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Related papers: The quantum adiabatic search with decoherence in t…

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We analyze three different quantum search algorithms, the traditional Grover's algorithm, its continuous-time analogue by Hamiltonian evolution, and finally the quantum search by local adiabatic evolution. We show that they are closely…

Quantum Physics · Physics 2009-11-10 J. Roland , N. J. Cerf

In quantum adiabatic algorithm, as the adiabatic parameter $s(t)$ changes slowly from zero to one with finite rate, a transition to excited states inevitably occurs and this induces an intrinsic computational error. We show that this…

Quantum Physics · Physics 2016-02-15 Hongye Hu , Biao Wu

We present an extension of Adiabatic Quantum Computing (AQC) algorithm for the unstructured search to the case when the number of marked items is unknown. The algorithm maintains the optimal Grover speedup and includes a small counting…

Mathematical Physics · Physics 2015-03-17 Zhenwei Cao , Alexander Elgart

We introduce a simple framework for estimating lower bounds on the runtime of a broad class of adiabatic quantum algorithms. The central formula consists of calculating the variance of the final Hamiltonian with respect to the initial…

Quantum Physics · Physics 2024-02-13 Jyong-Hao Chen

Enthusiast's perspective: We analyze the effectiveness of AQC for a small rank problem Hamiltonian $H_F$ with the arbitrary initial Hamiltonian $H_I$. We prove that for the generic $H_I$ the running time cannot be smaller than $O(\sqrt N)$,…

Quantum Physics · Physics 2010-05-05 Zhenwei Cao , Alexander Elgart

Decoherence in quantum searches, and in the Grover search in particular, has already been extensively studied, leading very quickly to the loss of the quadratic speedup over the classical case, when searching for some target (marked)…

Quantum Physics · Physics 2019-01-29 D. Reitzner , M. Hillery

The present paper finds the complete set of exact solutions of the general time-dependent dynamical models for quantum decoherence, by making use of the Lewis-Riesenfeld invariant theory and the invariant-related unitary transformation…

Quantum Physics · Physics 2016-09-08 Jian-Qi Shen , Pan Chen , Hong Mao

Quantum adiabatic algorithm is a method of solving computational problems by evolving the ground state of a slowly varying Hamiltonian. The technique uses evolution of the ground state of a slowly varying Hamiltonian to reach the required…

Quantum Physics · Physics 2015-06-26 Avik Mitra , Arindam Ghosh , Ranabir Das , Apoorva Patel , Anil Kumar

We consider the effect of two different environments on the performance of the quantum adiabatic search algorithm, a thermal bath at finite temperature, and a structured environment similar to the one encountered in systems coupled to the…

Quantum Physics · Physics 2017-08-17 Ines de Vega , Mari Carmen Bañuls , A. Pérez

Adiabaticity occurs when, during its evolution, a physical system remains in the instantaneous eigenstate of the hamiltonian. Unfortunately, existing results, such as the quantum adiabatic theorem based on a slow down evolution (H(epsilon…

Quantum Physics · Physics 2009-06-25 Daniel Comparat

Much research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians with Hamming symmetric potentials, such as the well studied "spike" example. Due to the large amount of symmetry in these potentials such problems…

Quantum Physics · Physics 2020-10-05 Jacob Bringewatt , William Dorland , Stephen P. Jordan

We study the fault tolerance of quantum computation by adiabatic evolution, a quantum algorithm for solving various combinatorial search problems. We describe an inherent robustness of adiabatic computation against two kinds of errors,…

Quantum Physics · Physics 2007-05-23 Andrew M. Childs , Edward Farhi , John Preskill

Quantum computation has revolutionary potential for speeding algorithms and for simulating quantum systems such as molecules. We report here a quantum computer design that performs universal quantum computation within a single…

Quantum Physics · Physics 2014-01-22 Ari Mizel

An adiabatic quantum algorithm is essentially given by three elements: An initial Hamiltonian with known ground state, a problem Hamiltonian whose ground state corresponds to the solution of the given problem and an evolution schedule such…

Quantum Physics · Physics 2019-09-17 Davide Pastorello , Enrico Blanzieri

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

Using the methods of quantum trajectories we study effects of dissipative decoherence on the accuracy of the Grover quantum search algorithm. The dependence on the number of qubits and dissipation rate are determined and tested numerically…

Quantum Physics · Physics 2007-05-23 O. V. Zhirov , D. L. Shepelyansky

Searching a database is a central task in computer science and is paradigmatic of transport and optimization problems in physics. For an unstructured search, Grover's algorithm predicts a quadratic speedup, with the search time…

Let $H(t)=(1-t/T)H_0 + (t/T)H_1$, $t\in [0,T]$, be the Hamiltonian governing an adiabatic quantum algorithm, where $H_0$ is diagonal in the Hadamard basis and $H_1$ is diagonal in the computational basis. We prove that $H_0$ and $H_1$ must…

Quantum Physics · Physics 2008-06-02 Lawrence M. Ioannou , Michele Mosca

A computation in adiabatic quantum computing is implemented by traversing a path of nondegenerate eigenstates of a continuous family of Hamiltonians. We introduce a method that traverses a discretized form of the path: At each step we apply…

Quantum Physics · Physics 2009-08-14 S. Boixo , E. Knill , R. D. Somma

Quantum computation that combines the coherence stabilization virtues of decoherence-free subspaces and the fault tolerance of geometric holonomic control is of great practical importance. Some schemes of adiabatic holonomic quantum…

Quantum Physics · Physics 2015-06-11 G. F. Xu , J. Zhang , D. M. Tong , Erik Sjoqvist , L. C. Kwek
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