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Title: Using automatic differentiation as a general framework for ptychographic reconstruction

Abstract

Coherent diffraction imaging methods enable imaging beyond lens-imposed resolution limits. In these methods, the object can be recovered by minimizing an error metric that quantifies the difference between diffraction patterns as observed, and those calculated from a present guess of the object. Efficient minimization methods require analytical calculation of the derivatives of the error metric, which is not always straightforward. This limits our ability to explore variations of basic imaging approaches. Here, we propose to substitute analytical derivative expressions with the automatic differentiation method, whereby we can achieve object reconstruction by specifying only the physics-based experimental forward model. We demonstrate the generality of the proposed method through straightforward object reconstruction for a variety of complex ptychographic experimental models.

Authors:
; ORCiD logo; ; ; ORCiD logo; ORCiD logo
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Scientific User Facilities Division; National Institutes of Health (NIH); USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Materials Sciences & Engineering Division
OSTI Identifier:
1527070
Alternate Identifier(s):
OSTI ID: 1543288
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Published Article
Journal Name:
Optics Express
Additional Journal Information:
Journal Name: Optics Express Journal Volume: 27 Journal Issue: 13; Journal ID: ISSN 1094-4087
Publisher:
Optical Society of America
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION

Citation Formats

Kandel, Saugat, Maddali, S., Allain, Marc, Hruszkewycz, Stephan O., Jacobsen, Chris, and Nashed, Youssef S. G. Using automatic differentiation as a general framework for ptychographic reconstruction. United States: N. p., 2019. Web. doi:10.1364/OE.27.018653.
Kandel, Saugat, Maddali, S., Allain, Marc, Hruszkewycz, Stephan O., Jacobsen, Chris, & Nashed, Youssef S. G. Using automatic differentiation as a general framework for ptychographic reconstruction. United States. doi:10.1364/OE.27.018653.
Kandel, Saugat, Maddali, S., Allain, Marc, Hruszkewycz, Stephan O., Jacobsen, Chris, and Nashed, Youssef S. G. Wed . "Using automatic differentiation as a general framework for ptychographic reconstruction". United States. doi:10.1364/OE.27.018653.
@article{osti_1527070,
title = {Using automatic differentiation as a general framework for ptychographic reconstruction},
author = {Kandel, Saugat and Maddali, S. and Allain, Marc and Hruszkewycz, Stephan O. and Jacobsen, Chris and Nashed, Youssef S. G.},
abstractNote = {Coherent diffraction imaging methods enable imaging beyond lens-imposed resolution limits. In these methods, the object can be recovered by minimizing an error metric that quantifies the difference between diffraction patterns as observed, and those calculated from a present guess of the object. Efficient minimization methods require analytical calculation of the derivatives of the error metric, which is not always straightforward. This limits our ability to explore variations of basic imaging approaches. Here, we propose to substitute analytical derivative expressions with the automatic differentiation method, whereby we can achieve object reconstruction by specifying only the physics-based experimental forward model. We demonstrate the generality of the proposed method through straightforward object reconstruction for a variety of complex ptychographic experimental models.},
doi = {10.1364/OE.27.018653},
journal = {Optics Express},
number = 13,
volume = 27,
place = {United States},
year = {2019},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1364/OE.27.018653

Figures / Tables:

Table 1 Table 1: Schema for reverse-mode automatic differentiation. The gradient is evaluated through an accumulation of intermediate values calculated for the individual elementary functions and their derivatives.

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    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.