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Chiral magnets have garnered significant interest due to the emergence of unique phenomena prohibited in inversion-symmetric magnets. While the equilibrium characteristics of chiral magnets have been extensively explored through the Dzyaloshinskii-Moriya interaction (DMI), non-equilibrium properties like magnetic damping have received comparatively less attention. We present the inaugural direct observation of chiral damping through Brillouin light scattering (BLS) spectroscopy. Employing BLS spectrum analysis, we independently deduce the Dzyaloshinskii-Moriya interaction (DMI) and chiral damping, extracting them from the frequency shift and linewidth of the spectrum peak, respectively. The resulting linewidths exhibit clear odd symmetry with respect to the magnon wave vector, unambiguously confirming the presence of chiral damping. Our study introduces a novel methodology for quantifying chiral damping, with potential ramifications on diverse nonequilibrium phenomena within chiral magnets.

Deep learning models excel in various computer vision tasks but are susceptible to adversarial examples-subtle perturbations in input data that lead to incorrect predictions. This vulnerability poses significant risks in safety-critical applications such as autonomous vehicles, security surveillance, and aircraft health monitoring. While numerous surveys focus on adversarial attacks in image classification, the literature on such attacks in object detection is limited. This paper offers a comprehensive taxonomy of adversarial attacks specific to object detection, reviews existing adversarial robustness evaluation metrics, and systematically assesses open-source attack methods and model robustness. Key observations are provided to enhance the understanding of attack effectiveness and corresponding countermeasures. Additionally, we identify crucial research challenges to guide future efforts in securing automated object detection systems., Comment: 14 pages

Orbital degrees of freedom play an important role for understanding the emergence of unconventional quantum phases. Ultracold atomic gases in optical lattices provide a wonderful platform to simulate orbital physics. In this work, we consider spinless fermionic atoms loaded into $p$-orbital bands of a two-dimensional frustrated triangular lattice. The system can be described by an extended Fermi-Hubbard model, which is numerically solved by using the orbital version of real-space dynamical mean-field theory. Low-temperature phase diagrams are obtained, which contain stripe-, ferro- and para-orbital ordered quantum phases, due to the interplay of anisotropic hoppings and geometrical frustration. In order to understand the underlying mechanics of competing orbital orders, we derive an effective orbital-exchange model, which yields consistent explanation with our main numerical results., Comment: 9 pages, 7 figures

We extract a precise internal description of the sequential commutation equivalence relation introduced in [KEP23] for tracial von Neumann algebras. As an application we prove that if a tracial von Neumann algebra $N$ is generated by unitaries $\{u_i\}_{i\in \mathbb{N}}$ such that $u_i\sim u_j$ (i.e, there exists a finite set of Haar unitaries $\{w_i\}_{i=1}^{n}$ in $N^\mathcal{U}$ such that $[u_i, w_1]= [w_k, w_{k+1}]=[w_n,u_j]=0$ for all $1\leq k< n$) then $N$ is singly generated. This generalizes and recovers several known single generation phenomena for II$_1$ factors in the literature with a unified proof., Comment: Comments welcome! 10 pages

Despite the significant success achieved by deep learning methods in medical image segmentation, researchers still struggle in the computer-aided diagnosis of abdominal lymph nodes due to the complex abdominal environment, small and indistinguishable lesions, and limited annotated data. To address these problems, we present a pipeline that integrates the conditional diffusion model for lymph node generation and the nnU-Net model for lymph node segmentation to improve the segmentation performance of abdominal lymph nodes through synthesizing a diversity of realistic abdominal lymph node data. We propose LN-DDPM, a conditional denoising diffusion probabilistic model (DDPM) for lymph node (LN) generation. LN-DDPM utilizes lymph node masks and anatomical structure masks as model conditions. These conditions work in two conditioning mechanisms: global structure conditioning and local detail conditioning, to distinguish between lymph nodes and their surroundings and better capture lymph node characteristics. The obtained paired abdominal lymph node images and masks are used for the downstream segmentation task. Experimental results on the abdominal lymph node datasets demonstrate that LN-DDPM outperforms other generative methods in the abdominal lymph node image synthesis and better assists the downstream abdominal lymph node segmentation task.

