X. Wei
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Chapter 1 is an introductory chapter which gives an overview of CDI techniques. The goal is to provide the necessary knowledge so that readers with different background can easily understand the following chapters. This chapter contains three parts. For the first part we introduce the problem statement of CDI, the approximations that are commonly used in CDI, i.e. the projection approximation, the Fraunhofer approximation, and the required conditions of these approximations. This part also includes the introduction about the discrete Fourier transform, the chirp-Z transform, the issue of sampling and the coherence requirements. The second part of this chapter gives a brief introduction about iterative and non-iterative phase retrieval methods in CDI. For the final part of this chapter, we discuss the fundamental of ptychography which is the main topic of this thesis. We first derive an iterative ptychographic algorithm based on the steepest descent method, then explain the extended field-of-view and the ambiguities in ptychography. Some of the recent developments of ptychography are included in this part as well.
For performing phase retrieval in the EUV regime more efficiently, developing polychromatic ptychography is desirable. As an alternative to the existing ptychographic information multiplexing method, we present in Chapter 2 an another scheme where all monochromatic exit waves are expressed in terms of the amplitude of the transmission function and the thickness function of the object. Our proposed algorithm is a gradient based method and its validity is studied numerically. In addition, the sampling issue which appears in the polychromatic ptychography scheme and its influence to the reconstruction quality are discussed.
In Chapter 3 we investigate the performance of ptychography with noisy data by analyzing the Cram\'{e}r Rao Lower Bound (CRLB). The lower bound of ptychography is derived and numerically computed for both top-hat plane wave and structured illumination. The influence of Poisson noise on the ptychography reconstruction is discussed. The computation result shows that, if the estimator is unbiased, the minimum variance for Poisson noise is mostly determined by the illumination power and the transmission function of the object. Monte Carlo analysis is conducted to validate our calculation results for different photon flux numbers. Furthermore, the performance of the maximum likelihood method and the approach of amplitude-based cost function minimization is studied in the Monte Carlo analysis.
In Chapter 4 we present a parameter retrieval method which combines ptychography and additional prior knowledge about the object. The proposed method is applied to two applications: (1) parameter retrieval of small particles from Fourier ptychographic dark field measurements; (2) parameter retrieval of a rectangular structure with real-space ptychography. The influence of Poisson noise is discussed in the second part of the chapter. The CRLB in both applications is computed and Monte Carlo analysis is used to verify the calculated lower bound. With the computation results we report the lower bound for various noise levels and the correlation of particles in application 1. For application 2 the correlation of parameters of the rectangular structure is discussed.
The thesis is concluded with Chapter 5 where the main contribution of this thesis is listed. Furthermore, the unfinished work during my PhD and the possible extensions of the topics discussed in this thesis are addressed in this last chapter. ...
Chapter 1 is an introductory chapter which gives an overview of CDI techniques. The goal is to provide the necessary knowledge so that readers with different background can easily understand the following chapters. This chapter contains three parts. For the first part we introduce the problem statement of CDI, the approximations that are commonly used in CDI, i.e. the projection approximation, the Fraunhofer approximation, and the required conditions of these approximations. This part also includes the introduction about the discrete Fourier transform, the chirp-Z transform, the issue of sampling and the coherence requirements. The second part of this chapter gives a brief introduction about iterative and non-iterative phase retrieval methods in CDI. For the final part of this chapter, we discuss the fundamental of ptychography which is the main topic of this thesis. We first derive an iterative ptychographic algorithm based on the steepest descent method, then explain the extended field-of-view and the ambiguities in ptychography. Some of the recent developments of ptychography are included in this part as well.
For performing phase retrieval in the EUV regime more efficiently, developing polychromatic ptychography is desirable. As an alternative to the existing ptychographic information multiplexing method, we present in Chapter 2 an another scheme where all monochromatic exit waves are expressed in terms of the amplitude of the transmission function and the thickness function of the object. Our proposed algorithm is a gradient based method and its validity is studied numerically. In addition, the sampling issue which appears in the polychromatic ptychography scheme and its influence to the reconstruction quality are discussed.
