Grant: Alliance Grants
University of British Columbia
$222,600.00
Establishing and exploiting Quantum advantage in superconducting Quantum annealer
EF 2022-23
Résumé
One of the key challenges facing the nascent field of quantum computation is the question of quantum advantage: By directly exploiting the laws of quantum mechanics is the new device capable of performing certain computational tasks more efficiently than the best available algorithm running on classical hardware? Answering this question for a particular quantum device has proven surprisingly difficult, in part because quantum advantage is often tested using artificial problems designed to be tractable for the quantum device but difficult to solve classically. For such problems it is not always obvious what the best classical algorithm might be and the verdict regarding quantum advantage can be reversed later when a better classical algorithm is found and deployed. In the proposed program of research we will study the quantum advantage in the quantum annealer developed by D-Wave Systems, a Burnaby BC-based quantum computing company, by employing state-of-the-art Tensor Network simulation techniques. The annealer architecture implements the transverse-field Ising model with individually adjustable couplings between superconducting qubits and very flexible connectivity, capable of simulating 1, 2 and 3-dimensional systems with up to ~5000 quantum spins. The D-Wave team has already established various aspects of quantum advantage as compared to certain classical algorithms, including the exact numerical diagonalization and quantum Monte Carlo. Our UBC-based team possesses extensive experience in Tensor Network (TN) methods which have not yet been applied to this problem despite being the most powerful known algorithm. In close collaboration with D-Wave team members we will work to adapt and refine the existing TN methods to the task of benchmarking the quantum annealer, then analyze the outcome of direct comparisons between the two and finally exploit the advantage by solving hard problems in quantum condensed matter physics and in real-life applications. The expected outcome will propel the Canadian quantum annealing effort to the world-leading position in this competitive field.
Programme
Alliance Grants
Bénéficiaire
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
580721-2022
Name nom
Franz, Marcel M
Department département
Physics and Astronomy
Organization id
2
Institution établissement
University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2022
Award amount
222600
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
3301
Research subject group en
Condensed matterphysics
Research subject group fr
Physique de la matière condensée
Research subject en
Superconductivity
Research subject fr
Supraconductivité
Installment
inst:1
Partie
1
Nb partie
1
Application title
Establishing and exploiting Quantum advantage in superconducting Quantum annealer
Application summary
One of the key challenges facing the nascent field of quantum computation is the question of quantum advantage: By directly exploiting the laws of quantum mechanics is the new device capable of performing certain computational tasks more efficiently than the best available algorithm running on classical hardware? Answering this question for a particular quantum device has proven surprisingly difficult, in part because quantum advantage is often tested using artificial problems designed to be tractable for the quantum device but difficult to solve classically. For such problems it is not always obvious what the best classical algorithm might be and the verdict regarding quantum advantage can be reversed later when a better classical algorithm is found and deployed. In the proposed program of research we will study the quantum advantage in the quantum annealer developed by D-Wave Systems, a Burnaby BC-based quantum computing company, by employing state-of-the-art Tensor Network simulation techniques. The annealer architecture implements the transverse-field Ising model with individually adjustable couplings between superconducting qubits and very flexible connectivity, capable of simulating 1, 2 and 3-dimensional systems with up to ~5000 quantum spins. The D-Wave team has already established various aspects of quantum advantage as compared to certain classical algorithms, including the exact numerical diagonalization and quantum Monte Carlo. Our UBC-based team possesses extensive experience in Tensor Network (TN) methods which have not yet been applied to this problem despite being the most powerful known algorithm. In close collaboration with D-Wave team members we will work to adapt and refine the existing TN methods to the task of benchmarking the quantum annealer, then analyze the outcome of direct comparisons between the two and finally exploit the advantage by solving hard problems in quantum condensed matter physics and in real-life applications. The expected outcome will propel the Canadian quantum annealing effort to the world-leading position in this competitive field.