Saved in:
Bibliographic Details
Main Author: Ramôa, Alexandra
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2412.00078
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917852809789440
author Ramôa, Alexandra
author_facet Ramôa, Alexandra
contents This thesis explores adaptive inference as a tool to characterize quantum systems using experimental data, with applications in sensing, calibration, control, and metrology. I propose and test algorithms for learning Hamiltonian and Kraus operators using Bayesian experimental design and advanced Monte Carlo techniques, including Sequential and Hamiltonian Monte Carlo. Application to the characterization of quantum devices from IBMQ shows a robust performance, surpassing the built-in characterization functions of Qiskit for the same number of measurements. Introductions to Bayesian statistics, experimental design, and numerical integration are provided, as well as an overview of existing literature.
format Preprint
id arxiv_https___arxiv_org_abs_2412_00078
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Learning the physics of open quantum systems from experiments
Ramôa, Alexandra
Quantum Physics
This thesis explores adaptive inference as a tool to characterize quantum systems using experimental data, with applications in sensing, calibration, control, and metrology. I propose and test algorithms for learning Hamiltonian and Kraus operators using Bayesian experimental design and advanced Monte Carlo techniques, including Sequential and Hamiltonian Monte Carlo. Application to the characterization of quantum devices from IBMQ shows a robust performance, surpassing the built-in characterization functions of Qiskit for the same number of measurements. Introductions to Bayesian statistics, experimental design, and numerical integration are provided, as well as an overview of existing literature.
title Learning the physics of open quantum systems from experiments
topic Quantum Physics
url https://arxiv.org/abs/2412.00078