Evaluating Quantum Search Applicability to NP-Hard Problems in Industry

Quantum computers, that is, computers that exploit quantum mechanical phenomena to process information, have been shown to theoretically perform some computations faster than the best available methods on traditional computers. One widely applicable quantum computing technique is quantum search which offers an improvement to the problem of finding a needle in a digital haystack. Despite its wide applicability, the usefulness of quantum search to performing any single computational task must often be evaluated on a case-by-case basis. As a result, the full applicability of quantum search is unknown. We analyze computational tasks important in industry and aim to determine if and when quantum search could offer improvements to these computations. Developing this knowledge is directly aligned with the Quantum Algorithm Institute’s goal of bringing together industry and academia to harness the power of quantum computing.

Faculty Supervisor:

Barry Sanders

Student:

Partner:

Quantum Algorithms Institute

Discipline:

Computer science

Sector:

Education; Professional, scientific and technical services

University:

University of Calgary

Program: