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The most common error models for quantum computers assume the independence of errors on different qubits. However, most noise mechanisms have some correlations in space. We show how to improve quantum information processing for few-qubit…

Quantum Physics · Physics 2018-12-19 Vickram N. Premakumar , Robert Joynt

We consider a problem of description of quantum correlations and dispersions of subsystems of complex open systems. Based on our previous results we proposed a method to evaluate pure quantum contributions from total statistical…

Quantum Physics · Physics 2016-01-26 Illarion Dorofeyev

We present a new perspective on thermal and quantum phase transitions (QPT) in $(2+1)$-dimensional quantum chromodynamics based on symmetries, topology, and quantum dynamical structure of the baryon ground state in the large $N_c$ limit for…

High Energy Physics - Theory · Physics 2019-04-25 Laith H. Haddad

Consistent chiral limit has been investigated in the curvature mass parametrized quark-meson (QM) model with the quark one-loop vacuum term (QMVT) employing the infrared regularized Chiral perturbation theory (ChPT) predicted scaling of the…

High Energy Physics - Phenomenology · Physics 2025-09-10 Vivek Kumar Tiwari

Quantum Machine Learning (QML) presents as a revolutionary approach to weather forecasting by using quantum computing to improve predictive modeling capabilities. In this study, we apply QML models, including Quantum Gated Recurrent Units…

Quantum Physics · Physics 2025-09-15 Saiyam Sakhuja , Shivanshu Siyanwal , Abhishek Tiwari , Britant , Savita Kashyap

The uncertainty principle is one of the comprehensive and fundamental concept in quantum theory. This principle states that it is not possible to simultaneously measure two incompatible observatories with high accuracy. Uncertainty…

Quantum Physics · Physics 2020-06-09 Soroush Haseli

Hybrid variational quantum algorithms (VQAs) are promising for solving practical problems such as combinatorial optimization, quantum chemistry simulation, quantum machine learning, and quantum error correction on noisy quantum computers.…

Qubits are typically reset into a known state by coupling them to a low-temperature environment. When treated in the Born-Markov approximation such couplings produce exponential relaxation to equilibrium, giving high reset fidelities…

Quantum Physics · Physics 2026-03-11 Carlos Ortega-Taberner , Eoin O'Neill , Paul Eastham

We check quantitatively the validity of some popular phenomenological approaches of QCD in simple models. Dispersion sum rules are considered within the ladder approximation of a field-theoretic model with OPE given by ordinary loop…

High Energy Physics - Phenomenology · Physics 2008-02-03 A. A. Penin , A. A. Pivovarov

A formulation for evaluating the performance of quantum error correcting codes for a general error model is presented. In this formulation, the correlation between errors is quantified by a Hamiltonian description of the noise process. We…

Quantum Physics · Physics 2009-11-13 A. Shabani

Local master equations are a widespread tool to model open quantum systems, especially in the context of many-body systems. These equations, however, are believed to lead to thermodynamic anomalies and violation of the laws of…

Quantum Physics · Physics 2021-02-23 Adam Hewgill , Gabriele De Chiara , Alberto Imparato

This paper presents a Quantum Reinforcement Learning (QRL) solution to the dynamic portfolio optimization problem based on Variational Quantum Circuits. The implemented QRL approaches are quantum analogues of the classical…

Machine Learning · Computer Science 2026-01-29 Vincent Gurgul , Ying Chen , Stefan Lessmann

We derive the general form of a master equation describing the interaction of an arbitrary multipartite quantum system, consisting of a set of subsystems, with an environment, consisting of a large number of sub-envirobments. Each subsystem…

Quantum Physics · Physics 2015-05-28 Vittorio Giovannetti , G. Massimo Palma

We present a projection-based, stability-preserving methodology for computing time correlation functions in open quantum systems governed by generalized quantum master equations with non-Markovian effects. Building upon the memory kernel…

Quantum Physics · Physics 2026-02-12 Wei Liu , Rui-Hao Bi , Yu Su , Limin Xu , Zhennan Zhou , Yao Wang , Wenjie Dou

Tracing out the environmental degrees of freedom is a necessary procedure when simulating open quantum systems. While being an essential step in deriving a tractable master equation it represents a loss of information. In situations where…

Quantum Physics · Physics 2022-11-02 Dominic Gribben , Aidan Strathearn , Gerald E. Fux , Peter Kirton , Brendon W. Lovett

For the purpose of understanding the quantum behavior such as quantum decoherence, fluctuations, dissipation, entanglement and teleportation of a mesoscopic or macroscopic object interacting with a general environment, we derive here a set…

Quantum Physics · Physics 2007-12-09 Chung-Hsien Chou , B. L. Hu , Ting Yu

Hybrid variational quantum algorithms are promising for solving practical problems, such as combinatorial optimization, quantum chemistry simulation, quantum machine learning, and quantum error correction on noisy quantum computers.…

Measurements on a single quantum system at different times reveal rich non-classical correlations similar to those observed in spatially separated multi-partite systems. Here we introduce a theory framework that unifies the description of…

Quantum Physics · Physics 2018-08-01 Fabio Costa , Martin Ringbauer , Michael E. Goggin , Andrew G. White , Alessandro Fedrizzi

We present an approach that allows quantifying decoherence processes in an open quantum system subject to external time-dependent control. Interactions with the environment are modeled by a standard bosonic heat bath. We develop two…

Mesoscale and Nanoscale Physics · Physics 2010-10-12 Dmitry Solenov , Vladimir Privman

A collection of quantile curves provides a complete picture of conditional distributions. Properly centered and scaled versions of estimated curves at various quantile levels give rise to the so-called quantile regression process (QRP). In…

Statistics Theory · Mathematics 2017-07-25 Shih-Kang Chao , Stanislav Volgushev , Guang Cheng
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