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In recent quantum algorithmic developments, a feedback-based approach has shown promise for preparing quantum many-body system ground states and solving combinatorial optimization problems. This method utilizes quantum Lyapunov control to…

Quantum state preparation lies at the heart of quantum computation and quantum simulations, enabling the investigation of complex manybody systems across physics, chemistry, and data science. While existing methods such as Variational…

Quantum Physics · Physics 2026-01-27 Davide Cugini , Giacomo Guarnieri , Mario Motta , Dario Gerace

We propose a novel non-Hermitian adiabatic quantum optimization algorithm. One of the new ideas is to use a non-Hermitian auxiliary "initial'' Hamiltonian that provides an effective level repulsion for the main Hamiltonian. This effect…

Quantum Physics · Physics 2012-11-15 Gennady P. Berman , Alexander I. Nesterov

Adiabatic state preparation provides an analytical solution for generating the ground state of a target Hamiltonian, starting from an easily prepared ground state of the initial Hamiltonian. While effective for time-dependent Hamiltonians…

Quantum Physics · Physics 2026-01-21 Zekun He , A. F. Kemper , J. K. Freericks

Recent experiments with increasingly larger numbers of qubits have sparked renewed interest in adiabatic quantum computation, and in particular quantum annealing. A central question that is repeatedly asked is whether quantum features of…

Quantum Physics · Physics 2015-06-22 Tameem Albash , Daniel A. Lidar

We decompose the quantum adiabatic evolution as the products of gauge invariant unitary operators and obtain the exact nonadiabatic correction in the adiabatic approximation. A necessary and sufficient condition that leads to adiabatic…

Quantum Physics · Physics 2016-05-12 Zhen-Yu Wang , Martin B. Plenio

A major challenge in machine learning is the computational expense of training these models. Model training can be viewed as a form of optimization used to fit a machine learning model to a set of data, which can take up significant amount…

Machine Learning · Computer Science 2021-11-16 Prasanna Date , Thomas Potok

We consider a periodically driven system where the high-frequency driving protocol consists of a sequence of potentials switched on and off at different instants within a period. We explore the possibility of introducing an adiabatic…

Quantum Physics · Physics 2025-02-26 Ashwin Murali , Tapomoy Guha Sarkar , Jayendra N. Bandyopadhyay

We give a careful proof that a parallelized version of adiabatic quantum computation can efficiently simulate universal gate model quantum computation. The proof specifies an explicit parameter-dependent Hamiltonian $H({\lambda})$ that is…

Quantum Physics · Physics 2019-02-20 Ari Mizel

Quantum systems with chaotic classical counterparts cannot be treated by perturbative techniques or any kind of adiabatic approximations. This is so, in spite of the quantum suppression of classical chaos. We explicitly calculate the…

chao-dyn · Physics 2008-02-03 G. Abal , A. J. Pereira , A. Romanelli , A. Sicardi-Schifino

Reliable preparation of many-body ground states is an essential task in quantum computing, with applications spanning areas from chemistry and materials modeling to quantum optimization and benchmarking. A variety of approaches have been…

Quantum Physics · Physics 2026-02-09 Ricard Puig , Berta Casas , Alba Cervera-Lierta , Zoë Holmes , Adrián Pérez-Salinas

We propose a new design heuristic to tackle combinatorial optimisation problems, inspired by Hamiltonians for optimal state-transfer. The result is a rapid approximate optimisation algorithm. We provide numerical evidence of the success of…

Quantum Physics · Physics 2024-02-14 Robert J. Banks , Dan E. Browne , P. A. Warburton

Quantum annealing is a promising algorithm for solving combinatorial optimization problems. It searches for the ground state of the Ising model, which corresponds to the optimal solution of a given combinatorial optimization problem. The…

Statistical Mechanics · Physics 2026-02-25 Tomohiro Hattori , Shu Tanaka

The preparation of quantum states using short quantum circuits is one of the most promising near-term applications of small quantum computers, especially if the circuit is short enough and the fidelity of gates high enough that it can be…

Quantum Physics · Physics 2015-10-07 D. Wecker , M. B. Hastings , M. Troyer

A central challenge in the successful implementation of adiabatic quantum algorithms is to maintain the quantum adiabaticity during the entire evolution. However, the energy gap between the ground and the excited states of interacting…

Quantum Physics · Physics 2018-02-08 Lin Tian

Adiabatic passage is a standard tool for achieving robust transfer in quantum systems. We show that, in the context of driven nonlinear Hamiltonian systems, adiabatic passage becomes highly non-robust when the target is unstable. We show…

Quantum Physics · Physics 2020-11-11 Jing-Jun Zhu , Xi Chen , Hans-Rudolf Jauslin , Stéphane Guérin

Among various algorithms designed to exploit the specific properties of quantum computers with respect to classical ones, the quantum adiabatic algorithm is a versatile proposition to find the minimal value of an arbitrary cost function…

Statistical Mechanics · Physics 2013-01-29 Victor Bapst , Laura Foini , Florent Krzakala , Guilhem Semerjian , Francesco Zamponi

Implementation of quantum logical gates for multilevel system is demonstrated through decoherence control under the quantum adiabatic method using simple phase modulated laser pulses. We make use of selective population inversion and…

Quantum Physics · Physics 2009-11-11 Debabrata Goswami

We show how to perform universal Hamiltonian and adiabatic computing using a time-independent Hamiltonian on a 2D grid describing a system of hopping particles which string together and interact to perform the computation. In this…

Quantum Physics · Physics 2016-03-23 Seth Lloyd , Barbara Terhal

The main obstacle for coherent control of open quantum systems is decoherence due to different dissipation channels and the inability to precisely control experimental parameters. To overcome these problems we propose to use…

Quantum Physics · Physics 2009-11-10 Carsten Marr , Almut Beige , Gerhard Rempe
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