We study conjugacy orbits of certain types of subalgebras in tracial von Neumann algebras. For any separable II$_1$ factor $N_0$ we construct a highly indecomposable non Gamma II$_1$ factor $N$ such that $N_0 \subset N$ and moreover every von Neumann subalgebra of $N$ with Haagerup's property admits a unique embedding up to unitary conjugation. Such a factor necessarily has to be non separable, but we show that it can be taken of density character $2^{\aleph_0}$. On the other hand we are able to construct for any separable II$_1$ factor $M_0$, a separable II$_1$ factor $M$ containing $M_0$ such that every property (T) subfactor admits a unique embedding into $M$ up to uniformly approximate unitary equivalence; i.e., any pair of embeddings can be conjugated up to a small uniform $2$-norm perturbation., Comment: Comments welcome! 21 pages

We introduce the first examples of groups $G$ with infinite center which in a natural sense are completely recognizable from their von Neumann algebras, $\mathcal{L}(G)$. Specifically, assume that $G=A\times W$, where $A$ is an infinite abelian group and $W$ is an ICC wreath-like product group [CIOS22a; AMCOS23] with property (T) and trivial abelianization. Then whenever $H$ is an \emph{arbitrary} group such that $\mathcal{L}(G)$ is $\ast$-isomorphic to $\mathcal L(H)$, via an \emph{arbitrary} $\ast$-isomorphism preserving the canonical traces, it must be the case that $H= B \times H_0$ where $B$ is infinite abelian and $H_0$ is isomorphic to $W$. Moreover, we completely describe the $\ast$-isomorphism between $\mathcal L(G)$ and $\mathcal L(H)$. This yields new applications to the classification of group C$^*$-algebras, including examples of non-amenable groups which are recoverable from their reduced C$^*$-algebras but not from their von Neumann algebras., Comment: After the first version was posted, Stefaan Vaes pointed out one of the equivalences in Theorem 4.5 does not hold as stated. In the current version we fixed this along with the proofs where it was used. This does not affect the main result or the substance of the arguments used. The only difference is that now Corollary D is slightly more restrictive. We also corrected a number of typos

We prove that if a separable II$_1$ factor $M$ is existentially closed, then every $M$-bimodule is weakly contained in the trivial $M$-bimodule, $\text{L}^2(M)$, and, equivalently, every normal completely positive map on $M$ is a pointwise 2-norm limit of maps of the form $x\mapsto\sum_{i=1}^ka_i^*xa_i$, for some $k\in\mathbb N$ and $(a_i)_{i=1}^k\subset M$. This provides the first examples of non-hyperfinite separable II$_1$ factors $M$ with the latter properties. We also obtain new characterizations of $M$-bimodules which are weakly contained in the trivial or coarse $M$-bimodule and of relative amenability inside $M$. Additionally, we give an operator algebraic presentation of the proof of the existence of existentially closed II$_1$ factors. While existentially closed II$_1$ factors have property Gamma, by adapting this proof we construct non-Gamma II$_1$ factors which are existentially closed in every weakly coarse extension.

Orbital degree of freedom plays an important role for understanding quantum many-body phenomena. In this work, we study an experimentally related setup with ultracold bosons loaded into hybridized bands of two-dimensional hexagonal optical lattices. We find that the system supports various quantum many-body phases at zero temperature, including chiral superfluid and chiral Mott insulator by breaking time-reversal symmetry, and time-reversal-even insulating phase, based on dynamical mean-field theory. To explain the time-reversal-even phase, a fourth-order orbital-exchange model is derived to explain the underlying mechanics. To relate to experimental situations, we make band-structure calculations to obtain the Hubbard parameters, and show that these orbital ordering phases persist also in the presence of next-nearest-neighbor hopping., Comment: 9 pages, 5 figures

Topological spin textures such as magnetic skyrmions hold considerable promise as robust, nanometre-scale, mobile bits for sustainable computing. A longstanding roadblock to unleashing their potential is the absence of a device enabling deterministic electrical readout of individual spin textures. Here we present the wafer-scale realization of a nanoscale chiral magnetic tunnel junction (MTJ) hosting a single, ambient skyrmion. Using a suite of electrical and multi-modal imaging techniques, we show that the MTJ nucleates skyrmions of fixed polarity, whose large readout signal - 20-70% relative to uniform states - corresponds directly to skyrmion size. Further, the MTJ exploits complementary mechanisms to stabilize distinctly sized skyrmions at zero field, thereby realizing three nonvolatile electrical states. Crucially, it can write and delete skyrmions using current densities 1,000 times lower than state-of-the-art. These results provide a platform to incorporate readout and manipulation of skyrmionic bits across myriad device architectures, and a springboard to harness chiral spin textures for multi-bit memory and unconventional computing., Comment: 8 pages, 5 figures

