NDLI: Survey and Review (SIREAD Vol. 44 Issue. 2)

Please wait, while we are loading the content...

Survey and Review (SIREAD Vol. 44 Issue. 2)

Content Provider	Society for Industrial and Applied Mathematics (SIAM)
Author	Trefethen, Nick
Copyright Year	2002
Abstract	These days we are all used to typing keywords into search engines, but even so, I was startled when I asked GoogleTM for information about "phase retrieval'' just now. The response was "Results 1--10 of about 271,000. Search took 0.04 seconds."We live in an era in which optics has met IT. Once upon a time, astronomers or chemists built the best telescope or microscope they could and then set about enjoying the images it produced. Now, the raw image is often just the first step in an elaborate process of adaptive analysis or control. Mirrors flutter under laser-guided computer direction to adjust for atmospheric aberrations; we "straighten out bent starlight." Diffracted X-rays are piped directly to the computer, not the crystallographer. Whether the scale is proteins or eyeballs or galaxies, at the frontiers of science, raw data is now cooked before digestion by humans. The applied mathematicians of the 19th century would have recognized some of the formulas, but they could not have begun to imagine the computational power that we deploy each second in working with them.The following article by Luke, Burke, and Lyon describes one of the major problems of phase retrieval associated with this new kind of optics. Light has propagated from a distant point to an image, undergoing distortions along the way caused by lenses, mirrors, or irregular media. If amplitudes are measured in the image, how can phases be recovered? Once this has been done, the information can be used to construct improved images. The authors consider the particular problem of optical wavefront reconstruction, which played a role in the analysis and improvement of images from the Hubble Space Telescope launched, defective, in 1990. Their methods blend classical physics, nontrivial mathematics, and large-scale algorithms of nonconvex optimization and least squares.
Starting Page	167
Ending Page	167
Page Count	1
File Format	PDF
ISSN	00361445
DOI	10.1137/SIREAD000044000002000167000001
e-ISSN	10957200
Journal	SIAM Review (SIREAD)
Issue Number	2
Volume Number	44
Language	English
Publisher	Society for Industrial and Applied Mathematics
Publisher Date	2006-08-04
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Theoretical Computer Science Computational Mathematics

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in