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Issue title: Special issue of the 25th RCRA International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Guest editors: Thomas Eiter, Marco Maratea and Mauro Vallati
Article type: Research Article
Authors: Oddi, Angelo | Rasconi, Riccardo; *
Affiliations: ISTC-CNR, Via San Martino della Battaglia, 44, 00185 Rome, Italy. angelo.oddi@istc.cnr.it, riccardo.rasconi@istc.cnr.it
Correspondence: [*] Address for correspondence: ISTC-CNR, Via San Martino della Battaglia, 44, 00185 Rome, Italy
Abstract: In this work we investigate the performance of greedy randomised search (GRS) techniques to the problem of compiling quantum circuits to emerging quantum hardware. Quantum computing (QC) represents the next big step towards power consumption minimisation and CPU speed boost in the future of computing machines. Quantum computing uses quantum gates that manipulate multi-valued bits (qubits). A quantum circuit is composed of a number of qubits and a series of quantum gates that operate on those qubits, and whose execution realises a specific quantum algorithm. Current quantum computing technologies limit the qubit interaction distance allowing the execution of gates between adjacent qubits only. This has opened the way to the exploration of possible techniques aimed at guaranteeing nearest-neighbor (NN) compliance in any quantum circuit through the addition of a number of so-called swap gates between adjacent qubits. In addition, technological limitations (decoherence effect) impose that the overall duration (makespan) of the quantum circuit realization be minimized. One core contribution of the paper is the definition of two lexicographic ranking functions for quantum gate selection, using two keys: one key acts as a global closure metric to minimise the solution makespan; the second one is a local metric, which favours the mutual approach of the closest qstates pairs. We present a GRS procedure that synthesises NN-compliant quantum circuits realizations, starting from a set of benchmark instances of different size belonging to the Quantum Approximate Optimization Algorithm (QAOA) class tailored for the MaxCut problem. We propose a comparison between the presented meta-heuristics and the approaches used in the recent literature against the same benchmarks, both from the CPU efficiency and from the solution quality standpoint. In particular, we compare our approach against a reference benchmark initially proposed and subsequently expanded in [1] by considering: (i) variable qubit state initialisation and (ii) crosstalk constraints that further restrict parallel gate execution.
Keywords: Quantum Computing, Optimization, Scheduling, Planning, Greedy Heuristics, Random Algorithms
DOI: 10.3233/FI-2020-1942
Journal: Fundamenta Informaticae, vol. 174, no. 3-4, pp. 259-281, 2020
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