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Related papers: A two reservoir model of quantum error correction

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We investigate the nonequilibrium refrigeration of one and two-qubit systems in a squeezed thermal bath. We characterize the performance of one and two-qubit refrigerators in the presence of squeezed heat baths, in terms of their…

Statistical Mechanics · Physics 2023-06-05 Ashutosh Kumar , Sourabh Lahiri

We develop a measurement-based protocol for simultaneously purifying arbitrary logical states in multiple quantum error correcting codes with unit fidelity and finite probability, starting from arbitrary thermal states of each code. The…

Quantum Physics · Physics 2025-02-04 Chandrima B. Pushpan , Tanoy Kanti Konar , Aditi Sen De , Amit Kumar Pal

We study the statistical distribution of the ergotropy and of the efficiency of a single-qubit battery ad of a single-qubit Otto engine, respectively fuelled by random collisions. The single qubit, our working fluid, is assumed to exchange…

Quantum Physics · Physics 2022-03-02 Vahid Shaghaghi , G. Massimo Palma , Giuliano Benenti

Algorithmic Cooling is a method that uses novel data compression techniques and simplecquantum computing devices to improve NMR spectroscopy, and to offer scalable NMR quantum computers. The algorithm recursively employs two steps. A…

Quantum Physics · Physics 2009-11-11 Jose M. Fernandez , Tal Mor , Yossi Weinstein

Standard approaches to quantum error correction (QEC) require active maintenance using measurements and classical processing. Passive QEC, by contrast, has so far been established only in unphysical spatial dimensions. Here, we give an…

Quantum Physics · Physics 2026-05-22 Gesa Dünnweber , Georgios Styliaris , Rahul Trivedi

The discovery of quantum error correction has greatly improved the long-term prospects for quantum computing technology. Encoded quantum information can be protected from errors that arise due to uncontrolled interactions with the…

Quantum Physics · Physics 2007-05-23 John Preskill

These lecture notes from the 2019 Les Houches Summer School on 'Quantum Information Machines' are intended to provide an introduction to classical and quantum error correction with bits and qubits, and with continuous variable systems…

Quantum Physics · Physics 2023-06-14 Steven M. Girvin

Reservoir computing is a machine learning framework that uses artificial or physical dissipative dynamics to predict time-series data using nonlinearity and memory properties of dynamical systems. Quantum systems are considered as promising…

Accurately estimating properties of quantum states, such as entanglement, while essential for the development of quantum technologies, remains a challenging task. Standard approaches to property estimation rely on detailed modeling of the…

Fluctuation Theorems are central in stochastic thermodynamics, as they allow for quantifying the irreversibility of single trajectories. Although they have been experimentally checked in the classical regime, a practical demonstration in…

Quantum Physics · Physics 2017-10-27 C. Elouard , N. K. Bernardes , A. R. R. Carvalho , M. F. Santos , A. Auffèves

A major milestone of quantum error correction is to achieve the fault-tolerance threshold beyond which quantum computers can be made arbitrarily accurate. This requires extraordinary resources and engineering efforts. We show that even…

Quantum Physics · Physics 2021-06-16 Miroslav Urbanek , Benjamin Nachman , Wibe A. de Jong

Traditional quantum error-correcting codes are designed for the depolarizing channel modeled by generalized Pauli errors occurring with equal probability. Amplitude damping channels model, in general, the decay process of a multilevel atom…

Quantum Physics · Physics 2018-05-29 Markus Grassl , Linghang Kong , Zhaohui Wei , Zhang-Qi Yin , Bei Zeng

Quantum cooling, a deterministic process that drives any state to the lowest eigenstate, has been widely used from studying ground state properties of chemistry and condensed matter quantum physics, to general optimization problems.…

Quantum Physics · Physics 2022-06-06 Pei Zeng , Jinzhao Sun , Xiao Yuan

Many physical systems considered promising qubit candidates are not, in fact, two-level systems. Such systems can leak out of the preferred computational states, leading to errors on any qubits that interact with leaked qubits. Without…

Quantum Physics · Physics 2013-10-09 Austin G. Fowler

It has recently been shown that there are efficient algorithms for quantum computers to solve certain problems, such as prime factorization, which are intractable to date on classical computers. The chances for practical implementation,…

Quantum Physics · Physics 2009-10-30 Adriano Barenco , Todd A. Brun , Ruediger Schack , Tim Spiller

Quantum thermodynamics supplies a consistent description of quantum heat engines and refrigerators up to the level of a single few level system coupled to the environment. Once the environment is split into three;a hot, cold and work…

Quantum Physics · Physics 2015-04-17 Ronnie Kosloff , Amikam Levy

Quantum error correction is an important ingredient for scalable quantum computing. Stabilizer codes are one of the most promising and straightforward ways to correct quantum errors, are convenient for logical operations, and improve…

Quantum Physics · Physics 2025-02-07 Ilya. A. Simakov , Ilya. S. Besedin

A fundamental challenge for quantum information processing is reducing the impact of environmentally-induced errors. Quantum error detection (QED) provides one approach to handling such errors, in which errors are rejected when they are…

Quantum Physics · Physics 2014-01-28 Y. P. Zhong , Z. L. Wang , John M. Martinis , A. N. Cleland , A. N. Korotkov , H. Wang

Quantum error correction protects quantum information against environmental noise. When using qubits, a measure of quality of a code is the maximum number of errors that it is able to correct. We show that a suitable notion of ``number of…

Quantum Physics · Physics 2007-05-23 Emanuel Knill , Raymond Laflamme , Lorenza Viola

Biomarker-based prediction of clinical outcomes is challenging due to nonlinear relationships, correlated features, and the limited size of many medical datasets. Classical machine-learning methods can struggle under these conditions,…