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Photo-Thermoelectric (PTE) response is usually one of the main working mechanisms for photodetectors. However, as another fast and easier way to measure thermoelectric characteristics of materials, it can also reveal important physics such as electric-phonon coupling, electron-electron correlation, etc. Recently, the spin entropy related to magnetic order transition which contributes to thermoelectric power is attracting more and more attention. Here, we demonstrate the PTE response can be reshaped when Ca3Ru2O7 undergoes meta-magnetic phase (MMP) transition driven by both temperature and magnetic field. Firstly, a sign change is observed crossing TS = 48 K and the linear polarization angle dependent PTE current maximizes along a-axis above TS while maximizes along b-axis below TS, which indicates that the antiferromagnetic spin order contributes to such spatial anisotropy. Secondly, in the temperature range of around 40 ~ 50 K, the PTE current is found to be sharply suppressed when external magnetic field is applied in plane along a-axis but is only gradually suppressed when applied field is along b-axis which gives out two critical fields. We attribute such suppression of PTE current under magnetic field to the suppression of the spin entropy in the phase transition between the antiferromagnetic state and the MMP state and the H-T phase diagrams of Ca3Ru2O7 is redrawn accordingly. Compared to previously work which trying to understand the magnetic phase transition in Ca3Ru2O7, such as neutron scattering, specific heat, and other advanced transport measurements, our work provides a more convenient yet efficient method, which may also find applications in other correlated spin materials in general.

2D ferroelectric \{beta}-InSe/graphene heterostructure was fabricated by mechanical exfoliation, and the carrier dynamics crossing the heterostructure interface has been systematically investigated by Raman, photoluminescence and transient absorption measurements. Due to the efficient interfacial photo excited electron transfer and photogating effect from trapped holes, the heterostructure devices demonstrate superior performance with maximum responsivity of 2.12*10e4 A/W, detectivity of 1.73*10e14 Jones and fast response time (241 us) under {\lambda} = 532 nm laser illumination. Furthermore, the photo responses influenced by ferroelectric polarization field are investigated. Our work confirms ferroelectric \{beta}-InSe/graphene heterostructure as an outstanding material platform for sensitive optoelectronic application.

As basic building blocks for next-generation information technologies devices, high-quality p-n junctions based on van der Waals (vdW) materials have attracted widespread interest.Compared to traditional two dimensional (2D) heterojunction diodes, the emerging homojunctions are more attractive owing to their intrinsic advantages, such as continuous band alignments and smaller carrier trapping. Here, utilizing the long-range migration of Cu + ions under in-plane electric field, a novel lateral p-n homojunction was constructed in the 2D layered copper indium thiophosphate (CIPS). The symmetric Au/CIPS/Au devices demonstrate an electric-field-driven resistance switching (RS) accompanying by a rectification behavior without any gate control. Moreover, such rectification behavior can be continuously modulated by poling voltage. We deduce that the reversable rectifying RS behavior is governed by the effective lateral build-in potential and the change of the interfacial barrier during the poling process. Furthermore, the CIPS p-n homojuction is evidenced by the photovoltaic effect, with the spectral response extending up to visible region due to the better photogenerated carrier separation efficiency. Our study provides a facile route to fabricate homojuctions through electric-field-driven ionic migration and paves the way towards the use of this method in other vdW materials.

Interface interactions in 2D vertically stacked heterostructures play an important role in optoe-lectronic applications, photodetectors based on graphene/InSe heterostructures had shown promising performance nowadays. However, nonlinear optical properties studies based on the graphene/InSe heterostructure was insufficient. Here, we fabricated graphene/InSe heterostruc-ture by mechanical exfoliation, and investigated the optically induced charge transfer between graphene/InSe heterostructures by taking photoluminescence and pump-probe measurements. The large built-in electric field at the interface is confirmed by Kelvin probe force microscopy. Furthermore, due to the efficient interfacial carrier transfer driven by built-in electric potential (~ 286 meV) and broadband nonlinear absorption, the application of graphene/InSe heterostruc-ture in mode-locked laser is realized. Our work not only provides a deeper understanding for the dipole orientation related interface interactions on the photoexcited charge transfer of gra-phene/InSe heterostructure, but also enrich the saturable absorber family for ultrafast photon-ics application.

