US 12,475,401 B2
Quantum computer system and method for combinatorial optimization
David Amaro, London (GB); Carlo Modica, London (GB); Marcello Benedetti, Vilnius (LT); Mattia Fiorentini, London (GB); Michael Lubasch, London (GB); and Matthias Rosenkranz, London (GB)
Assigned to Quantinuum Ltd, London (GB)
Filed by Quantinuum Ltd, London (GB)
Filed on May 26, 2022, as Appl. No. 17/825,908.
Claims priority of application No. 2107468 (GB), filed on May 26, 2021.
Prior Publication US 2022/0391742 A1, Dec. 8, 2022
Int. Cl. G06N 10/60 (2022.01); G06N 10/20 (2022.01); G06N 10/80 (2022.01)
CPC G06N 10/60 (2022.01) [G06N 10/20 (2022.01); G06N 10/80 (2022.01)] 22 Claims
OG exemplary drawing
 
1. A computing system configured to perform at least one combinatorial optimization task, the computing system comprising:
one or more quantum computers; and
one or more classical binary computers coupled to the one or more quantum computers,
wherein the one or more classical binary computers are configured to:
receive one or more computing tasks including the at least one combinatorial optimization task, via an input port of the one or more classical binary computers;
generate a filtered cost function arrangement using a filtering operator;
configure the one or more quantum computers based at least in part on the one or more computing tasks and the filtered cost function arrangement;
generate computational results using output results received from the one or more quantum computers; and
output the computational results via an output port of the one or more classical binary computers;
wherein the one or more quantum computers are configured to execute one or more quantum circuits to generate the output results,
wherein the computing system is configured to generate and configure the one or more quantum circuits using a Filtering Variation Quantum Eigensolver (F-VQE) algorithm implemented based at least in part on one or more Ansätze circuits and the filtered cost function arrangement, and
wherein the computing system is configured to generate the computational results by applying the filtering operator to increase a probability of sampling of eigenstates having lower energies.