QuAADS is targeting technical advances key to successful quantum computing, focused on quantum algorithms, architectures, and hybrid computing. These advances underpin applications-based projects, providing a consistent approach to advancing quantum computing. 

Algorithms

Advanced Quantum Algorithms for Simulation and Differential Equations 

PI – Ang Li

Existing approaches to chemistry and differential equations on quantum computers have been shown to yield exponential advantages relative to the best classical algorithms, yet are still expected to take hours to months on realistic quantum computers. Additionally, differential equation methods are not significantly mature enough to enable classical–quantum comparisons. We will develop advanced versions of differential equation solvers based on linear combinations of Hamiltonian simulations and recently developed shadow Hamiltonian simulation methods. We will also develop open-source versions of the library functions to empower these quantum developments within the lab’s quantum initiative and establish PNNL as a leader in applied quantum algorithm development.

Northwest Quantum Library

PI – Ang Li

We will generate a comprehensive library of tested and optimized quantum algorithms for scientific computing. The package aims to provide reference implementations for quantum development and benchmark data for the performance of subroutines, enabling new quantum science. A major outcome of our work will be the ability to readily swap and compare the performance of different quantum algorithms and clearly and easily demonstrate their advantages relative to other approaches.

Architectures

Co-designed Quantum Architecture Development for Domain Science Quantum Algorithm Development

PI – Sam Stein

Quantum computing holds the promise to revolutionize various scientific and industrial domains by solving problems that are infeasible on reach classical computers. However, realizing this potential requires deploying domain-specific algorithms on quantum hardware, which need significant joint optimization to successfully run on quantum hardware. We focus on the codesign of quantum architectures and domain science algorithms to achieve optimized transpilation, compilation, and design, all motivated by resource estimation models grounded in numerical simulation. Leveraging a collaborative approach between quantum computing architects and domain specialists, we will develop fundamental tools within our quantum software stack, required for the design and deployment of these algorithms. We will create a fault-tolerant computation transpiler, research optimization procedures to minimize resource demands, and explore architectural design spaces for fault-tolerant architectures, aligning with current hardware projections.

Quantum Software Tool Development for Domain Science Quantum Algorithm Design, Benchmark, and Verification

PI – Chenxu Liu

In this project, we aim to address critical gaps in quantum software tools needed to facilitate the transition from the noisy intermediate-scale quantum era to fault-tolerant quantum computing. Key objectives include enhancing quantum simulation frameworks to model logical qubit performance, developing architectural abstractions for error-corrected qubits and quantum computing systems, and bridging quantum algorithms with quantum hardware. By testing algorithm performance on available fault-tolerant quantum hardware, our results will guide algorithm improvements in close collaboration with algorithm and domain science research efforts.