Miracle-dz/UniFAR-FTUs huggingface dataset:
Canada-France Redshift Survey: Hubble Space Telescope Imaging of High-Redshift Field Galaxies

Hubble Space Telescope B and I images are presented of 32 galaxies with secure redshifts in the range 0.5 < z < 1.2 from the Canada-France Redshift Survey, a complete sample of galaxies with 17.5 ≤ IAB ≤ 22.5. These galaxies exhibit the same range of morphological types as seen locally, i.e., ellipticals, spirals, and irregulars. The galaxies look far less regular in the B images (rest-frame ultraviolet) than at longer wavelengths, underlining the fact that optical images of galaxies at still higher redshift should be interpreted with caution. Quantitative analyses of the galaxies yield disk sizes, bulge fractions, and colors for each component. At these redshifts, galaxy disks show clear evidence for surface brightness evolution. The mean rest-frame central surface brightness of the disks of normal late-type galaxies is μAB(B) = 20.2 ± 0.25 mag arcsec-2, about 1.2 mag brighter than the Freeman law for nearby galaxies. Some degree of peculiarity/asymmetry is measurable in 10 (30%) of the galaxies, and four (13%) show clear signs of interaction/mergers. There are nine galaxies (30%) dominated by blue compact components. These components, which appear to be related to star formation, occur most often in peculiar/asymmetric galaxies (some of which appear to be interacting), but a few are in otherwise normal galaxies. Thus, of the galaxies bluer than present-day Sb, one-third are “blue nucleated galaxies” and half are late-type galaxies with disks which are significantly brighter than normal galaxies at z = 0. Taken together, these two effects must be responsible for much of the observed evolution of the luminosity function of blue galaxies.
ELECTRON ACCELERATIONS AT HIGH MACH NUMBER SHOCKS: TWO-DIMENSIONAL PARTICLE-IN-CELL SIMULATIONS IN VARIOUS PARAMETER REGIMES

Electron accelerations at high Mach number collisionless shocks are investigated by means of two-dimensional electromagnetic particle-in-cell simulations with various Alfvén Mach numbers, ion-to-electron mass ratios, and the upstream electron βe (the ratio of the thermal pressure to the magnetic pressure). We find electrons are effectively accelerated at a super-high Mach number shock (MA ∼ 30) with a mass ratio of M/m = 100 and βe = 0.5. The electron shock surfing acceleration is an effective mechanism for accelerating the particles toward the relativistic regime even in two dimensions with a large mass ratio. Buneman instability excited at the leading edge of the foot in the super-high Mach number shock results in a coherent electrostatic potential structure. While multi-dimensionality allows the electrons to escape from the trapping region, they can interact with the strong electrostatic field several times. Simulation runs in various parameter regimes indicate that the electron shock surfing acceleration is an effective mechanism for producing relativistic particles in extremely high Mach number shocks in supernova remnants, provided that the upstream electron temperature is reasonably low.
Planar dual-polarized millimeter-wave shared-aperture array antenna with high band isolation

A planar millimeter-wave shared-aperture array antenna is proposed and designed in this paper. By composing the substrate integrated waveguide (SIW) and the stripline, the K-band antenna is embedded inside the Ka-band antenna to achieve a smaller size and a low profile by sharing an aperture. The Ka-band antenna radiates through the parallel slot pairs on the surface of the SIW cavities with horizontal polar‐ ization, while the K-band antenna radiates through the butterfly-shaped slots with vertical polarization, which are also designed on the surface. Then the two array antennas can radiate by sharing a common ap‐ erture with high isolation. To verify this idea, a proto‐ type of an 8×8 shared-aperture array antenna has been designed with center frequencies of 19 and 30 GHz and fabricated using multilayer printed circuit board (PCB) technology. The measurement results show that the − 10 dB impedance bandwidths in the K- and Ka-bands are 7.73% and >20%, and the corresponding isolations are higher than 60 and 44 dB, respectively. The proposed shared-aperture antenna has a small footprint, a low profile, and high isolation, and is a promising candidate to design compact millimeter-wave wireless systems.
IM-TQA: A Chinese Table Question Answering Dataset with Implicit and Multi-type Table Structures

