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arXiv:0812.1760

Efficiency of structured adiabatic quantum computation

Juan José García‐Ripoll, Mari Carmen Bañuls

Published Dec 9, 2008• 2 citations
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Abstract

We show enough evidence that a structured version of Adiabatic Quantum Computation (AQC) is efficient for most satisfiability problems. More precisely, when the success probability is fixed beforehand, the computational resources grow subexponentially in the number of qubits. Our study focuses on random satisfiability and exact cover problems, developing a multi-step algorithm that solves clauses one by one. Relating the computational cost to classical properties of the problem, we collect significant statistics with up to N=140 qubits, around the phase transitions, which is where the hardest problems appear.

DOI
10.48550/arxiv.0812.1760

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We show enough evidence that a structured version of Adiabatic Quantum Computation (AQC) is efficient for most satisfiability problems. More precisely, when the success probability is fixed beforehand, the computational resources grow subexponentially in the number of qubits. Our study focuses on random satisfiability and exact cover problems, developing a multi-step algorithm that solves clauses one by one. Relating the computational cost to classical properties of the problem, we collect significant statistics with up to N=140 qubits, around the phase transitions, which is where the hardest problems appear.
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Quantum computation by adiabatic evolution, as described in quant-ph/0001106, will solve satisfiability problems if the running time is long enough. In certain special cases (that are classically easy) we know that the quantum algorithm requires a running time that grows as a polynomial in the number of bits. In this paper we present numerical results on randomly generated instances of an NP-complete problem and of a problem that can be solved classically in polynomial time. We simulate a quantum computer (of up to 16 qubits) by integrating the Schrodinger equation on a conventional computer. For both problems considered, for the set of instances studied, the required running time appears to grow slowly as a function of the number of bits.
I describe one quantum approach to solving 3-satisfiability (3-SAT), the well known problem in computer science. The approach is based on repeatedly measuring the truth value of the clauses forming the 3-SAT proposition using a non-orthogonal basis. If the basis slowly evolves then there is a strong analogy to adiabatic quantum computing, although the approach is entirely circuit-based. To solve a 3-SAT problem of n variables requires a quantum register of nnn qubits, or more precisely rebits i.e. qubits whose phase need only be real. For cases of up to n=26 qubits numerical simulations indicate that the algorithm runs fast, outperforming Grover's algorithm and having a scaling with n that is superior to the best reported classical algorithms. There are indications that the approach has an inherent robustness versus imperfections in the elementary operations.
In the continuum limit (large number of qubits), adiabatic quantum algorithms display a remarkable similarity to sweeps through quantum phase transitions. We find that transitions of second or higher order are advantageous in comparison to those of first order. With this insight, we propose an adiabatic quantum algorithm for the solution of 3-satisfiability (3-SAT) problems (exact cover), which is significantly faster than previous proposals according to numerical simulations (up to 20 qubits). These findings suggest that adiabatic quantum algorithms can solve NP-complete problems such as 3-SAT much faster than the Grover search routine (yielding a quadratic enhancement), possibly even with an exponential speedup.
We outline an algorithm for the quantum counting problem using adiabatic quantum computation (AQC). We show that the mechanism of quantum-adiabatic evolution may be utilized toward estimating the number of solutions to a problem, and not only to find them. Using local adiabatic evolution, a process in which the adiabatic procedure is performed at a variable rate, the problem of counting the number of marked items in an unstructured database is solved quadratically faster than the corresponding classical algorithm. The above algorithm provides further evidence for the potentially powerful capabilities of AQC as a paradigm for more efficient problem solving on a quantum computer, and may be used as the basis for solving more sophisticated problems.
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