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Adiabatic limit is the presumption of the adiabatic geometric quantum computation and of the adiabatic quantum algorithm. But in reality, the variation speed of the Hamiltonian is finite. Here we develop a general formulation of adiabatic…

Quantum Physics · Physics 2009-11-10 Yu Shi , Yong-Shi Wu

In this paper we present a simulation environment enhanced with parallel processing which can be used on personal computers, based on a high-level user interface developed on Mathematica\copyright which is connected to C++ code in order to…

Quantum Physics · Physics 2011-03-09 Sandra Díaz-Pier , Salvador E. Venegas-Andraca , José Luis Gómez-Muñoz

Using a recently constructed ensemble of hard 2SAT realizations, that has a unique ground-state we calculate for the quantized theory the median gap correlation length values $\xi_{GAP}$ along the direction of the quantum adiabatic control…

Quantum Physics · Physics 2014-12-18 Neuhaus Thomas

This paper explores several aspects of the adiabatic quantum computation model. We first show a way that directly maps any arbitrary circuit in the standard quantum computing model to an adiabatic algorithm of the same depth. Specifically,…

Quantum Physics · Physics 2009-11-10 M. Stewart Siu

A promising approach to solving hard binary optimisation problems is quantum adiabatic annealing (QA) in a transverse magnetic field. An instantaneous ground state --- initially a symmetric superposition of all possible assignments of $N$…

Quantum Physics · Physics 2016-05-18 Sergey Knysh

Designing quantum algorithms with a speedup over their classical analogs is a central challenge in quantum information science. Motivated by recent experimental observations of a superlinear quantum speedup in solving the Maximum…

Results are presented of a large-scale simulation of the quantum adiabatic search (QuAdS) algorithm in the presence of noise. The algorithm is applied to the NP-Complete problem Exact Cover 3 (EC3). The noise is assumed to Zeeman-couple to…

Quantum Physics · Physics 2007-05-23 Frank Gaitan

The majorization theory has been applied to analyze the mathematical structure of quantum algorithms. An empirical conclusion by numerical simulations obtained in the previous literature indicates that step-by-step majorization seems to…

Quantum Physics · Physics 2010-09-02 Zhaohui Wei , Zhengfeng Ji , Mingsheng Ying

Quantum adiabatic algorithm is of vital importance in quantum computation field. It offers us an alternative approach to manipulate the system instead of quantum gate model. Recently, an interesting work arXiv:1805.10549 indicated that we…

Quantum Physics · Physics 2019-01-23 Jingwei Wen , Xiangyu Kong , Shijie Wei , Bixue Wang , Tao Xin , Guilu Long

Adiabatic quantum optimization is a procedure to solve a vast class of optimization problems by slowly changing the Hamiltonian of a quantum system. The evolution time necessary for the algorithm to be successful scales inversely with the…

Quantum Physics · Physics 2015-12-16 Salvatore Mandrà , Gian Giacomo Guerreschi , Alán Aspuru-Guzik

Matrix product states provide a natural entanglement basis to represent a quantum register and operate quantum gates on it. This scheme can be materialized to simulate a quantum adiabatic algorithm solving hard instances of a NP-Complete…

Quantum Physics · Physics 2009-11-11 M. C. Banuls , R. Orus , J. I. Latorre , A. Perez , P. Ruiz-Femenia

We present two quantum algorithms based on evolution randomization, a simple variant of adiabatic quantum computing, to prepare a quantum state $\vert x \rangle$ that is proportional to the solution of the system of linear equations $A…

Quantum Physics · Physics 2019-02-20 Yigit Subasi , Rolando D. Somma , Davide Orsucci

The adiabatic theorem has been recently used to design quantum algorithms of a new kind, where the quantum computer evolves slowly enough so that it remains near its instantaneous ground state which tends to the solution [Farhi et al.,…

Quantum Physics · Physics 2009-11-07 Jeremie Roland , Nicolas J. Cerf

In quantum adiabatic evolution algorithms, the quantum computer follows the ground state of a slowly varying Hamiltonian. The ground state of the initial Hamiltonian is easy to construct; the ground state of the final Hamiltonian encodes…

Quantum Physics · Physics 2007-05-23 Edward Farhi , Jeffrey Goldstone , Sam Gutmann

A gapped quantum system that is adiabatically perturbed remains approximately in its eigenstate after the evolution. We prove that, for constant gap, general quantum processes that approximately prepare the final eigenstate require a…

Quantum Physics · Physics 2010-04-02 S. Boixo , R. D. Somma

The number of qubits used by a quantum algorithm will be a crucial computational resource for the foreseeable future. We show how to obtain the classical query complexity for continuous problems. We then establish a simple formula for a…

Quantum Physics · Physics 2007-05-23 A. Papageorgiou , J. F. Traub

In this work, we are interested in the detailed analysis of complexity aspects of both time and space that arises from the implementation of a quantum algorithm on a quantum based hardware. In particular, some steps of the implementation,…

Advances in quantum algorithms suggest a tentative scaling advantage on certain combinatorial optimization problems. Recent work, however, has also reinforced the idea that barren plateaus render variational algorithms ineffective on large…

Quantum Physics · Physics 2025-03-14 Tim Bode , Krish Ramesh , Tobias Stollenwerk

We analyze the performance of adiabatic quantum computation (AQC) under the effect of decoherence. To this end, we introduce an inherently open-systems approach, based on a recent generalization of the adiabatic approximation. In contrast…

Quantum Physics · Physics 2009-11-11 M. S. Sarandy , D. A. Lidar

Adiabatic quantum optimization has been proposed as a route to solve NP-complete problems, with a possible quantum speedup compared to classical algorithms. However, the precise role of quantum effects, such as entanglement, in these…

Quantum Gases · Physics 2015-06-23 Philipp Hauke , Lars Bonnes , Markus Heyl , Wolfgang Lechner
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