Quantum-Capacitance Simulation Using Gaussian Subspace Aggregation

ChangeBridge: Patent Apps - AI & Computing (G06N)

Published March 26th, 2026

Detected March 31st, 2026

Summary

The USPTO published Microsoft Technology Licensing's patent application US20260087390A1 for a quantum-capacitance simulation method using Gaussian-subspace aggregation. The method constructs and projects non-interacting Hamiltonians for material configurations, then uses sums-of-Gaussians procedures to approximate low-energy eigenstates under interacting Hamiltonians. Inventors are Samuel Boutin and Roman Bela Bauer.

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What changed

Microsoft Technology Licensing filed USPTO Application US20260087390A1 on December 1, 2025, published March 26, 2026, for a quantum-capacitance simulation method using Gaussian-subspace aggregation. The invention involves constructing non-interacting Hamiltonians for material configurations, computing natural-orbitals basis for parts of the configuration, projecting the Hamiltonian to obtain quantum-mechanical descriptions, adding electron-interaction terms, and using sums-of-Gaussians procedures to assemble Gaussian states for approximating low-energy eigenstates. The method forecasts quantum-capacitance response within sample spaces using extended bases combining nearby representative point bases.

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Source document (simplified)

← USPTO Patent Applications

QUANTUM-CAPACITANCE SIMULATION USING GAUSSIAN-SUBSPACE AGGREGATION

Application US20260087390A1 Kind: A1 Mar 26, 2026

Assignee

Microsoft Technology Licensing, LLC

Inventors

Samuel BOUTIN, Roman Bela BAUER

Abstract

A method for simulating a quantum-capacitance response of a material configuration comprises (a) constructing a non-interacting Hamiltonian for the material configuration based on input data; (b) computing a natural-orbitals basis for each of a plurality of parts of the material configuration under the non-interacting Hamiltonian; (c) projecting the non-interacting Hamiltonian in the natural-orbitals basis to obtain a non-interacting quantum-mechanical description for each part; (d) constructing an interacting Hamiltonian by adding an electron-interaction term to the non-interacting Hamiltonian for each of the plurality of parts; (e) for each of a plurality of representative points in a sample space of at least one tunable parameter of the material configuration, using a sums-of-Gaussians procedure to assemble a basis of Gaussian states for approximating low-energy eigenstates of the material configuration under the interacting Hamiltonian; (f) for each of a plurality of vicinities of representative points in the sample space, combining bases of Gaussian states assembled for nearby representative points to form an extended basis; and (g) forecasting the quantum-capacitance response within the sample space using the extended basis.