Magnetic skyrmions have emerged as promising elements for encoding information towards biomimetic computing applications due to their pseudoparticle nature and efficient coupling to spin currents. A key hindrance for skyrmionic devices is their instability against elongation at zero magnetic field (ZF). Prevailing materials approaches focussed on tailoring skyrmion energetics have found ZF configurations to be highly sensitive, which imposes significant growth constraints and limits their device scalability. Here we propose that designer ZF skyrmion configurations can be robustly stabilized within chiral multilayer stacks by exploiting a duet of interlayer exchange couplings (IECs). Microscopic imaging experiments show that varying the two IECs enables the coarse and fine-tuning of ZF skyrmion stability and density. Micromagnetic simulations reveal that the duo-IEC approach is distinguished by its influence on the kinetics of skyrmion nucleation, in addition to the ability to tailor energetics, resulting in a substantially expanded parameter space, and enhanced stability for individual ZF skyrmions. Our work underscores the importance of IEC as a means of stabilizing and controlling ZF skyrmions, paving the way to scalable skyrmion-based devices.

Fine-grained action recognition is a challenging task in computer vision. As fine-grained datasets have small inter-class variations in spatial and temporal space, fine-grained action recognition model requires good temporal reasoning and discrimination of attribute action semantics. Leveraging on CNN's ability in capturing high level spatial-temporal feature representations and Transformer's modeling efficiency in capturing latent semantics and global dependencies, we investigate two frameworks that combine CNN vision backbone and Transformer Encoder to enhance fine-grained action recognition: 1) a vision-based encoder to learn latent temporal semantics, and 2) a multi-modal video-text cross encoder to exploit additional text input and learn cross association between visual and text semantics. Our experimental results show that both our Transformer encoder frameworks effectively learn latent temporal semantics and cross-modality association, with improved recognition performance over CNN vision model. We achieve new state-of-the-art performance on the FineGym benchmark dataset for both proposed architectures., Comment: The Ninth Workshop on Fine-Grained Visual Categorization (FGVC9) @ CVPR2022

More infectious virus variants can arise from rapid mutations in their proteins, creating new infection waves. These variants can evade one's immune system and infect vaccinated individuals, lowering vaccine efficacy. Hence, to improve vaccine design, this project proposes Optimus PPIme - a deep learning approach to predict future, more infectious variants from an existing virus (exemplified by SARS-CoV-2). The approach comprises an algorithm which acts as a "virus" attacking a host cell. To increase infectivity, the "virus" mutates to bind better to the host's receptor. 2 algorithms were attempted - greedy search and beam search. The strength of this variant-host binding was then assessed by a transformer network we developed, with a high accuracy of 90%. With both components, beam search eventually proposed more infectious variants. Therefore, this approach can potentially enable researchers to develop vaccines that provide protection against future infectious variants before they emerge, pre-empting outbreaks and saving lives.

When deploying a robot to a new task, one often has to train it to detect novel objects, which is time-consuming and labor-intensive. We present TAILOR -- a method and system for object registration with active and incremental learning. When instructed by a human teacher to register an object, TAILOR is able to automatically select viewpoints to capture informative images by actively exploring viewpoints, and employs a fast incremental learning algorithm to learn new objects without potential forgetting of previously learned objects. We demonstrate the effectiveness of our method with a KUKA robot to learn novel objects used in a real-world gearbox assembly task through natural interactions., Comment: 5 pages, 4 figures, AAAI conference

Magnetic skyrmions form in chiral multilayers from the shrinking or fission of elongated stripe textures. Here we report an experimental and theoretical study of the temperature dependence of this stripe-to-skyrmion transition in Co/Pt-based multilayers. Field-reversal magnetometry and Lorentz microscopy experiments over 100 - 350 K establish the increased efficacy of stripe-to-skyrmion fission at higher temperatures - driven primarily by the thermal evolution of key magnetic interactions - thereby enhancing skyrmion density. Atomistic calculations elucidate that the energy barrier to fission governs the thermodynamics of the skyrmion formation. Our results establish a mechanistic picture of the stripe-to-skyrmion transition and advance the use of thermal knobs for efficient skyrmion generation., Comment: 11 pages, 11 figures

Magnetic skyrmions are topologically wound nanoscale textures of spins whose ambient stability and electrical manipulation in multilayer films have led to an explosion of research activities. While past efforts focused predominantly on isolated skyrmions, recently ensembles of chiral spin textures, consisting of skyrmions and magnetic stripes, were shown to possess rich interactions with potential for device applications. However, several fundamental aspects of chiral spin texture phenomenology remain to be elucidated, including their domain wall structure, thermodynamic stability, and morphological transitions. Here we unveil the evolution of these textural characteristics on a tunable multilayer platform - wherein chiral interactions governing spin texture energetics can be widely varied - using a combination of full-field electron and soft X-ray microscopies with numerical simulations. With increasing chiral interactions, we demonstrate the emergence of N\'eel helicity, followed by a marked reduction in domain compressibility, and finally a transformation in the skyrmion formation mechanism. Together with an analytical model, these experiments establish a comprehensive microscopic framework for investigating and tailoring chiral spin texture character in multilayer films.

