US 11,734,387 B2
Iterative energy-scaled variational quantum eigensolver
Antonio Mezzacapo, Westchester, NY (US); Richard Chen, Mount Kisco, NY (US); and Marco Pistoia, Amawalk, NY (US)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Mar. 3, 2022, as Appl. No. 17/653,386.
Application 17/653,386 is a continuation of application No. 16/691,941, filed on Nov. 22, 2019, granted, now 11,294,986.
Prior Publication US 2022/0188381 A1, Jun. 16, 2022
Int. Cl. G06F 17/16 (2006.01); G06N 10/00 (2022.01)
CPC G06F 17/16 (2013.01) [G06N 10/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
a memory that stores computer executable components; and
a processor, operably coupled to the memory, and that executes the computer executable components stored in the memory, wherein the computer executable components comprise:
a read-out component that defines a final variational wavefunction for a quantum Hamiltonian, comprising:
initialize variational quantum parameters; and
iteratively perform, in a sequential order, on respective block-diagonalized Hamiltonians of a group of block-diagonalized Hamiltonians, associated with the quantum Hamiltonian, formed using energy scale based symmetries:
determine a variational wavefunction for a current block-diagonalized Hamiltonian in the sequential order based on the variational quantum parameters, and
execute, via a quantum processor, a variational quantum eigensolver algorithm to optimize the variational quantum parameters for the variational wavefunction for the current block-diagonalized Hamiltonian;
define the final variational wavefunction for the quantum Hamiltonian using the variational quantum parameters optimized during a final iteration of the sequential order.