Show simple item record

Efficient Algorithms for Light Transmission, Focusing and Scattering Matrix Retrieval in Highly Diffusive 3D Random Media

dc.contributor.authorGuo, Han
dc.date.accessioned2019-02-07T17:54:37Z
dc.date.availableNO_RESTRICTION
dc.date.available2019-02-07T17:54:37Z
dc.date.issued2018
dc.date.submitted2018
dc.identifier.urihttps://hdl.handle.net/2027.42/147580
dc.description.abstractWavefront shaping provides an increasingly appealing avenue for imaging and other applications that require controlling electromagnetic waves passing through complex and disordered media. Indeed, these techniques allow researchers and engineers to exploit the properties of high-frequency waves, particularly optical ones, as they interact with these media to obtain nearly perfect transmission and a high degree of focusing. Here, we simulate the process of wave propagation in 3D random media using full-wave, integral equation-based computational electromagnetics schemes. We replicate many experimental observations relating to the existence of so-called open channels in non-absorbing random media and the distribution of their transmission coefficients. In addition, we develop new schemes for manipulating these waves, e.g. by focusing them onto one or multiple spots in the output plane. Furthermore, we leverage the computational methods to develop new schemes for characterizing random media, e.g. by computing their scattering and transmission matrices under a variety of conditions. Finally, we study the transmission properties of absorbing media and find a universal fluctuant pattern of their maximal transmission coefficients.
dc.language.isoen_US
dc.subjectwave propagation and scattering
dc.subjectwavefront shaping technique
dc.subjectcomputational electromagnetics
dc.subjectapplied optics
dc.subjectnumerical simulation
dc.subjectrandom media
dc.titleEfficient Algorithms for Light Transmission, Focusing and Scattering Matrix Retrieval in Highly Diffusive 3D Random Media
dc.typeThesisen_US
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineElectrical Engineering
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studies
dc.contributor.committeememberMichielssen, Eric
dc.contributor.committeememberNadakuditi, Raj Rao
dc.contributor.committeememberSchotland, John Carl
dc.contributor.committeememberGrbic, Anthony
dc.subject.hlbsecondlevelComputer Science
dc.subject.hlbsecondlevelElectrical Engineering
dc.subject.hlbsecondlevelEngineering (General)
dc.subject.hlbsecondlevelMathematics
dc.subject.hlbsecondlevelPhysics
dc.subject.hlbsecondlevelScience (General)
dc.subject.hlbsecondlevelStatistics and Numeric Data
dc.subject.hlbtoplevelEngineering
dc.subject.hlbtoplevelScience
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/147580/1/hanguo_1.pdf
dc.identifier.orcid0000-0002-7206-8528
dc.identifier.name-orcidGuo, Han; 0000-0002-7206-8528en_US
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.