An Efficient Quantum Algorithm for the Traveling Salesman Problem

The traveling salesman problem is the problem of finding out the shortest route in a network of cities, that a salesman needs to travel to cover all the cities, without visiting the same city more than once. This problem is known to be N P -hard with a brute-force complexity of O(N N) or O(N 2N) for...

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Detalles Bibliográficos
Autores: Sharma, Anant, Deshpande, Nupur, Ghosh, Sanchita, Das, Sreetama, Roy, Shibdas
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/401701
Acceso en línea:http://hdl.handle.net/10261/401701
https://api.elsevier.com/content/abstract/scopus_id/105005323156
Access Level:acceso abierto
Palabra clave:Traveling salesman problem
Efficient quantum algorithm
Hamiltonian cycle problem
Descripción
Sumario:The traveling salesman problem is the problem of finding out the shortest route in a network of cities, that a salesman needs to travel to cover all the cities, without visiting the same city more than once. This problem is known to be N P -hard with a brute-force complexity of O(N N) or O(N 2N) for N number of cities. This problem is equivalent to finding out the shortest Hamiltonian cycle in a given graph, if at least one Hamiltonian cycle exists in it. Quantum algorithms for this problem typically provide with a quadratic speedup only, using Grover's search, thereby having a complexity of O(N N/2) or O(N N). We present a bounded-error quantum polynomial-time (BQP) algorithm for solving the problem, providing with an exponential speedup. The overall complexity of our algorithm is O(N 3 log(N)κ/ϵ + 1/ϵ3), where the errors ϵ are O(1/poly(N)), and κ is the not-too-large condition number of the matrix encoding all Hamiltonian cycles.