Multi-pass System For Emulating A Quantum Computer And Methods For Use Therewith
A system is presented for emulating sampling of a quantum computer having a plurality of qubits arranged in a grid topology with N columns. The system includes a classical processor that is configured by operational instructions to perform operations that include producing final weights and variable assignments for the N columns based on N iterative passes through the grid topology, wherein each of the N iterative passes generates preliminary weights and variable assignments for a corresponding subset of the N columns, wherein the preliminary weights and variable assignments for a selected column of the corresponding subset based on the preliminary weights and variable assignments generated for a column adjacent to the selected column of the corresponding subset, and wherein the sampling of the plurality of qubits is emulated by a sample based on the final weights and variable assignments for each of the N columns.
Claim CLM-00001. 1. A system for emulating sampling of a quantum computer having a plurality of qubits arranged in a grid topology with N columns, the system comprising:
a memory that stores operational instructions; at least one classical processor that is configured by the operational instructions to perform operations, the operations including: producing final weights and variable assignments for the N columns based on N iterative passes through the grid topology, wherein each of the N iterative passes generates preliminary weights and variable assignments for a corresponding subset of the N columns, and wherein the preliminary weights and variable assignments for a selected column of the corresponding subset of the N columns is based on the preliminary weights and variable assignments generated for a column adjacent to the selected column of the corresponding subset of the N columns; wherein the sampling of the quantum computer having the plurality of qubits is emulated by a sample based on the final weights and variable assignments for each of the N columns.
Claim CLM-00011. 11. A system for emulating sampling of a quantum computer having a plurality of qubits arranged in a grid topology with N columns, the system comprising:
a memory that stores operational instructions; at least one classical processor that is configured by the operational instructions to perform operations, the operations including: producing final weights and variable assignments for the N columns based on N iterative passes through the grid topology, wherein each of the N iterative passes generates preliminary weights and variable assignments for a number of columns of the N columns based on preliminary weights and variable assignments generated for an adjacent column for each of the number of columns, wherein final weights and variable assignments are generated for a final column of the N columns for each of the N iterative passes based on the preliminary weights and variable assignments generated for a column of the N columns adjacent to the final column of the N columns, wherein the final weights and variable assignments for the final column of the N columns are used in a next successive pass of the N iterative passes to reduce the number of columns of the N columns where the preliminary weights and variable assignments are regenerated until the N iterative passes are complete and final weights and variable assignments for each of the N columns have been generated; wherein the sampling of the quantum computer having the plurality of qubits is emulated by a sample based on the final weights and variable assignments for each of the N columns.
Claim CLM-00017. 17. A method for emulating sampling of a quantum computer having a plurality of qubits arranged in a grid topology with N columns, the method comprising:
performing a first iterative pass through the grid topology to produce final weights and variable assignments for a Nth column of the N columns, by generating preliminary weights and variable assignments for N−1 columns of the N columns based on preliminary weights and variable assignments generated for an adjacent column for each of the N−1 columns, wherein the final weights and variable assignments are generated for the Nth column based on the preliminary weights and variable assignments generated for an (N−1)st column of the N columns adjacent to the Nth column; performing N−1 other iterative passes of N iterative passes through the grid topology by:
(a) setting p=2;(b) performing an pth pass through the grid topology, to produce final weights and variable assignments for the (N−p+1)st column of the N columns, by regenerating preliminary weights and variable assignments for N−p columns of the N columns based on preliminary weights and variable assignments regenerated for an adjacent column for each of the N−p columns, wherein the final weights and variable assignments are generated for the (N−p+1)st column based on the preliminary weights and variable assignments regenerated for an (N−p)th column of the N columns adjacent to the (N−p+1)st column and the final weights and variable assignments generated for the (N−p+2)nd column;(c) incrementing p;(d) repeating steps (b) and (c) until p=N; and(e) performing a final pass through the grid topology, to produce final weights and variable assignments for a first column of the N columns, based on the final weights and variable assignments generated for a second column of the N columns;
wherein the sampling of the quantum computer having the plurality of qubits is emulated by a sample based on the final weights and variable assignments for each of the N columns.
