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Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic…

Adiabatic quantum computing is a universal model for quantum computing whose implementation using a gate-based quantum computer requires depths that are unreachable in the early fault-tolerant era. To mitigate the limitations of near-term…

Quantum Physics · Physics 2024-10-18 Ioannis Kolotouros , Ioannis Petrongonas , Miloš Prokop , Petros Wallden

Quantum algorithms are prominent in the pursuit of achieving quantum advantage in various computational tasks. However, addressing challenges, such as limited qubit coherence and high error rate in near-term devices, requires extensive…

Quantum Physics · Physics 2024-07-31 Julián Ferreiro-Vélez , Iñaki Iriarte-Zendoia , Yue Ban , Xi Chen

Adiabatic quantum computation provides an alternative approach to quantum computation using a time-dependent Hamiltonian. The time evolution of entanglement during the adiabatic quantum search algorithm is studied, and its relevance as a…

Quantum Physics · Physics 2009-11-11 Daria Ahrensmeier

In adiabatic quantum computing the aim is to track an eigenstate as the Hamiltonian changes. In the usual setup this is achieved using the natural time-dependent Hamiltonian evolution of the system and the main technical tool is the…

Quantum Physics · Physics 2026-05-29 Joseph Cunningham , Jérémie Roland

We analyze the accuracy and sample complexity of variational Monte Carlo approaches to simulate the dynamics of many-body quantum systems classically. By systematically studying the relevant stochastic estimators, we are able to: (i) prove…

Quantum Physics · Physics 2023-10-11 Alessandro Sinibaldi , Clemens Giuliani , Giuseppe Carleo , Filippo Vicentini

We introduce an approach for quantum computing in continuous time based on the Lewis-Riesenfeld dynamic invariants. This approach allows, under certain conditions, for the design of quantum algorithms running on a nonadiabatic regime. We…

Quantum Physics · Physics 2011-08-18 M. S. Sarandy , E. I. Duzzioni , R. M. Serra

At present, several models for quantum computation have been proposed. Adiabatic quantum computation scheme particularly offers this possibility and is based on a slow enough time evolution of the system, where no transitions take place. In…

Quantum Physics · Physics 2012-10-12 P. J. Salas Peralta

Suppressing unwanted transitions out of the instantaneous ground state is a major challenge in unitary adiabatic quantum computation. A recent approach consists in building counterdiabatic potentials approximated using variational…

Quantum Physics · Physics 2022-03-14 Gianluca Passarelli , Rosario Fazio , Procolo Lucignano

The discrete formulation of adiabatic quantum computing is compared with other search methods, classical and quantum, for random satisfiability (SAT) problems. With the number of steps growing only as the cube of the number of variables,…

Quantum Physics · Physics 2009-11-07 Tad Hogg

The evaluation of the performance of adiabatic annealers is hindered by lack of efficient algorithms for simulating their behaviour. We exploit the analyticity of the standard model for the adiabatic quantum process to develop an efficient…

We show that by a suitable choice of a time dependent Hamiltonian, Deutsch's algorithm can be implemented by an adiabatic quantum computer. We extend our analysis to the Deutsch-Jozsa problem and estimate the required running time for both…

Quantum Physics · Physics 2009-11-07 Saurya Das , Randy Kobes , Gabor Kunstatter

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

Simulated quantum annealing based on the path-integral Monte Carlo is one of the most common tools to simulate quantum annealing on classical hardware. Nevertheless, it is in principle highly non-trivial whether or not this classical…

Quantum Physics · Physics 2021-08-25 Yuki Bando , Hidetoshi Nishimori

We explore to what extent path-integral quantum Monte Carlo methods can efficiently simulate the tunneling behavior of quantum adiabatic optimization algorithms. Specifically we look at symmetric cost functions defined over n bits with a…

Quantum Physics · Physics 2016-03-09 Lucas T. Brady , Wim van Dam

We outline an algorithm for the Quantum Counting problem using Adiabatic Quantum Computation (AQC). We show that using local adiabatic evolution, a process in which the adiabatic procedure is performed at a variable rate, the problem is…

Quantum Physics · Physics 2014-06-02 Itay Hen

Adiabatic quantum programming defines the time-dependent mapping of a quantum algorithm into an underlying hardware or logical fabric. An essential step is embedding problem-specific information into the quantum logical fabric. We present…

Quantum Physics · Physics 2012-11-08 Christine Klymko , Blair D. Sullivan , Travis S. Humble

We construct a set of instances of 3SAT which are not solved efficiently using the simplest quantum adiabatic algorithm. These instances are obtained by picking random clauses all consistent with two disparate planted solutions and then…

Quantum Physics · Physics 2012-03-30 Edward Farhi , Jeffrey Goldstone , David Gosset , Sam Gutmann , Harvey B. Meyer , Peter Shor

We propose a numerical approach to design highly efficient adiabatic schedules for analog quantum computing, focusing on the maximum-independent-set problem and neutral atom platforms. On the basis of a representative dataset of small…

Quantum Physics · Physics 2025-06-13 Sébastien Perseguers

Quantum computing for machine learning attracts increasing attention and recent technological developments suggest that especially adiabatic quantum computing may soon be of practical interest. In this paper, we therefore consider this…

Machine Learning · Statistics 2017-06-20 Christian Bauckhage , Eduardo Brito , Kostadin Cvejoski , Cesar Ojeda , Rafet Sifa , Stefan Wrobel
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