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Related papers: Schmidt quantum compressor

200 papers

We study quantum compression and decompression of light pulses that carry quantum information using a photon-echo quantum memory technique with controllable inhomogeneous broadening of an isolated atomic absorption line. We investigate…

Quantum Physics · Physics 2025-02-06 S. A. Moiseev , W. Tittel

Quantum computing and quantum sensing represent two distinct frontiers of quantum information science. In this work, we harness quantum computing to solve a fundamental and practically important sensing problem: the detection of weak…

Quantum Physics · Physics 2025-01-15 Richard R. Allen , Francisco Machado , Isaac L. Chuang , Hsin-Yuan Huang , Soonwon Choi

Well-controlled quantum devices with their increasing system size face a new roadblock hindering further development of quantum technologies: The effort of quantum tomography---the characterization of processes and states within a quantum…

Quantum Physics · Physics 2017-05-26 C. A. Riofrio , D. Gross , S. T. Flammia , T. Monz , D. Nigg , R. Blatt , J. Eisert

Quantum sensing can enhance imaging performance by reducing measurement noise below the classical limit, thereby improving the signal-to-noise ratio (SNR) of acquired data. In conventional quantum imaging schemes, squeezing is applied…

Quantum Physics · Physics 2026-04-21 Haowei Shi , Visuttha Manthamkarn , Christopher M. Jones , Zheshen Zhang , Quntao Zhuang

Advances in development of quantum computing processors brought ample opportunities to test the performance of various quantum algorithms with practical implementations. In this paper we report on implementations of quantum compression…

Quantum Physics · Physics 2022-09-22 Matej Pivoluska , Martin Plesch

The emerging field of quantum machine learning has the potential of revolutionizing our perspectives of quantum computing and artificial intelligence. In the predominantly empirical realm of quantum machine learning, a theoretical void…

Quantum Physics · Physics 2023-11-14 Zhou Shangnan

The canonical Schmidt decomposition of quantum states is discussed and its implementation to the Quantum Computation Simulator is outlined. In particular, the semiorder relation in the space of quantum states induced by the lexicographic…

Quantum Physics · Physics 2009-03-12 Roman Gielerak , Marek Sawerwain

By looking at quantum data compression in the second quantisation, we present a new model for the efficient generation and use of variable length codes. In this picture lossless data compression can be seen as the {\em minimum energy}…

Quantum Physics · Physics 2009-11-07 Luke Rallan , Vlatko Vedral

Inspired by the `computable cross norm' or `realignment' criterion, we propose a new point of view about the characterization of the states of bipartite quantum systems. We consider a Schmidt decomposition of a bipartite density operator.…

Quantum Physics · Physics 2008-09-16 Cosmo Lupo , Paolo Aniello , Antonello Scardicchio

Ask how the quantum compression of ensembles of pure states is affected by the availability of entanglement, and in settings where the encoder has access to side information. We find the optimal asymptotic quantum rate and the optimal…

Quantum Physics · Physics 2020-05-22 Zahra Baghali Khanian , Andreas Winter

Entanglement plays an important role in quantum communication, algorithms, and error correction. Schmidt coefficients are correlated to the eigenvalues of the reduced density matrix. These eigenvalues are used in Von Neumann entropy to…

Quantum Physics · Physics 2014-09-25 Anmer Daskin , Ananth Grama , Sabre Kais

We study classical source coding with quantum side-information where the quantum side-information is observed by a helper and sent to the decoder via a classical channel. We derive a single-letter characterization of the achievable rate…

Quantum Physics · Physics 2017-01-12 Min-Hsiu Hsieh , Shun Watanabe

We present the enhanced feature quantum autoencoder, or EF-QAE, a variational quantum algorithm capable of compressing quantum states of different models with higher fidelity. The key idea of the algorithm is to define a parameterized…

Quantum Physics · Physics 2021-07-13 Carlos Bravo-Prieto

Compressive sensing is a signal processing technique that enables the reconstruction of sparse signals from a limited number of measurements, leveraging the signal's inherent sparsity to facilitate efficient recovery. Recent works on the…

Quantum Physics · Physics 2025-01-22 Naveed Naimipour , Collin Frink , Harry Shaw , Haleh Safavi , Mojtaba Soltanalian

Recent quantum technologies utilize complex multidimensional processes that govern the dynamics of quantum systems. We develop an adaptive diagonal-element-probing compression technique that feasibly characterizes any unknown quantum…

Transmission of high dimensional entanglement through quantum channels is a significant area of interest in quantum information science. The certification of high dimensional entanglement is usually done through Schmidt numbers. Schmidt…

Quantum Physics · Physics 2024-12-02 Bivas Mallick , Nirman Ganguly , A. S. Majumdar

Starting from a new principle inspired by quantum tomography rather than from Born's rule, this paper gives a self-contained deductive approach to quantum mechanics and quantum measurement. A suggestive notion for what constitutes a quantum…

Quantum Physics · Physics 2024-05-22 Arnold Neumaier

Quantum computing offers the potential for superior computational capabilities, particularly for data-intensive tasks. However, the current state of quantum hardware puts heavy restrictions on input size. To address this, hybrid transfer…

The well-known Schmidt decomposition, or equivalently, the complex singular value decomposition, states that a pure quantum state of a bipartite system can always be brought into a "diagonal" form using local unitary transformations. In…

Quantum Physics · Physics 2024-01-17 Emanuel Malvetti

Image classification is a core task of intelligent sensing, conventionally follows a sequential imaging then processing pipeline. However, redundant high-dimensional image reconstruction is inherently inefficient, especially in photon…