Generalized linear models (GLMs) are a widely utilized family of machine learning models in real-world applications. As data size increases, it is essential to perform efficient distributed training for these models. However, existing systems for distributed training have a high cost for communication and often use large batch sizes to balance computation and communication, which negatively affects convergence. Therefore, we argue for an efficient distributed GLM training system that strives to achieve linear scalability, while keeping batch size reasonably low. As a start, we propose P4SGD, a distributed heterogeneous training system that efficiently trains GLMs through model parallelism between distributed FPGAs and through forward-communication-backward pipeline parallelism within an FPGA. Moreover, we propose a light-weight, latency-centric in-switch aggregation protocol to minimize the latency of the AllReduce operation between distributed FPGAs, powered by a programmable switch. As such, to our knowledge, P4SGD is the first solution that achieves almost linear scalability between distributed accelerators through model parallelism. We implement P4SGD on eight Xilinx U280 FPGAs and a Tofino P4 switch. Our experiments show P4SGD converges up to 6.5X faster than the state-of-the-art GPU counterpar.

In computing, the aim of personalization is to train a model that caters to a specific individual or group of people by optimizing one or more performance metrics and adhering to specific constraints. In this paper, we discuss the need for personalization in affective and personality computing (hereinafter referred to as affective computing). We present a survey of state-of-the-art approaches for personalization in affective computing. Our review spans training techniques and objectives towards the personalization of affective computing models. We group existing approaches into seven categories: (1) Target-specific Models, (2) Group-specific Models, (3) Weighting-based Approaches, (4) Fine-tuning Approaches, (5) Multitask Learning, (6) Generative-based Models, and (7) Feature Augmentation. Additionally, we provide a statistical meta-analysis of the surveyed literature, analyzing the prevalence of different affective computing tasks, interaction modes, interaction contexts, and the level of personalization among the surveyed works. Based on that, we provide a road-map for those who are interested in exploring this direction.

Increasing data center network speed coupled with application requirements for high throughput and low latencies have raised the efficiency bar for network stacks. To reduce substantial kernel overhead in network processing, recent proposals bypass the kernel or implement the stack as user space OS service -- both with performance isolation, security, and resource efficiency trade-offs. We present Tardis, a new network stack architecture that combines the performance and resource efficiency benefits of kernel-bypass and the security and performance enforcement of in-kernel stacks. Tardis runs the OS I/O stack in user-level threads that share both address spaces and kernel threads with applications, avoiding almost all kernel context switch and cross-core communication overheads. To provide sufficient protection, Tardis leverages x86 protection keys (MPK) extension to isolate the I/O stack from application code. And to enforce timely scheduling of network processing and fine-grained performance isolation, Tardis implements lightweight scheduler activations with preemption timers.

Model parallelism has become necessary to train large neural networks. However, finding a suitable model parallel schedule for an arbitrary neural network is a non-trivial task due to the exploding search space. In this work, we present a model parallelism framework TAP that automatically searches for the best data and tensor parallel schedules. Leveraging the key insight that a neural network can be represented as a directed acyclic graph, within which may only exist a limited set of frequent subgraphs, we design a graph pruning algorithm to fold the search space efficiently. TAP runs at sub-linear complexity concerning the neural network size. Experiments show that TAP is $20\times- 160\times$ faster than the state-of-the-art automatic parallelism framework, and the performance of its discovered schedules is competitive with the expert-engineered ones.

