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Main Authors: Colombo, Alessandro, Galli, Davide Emilio, De Caro, Liberato, Scattarella, Francesco, Carlino, Elvio
Format: Preprint
Published: 2017
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Online Access:https://arxiv.org/abs/1701.07685
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author Colombo, Alessandro
Galli, Davide Emilio
De Caro, Liberato
Scattarella, Francesco
Carlino, Elvio
author_facet Colombo, Alessandro
Galli, Davide Emilio
De Caro, Liberato
Scattarella, Francesco
Carlino, Elvio
contents Coherent Diffractive Imaging is a lensless technique that allows imaging of matter at a spatial resolution not limited by lens aberrations. This technique exploits the measured diffraction pattern of a coherent beam scattered by periodic and non-periodic objects to retrieve spatial information. The diffracted intensity, for weak-scattering objects, is proportional to the modulus of the Fourier Transform of the object scattering function. Any phase information, needed to retrieve its scattering function, has to be retrieved by means of suitable algorithms. Here we present a new approach, based on a memetic algorithm, i.e. a hybrid genetic algorithm, to face the phase problem, which exploits the synergy of deterministic and stochastic optimization methods. The new approach has been tested on simulated data and applied to the phasing of transmission electron microscopy coherent electron diffraction data of a $\text{SrTiO}_\text{3}$ sample. We have been able to quantitatively retrieve the projected atomic potential, and also image the oxygen columns, which are not directly visible in the relevant high-resolution transmission electron microscopy images. Our approach proves to be a new powerful tool for the study of matter at atomic resolution and opens new perspectives in those applications in which effective phase retrieval is necessary.
format Preprint
id arxiv_https___arxiv_org_abs_1701_07685
institution arXiv
publishDate 2017
record_format arxiv
spellingShingle Facing the phase problem in Coherent Diffractive Imaging via Memetic Algorithms
Colombo, Alessandro
Galli, Davide Emilio
De Caro, Liberato
Scattarella, Francesco
Carlino, Elvio
Computational Physics
Materials Science
Optimization and Control
Coherent Diffractive Imaging is a lensless technique that allows imaging of matter at a spatial resolution not limited by lens aberrations. This technique exploits the measured diffraction pattern of a coherent beam scattered by periodic and non-periodic objects to retrieve spatial information. The diffracted intensity, for weak-scattering objects, is proportional to the modulus of the Fourier Transform of the object scattering function. Any phase information, needed to retrieve its scattering function, has to be retrieved by means of suitable algorithms. Here we present a new approach, based on a memetic algorithm, i.e. a hybrid genetic algorithm, to face the phase problem, which exploits the synergy of deterministic and stochastic optimization methods. The new approach has been tested on simulated data and applied to the phasing of transmission electron microscopy coherent electron diffraction data of a $\text{SrTiO}_\text{3}$ sample. We have been able to quantitatively retrieve the projected atomic potential, and also image the oxygen columns, which are not directly visible in the relevant high-resolution transmission electron microscopy images. Our approach proves to be a new powerful tool for the study of matter at atomic resolution and opens new perspectives in those applications in which effective phase retrieval is necessary.
title Facing the phase problem in Coherent Diffractive Imaging via Memetic Algorithms
topic Computational Physics
Materials Science
Optimization and Control
url https://arxiv.org/abs/1701.07685