6 papers
Scaling Sample-Based Quantum Diagonalization on GPU-Accelerated Systems using OpenMP Offload
Robert Walkup, Juha Jäykkä, Igor Pasichnyk +14
Hybrid quantum-HPC algorithms advance research by delegating complex tasks to quantum processors and using HPC systems to orchestrate workflows and complementary computations. Samp…
Closed-loop calculations of electronic structure on a quantum processor and a classical supercomputer at full scale
Tomonori Shirakawa, Javier Robledo-Moreno, Toshinari Itoko +18
Quantum computers must operate in concert with classical computers to deliver on the promise of quantum advantage for practical problems. To achieve that, it is important to unders…
Quantum Krylov Algorithm for Szegö Quadrature
William Kirby, Yizhi Shen, Daan Camps +3
We present a quantum algorithm to evaluate matrix elements of functions of unitary operators. The method is based on calculating quadrature nodes and weights using data collected f…
Quantum chemistry with provable convergence via randomized sample-based Krylov quantum diagonalization
Samuele Piccinelli, Alberto Baiardi, Stefano Barison +12
Quantum algorithms based on classical processing of individual samples have recently emerged as the most effective and robust methods to approximate ground-state wave functions of…
Quantum-Centric Algorithm for Sample-Based Krylov Diagonalization
Jeffery Yu, Javier Robledo Moreno, Joseph T. Iosue +17
Approximating the ground state of many-body systems is a key computational bottleneck underlying important applications in physics and chemistry. The most widely known quantum algo…
The quantum super-Krylov method
Adam Byrne, William Kirby, Kirk M. Soodhalter +1
The problem of estimating the ground-state energy of a quantum system is ubiquitous in chemistry and condensed matter physics. Krylov quantum diagonalization (KQD) has emerged as a…