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Related papers: From quantum circuits to adiabatic algorithms

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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

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

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

We investigate the connection between local minima in the problem Hamiltonian and first order quantum phase transitions during an adiabatic quantum computation. We demonstrate how some properties of the local minima can lead to an extremely…

Quantum Physics · Physics 2013-05-29 M. H. S. Amin , V. Choi

The design of new quantum algorithms has proven to be an extremely difficult task. This paper considers a different approach to the problem, by studying the problem of 'quantum state generation'. This approach provides intriguing links…

Quantum Physics · Physics 2007-05-23 Dorit Aharonov , Amnon Ta-Shma

We study the Hamiltonian associated with the quantum adiabatic algorithm with a random cost function. Because the cost function lacks structure we can prove results about the ground state. We find the ground state energy as the number of…

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

Despite its simplicity and strong theoretical guarantees, adiabatic state preparation has received considerably less interest than variational approaches for the preparation of low-energy electronic structure states. Two major reasons for…

Quantum Physics · Physics 2025-02-19 Etienne Granet , Khaldoon Ghanem , Henrik Dreyer

We develop a resource efficient method by which the ground-state of an arbitrary k-local, optimization Hamiltonian can be encoded as the ground-state of a (k-1)-local optimization Hamiltonian. This result is important because adiabatic…

Quantum Physics · Physics 2014-10-16 Ryan Babbush , Bryan O'Gorman , Alán Aspuru-Guzik

We present a variational quantum adiabatic theorem, which states that, under certain assumptions, the adiabatic dynamics projected onto a variational manifold follow the instantaneous variational ground state. We focus on low-entanglement…

Quantum Physics · Physics 2024-06-19 Bojan Žunkovič , Pietro Torta , Giovanni Pecci , Guglielmo Lami , Mario Collura

Quantum fluctuations driven by non-stoquastic Hamiltonians have been conjectured to be an important and perhaps essential missing ingredient for achieving a quantum advantage with adiabatic optimization. We introduce a transformation that…

Quantum Physics · Physics 2020-09-30 Elizabeth Crosson , Tameem Albash , Itay Hen , A. P. Young

We propose a hybrid quantum-classical approximate optimization algorithm for photonic quantum computing, specifically tailored for addressing continuous-variable optimization problems. Inspired by counterdiabatic protocols, our algorithm…

Quantum Physics · Physics 2024-10-03 Pranav Chandarana , Koushik Paul , Mikel Garcia-de-Andoin , Yue Ban , Mikel Sanz , Xi Chen

We generalize the adiabatic approximation to the case of open quantum systems, in the joint limit of slow change and weak open system disturbances. We show that the approximation is ``physically reasonable'' as under wide conditions it…

Quantum Physics · Physics 2016-08-16 Patrik Thunström , Johan Åberg , Erik Sjöqvist

Adiabatic quantum computing is a powerful framework for state preparation, while its evolution time often scales quadratically in the inverse Hamiltonian spectral gap, leading to sub-optimal computational complexity. In this work, we…

Quantum Physics · Physics 2025-12-16 Xi Guo , Dong An

We show that the quasi-adiabatic evolution of a system governed by the Dicke Hamiltonian can be described in terms of a self-induced quantum many-body metrological protocol. This effect relies on the sensitivity of the ground state to a…

Quantum Physics · Physics 2015-06-16 P. A. Ivanov , D. Porras

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…

We present a quantum adiabatic algorithm for a set of quantum 2-satisfiability (Q2SAT) problem, which is a generalization of 2-satisfiability (2SAT) problem. For a Q2SAT problem, we construct the Hamiltonian which is similar to that of a…

Quantum Physics · Physics 2021-02-08 Yanglin Hu , Zhelun Zhang , Biao Wu

We present a new technique for efficiently transitioning a quantum system from an initial to a final stationary state in less time than is required by an adiabatic (quasi-static) process. Our approach makes use of Nelson's stochastic…

Quantum Physics · Physics 2024-08-07 Vincent Hardel , Giovanni Manfredi , Paul-Antoine Hervieux , Rémi Goerlich

Application of the adiabatic model of quantum computation requires efficient encoding of the solution to computational problems into the lowest eigenstate of a Hamiltonian that supports universal adiabatic quantum computation. Experimental…

Quantum Physics · Physics 2015-01-22 Yudong Cao , Ryan Babbush , Jacob Biamonte , Sabre Kais

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 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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