For II$_1$ factors, we show that property (T) is equivalent to weak spectral gap in any inclusion into a larger tracial von Neumann algebra. We also show that not having non-zero almost central vectors in weakly mixing bimodules characterizes property (T) for II$_1$ factors, which allows us to obtain a stronger characterization of property (T) where only weak spectral gap in any irreducible inclusion is required.

Fine-grained human action recognition is a core research topic in computer vision. Inspired by the recently proposed hierarchy representation of fine-grained actions in FineGym and SlowFast network for action recognition, we propose a novel multi-task network which exploits the FineGym hierarchy representation to achieve effective joint learning and prediction for fine-grained human action recognition. The multi-task network consists of three pathways of SlowOnly networks with gradually increased frame rates for events, sets and elements of fine-grained actions, followed by our proposed integration layers for joint learning and prediction. It is a two-stage approach, where it first learns deep feature representation at each hierarchical level, and is followed by feature encoding and fusion for multi-task learning. Our empirical results on the FineGym dataset achieve a new state-of-the-art performance, with 91.80% Top-1 accuracy and 88.46% mean accuracy for element actions, which are 3.40% and 7.26% higher than the previous best results., Comment: Camera ready for IEEE ICIP 2021

The symmetric (Heisenberg) exchange interaction is fundamental to magnetism and assumes critical importance in designing magnetic materials for novel emergent phenomena and device applications. However, quantifying exchange is extremely challenging for ultrathin ($\sim$ 1 nm) magnetic films, as techniques and approximations reliably used for bulk materials are largely inapplicable in the two-dimensional (2D) limit. Here we present and contrast the measurement of exchange stiffness, $A$, by several methods on a series of five Co/Pt-based ultrathin ($1-2$ nm) films. We compare results from (a) spin-wave spectroscopy by Brillouin light scattering (BLS), (b) three analytical models describing the temperature dependence of magnetization obtained by magnetometry, (c) microscopic domain periodicity measurements and simulations, and (d) ab initio density functional theory (DFT) calculations. While different methods present some qualitatively consistent trends across samples, we note, for any given sample, considerable differences (up to $5\times$) in the absolute values of $A$ across the techniques, consistent with discrepancies of $A$ reported in literature for nominally similar samples. We analyze possible sources of the discrepancies across various methods, notably including their relationship to the spin-wave dispersion, and the wave-vector ranges probed. We compare the strengths and limitations of the techniques, and outline directions for their future use in characterizing exchange interactions in ultrathin films., Comment: 14 pages, 9 figures

Orbital degree of freedom plays an important role in understanding exotic phenomena of strongly correlated materials. We study strongly correlated ultracold bosonic gases coupled to a high-finesse cavity, pumped by a blue-detuned laser in the transverse direction. Based on an extended Bose-Hubbard model with parameters adapted to recent experiments, we find that by tuning the reflection of pump laser, atoms can be selectively transferred to the odd-parity $p$-orbital, or to even-parity $d$-orbital band of a two-dimensional square lattice, accompanied with cavity-photon excitations. By interacting with cavity field, atoms self-organize to form stable higher-orbital superfluid and Mott-insulating phases with orbital-density waves, as a result of cavity induced orbital-flip processes. Our study opens the route to manipulate orbital degrees of freedom in strongly correlated quantum gases via coupling to optical cavities., Comment: 6 pages, 4 figures, with supplementary materials

