Grants and Contributions:
Title:
Learning the density functional with quantum computers
Agreement Number:
1017150
Agreement Value:
$419,540.00
Agreement Date:
Nov 4, 2024 - Dec 15, 2027
Description:
One of the great successes of computational chemistry is the Density Functional Theory (DFT). By expressing the energy of a system in terms of a functional of the density instead of a wave function, the problem of determining the correct electronic structure for a given nuclei configuration becomes classically tractable. However, the exact form of this energy functional is unknown, leaving us with approximations which break down when electrons are strongly correlated. The design of better functionals is an active research field. The Project proposes to get around this difficulty by performing Hamiltonian simulation on quantum computers for a wide variety of nuclei configuration from which an accurate electronic density is extracted, total energy and pair correlation. By performing a regression on a database generated in this manner, a better approximation to the density functional could be learned. In turn, it would allow to use DFT for problems beyond the reach of the usual approximate functionals. Even when fault-tolerant quantum computers come into existence, one cannot expect them to be widely available. Therefore, the Project aims at gaining the most out of every computation; The recipients believe that applications that extend the abilities of classical computers are one of the best uses for quantum computers. Because of the considerable classical computation infrastructure already available, this project will allow the discovery of novel materials and molecules faster than exclusive use of quantum computers.
Organization:
National Research Council Canada
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.
Location:
Sherbrooke, Quebec, CA J1K 2R1
Reference Number:
172-2024-2025-Q3-1017150
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
108161076
Recipient Type:
Academia
Recipient's Legal Name:
Université de Sherbrooke
Federal Riding Name:
Sherbrooke
Federal Riding Number:
24072
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
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.
NAICS Code:
541710