The novel weak-value-amplification (WVA) scheme of precision metrology is deeply rooted in the quantum nature of destructive interference between the pre- and post-selection states. And, an alternative version, termed as joint WVA (JWVA), which employs the difference-signal from the post-selection accepted and rejected results, has been found possible to achieve even better sensitivity (two orders of magnitude higher) under some technical limitations (e.g. misalignment errors). In this work, after erasing the quantum coherence, we analyze the difference-signal amplification (DSA) technique, which serves as a classical counterpart of the JWVA, and show that similar amplification effect can be achieved. We obtain a simple expression for the amplified signal, carry out characterization of precision, and point out the optimal working regime. We also discuss how to implement the post-selection of a classical mixed state. The proposed classical DSA technique holds similar technical advantages of the JWVA and may find interesting applications in practice., Comment: 7pages, 5 figures. arXiv admin note: text overlap with arXiv:2207.03668

Choropleth maps are a common visual representation for region-specific tabular data and are used in a number of different venues (newspapers, articles, etc). These maps are human-readable but are often challenging to deal with when trying to extract data for screen readers, analyses, or other related tasks. Recent research into Visual-Question Answering (VQA) has studied question answering on human-generated charts (ChartQA), such as bar, line, and pie charts. However, little work has paid attention to understanding maps; general VQA models, and ChartQA models, suffer when asked to perform this task. To facilitate and encourage research in this area, we present MapQA, a large-scale dataset of ~800K question-answer pairs over ~60K map images. Our task tests various levels of map understanding, from surface questions about map styles to complex questions that require reasoning on the underlying data. We present the unique challenges of MapQA that frustrate most strong baseline algorithms designed for ChartQA and general VQA tasks. We also present a novel algorithm, Visual Multi-Output Data Extraction based QA (V-MODEQA) for MapQA. V-MODEQA extracts the underlying structured data from a map image with a multi-output model and then performs reasoning on the extracted data. Our experimental results show that V-MODEQA has better overall performance and robustness on MapQA than the state-of-the-art ChartQA and VQA algorithms by capturing the unique properties in map question answering.

Mission critical systems deployed in data centers today are facing more sophisticated failures. Byzantine fault tolerant (BFT) protocols are capable of masking these types of failures, but are rarely deployed due to their performance cost and complexity. In this work, we propose a new approach to designing high performance BFT protocols in data centers. By re-examining the ordering responsibility between the network and the BFT protocol, we advocate a new abstraction offered by the data center network infrastructure. Concretely, we design a new authenticated ordered multicast primitive (AOM) that provides transferable authentication and non-equivocation guarantees. Feasibility of the design is demonstrated by two hardware implementations of AOM -- one using HMAC and the other using public key cryptography for authentication -- on new-generation programmable switches. We then co-design a new BFT protocol, Matrix, that leverages the guarantees of AOM to eliminate cross-replica coordination and authentication in the common case. Evaluation results show that Matrix outperforms state-of-the-art protocols on both latency and throughput metrics by a wide margin, demonstrating the benefit of our new network ordering abstraction for BFT systems., Comment: 19 pages, 5 figures, under submission

Titan has a diverse range of materials in its atmosphere and on its surface: the simple organics that reside in various phases (gas, liquid, ice) and the solid complex refractory organics that form Titan's haze layers. These materials all actively participate in various physical processes on Titan, and many material properties are found to be important in shaping these processes. Future in-situ exploration on Titan would likely encounter a range of materials, and a comprehensive database to archive the material properties of all possible material candidates will be needed. Here we summarize several important material properties of the organic liquids, ices, and the refractory hazes on Titan that are available in the literature and/or that we have computed. These properties include thermodynamic properties (phase change points, sublimation and vaporization saturation vapor pressure, and latent heat), physical property (density), and surface properties (liquid surface tensions and solid surface energies). We have developed a new database to provide a repository for these data and make them available to the science community. These data can be used as inputs for various theoretical models to interpret current and future remote sensing and in-situ atmospheric and surface measurements on Titan. The material properties of the simple organics may also be applicable to giant planets and icy bodies in the outer solar system, interstellar medium, protoplanetary disks, and exoplanets., Comment: 64 pages, 6 figures, 20 tables

The Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy (SCALES) is an instrument being designed to perform direct imaging of exoplanets in the mid-infrared (2-5 {\mu}m) with the Adaptive Optics System of W.M. Keck Observatory. To eliminate unwanted thermal infrared radiation, SCALES utilizes both a cold stop for excluding background radiation and a vector vortex coronagraph with Lyot stops for starlight suppression. Optimal geometric masks have been designed. We simulate the propagation of light through the Lyot plane and analyze the on-axis images of stars in the K, L, and M band for the performance of the Lyot stops. Additionally, finalized cold stop and Lyot stop designs are presented along with evaluations on the effects of manufacturing tolerances and tilt in pupil planes caused by off-axis parabolic mirror relays.

SCALES is a high-contrast, infrared coronagraphic imager and integral field spectrograph (IFS) to be deployed behind the W.M. Keck Observatory adaptive optics system. A reflective optical design allows diffraction-limited imaging over a large wavelength range (1.0 - 5.0 microns). A microlens array-based IFS coupled with a lenslet reformatter ("slenslit") allow spectroscopy at both low (R = 35 - 250) and moderate (R = 2000 - 6500) spectral resolutions. The large wavelength range, diffraction-limited performance, high contrast coronagraphy and cryogenic operation present a unique optical design challenge. We present the full SCALES optical design, including performance modeling and analysis and manufacturing., Comment: SPIE Astronomical Telescopes and Instrumentation, 2022

We present the design of SCALES (Slicer Combined with Array of Lenslets for Exoplanet Spectroscopy) a new 2-5 micron coronagraphic integral field spectrograph under construction for Keck Observatory. SCALES enables low-resolution (R~50) spectroscopy, as well as medium-resolution (R~4,000) spectroscopy with the goal of discovering and characterizing cold exoplanets that are brightest in the thermal infrared. Additionally, SCALES has a 12x12" field-of-view imager that will be used for general adaptive optics science at Keck. We present SCALES's specifications, its science case, its overall design, and simulations of its expected performance. Additionally, we present progress on procuring, fabricating and testing long lead-time components., Comment: 19 pages, 12 Figures, SPIE Astronomical Telescopes + Instrumentation, (#12184-18), 2022, Montreal, Canada

Blockchain systems are designed, built and operated in the presence of failures. There are two dominant failure models, namely crash fault and Byzantine fault. Byzantine fault tolerance (BFT) protocols offer stronger security guarantees, and thus are widely used in blockchain systems. However, their security guarantees come at a dear cost to their performance and scalability. Several works have improved BFT protocols, and Trusted Execution Environment (TEE) has been shown to be an effective solution. However, existing such works typically assume that each participating node is equipped with TEE. For blockchain systems wherein participants typically have different hardware configurations, i.e., some nodes feature TEE while others do not, existing TEE-based BFT protocols are not applicable. This work studies the setting wherein not all participating nodes feature TEE, under which we propose a new fault model called mixed fault. We explore a new approach to designing efficient distributed fault-tolerant protocols under the mixed fault model. In general, mixed fault tolerance (MFT) protocols assume a network of $n$ nodes, among which up to $f = \frac{n-2}{3}$ can be subject to mixed faults. We identify two key principles for designing efficient MFT protocols, namely, (i) prioritizing non-equivocating nodes in leading the protocol, and (ii) advocating the use of public-key cryptographic primitives that allow authenticated messages to be aggregated. We showcase these design principles by prescribing an MFT protocol, namely MRaft. We implemented a prototype of MRaft using Intel SGX, integrated it into the CCF blockchain framework, conducted experiments, and showed that MFT protocols can obtain the same security guarantees as their BFT counterparts while still providing better performance (both transaction throughput and latency) and scalability., Comment: 12 pages, 3 figures