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We present a formalism for self-calibrating tomography of arbitrary dimensional systems. Self-calibrating quantum state tomography was first introduced in the context of qubits, and allows the reconstruction of the density matrix of an…

Quantum Physics · Physics 2013-06-26 Nicolás Quesada , Agata M. Brańczyk , Daniel F. V. James

The reconstruction of density matrices from measurement data (quantum state tomography) is the most comprehensive method for assessing the accuracy and performance of quantum devices. Existing methods to reconstruct two-photon density…

Quantum Physics · Physics 2025-03-12 Salini Rajeev , Mayukh Lahiri

The quantum density matrix generalises the classical concept of probability distribution to quantum theory. It gives the complete description of a quantum state as well as the observable quantities that can be extracted from it. Its…

Quantum Physics · Physics 2023-08-31 Apoorva D. Patel

A quantum system's state is identified with a density matrix. Though their probabilistic interpretation is rooted in ensemble theory, density matrices embody a known shortcoming. They do not completely express an ensemble's physical…

Quantum Physics · Physics 2021-06-30 Fabio Anza , James P. Crutchfield

We develop a practical quantum tomography protocol and implement measurements of pure states of ququarts realized with polarization states of photon pairs (biphotons). The method is based on an optimal choice of the measuring scheme's…

Quantum Physics · Physics 2008-11-17 E. V. Moreva , Yu. I. Bogdanov , A. K. Gavrichenko , S. P. Kulik , I. Tikhonov

Quantum tomography requires repeated measurements of many copies of the physical system, all prepared by a source in the unknown state. In the limit of very many copies measured, the often-used maximum-likelihood (ML) method for converting…

Quantum Physics · Physics 2014-10-09 Hui Khoon Ng , Berthold-Georg Englert

Learning faithful representations of quantum states is crucial to fully characterizing the variety of many-body states created on quantum processors. While various tomographic methods such as classical shadow and MPS tomography have shown…

The promise of quantum neural nets, which utilize quantum effects to model complex data sets, has made their development an aspirational goal for quantum machine learning and quantum computing in general. Here we provide new methods of…

Quantum Physics · Physics 2017-12-27 Maria Kieferova , Nathan Wiebe

A long-standing problem in quantum physics is to determine the minimal number of measurement bases required for the complete characterization of unknown quantum states, a question of particular relevance to high-dimensional quantum…

Quantum Physics · Physics 2025-08-12 Tianqi Xiao , Yaxin Wang , Ying Xia , Zhihao Li , Xiaoqi Zhou

We present a framework that formulates the quest for the most efficient quantum state tomography scheme as an optimization problem which can be solved numerically. This approach can be applied to a broad spectrum of relevant setups…

Quantum Physics · Physics 2021-12-17 Violeta N. Ivanova-Rohling , Guido Burkard , Niklas Rohling

The quantum state associated to an unknown experimental preparation procedure can be determined by performing quantum state tomography. If the statistical uncertainty in the data dominates over other experimental errors, then a tomographic…

Quantum Physics · Physics 2023-11-15 Jessica O. de Almeida , Matthias Kleinmann , Gael Sentís

The deployment of intermediate- and large-scale quantum devices necessitates the development of efficient full state tomographical techniques for quantum benchmarks. Here, we introduce a matrix filling-based method for tomography of pure…

Quantum Physics · Physics 2021-11-23 Ahmad Farooq , Junaid ur Rehman , Hyundong Shin

The reliable characterization of quantum states as well as any potential noise in various quantum systems is crucial for advancing quantum technologies. In this work we propose the concept of corrupted sensing quantum state tomography which…

Quantum Physics · Physics 2025-05-07 Mengru Ma , Jiangwei Shang

We present a method for performing quantum state reconstruction on qubits and qubit registers in the presence of decoherence and inhomogeneous broadening. The method assumes only rudimentary single qubit rotations as well as knowledge of…

Quantum Physics · Physics 2016-08-14 Karl Tordrup , Klaus Mølmer

Quantum device characterization via state tomography plays an important role in both validating quantum hardware and processing quantum information, but it needs the exponential number of the measurements. For the systems with XX+YY-type…

Quantum Physics · Physics 2020-11-18 Tao Xin

The reconstruction of quantum states from a sufficient set of experimental data can be achieved with arbitrarily weak measurement interactions. Since such weak measurements have negligible back-action, the quantum state reconstruction is…

Quantum Physics · Physics 2010-03-16 Holger F. Hofmann

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 consider the problem of reconstructing global quantum states from local data. Because the reconstruction problem has many solutions in general, we consider the reconstructed state of maximum global entropy consistent with the local data.…

Quantum Physics · Physics 2014-12-31 Brian Swingle , Isaac H. Kim

Modelling quantum devices is to find a model according to quantum theory that can explain the result of experiments in a quantum device. We find that usually we cannot correctly identify the model describing the actual physics of the device…

Quantum Physics · Physics 2019-10-08 Hang Ren , Ying Li

The density matrix is a positive semidefinite operator of trace 1 characterizing the state of a quantum system. We consider the inverse problem to reconstruct such density matrices from indirect measurements, also known as quantum state…

Numerical Analysis · Mathematics 2026-03-06 Florian Oberender , Thorsten Hohage
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