Quantum Computation of Molecules and Materials
This project aims to enhance quantum simulations of molecules/materials on near-term quantum computers by leveraging symmetries and improving algorithms for greater accuracy with limited resources.
This grant is no longer accepting proposals
NRC Research Associateship Programs has archived this opportunity.
Funder: NRC Research Associateship Programs
Due Dates: May 1, 2025 (Naval Research Laboratory opportunity)
Funding Amounts: $99,200 stipend plus $3,000 travel allowance; typical fellowship duration 2-3 years
Summary: Supports postdoctoral research to advance quantum simulations of molecules and materials on near-term quantum computers by improving algorithms and leveraging Hamiltonian symmetries.
Key Information: Open to U.S. citizens and permanent residents; requires contacting Research Adviser prior to applying; relocation and health insurance benefits included.
Description
This fellowship opportunity, offered through the NRC Research Associateship Programs at the Naval Research Laboratory (NRL) in Washington, DC, focuses on advancing quantum computation methods for simulating molecules and materials. Classical computation of exact molecular and material properties scales exponentially with the number of orbitals, limiting system size. Quantum computation reduces this cost to polynomial scaling, enabling simulations of larger systems.
The research aims to maximize the computational power of current Noisy Intermediate-Scale Quantum (NISQ) devices, which are limited to short-depth quantum circuits on tens of qubits but are rapidly improving. The project will enhance Variational Quantum Eigensolvers (VQE) by:
- Exploiting symmetries in Hamiltonians to reduce the Hilbert space size, allowing larger systems to be simulated on smaller quantum computers.
- Improving VQE implementations to achieve more accurate solutions with shorter-depth quantum circuits.
This work is relevant to fields including quantum computing, quantum simulations, quantum algorithms, materials science, condensed matter physics, and computational physics.