There has been an emerging paradigm shift from the era of "internet AI" to "embodied AI", where AI algorithms and agents no longer learn from datasets of images, videos or text curated primarily from the internet. Instead, they learn through interactions with their environments from an egocentric perception similar to humans. Consequently, there has been substantial growth in the demand for embodied AI simulators to support various embodied AI research tasks. This growing interest in embodied AI is beneficial to the greater pursuit of Artificial General Intelligence (AGI), but there has not been a contemporary and comprehensive survey of this field. This paper aims to provide an encyclopedic survey for the field of embodied AI, from its simulators to its research. By evaluating nine current embodied AI simulators with our proposed seven features, this paper aims to understand the simulators in their provision for use in embodied AI research and their limitations. Lastly, this paper surveys the three main research tasks in embodied AI -- visual exploration, visual navigation and embodied question answering (QA), covering the state-of-the-art approaches, evaluation metrics and datasets. Finally, with the new insights revealed through surveying the field, the paper will provide suggestions for simulator-for-task selections and recommendations for the future directions of the field., Comment: This work has been accepted by IEEE Transactions on Emerging Topics in Computational Intelligence

The problem of task planning for artificial agents remains largely unsolved. While there has been increasing interest in data-driven approaches for the study of task planning for artificial agents, a significant remaining bottleneck is the dearth of large-scale comprehensive task-based datasets. In this paper, we present ActioNet, an interactive end-to-end platform for data collection and augmentation of task-based dataset in 3D environment. Using ActioNet, we collected a large-scale comprehensive task-based dataset, comprising over 3000 hierarchical task structures and videos. Using the hierarchical task structures, the videos are further augmented across 50 different scenes to give over 150,000 video. To our knowledge, ActioNet is the first interactive end-to-end platform for such task-based dataset generation and the accompanying dataset is the largest task-based dataset of such comprehensive nature. The ActioNet platform and dataset will be made available to facilitate research in hierarchical task planning., Comment: https://github.com/SamsonYuBaiJian/actionet

Motivation: High resolution 2D whole slide imaging provides rich information about the tissue structure. This information can be a lot richer if these 2D images can be stacked into a 3D tissue volume. A 3D analysis, however, requires accurate reconstruction of the tissue volume from the 2D image stack. This task is not trivial due to the distortions that each individual tissue slice experiences while cutting and mounting the tissue on the glass slide. Performing registration for the whole tissue slices may be adversely affected by the deformed tissue regions. Consequently, regional registration is found to be more effective. In this paper, we propose an accurate and robust regional registration algorithm for whole slide images which incrementally focuses registration on the area around the region of interest. Results: Using mean similarity index as the metric, the proposed algorithm (mean $\pm$ std: $0.84 \pm 0.11$) followed by a fine registration algorithm ($0.86 \pm 0.08$) outperformed the state-of-the-art linear whole tissue registration algorithm ($0.74 \pm 0.19$) and the regional version of this algorithm ($0.81 \pm 0.15$). The proposed algorithm also outperforms the state-of-the-art nonlinear registration algorithm (original : $0.82 \pm 0.12$, regional : $0.77 \pm 0.22$) for whole slide images and a recently proposed patch-based registration algorithm (patch size 256: $0.79 \pm 0.16$ , patch size 512: $0.77 \pm 0.16$) for medical images. Availability: The C++ implementation code is available online at the github repository: https://github.com/MahsaPaknezhad/WSIRegistration

We theoretically investigate zero-temperature magnetic ordering of mixtures of spin-1 (alkali atoms) and spin-0 (alkaline-earth atoms) bosons in a three-dimensional optical lattice. With the single-mode approximation for the spin-1 bosons, we obtain an effective Bose-Hubbard model for describing the heteronuclear mixtures in optical lattices. By controlling the interspecies interactions between alkali and alkaline-earth atoms, we map out complete phase diagrams of the system with both positive and negative spin-dependent interactions for spin-1 atoms, based on bosonic dynamical mean-field theory. We find that the spin-1 components feature ferromagnetic and nematic insulating phases, in addition to the superfluid, depending on spin-dependent interactions. Take the spin-1 alkali bosons as spin $\uparrow$, and spin-0 alkaline-earth bosons as spin $\downarrow$, we observe that the system favors ferromagnetic insulator at filling $n=1$, and unorder insulator at $n=2$. Interestingly, we observe a two-step Mott-insulating-superfluid phase transition, as a result of mass imbalance between alkali and alkaline-earth atoms., Comment: 9 pages, and 5 figures, Accepted by Phys. Rev. A

