Work

Machine Learning Methods for the Simulation and Characterization of Many-Body Quantum Systems

Year: 2024

Type: dissertation

Abstract: This thesis explores Neural Network Quantum States for simulating the time evolution of quantum systems. We introduce an optimization method based on gradient descent applied to a numerical integration cost function. This approach offers a less sensitive alternative compared to Stochastic Reconfiguration. We also explore an optimization approach for Quantum process tomography to reduce the number of measurements required, with Takens embedding theorem as the underlying mathematical framework.

Authors: López Gutiérrez, Irene, Mendl, Christian Bernhard 1982-, Technische Universität München

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6983225952

Cites: 175

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Related to: 10