In Chapter 3 we investigate the performance of ptychography with noisy data by analyzing the Cram\'{e}r Rao Lower Bound (CRLB). The lower bound of ptychography is derived and numerically computed for both top-hat plane wave and structured illumination. The influence of Poisson noise on the ptychography reconstruction is discussed. The computation result shows that, if the estimator is unbiased, the minimum variance for Poisson noise is mostly determined by the illumination power and the transmission function of the object. Monte Carlo analysis is conducted to validate our calculation results for different photon flux numbers. Furthermore, the performance of the maximum likelihood method and the approach of amplitude-based cost function minimization is studied in the Monte Carlo analysis.
In Chapter 4 we present a parameter retrieval method which combines ptychography and additional prior knowledge about the object. The proposed method is applied to two applications: (1) parameter retrieval of small particles from Fourier ptychographic dark field measurements; (2) parameter retrieval of a rectangular structure with real-space ptychography. The influence of Poisson noise is discussed in the second part of the chapter. The CRLB in both applications is computed and Monte Carlo analysis is used to verify the calculated lower bound. With the computation results we report the lower bound for various noise levels and the correlation of particles in application 1. For application 2 the correlation of parameters of the rectangular structure is discussed.
The thesis is concluded with Chapter 5 where the main contribution of this thesis is listed. Furthermore, the unfinished work during my PhD and the possible extensions of the topics discussed in this thesis are addressed in this last chapter.
We present a parameter retrieval method which incorporates prior knowledge about the object into ptychography. The proposed method is applied to two applications: (1) parameter retrieval of small particles from Fourier ptychographic dark field measurements; (2) parameter retrieval of a rectangular structure with real-space ptychography. The influence of Poisson noise is discussed in the second part of the paper. The Cramér Rao Lower Bound in both applications is computed and Monte Carlo analysis is used to verify the calculated lower bound. With the computation results we report the lower bound for various noise levels and analyze the correlation of particles in application 1. For application 2 the correlation of parameters of the rectangular structure is discussed.
We investigate the performance of ptychography with noisy data by analyzing the Cramér-Rao lower bound. The lower bound of ptychography is derived and numerically computed for both top-hat plane wave and structured illumination. The influence of Poisson noise on the ptychography reconstruction is discussed. The computation result shows that, if the estimator is unbiased, the minimum variance for Poisson noise is mostly determined by the illumination power and the transmission function of the object. Monte Carlo analysis is conducted to validate our calculation results for different photon flux numbers. Furthermore, the performance of the maximum-likelihood method and the approach of amplitude-based cost-function minimization is studied in the Monte Carlo analysis.
For performing phase retrieval in the extreme ultraviolet (EUV) regime more efficiently, developing polychromatic ptychography is desirable. As an alternative to the existing ptychographic information multiplexing (PIM) method, we present an another scheme where all monochromatic exit waves are expressed in terms of the amplitude of the transmission function and the thickness function of the object. Our proposed algorithm is a gradient based method and its validity is studied numerically. In addition, the sampling issue which appears in the polychromatic ptychography scheme and its influence to the reconstruction quality are discussed.
The classical problem of subwavelength particle detection on a flat surface is especially challenging when the refractive index of the particle is close to that of the substrate. We demonstrate a method to improve the detection ability several times for such a situation, by enhancing the "forbidden" evanescent waves in the substrate using the principle of super-resolution with evanescent waves amplification. The working mechanism of the system and experimental validation from a design with a thin single dielectric layer is presented. The resulting system is a simple but complete example of evanescent-wave generation, amplification, and the consequent modulation of the far field. This principle can have far reaching impact in the field of particle detection in several applications ranging from contamination control to interferometric scattering microscopy for biological samples.