English
Related papers

Related papers: Quantum Hopfield Model with Dilute Memories

200 papers

Quantum computing allows for the potential of significant advancements in both the speed and the capacity of widely used machine learning techniques. Here we employ quantum algorithms for the Hopfield network, which can be used for pattern…

Quantum Physics · Physics 2018-10-10 Patrick Rebentrost , Thomas R. Bromley , Christian Weedbrook , Seth Lloyd

Many physically interesting models show a quantum phase transition when a single parameter is varied through a critical point, where the ground state and the first excited state become degenerate. When this parameter appears as a coupling…

Quantum Physics · Physics 2008-09-24 Gernot Schaller

We study temporal behavior of a quantum system under a slow external perturbation, which drives the system across a second order quantum phase transition. It is shown that despite the conventional adiabaticity conditions are always violated…

Statistical Mechanics · Physics 2007-05-23 Anatoli Polkovnikov

A numerical method is proposed for simulation of composite open quantum systems. It is based on Lindblad master equations and adiabatic elimination. Each subsystem is assumed to converge exponentially towards a stationary subspace, slightly…

Quantum Physics · Physics 2023-11-10 François-Marie Le Régent , Pierre Rouchon

Adiabatic quantum computation is a paradigmatic model aiming to solve a computational problem by finding the many-body ground state encapsulating the solution. However, its use of an adiabatic evolution depending on the spectral gap of an…

Quantum Physics · Physics 2024-06-13 Jaeyoon Cho

The quantum phase transition (QPT) of the one-dimensional (1D) quantum compass model in a transverse magnetic field is studied in this paper. An exact solution is obtained by using an extended Jordan and Wigner transformation to the…

Quantum Physics · Physics 2009-11-21 Ke-Wei Sun , Qing-Hu Chen

Models of interacting complex systems provide the fundamental statistical physics reference frame for the study and the understanding of associative memories, machine learning, and the dynamics of neural networks. On the other hand,…

In this review, after providing the basic physical concept behind quantum annealing (or adiabatic quantum computation), we present an overview of some recent theoretical as well as experimental developments pointing to the issues which are…

Statistical Mechanics · Physics 2023-01-18 Atanu Rajak , Sei Suzuki , Amit Dutta , Bikas K. Chakrabarti

We develop the statistical mechanics of the Hopfield model in a transverse field to investigate how quantum fluctuations affect the macroscopic behavior of neural networks. When the number of embedded patterns is finite, the Trotter…

Condensed Matter · Physics 2009-10-28 Hidetoshi Nishimori , Yoshihiko Nonomura

The adiabatic quantum evolution of the Lipkin-Meshkov-Glick (LMG) model across its quantum critical point is studied. The dynamics is realized by linearly switching the transverse field from an initial large value towards zero and…

Statistical Mechanics · Physics 2009-11-13 Tommaso Caneva , Rosario Fazio , Giuseppe E. Santoro

Quantum annealing is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare…

A simulated Hopfield-type neural-net-like model, which is realizable using quantum holography, is proposed for quantum associative memory and pattern recognition.

Quantum Physics · Physics 2007-05-23 Mitja Perus , Horst Bischof

We propose an experimental method for evaluating the adiabatic condition during quantum annealing (QA), which will be essential for solving practical problems. The adiabatic condition consists of the transition matrix element and the energy…

Quantum Physics · Physics 2024-04-10 Yuichiro Mori , Shiro Kawabata , Yuichiro Matsuzaki

This study investigates the quantum effects in transverse-field Ising spin glass models with rotationally invariant random interactions. The primary aim is to evaluate the validity of a quasi-static approximation that captures the…

Disordered Systems and Neural Networks · Physics 2025-10-10 Yoshinori Hara , Yoshiyuki Kabashima

We introduce the transverse Ising model as a prototype for discussing quantum phase transition. Next we introduce Suzuki-Trotter formalism to show the correspondence between $d$-dimensional quantum system with a $(d+1)$-dimensional…

Disordered Systems and Neural Networks · Physics 2007-05-23 Bikas K. Chakrabarti , Arnab Das

By using a continuum of oscillators as a reservoir, we present a classical and a quantum-mechanical treatment for the Higgs model in the presence of dissipation. In this base, a fully canonical approach is used to quantize the damped…

Quantum Physics · Physics 2015-01-15 Ehsan Amooghorban , Ali Mahdifar

We introduce and study the adiabatic dynamics of free-fermion models subject to a local Lindblad bath and in the presence of a time-dependent Hamiltonian. The merit of these models is that they can be solved exactly, and will help us to…

Quantum Physics · Physics 2017-11-20 Maximilian Keck , Simone Montangero , Giuseppe E. Santoro , Rosario Fazio , Davide Rossini

Quantum phase estimation (QPE) is a central algorithmic primitive that estimates eigenvalues of a Hamiltonian up to precision $\epsilon$ in Heisenberg-limited time $T=\Theta(1/\epsilon)$. Standard gate-based implementations of QPE require…

Quantum Physics · Physics 2026-05-22 Alexander Schmidhuber , Seth Lloyd

Adiabatic quantum computation is based on the adiabatic evolution of quantum systems. We analyse a particular class of qauntum adiabatic evolutions where either the initial or final Hamiltonian is a one-dimensional projector Hamiltonian on…

Quantum Physics · Physics 2015-05-13 Avatar Tulsi

We discuss the application of the adiabatic perturbation theory to analyze the dynamics in various systems in the limit of slow parametric changes of the Hamiltonian. We first consider a two-level system and give an elementary derivation of…

Statistical Mechanics · Physics 2015-05-14 C. De Grandi , A. Polkovnikov