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Quantum metrology with photoelectrons. Volume 3, Analysis methodologies / Paul Hockett with Varun Makhija.

By: Contributor(s): Material type: TextSeries: IOP (Series). Release 23. | IOP ebooks. 2023 collection.Publisher: Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2023]Description: 1 online resource (various pagings) : illustrations (some color)Content type:
  • text
Media type:
  • electronic
Carrier type:
  • online resource
ISBN:
  • 9780750350228
  • 9780750350211
Subject(s):
Additional physical formats: Print version:: No titleLOC classification:
  • QC174.17.M4 H637 2018eb vol. 3
Online resources:
Available additional physical forms:
  • Also available in print.
Contents:
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.
Abstract: 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).
Item type: List(s) this item appears in: Titluri cărți electronice Institute of Physics 2025 (221 titluri)
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"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.

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).

Research scientists & advanced students in quantum metrology and AMO physics.

Also available in print.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.

Paul Hockett earned his PhD in 2008 from the University of Nottingham, UK and joined the National Research Council of Canada in 2009. Paul's research interests cover a range of topics spanning the areas of AMO (atomic, molecular, and optical), quantum, and computational physics (and physical chemistry), with a particular focus on fundamental light-matter interactions, spectroscopy, and application to complex systems.

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