TY  - BOOK
AU  - Hockett,Paul
AU  - Makhija,Varun
ED  - Institute of Physics (Great Britain),
TI  - Quantum metrology with photoelectrons
T2  - [IOP release $release]
SN  - 9780750350228
AV  - QC174.17.M4 H637 2018eb vol. 3
PY  - 2023///]
CY  - Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK)
PB  - IOP Publishing
KW  - Metrology
KW  - Quantum measure theory
KW  - Quantum physics (quantum mechanics & quantum field theory)
KW  - bicssc
KW  - SCIENCE / Physics / Quantum Theory
KW  - bisacsh
N1  - "Version: 20231101"--Title page verso; Includes bibliographical references; part I. Theory and software. 1. Introduction -- 1.1. Topical introduction : from quantum metrology to a generalised bootstrapping protocol  -- 1.2. Context and aims for Volume 3 : Analysis methodologies; 2. Quantum metrology software platform/ecosystem overview -- 2.1. Analysis components -- 2.2. Additional tools -- 2.3. Python ecosystem (backends, libraries and packages) -- 2.4. Installation and environment set up -- 2.5. General platform discussion; 3. Theory -- 3.1. Photoionization dynamics -- 3.2. Symmetry in photoionization -- 3.3. Tensor formulation of photoionization -- 3.4. Density matrix representation -- 3.5. Molecular alignment -- 3.6. Observables : photoelectron flux in the laboratory frame and molecular frame -- 3.7. Information content and sensitivity; 4. Numerical methodologies for extracting matrix elements -- 4.1. Fitting methodologies -- 4.2. Fitting strategies; part II. Extracting matrix elements--numerical methods and case studies. 5. Extracting matrix elements overview -- 5.1. General notes on the case studies; 6. Basis sets for fitting -- 6.1. Symmetry-defined basis sets -- 6.2. Computationally defined basis sets -- 6.3. Basis creation worked examples -- 6.4. Comparison with symmetry-defined and computational matrix elements; 7. General fit setup and numerics -- 7.1. Init and pulling data -- 7.2. Setup with options -- 7.3. Compute AF-[beta]LM and simulate data -- 7.4. Fitting the data : configuration -- 7.5. Fitting the data : running fits; 8. Case study : generalised bootstrapping for a homonuclear diatomic scattering system, N2 (D[infinity]h) -- 8.1. General setup -- 8.2. Load existing fit data or run fits -- 8.3. Post-processing and data overview -- 8.4. Data exploration -- 8.5. Classify candidate sets -- 8.6. Explore candidate result sets -- 8.7. Parameter estimation and fidelity -- 8.8. Using the reconstructed matrix elements; 9. Case study : generalised bootstrapping for a linear heteronuclear scattering system, OCS C([infinity]v) -- 9.1. General setup -- 9.2. Load existing fit data or run fits -- 9.3. Post-processing and data overview -- 9.4. Data exploration -- 9.5. Classify candidate sets -- 9.6. Explore candidate result sets -- 9.7. Parameter estimation and fidelity -- 9.8. Using the reconstructed matrix elements; 10. Case study : generalised bootstrapping for a general asymmetric top scattering system, C2H4(D2h) -- 10.1. General setup -- 10.2. Load existing fit data or run fits -- 10.3. Post-processing and data overview -- 10.4. Data exploration -- 10.5. Classify candidate sets -- 10.6. Explore candidate result sets -- 10.7. Parameter estimation and fidelity -- 10.8. Using the reconstructed matrix elements; 11. Case studies : summaries, conclusions and outlook -- 11.1. General notes on fitting methodologies for the case studies -- 11.2. Retrieval fidelity -- 11.3. Molecular frame photoelectron angular distribution retrieval -- 11.4. Conclusions and outlook; Research scientists & advanced students in quantum metrology and AMO physics; Also available in print
N2  - The overall aim of Quantum Metrology with Photoelectrons, Volume 3 is to expand, explore, and illustrate new computational developments in quantum metrology with photoelectrons: specifically, the application of new Python-based tools to tackle general problems in photoionization matrix element retrieval. Part I details the topic, theory and computational methods; Part II provides further numerical details and case-studies, specifically employing the generalised bootstrap retrieval protocol, which makes use of rotational wavepackets as a geometric control parameter. Problems of various size and difficulty are investigated, with the largest for an asymmetric top with 38 complex matrix elements (equivalently, a 38x38 density matrix retrieval)
UR  - https://iopscience.iop.org/book/mono/978-0-7503-5022-8
ER  -