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Pure entangled states of two spatial qudits have been produced by using the momentum transverse correlation of the parametric down-converted photons [Phys. Rev. Lett. \textbf{94} 100501]. Here we show a generalization of this process to…

Quantum Physics · Physics 2009-11-13 G. Lima , F. A. Torres-Ruiz , L. Neves , A. Delgado , C. Saavedra , S. Pádua

Suppose you receive a sequence of qubits where each qubit is guaranteed to be in one of two pure states, but you do not know what those states are. Your task is to determine the states. This can be viewed as a kind of quantum state learning…

Quantum machine learning algorithms, the extensions of machine learning to quantum regimes, are believed to be more powerful as they leverage the power of quantum properties. Quantum machine learning methods have been employed to solve…

Computational Physics · Physics 2021-06-01 Shree Hari Sureshbabu , Manas Sajjan , Sangchul Oh , Sabre Kais

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

Dynamical quantum phase transitions (DQPTs) occur at times when a quantum state exhibits a nonanalytic change in its return probability. This can be viewed as the probability of collapsing the evolved state to the initial state by quantum…

Quantum Physics · Physics 2026-05-18 Guan-Hua Chen , Guo-Yi Zhu

Quantum dots (QDs) defined with electrostatic gates are a leading platform for a scalable quantum computing implementation. However, with increasing numbers of qubits, the complexity of the control parameter space also grows. Traditional…

Since Shor's discovery of an algorithm to factor numbers on a quantum computer in polynomial time, quantum computation has become a subject of immense interest. Unfortunately, one of the key features of quantum computers - the difficulty of…

Quantum Physics · Physics 2009-08-21 Daniel Gottesman

We revisit quantum tomography in an informationally incomplete scenario and propose improved state reconstruction methods using deep neural networks. In the first approach, the trained network predicts an optimal linear or quadratic…

Quantum Physics · Physics 2026-01-21 Mateusz Krawczyk , Pavel Baláž , Katarzyna Roszak , Jarosław Pawłowski

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

In the light of the progress in quantum technologies, the task of verifying the correct functioning of processes and obtaining accurate tomographic information about quantum states becomes increasingly important. Compressed sensing, a…

Quantum Physics · Physics 2017-05-15 A. Steffens , C. Riofrio , W. McCutcheon , I. Roth , B. A. Bell , A. McMillan , M. S. Tame , J. G. Rarity , J. Eisert

High-quality quantum state generation is essential for advanced quantum information processing, including quantum communication, quantum sensing, and quantum computing. In practice, various error sources degrade the quality of quantum…

We train convolutional neural networks to predict whether or not a set of measurements is informationally complete to uniquely reconstruct any given quantum state with no prior information. In addition, we perform fidelity benchmarking…

We propose a general methodology for efficient statistical reconstruction of a quantum state through collection and analysis of photon counting statistics. Our approach includes both strict quantitative criteria for adequacy and…

Quantum Physics · Physics 2013-11-07 Yu. I. Bogdanov , S. P. Kulik

Preparation of a target quantum many-body state on quantum simulators is one of the significant steps in quantum science and technology. With a small number of qubits, a few quantum states, such as the Greenberger-Horne-Zeilinger state,…

Quantum Physics · Physics 2023-07-28 Donggyu Kim , Eun-Gook Moon

Learning about physical systems from quantum-enhanced experiments, relying on a quantum memory and quantum processing, can outperform learning from experiments in which only classical memory and processing are available. Whereas quantum…

Quantum Physics · Physics 2024-06-21 Matthias C. Caro

When an informationally incomplete set of observables is considered there are several solutions to the quantum state reconstruction problem using von Neumann measurements. The set of solutions are known as Pauli partners, which are not easy…

Quantum Physics · Physics 2013-12-30 D. Goyeneche , A. C. de la Torre

Quantum computers are now on the brink of outperforming their classical counterparts. One way to demonstrate the advantage of quantum computation is through quantum random sampling performed on quantum computing devices. However, existing…

Quantum State Tomography (QST) is a fundamental technique in Quantum Information Processing (QIP) for reconstructing unknown quantum states. However, the conventional QST methods are limited by the number of measurements required, which…

The aim of this paper is to introduce a new graphic representation of quantum states by means of a specific application: the analysis of two models of quantum copying machines. The graphic representation by diagrams of states offers a clear…

Quantum Physics · Physics 2007-05-23 Sara Felloni , Giuliano Strini

Measurement-based quantum computing is one of the most promising quantum computing models. Although various universal resource states have been proposed so far, it was open whether only two Pauli bases are enough for both of universal…

Quantum Physics · Physics 2019-09-24 Yuki Takeuchi , Tomoyuki Morimae , Masahito Hayashi