Lijiang 2.4-meter Telescope(LJT), the largest common-purpose optical telescope in China, has been applied to the world-wide astronomers since 2008. It is located at Gaomeigu site, Lijiang Observatory(LJO), the southwest of China. The site has very good observational conditions. Since 10-year operation, several instruments have been equipped on the LJT. Astronomers can perform both photometric and spectral observations. The main scientific goals of LJT include photometric and spectral evolution of supernova, reverberation mapping of active galactic nucleus, physical properties of binary star and near-earth object(comet and asteroid), identification of exoplanet, and all kinds of transients. Until now, the masses of 41 high accretion rate black holes have been measured, and more than 168 supernova have been identified by the LJT. More than 190 papers related to the LJT have been published. In this paper, the general observation condition of the Gaomeigu site is introduced at first. Then, the LJT structure is described in detail, including the optical, mechanical, motion and control system. The specification of all the instruments, and some detailed parameters of the YFOSC is also presented. Finally, some important scientific results and future expectations are summarized., Comment: 20 pages, 14 figures, accepted by Research in Astronomy and Astrophysics(RAA)

The use in education of small groups of two to four members receives substantial support from both theory and research (e.g., (Deutsch, 1949, 1962; Gillies, 2007; Johnson & Johnson, 2006; Lewin, 1935; Sharan, 1999; Slavin, 1995; Vygotsky, 1978, Webb, et al., 2009). This theory and research suggests that people learn more and gain affective benefits when they spend some time collaborating with others. However, in the author's experience, workshop facilitators and other educators are often reluctant to ask participants to form small groups and to participate in small group activities, especially when participants have not met each other or for whatever reason may be uncomfortable interacting with one another. Thus, workshop facilitators and other educators may hesitate to use small group activities. This paper proposes a wide variety of ideas that educators can try to increase people's willingness to form groups and participate in group activities. These ideas are divided into three groups: before the event, at the beginning of the event and at the end of the event and beyond. [Workshop presented at the conference of the International Association for the Study of Cooperation in Education in partnership with the University College Lillebaelt, Odense, Denmark, Oct 2015.]

We have synthesized high-quality, micrometer-sized, single-crystal GeSe nanosheets using vapor transport and deposition techniques. Photoresponse is investigated based on mechanically exfoliated GeSe nanosheet combined with Au contacts under a global laser irradiation scheme. The nonlinearship, asymmetric, and unsaturated characteristics of the I-V curves reveal that two uneven back-to-back Schottky contacts are formed. First-principles calculations indicate that the occurrence of defects-induced in-gap defective states, which are responsible for the slow decay of the current in the OFF state and for the weak light intensity dependence of photocurrent. The Schottky photodetector exhibits a marked photoresponse to NIR light illumination at a wavelength of 808 nm. The significant photoresponse and good responsitivity suggests its potential applications as photodetectors.

We report here a real-time pulse processing algorithm for superconducting transition-edge sensor (TES) based x-ray microcalorimeters. TES-based. microca1orimeters offer ultra-high energy resolutions, but the small volume of each pixel requires that large arrays of identical microcalorimeter pixe1s be built to achieve sufficient detection efficiency. That in turn requires as much pulse processing as possible must be performed at the front end of readout electronics to avoid transferring large amounts of data to a host computer for post-processing. Therefore, a real-time pulse processing algorithm that not only can be implemented in the readout electronics but also achieve satisfactory energy resolutions is desired. We have developed an algorithm that can be easily implemented. in hardware. We then tested the algorithm offline using several data sets acquired with an 8 x 8 Goddard TES x-ray calorimeter array and 2x16 NIST time-division SQUID multiplexer. We obtained an average energy resolution of close to 3.0 eV at 6 keV for the multiplexed pixels while preserving over 99% of the events in the data sets.

This project discusses the application of parallel computations related with respect to material analyses. Briefly speaking, we analyze some kind of material by elements computations. We call an element a cell here. A cell is divided into a number of subelements called subcells and all subcells in a cell have the identical structure. The detailed structure will be given later in this paper. It is obvious that the problem is "well-structured". SIMD machine would be a better choice. In this paper we try to look into the potentials of SIMD machine in dealing with finite element computation by developing appropriate algorithms on MasPar, a SIMD parallel machine. In section 2, the architecture of MasPar will be discussed. A brief review of the parallel programming language MPL also is given in that section. In section 3, some general parallel algorithms which might be useful to the project will be proposed. And, combining with the algorithms, some features of MPL will be discussed in more detail. In section 4, the computational structure of cell/subcell model will be given. The idea of designing the parallel algorithm for the model will be demonstrated. Finally in section 5, a summary will be given.

A FORTRAN program for calculating the stresses of n cracks embedded in an isotropic plate is presented. Formulas are given for calculating the stresses of one crack, two cracks, and n cracks in an isotropic plate. Then the program code that accomplishes this is provided.