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Grant: Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives

Concordia University

$264,000.00

AI-Enhanced Quantum Computing Algorithms and Simulations Based on Entanglement for Advanced Quantum Defense Science and Technology Applications

EF 2023-24 · 2024-03-26

Résumé
In quantum mechanical momentum theory, Clebsch-Gordan (CG) transforms coefficients can measure the degree of momentum entanglement in molecules. The complexity of the degree of entanglement generated by molecular orbital interaction needs to be elucidated in order to develop efficient quantum algorithms based on quantum mechanics, particularly under Coulomb and external fields. The potential of solid harmonic Gaussian orbitals (SHGOs), which are eigenfunctions of the angular momentum operator, has been largely underestimated for this purpose. Using SHGOs, Concordia University (CU) aims to develop an atom-centred angular momentum basis, a projection operator of c fermions acting on spherical harmonics. Compared with the existing tensor hypercontraction (THC) method, this new approach could overcome the need for computationally intensive density adjustment. In the orthogonal, unitary angular momentum basis, we can diagonalize the Coulomb operator. CU can derive a highly efficient quantum algorithm for simulating the electronic Hamiltonian using spherical harmonics as the projection function. The total number of atom-centred angular momentum basis functions is smaller than that of the atomic basis of an original molecular Hamiltonian. This new angular momentum algorithm can achieve O(N) scaling and reduce T complexity by several orders of magnitude compared with state-of-the-art THC methods. Integrating quantum simulation and machine learning into the project enables the team to use available NISQ devices and more mature classical computing techniques using GPUs and CPUs. The strategy involves increasing the complexity of the molecular systems generated as larger quantum computing systems are targeted.
Programme
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Bénéficiaire
Emplacement
Montreal|Montréal, Quebec, Canada
Type de bénéficiaire
Academia
Numéro d'entreprise
106966591
Type
Grant
Source
Proactive Disclosure - Grants and Contributions

Tel que publié

Agreement End Date
2026-03-01
Agreement Number
1016614
Agreement Start Date
2024-03-26
Agreement Title
AI-Enhanced Quantum Computing Algorithms and Simulations Based on Entanglement for Advanced Quantum Defense Science and Technology Applications
Agreement Title (French)
Algorithmes et simulations de calcul quantique améliorés par l'IA basés sur l'intrication pour les applications scientifiques et technologiques avancées de la défense quantique
Agreement Type
Grant
Agreement Value
$264,000.00
Amendment Number
0
Description
In quantum mechanical momentum theory, Clebsch-Gordan (CG) transforms coefficients can measure the degree of momentum entanglement in molecules. The complexity of the degree of entanglement generated by molecular orbital interaction needs to be elucidated in order to develop efficient quantum algorithms based on quantum mechanics, particularly under Coulomb and external fields. The potential of solid harmonic Gaussian orbitals (SHGOs), which are eigenfunctions of the angular momentum operator, has been largely underestimated for this purpose. Using SHGOs, Concordia University (CU) aims to develop an atom-centred angular momentum basis, a projection operator of c fermions acting on spherical harmonics. Compared with the existing tensor hypercontraction (THC) method, this new approach could overcome the need for computationally intensive density adjustment. In the orthogonal, unitary angular momentum basis, we can diagonalize the Coulomb operator. CU can derive a highly efficient quantum algorithm for simulating the electronic Hamiltonian using spherical harmonics as the projection function. The total number of atom-centred angular momentum basis functions is smaller than that of the atomic basis of an original molecular Hamiltonian. This new angular momentum algorithm can achieve O(N) scaling and reduce T complexity by several orders of magnitude compared with state-of-the-art THC methods. Integrating quantum simulation and machine learning into the project enables the team to use available NISQ devices and more mature classical computing techniques using GPUs and CPUs. The strategy involves increasing the complexity of the molecular systems generated as larger quantum computing systems are targeted.
Description (French)
Algorithmes et simulations de calcul quantique améliorés par l'IA basés sur l'intrication pour les applications scientifiques et technologiques avancées de la défense quantique
Expected Results
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Expected Results (French)
À court terme, les résultats prévus seront des collaborations renforcées entre l'industrie, le milieu universitaire et le gouvernement pour soutenir l'excellence en recherche. À moyen terme, les résultats attendus seront le développement de nouvelles technologies potentiellement perturbatrices avec des collaborateurs. À long terme, trouver des solutions collaboratives aux défis des politiques publiques et créer des systèmes d'innovation plus solides.
Federal Riding
Ville-Marie–Le Sud-Ouest–Île-des-Soeurs
Federal Riding (French)
Ville-Marie–Le Sud-Ouest–Île-des-Soeurs
Federal Riding Number
24077
NAICS Code
541710 - R&D in the physical, engineering and life sciences
Organization Code
nrc-cnrc
Organization
National Research Council Canada | Conseil national de recherches Canada
Program Name
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Name (French)
Programme de collaboration en science, en technologie et en innovation - Initiatives de collaboration en R-D
Program Purpose
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
Program Purpose (French)
Collaborer à des programmes multipartites de recherche-développement dans le but de profiter de la synergie entre la recherche transformatrice à haut risque et à haut rendement et le potentiel de découvertes scientifiques et de percées technologiques révolutionnaires dans des secteurs d’intervention prioritaires.
Recipient Business Number
106966591
Recipient City
Montreal|Montréal
Recipient Country
CA
Recipient Legal Name
Concordia University
Recipient Postal Code
H3G 1M8
Recipient Province or Territory
QC
Recipient Type
S
Reference Number
172-2023-2024-Q4-1016614