Adam Hammoumi - Academia.edu (original) (raw)
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Ministero dell'Istruzione, dell'Università e della Ricerca (M.I.U.R.)
Jet Propulsion Laboratory, California Institute of Technology
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Papers by Adam Hammoumi
Digital twins of materials allow to achieve accurate predictions that help creating novel and tai... more Digital twins of materials allow to achieve accurate predictions that help creating novel and tailor-made materials with higher standards. In this paper, we are interested in the characterization of porous media. Our attention is drawn to develop a method to describe accurately the pore network microstructure of porous materials as presented in [7]. This work proposes an efficient algorithm based on the distance transform method [12] which is a widely used method in image processing. The followed approach suggests that a distance transform map, obtained from a microstructure image, passes through different steps. Starting from local maxima extraction and filtering operation, to end up with another distance transform with source propagation. We illustrate our algorithm with the well-known Pore Network Model of the literature [13], which supposes that the pore structure is either a network of connected cylinders or cylinders and spheres. Our approach is also applied on multi-scale Boo...
Most recent methods of image augmentation and prediction are building upon the deep learning para... more Most recent methods of image augmentation and prediction are building upon the deep learning paradigm. A careful preparation of the image dataset and the choice of a suitable network architecture are crucial steps to assess the desired image features and, thence, achieve accurate predictions. We first propose to help the learning process by adding structural information with specific distance transform to the input image data. To handle cases with limited number of training samples (as 12 training and 2 validation images), we propose a patch-based procedure with a stratified sampling method. We illustrate our approaches on image dataset generated by an FFT-based ho-mogeneization technique for heterogeneous media physical properties. The obtained results are evaluated using SSIM, UIQ and PSNR metrics. The proposed techniques demonstrate that the established framework is a reliable estimation method that could be used for a wide range of applications.
Physical Review A
Time-dependent Lindblad master equations have important applications in areas ranging from quantu... more Time-dependent Lindblad master equations have important applications in areas ranging from quantum thermodynamics to dissipative quantum computing. In this paper we outline a general method for writing down exact solutions of time-dependent Lindblad equations whose superoperators form closed algebras. We focus on the particular case of a single qubit and study the exact solution generated by both coherent and incoherent mechanisms. We also show that if the time-dependence is periodic, the problem may be recast in terms of Floquet theory. As an application, we give an exact solution for a two-levels quantum heat engine operating in a finite-time.
Digital twins of materials allow to achieve accurate predictions that help creating novel and tai... more Digital twins of materials allow to achieve accurate predictions that help creating novel and tailor-made materials with higher standards. In this paper, we are interested in the characterization of porous media. Our attention is drawn to develop a method to describe accurately the pore network microstructure of porous materials as presented in [7]. This work proposes an efficient algorithm based on the distance transform method [12] which is a widely used method in image processing. The followed approach suggests that a distance transform map, obtained from a microstructure image, passes through different steps. Starting from local maxima extraction and filtering operation, to end up with another distance transform with source propagation. We illustrate our algorithm with the well-known Pore Network Model of the literature [13], which supposes that the pore structure is either a network of connected cylinders or cylinders and spheres. Our approach is also applied on multi-scale Boo...
Most recent methods of image augmentation and prediction are building upon the deep learning para... more Most recent methods of image augmentation and prediction are building upon the deep learning paradigm. A careful preparation of the image dataset and the choice of a suitable network architecture are crucial steps to assess the desired image features and, thence, achieve accurate predictions. We first propose to help the learning process by adding structural information with specific distance transform to the input image data. To handle cases with limited number of training samples (as 12 training and 2 validation images), we propose a patch-based procedure with a stratified sampling method. We illustrate our approaches on image dataset generated by an FFT-based ho-mogeneization technique for heterogeneous media physical properties. The obtained results are evaluated using SSIM, UIQ and PSNR metrics. The proposed techniques demonstrate that the established framework is a reliable estimation method that could be used for a wide range of applications.
Physical Review A
Time-dependent Lindblad master equations have important applications in areas ranging from quantu... more Time-dependent Lindblad master equations have important applications in areas ranging from quantum thermodynamics to dissipative quantum computing. In this paper we outline a general method for writing down exact solutions of time-dependent Lindblad equations whose superoperators form closed algebras. We focus on the particular case of a single qubit and study the exact solution generated by both coherent and incoherent mechanisms. We also show that if the time-dependence is periodic, the problem may be recast in terms of Floquet theory. As an application, we give an exact solution for a two-levels quantum heat engine operating in a finite-time.