Triangle Quantum Computing Seminar Series: Towards Utility-Scale Electronic Structure with Sample-Based Quantum Bootstrap Embedding

ABSTRACT: Computing ground state energies of molecular chemical systems is one application where near-term quantum computers are hoped to find utility. However, significant challenges must be overcome for this to become a reality. The most significant of these is that the number of terms in chemical Hamiltonians scales as a fourth degree polynomial with the size of the system, which translates to either deep circuits or a large number of measurements being required for established quantum eigensolvers such as quantum phase estimation or the variation quantum eigensolver. Quantum bootstrap embedding (QBE) is a method that addresses both of these issues by fragmenting a large molecule into non-disjoint pieces and running a quantum eigensolver for each of the smaller fragments. The recently proposed sample-based diagonalization (SQD) is a quantum eigensolver which has been implemented on quantum hardware for systems as large as 85 qubits. I will discuss how we combined QBE with SQD (QBE-SQD) and tested the method on ibm_pittsburgh for fragments with a 43 qubit footprint. We demonstrate that QBE-SQD can outperform SQD calculations for unfragmented chemical systems that use a 67 qubit footprint. BIO: Joel Bierman is a postdoctoral researcher at North Carolina State University, where he has been working with Professor Yuan Liu on developing algorithms for hybrid CV-DV quantum processors and solving problems in quantum chemistry. He obtained his PhD in physics in 2024 from Duke University for work with advisor Jianfeng Lu on variational quantum algorithms in quantum chemistry. His research interests include developing near-term and early-fault tolerant algorithms, quantum chemistry, hybrid CV-DV quantum algorithms and architectures, as well as quantum error correction. --- Co-hosted by the Duke Quantum Center, the NC State Quantum Initiative, and the UNC Kenan-Flagler's Rethinc. Labs.