Research Data Leeds Repository
Dataset relating to 'Apertureless near-field terahertz imaging using the self-mixing effect in a quantum cascade laser'
Citation
Dean, Paul and Mitrofanov, Oleg and Keeley, James and Kundu, Iman and Li, Lianhe and Linfield, Edmund and Davies, A. Giles (2015) Dataset relating to 'Apertureless near-field terahertz imaging using the self-mixing effect in a quantum cascade laser'. University of Leeds. [Dataset] https://doi.org/10.5518/201
Dataset description
This dataset relates to data presented in the work, 'Apertureless near-field terahertz imaging using the self-mixing effect in a quantum cascade laser'. In this work we report two-dimensional apertureless near-field terahertz (THz) imaging using a quantum cascade laser (QCL) source and scattering probe, and demonstrate a resolution of ~1 μm (~λ/100), which represents the highest value achieved to date with a THz QCL. By employing a detection scheme based on self-mixing interferometry, our approach offers experimental simplicity by removing the need for an external detector, and also provides sensitivity to the phase of the reinjected field. We demonstrate a near-field enhancement of the scattered field amplitude for small probe-sample separations, and investigate how the phase of the reinjected field varies with the round-trip time in the external cavity.
Keywords: | terahertz imaging, quantum cascade laser, near-field imaging | ||||||
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Subjects: | F000 - Physical sciences > F300 - Physics > F310 - Applied physics2 F000 - Physical sciences > F300 - Physics > F360 - Optical physics > F361 - Laser physics3 |
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Divisions: | Faculty of Engineering and Physical Sciences > School of Electronic and Electrical Engineering4 | ||||||
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License: | Creative Commons Attribution 4.0 International (CC BY 4.0) | ||||||
Date deposited: | 17 Nov 2015 16:29 | ||||||
URI: | https://archive.researchdata.leeds.ac.uk/id/eprint/177 | ||||||
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Documentation
Data
- 1. https://doi.org/10.5518/20
- 2. https://archive.researchdata.leeds.ac.uk/view/subjects/F310.html
- 3. https://archive.researchdata.leeds.ac.uk/view/subjects/F361.html
- 4. https://archive.researchdata.leeds.ac.uk/view/divisions/SEEE/
- 5. https://doi.org/10.1063/1.4943088
- 6. https://eprints.whiterose.ac.uk/96091/
- 7. https://archive.researchdata.leeds.ac.uk/id/eprint/17
- 8. https://orcid.org/0000-0002-3950-4359
- 9. https://orcid.org/0000-0003-3510-2675
- 10. https://orcid.org/0000-0001-5251-6648
- 11. https://orcid.org/0000-0002-3564-1903
- 12. https://orcid.org/0000-0003-4998-7259
- 13. https://orcid.org/0000-0001-6912-0535
- 14. https://orcid.org/0000-0002-1987-4846
- 15. mailto:P.Dean@leeds.ac.uk
- 16. https://archive.researchdata.leeds.ac.uk/17/1/summary.txt
- 17. https://archive.researchdata.leeds.ac.uk/17/1/summary.txt
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- 19. https://archive.researchdata.leeds.ac.uk/17/1/summary.txt
- 20. https://archive.researchdata.leeds.ac.uk/17/2/Fig2.xlsx
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- 23. https://archive.researchdata.leeds.ac.uk/17/2/Fig2.xlsx
- 24. https://archive.researchdata.leeds.ac.uk/17/3/Fig3.xlsx
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- 26. https://archive.researchdata.leeds.ac.uk/17/3/Fig3.xlsx
- 27. https://archive.researchdata.leeds.ac.uk/17/3/Fig3.xlsx
- 28. https://archive.researchdata.leeds.ac.uk/17/4/Fig4a.xlsx
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- 34. https://archive.researchdata.leeds.ac.uk/17/5/Fig4b.xlsx
- 35. https://archive.researchdata.leeds.ac.uk/17/5/Fig4b.xlsx
- 36. https://archive.researchdata.leeds.ac.uk/17/6/Fig4c.xlsx
- 37. https://archive.researchdata.leeds.ac.uk/17/6/Fig4c.xlsx
- 38. https://archive.researchdata.leeds.ac.uk/17/6/Fig4c.xlsx
- 39. https://archive.researchdata.leeds.ac.uk/17/6/Fig4c.xlsx