Verfahren und System zur Konstruktion eines Klassischen Äquivalenten Modells eines Trainierten Quantenmaschinenlernmodells

Details

Veröffentlichungs-Nr.

EP4734003

Anmeldetag

18. September 2025

Veröffentlichung

29. April 2026

Rechtsraum

EP

Abstract

Existing techniques of constructing classical equivalents of QML models expand measurements from QML model as truncated Fourier series and find Fourier coefficients by solving an optimization problem. However, this is computationally expensive and since approximate Fourier coefficients are determined, the resulting classical surrogate does not necessarily give exactly same predictions as that of the QML model. Embodiments of the present disclosure provide a method and system for constructing classical equivalent of trained Quantum Machine Learning (QML) model by distilling knowledge from the QML model to a classical model. The method includes training QML model using a first dataset, creating a second dataset using measurements from the QML model, training classical model using the second dataset and learning a processing function using predictions of the classical model and target outputs. The trained classical model combined with the learned processing function serve as classical equivalent of the QML model.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien