at determining the quantum state from observed data. Estimating the full state can require considerable efforts, but one is often only interested in a few properties of the state, such as the fidelity with a…

Quantum Physics · Physics 2016-12-15 Xikun Li , Jiangwei Shang , Hui Khoon Ng , Berthold-Georg Englert

We extend quantum state tomography with minimal cumulative disturbance, first investigated in [arXiv:2406.18370], to arbitrary finite-dimensional pure states. A learner sequentially receives fresh copies of an unknown pure state, chooses a…

Quantum Physics · Physics 2026-05-12 Josep Lumbreras , Marco Tomamichel

Approximate combinatorial optimization is a promising use case for quantum computers. The quantum optimization algorithms often employ a fixed ansatz that evolves an unbiased initial state towards states with better values of the optimand,…

Quantum Physics · Physics 2026-04-30 Phillip C. Lotshaw , Titus Morris , Stuart Hadfield , Ryan Bennink

We propose an estimation method for quantum measurement tomography (QMT) based on semidefinite programming (SDP), and discuss how it may be employed to detect experimental imperfections, such as shot noise and/or faulty preparation of the…

We consider robust optimal experimental design (ROED) for nonlinear Bayesian inverse problems governed by partial differential equations (PDEs). An optimal design is one that maximizes some utility quantifying the quality of the solution of…

Numerical Analysis · Mathematics 2026-05-01 Abhijit Chowdhary , Ahmed Attia , Alen Alexanderian

Characterizing complex quantum systems is a vital task in quantum information science. Quantum tomography, the standard tool used for this purpose, uses a well-designed measurement record to reconstruct quantum states and processes. It is,…

Quantum Physics · Physics 2015-12-10 Amir Kalev , Robert L. Kosut , Ivan H. Deutsch

Quantum information has been drawing a wealth of research in recent years, shedding light on questions at the heart of quantum mechanics, as well as advancing fields such as complexity theory, cryptography, key distribution, and chemistry.…

Quantum Physics · Physics 2017-04-25 Dikla Oren , Maor Mutzafi , Yonina C. Eldar , Mordechai Segev

Amongst the multitude of state reconstruction techniques, the so-called "quantum tomography" seems to be the most fruitful. In this letter, I will start by developing the mathematical apparatus of quantum tomography and, later, I will…

Quantum Physics · Physics 2007-05-23 M. Paini

Conventional Bayesian optimal experimental design seeks to maximize the expected information gain (EIG) on model parameters. However, the end goal of the experiment often is not to learn the model parameters, but to predict downstream…

Computation · Statistics 2024-08-20 Atlanta Chakraborty , Xun Huan , Tommie Catanach

Many quantum states arising in algorithms and physical systems occupy only a small, structured subset of the exponentially large Hilbert space, yet standard quantum state tomography fails to exploit this structure. We present an efficient…

Quantum Physics · Physics 2025-12-24 Chi-Kwong Li , Kevin Yipu Wu , Zherui Zhang

In recent years, quantum, quantum-inspired, and hybrid algorithms are increasingly showing promise for solving software engineering optimization problems. However, best-intended practices for conducting empirical studies have not yet well…

Software Engineering · Computer Science 2025-11-03 Man Zhang , Yuechen Li , Tao Yue , Kai-Yuan Cai

We apply quantum optimal control theory (QOCT) to an exactly solvable non-Markovian open quantum bit (qubit) system to achieve state-independent quantum control and construct high-fidelity quantum gates for moderate qubit decaying…

Quantum Physics · Physics 2014-06-12 Jung-Shen Tai , Kuan-Ting Lin , Hsi-Sheng Goan

Experimental design is central to science and engineering. A ubiquitous challenge is how to maximize the value of information obtained from expensive or constrained experimental settings. Bayesian optimal experimental design (OED) provides…

Methodology · Statistics 2026-02-13 Sofia Mäkinen , Andrew B. Duncan , Tapio Helin

Quantum detector tomography (QDT) is a fundamental technique for calibrating quantum devices and performing quantum engineering tasks. In this paper, we utilize regularization to improve the QDT accuracy whenever the probe states are…

Optimal quantum cloning is the process of making one or more copies of an arbitrary unknown input quantum state with the highest possible fidelity. All reported demonstrations of quantum cloning have so far been limited to copying…

In optimal experimental design, the objective is to select a limited set of experiments that maximizes information about unknown model parameters based on factor levels. This work addresses the generalized D-optimal design problem, allowing…

Data Structures and Algorithms · Computer Science 2024-11-05 Aditya Pillai , Gabriel Ponte , Marcia Fampa , Jon Lee , and Mohit Singh , Weijun Xie