High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs

Ptychography is an emerging imaging technique that is able to provide wavelength-limited spatial resolution from specimen with extended lateral dimensions. As a scanning microscopy method, a typical two-dimensional image requires a number of data frames. As a diffraction-based imaging technique, the real-space image has to be recovered through iterative reconstruction algorithms. Due to these two inherent aspects, a ptychographic reconstruction is generally a computation-intensive and time-consuming process, which limits the throughput of this method. We report an accelerated version of the multi-mode difference map algorithm for ptychography reconstruction using multiple distributed GPUs. This approach leverages available scientific computing packages in Python, including mpi4py and PyCUDA, with the core computation functions implemented in CUDA C. We find that interestingly even with MPI collective communications, the weak scaling in the number of GPU nodes can still remain nearly constant. Most importantly, for realistic diffraction measurements, we observe a speedup ranging from a factor of $10$ to $10^3$ depending on the data size, which reduces the reconstruction time remarkably from hours to typically about 1 minute and is thus critical for real-time data processing and visualization.Comment: work presented in NYSDS 201

Coordinate-based Neural Network for Fourier Phase Retrieval

Fourier phase retrieval is essential for high-definition imaging of nanoscale structures across diverse fields, notably coherent diffraction imaging. This study presents the Single impliCit neurAl Network (SCAN), a tool built upon coordinate neural networks meticulously designed for enhanced phase retrieval performance. Remedying the drawbacks of conventional iterative methods which are easiliy trapped into local minimum solutions and sensitive to noise, SCAN adeptly connects object coordinates to their amplitude and phase within a unified network in an unsupervised manner. While many existing methods primarily use Fourier magnitude in their loss function, our approach incorporates both the predicted magnitude and phase, enhancing retrieval accuracy. Comprehensive tests validate SCAN's superiority over traditional and other deep learning models regarding accuracy and noise robustness. We also demonstrate that SCAN excels in the ptychography setting

A Metal-Ion-Incorporated Mussel-Inspired Poly(Vinyl Alcohol)-Based Polymer Coating Offers Improved Antibacterial Activity and Cellular Mechanoresponse Manipulation

Cobalt (CoII) ions have been an attractive candidate for the biomedical modification of orthopedic implants for decades. However, limited research has been performed into how immobilized CoII ions affect the physical properties of implant devices and how these changes regulate cellular behavior. In this study we modified biocompatible poly(vinyl alcohol) with terpyridine and catechol groups (PVA-TP-CA) to create a stable surface coating in which bioactive metal ions could be anchored, endowing the coating with improved broad-spectrum antibacterial activity against Escherichia coli and Staphylococcus aureus, as well as enhanced surface stiffness and cellular mechanoresponse manipulation. Strengthened by the addition of these metal ions, the coating elicited enhanced mechanosensing from adjacent cells, facilitating cell adhesion, spreading, proliferation, and osteogenic differentiation on the surface coating. This dual-functional PVA-TP-CA/Co surface coating offers a promising approach for improving clinical implantation outcomes

Comments on Noncommutative Open String Theory: V-duality and Holography

In this paper we study the interplay of electric and magnetic backgrounds in determining the decoupling limit of coincident D-branes towards a noncommutative Yang-Mills (NCYM) or open string (NCOS) theory. No decoupling limit has been found for NCYM with space-time noncommutativity. It is suggested that there is a new duality, which we call V-duality, which acts on NCOS with both space-space and space-time noncommutativity, resulting from decoupling in Lorentz-boost related backgrounds. We also show that the holographic correspondence, previously suggested by Li and Wu, between NCYM and its supergravity dual can be generalized to NCOS as well.Comment: 23 pages, RevTex, typos corrected,PRD final versio

Note on Generalized Janus Configurations

We study several aspects of generalized Janus configuration, which includes a theta term. We investigate the vacuum structure of the theory and find that unlike the Janus configuration without theta term there is no nontrivial vacuum. We also discuss BPS soliton configuration both by supersymmetry analysis and from energy functional. The half BPS configurations could be realized by introducing transverse (p,q)-strings in original brane configuration corresponding to generalized Janus configuration. It turns out the BPS soliton could be taken as modified dyon. We discuss the solution of half BPS equations for the sharp interface case. Moreover we construct less supersymmetric Janus configuration with theta term.Comment: 27 pages; References adde

Moyal Representation of the String Field Star Product in the Presence of a B-background

In this paper we show that in the presence of an anti-symmetric tensor $B$-background, Witten's star algebra for open string fields persists to possess the structure of a direct product of commuting Moyal pairs. The interplay between the noncommutativity due to three-string overlap and that due to the $B$-background is our main concern. In each pair of noncommutative directions parallel to the $B$-background, the Moyal pairs mix string modes in the two directions and are labeled, in addition to a continuous parameter, by {\it two} discrete values as well. However, the Moyal parameters are $B$-dependent only for discrete pairs. We have also demonstrated the large-$B$ contraction of the star algebra, with one of the discrete Moyal pairs dropping out while the other giving rise to the center-of-mass noncommutative function algebra.Comment: minor notation chang

Characterization of 3D Interconnected Microstructural Network in Mixed Ionic and Electronic Conducting Ceramic Composites

The microstructure and connectivity of the ionic and electronic conductive phases in composite ceramic membranes are directly related to device performance. Transmission electron microscopy (TEM) including chemical mapping combined with X-ray nanotomography (XNT) have been used to characterize the composition and 3-D microstructure of a MIEC composite model system consisting of a Ce0.8Gd0.2O2 (GDC) oxygen ion conductive phase and a CoFe2O4 (CFO) electronic conductive phase. The microstructural data is discussed, including the composition and distribution of an emergent phase which takes the form of isolated and distinct regions. Performance implications are considered with regards to the design of new material systems which evolve under non-equilibrium operating conditions

Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure