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dc.contributor.advisorFleischer, Jason Wen_US
dc.contributor.authorBarsi, Christopheren_US
dc.contributor.otherElectrical Engineering Departmenten_US
dc.date.accessioned2011-11-18T14:44:48Z-
dc.date.available2011-11-18T14:44:48Z-
dc.date.issued2011en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01dr26xx39q-
dc.description.abstractThe limitations common to linear imaging techniques were formalized succinctly by Ernst Abbe in 1873. In his theory, each Fourier component of a signal propagates independently from the source to the detector, and the corresponding feature can be detected only if the modal wavenumber lies within the spatial bandwidth of the imaging system. For systems with small numerical apertures, only those modes with low wavenumbers can be detected, so that the resulting image suffers in quality. On the other hand, Abbe's theory does not take into account the dynamical propagation of a signal. It is true that nonlinear optics has been used in imaging methods by exploiting the presence and interaction of many photons at once. However, to date, all nonlinear methods have utilized only temporal frequency mixing, which are typically point processes that circumvent linear limits by generating shorter wavelengths, tighter focal spots, and less unwanted scattering. Beam propagation from the sample to detector is still linear, so that observations are still restricted by the numerical aperture of the system. In this work, Abbe's theory of image formation is generalized to accommodate spatial nonlinearity. In this case, spatial nonlinearity acts as a mechanism to transfer energy among the different spatial modes. Thus, the high-frequency content couples to the low-frequency content and then scatters into the field of view. Numerical processing can reverse the scattering and reconstruct the object to provide increased field of view and super-resolution effects. To accomplish this task, insight into dynamical propagation is sought first by studying nonlinear propagation of optical shock waves. Shock propagation is complex, but well-understood, and provides knowledge of the properties of unknown material responses. This information is then used to develop a computational algorithm for reconstructing (unknown) objects with only measured nonlinear output information. As a final step, spatial nonlinearity is introduced into diffraction limited systems and is shown to surpass these very limits. This new, dynamical method of imaging provides a new degree of freedom in system design and invites reexamination of all linear limits, and methods to overcome them, in light of spatial wave mixing.en_US
dc.language.isoenen_US
dc.publisherPrinceton, NJ : Princeton Universityen_US
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the <a href=http://catalog.princeton.edu> library's main catalog </a>en_US
dc.subjectDigital holographyen_US
dc.subjectImagingen_US
dc.subjectNonlinear opticsen_US
dc.subjectWave dynamicsen_US
dc.subject.classificationElectrical engineeringen_US
dc.subject.classificationOpticsen_US
dc.subject.classificationPhysicsen_US
dc.titleDynamical Imaging Using Spatial Nonlinearityen_US
dc.typeAcademic dissertations (Ph.D.)en_US
pu.projectgrantnumber690-2143en_US
Appears in Collections:Electrical Engineering

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