The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 23, 2025

Filed:

Jul. 13, 2022
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Ismail Yunus Akhalwaya, Emmarentia, ZA;

Shashanka Ubaru, Ossining, NY (US);

Kenneth Lee Clarkson, Madison, NJ (US);

Mark S. Squillante, Greenwich, CT (US);

Vasileios Kalantzis, White Plains, NY (US);

Lior Horesh, North Salem, NY (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06N 10/20 (2022.01); G06N 10/40 (2022.01);
U.S. Cl.
CPC ...
G06N 10/40 (2022.01); G06N 10/20 (2022.01);
Abstract

A quantum computer-implemented system, method, and computer program product for quantum topological domain analysis (QTDA). The QTDA method achieves an improved exponential speedup and depth complexity of O(n log(1/(δ∈))) where n is the number of data points, ∈ is the error tolerance, δ is the smallest nonzero eigenvalue of the restricted Laplacian, and achieves quantum advantage on general classical data. The QTDA system and method efficiently realizes a combinatorial Laplacian as a sum of Pauli operators; performs a quantum rejection sampling and projection approach to build the relevant simplicial complex repeatedly and restrict the superposition to the simplices of a desired order in the complex; and estimates Betti numbers using a stochastic trace/rank estimation method that does not require Quantum Phase Estimation. The quantum circuit and QTDA method exhibits computational time and depth complexities for Betti number estimation up to an error tolerance ∈.


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