Various datasets have been proposed to promote the development of Table Question Answering (TQA) technique. However, the problem setting of existing TQA benchmarks suffers from two limitations. First, they directly provide models with explicit table structures where row headers and column headers of the table are explicitly annotated and treated as model input during inference. Second, they only consider tables of limited types and ignore other tables especially complex tables with flexible header locations. Such simplified problem setting cannot cover practical scenarios where models need to process tables without header annotations in the inference phase or tables of different types. To address above issues, we construct a new TQA dataset with implicit and multi-type table structures, named IM-TQA, which not only requires the model to understand tables without directly available header annotations but also to handle multi-type tables including previously neglected complex tables. We investigate the performance of recent methods on our dataset and find that existing methods struggle in processing implicit and multi-type table structures. Correspondingly, we propose an RGCN-RCI framework outperforming recent baselines. We will release our dataset to facilitate future research.
Correlation of Photon and Neutrino Fluxes in Blazars and Gamma-Ray Bursts

Relativistic black hole jet sources are leading candidates for high-energy (≫TeV) neutrino production. The relations defining (1) efficient photopion losses of cosmic-ray protons on target photons and (2) γγ opacity of γ-rays through that same target photon field imply clear multiwavelength predictions for when and at what energies blazars and gamma-ray bursts should be most neutrino-bright and γ-ray-dim. The use of multiwavelength observations to test the standard relativistic jet model for these source is illustrated.
The relation between atomic gas and star formation rate densities in faint dwarf irregular galaxies

We use data for faint (M_B > -14.5) dwarf irregular galaxies drawn from the FIGGS survey to study the correlation between the atomic gas density (Sigma_gas,atomic) and star formation rate (Sigma_SFR) in the galaxies. The estimated gas phase metallicity of our sample galaxies is Z ~ 0.1 Z_sun. Understanding star formation in such molecule poor gas is of particular importance since it is likely to be of direct relevance to simulations of early galaxy formation. For about 20% (9/43) of our sample galaxies, we find that the HI distribution is significantly disturbed, with little correspondence between the optical and HI distributions. We exclude these galaxies from the comparison. We also exclude galaxies with very low star formation rates, for which stochastic effects make it difficult to estimate the true star formation rates. For the remaining galaxies we compute the Sigma_gas,atomic and Sigma_SFR averaged over the entire star forming disk of the galaxy. For these galaxies we find a nearly linear relation between the star formation rate and the atomic gas surface densities. The corresponding gas consumption timescale is ~ 10 Gyr, i.e. significantly smaller than the ~ 100 Gyr estimated for the outer regions of spiral galaxies. We also estimate the gas consumption timescale computed using the global gas content and the global star formation rate for all galaxies with a reliable measurement of the star formation rate, regardless of whether the HI distribution is disturbed or not. The mean gas consumption timescale computed using this entire gas reservoir is ~ 18 Gyr, i.e. still significantly smaller than that estimated for the outer parts of spirals. The gas consumption timescale for dwarfs is intermediate between the values of ~ 100 Gyr and ~ 2 Gyr estimated for the outer molecule poor and inner molecule rich regions of spiral disks.
Efficient classical-communication-assisted local simulation of n-qubit GHZ correlations

We present a local hidden-variable model supplemented by classical communication that reproduces the quantum-mechanical predictions for measurements of all products of Pauli operators on an n-qubit GHZ state (or "cat state"). The simulation is efficient since the required amount of communication scales linearly with the number of qubits, even though there are Bell-type inequalities for these states for which the amount of violation grows exponentially with n. The structure of our model yields insight into the Gottesman-Knill theorem by demonstrating that, at least in this limited case, the correlations in the set of nonlocal hidden variables represented by the stabilizer generators are captured by an appropriate set of local hidden variables augmented by n-2 bits of classical communication.
MIST: Mutual Information Maximization for Short Text Clustering

Short text clustering poses substantial chal-001 lenges due to the limited amount of informa-002 tion provided by each sample. Previous efforts 003 based on dense representations are still inad-004 equate since texts from different clusters are 005 not sufficiently segregated in the embedding 006 space prior to the clustering step. Even though 007 the state-of-the-art technique integrated con-008 trastive learning with a soft clustering objective 009 to address this issue, the step in which all local 010 tokens are summarized to form a sequence rep-011 resentation for the whole text may include noise 012 that obscures the key information. We propose 013 a framework called MIST: M utual I nformation 014 Maximization for S hort T ext Clustering, which 015 overcomes the information limitation by max-016 imizing the mutual information between text 017 samples on both sequence and token levels. We 018 assess the performance of our proposed method 019 on eight standard short text datasets. Experi-020 mental results show that MIST outperforms 021 the state-of-the-art methods in terms of Accu-022 racy or Normalized Mutual Information in most 023 cases. 024
Transformer-based normative modelling for anomaly detection of early schizophrenia

Despite the impact of psychiatric disorders on clinical health, early-stage diagnosis remains a challenge. Machine learning studies have shown that classifiers tend to be overly narrow in the diagnosis prediction task. The overlap between conditions leads to high heterogeneity among participants that is not adequately captured by classification models. To address this issue, normative approaches have surged as an alternative method. By using a generative model to learn the distribution of healthy brain data patterns, we can identify the presence of pathologies as deviations or outliers from the distribution learned by the model. In particular, deep generative models showed great results as normative models to identify neurological lesions in the brain. However, unlike most neurological lesions, psychiatric disorders present subtle changes widespread in several brain regions, making these alterations challenging to identify. In this work, we evaluate the performance of transformer-based normative models to detect subtle brain changes expressed in adolescents and young adults. We trained our model on 3D MRI scans of neurotypical individuals (N=1,765). Then, we obtained the likelihood of neurotypical controls and psychiatric patients with early-stage schizophrenia from an independent dataset (N=93) from the Human Connectome Project. Using the predicted likelihood of the scans as a proxy for a normative score, we obtained an AUROC of 0.82 when assessing the difference between controls and individuals with early-stage schizophrenia. Our approach surpassed recent normative methods based on brain age and Gaussian Process, showing the promising use of deep generative models to help in individualised analyses.
Prospects of AI in Architecture: Symbolicism, Connectionism, Actionism

The Architectural creation is always affected by technological development and available resources. The presence of computation and the advent of artificial intelligence opens new ways in architectural design and implementation, which is not only embodies in the technical application of the new medium, but present in the new design logic as well. This paper provides an overview about the three main branches of artificial intelligence starting with a short introduction of the long-lasting relationship of computation and architecture. Starting from a theoretical base and reaching to the architectural application of symbolicism, connectionism and actionism. The achievement of the research will point out how digital tools foster a novel design approach in architecture.
How PINNs cheat: Predicting chaotic motion of a double pendulum

Despite extensive research, physics-informed neural networks (PINNs) are still difficult to train, especially when the optimization relies heavily on the physics loss term. Convergence problems frequently occur when simulating dynamical systems with high-frequency components, chaotic or turbulent behavior. In this work, we discuss whether the traditional PINN framework is able to predict chaotic motion by conducting experiments on the undamped double pendulum. Our results demonstrate that PINNs do not exhibit any sensitivity to perturbations in the initial condition. Instead, the PINN optimization consistently converges to physically correct solutions that violate the initial condition only marginally, but diverge significantly from the desired solution due to the chaotic nature of the system. In fact, the PINN predictions primarily exhibit low-frequency components with a smaller magnitude of higher-order derivatives, which favors lower physics loss values compared to the desired solution. We thus hypothesize that the PINNs “cheat” by shifting the initial conditions to values that correspond to physically correct solutions that are easier to learn. Initial experiments suggest that domain decomposition combined with an appropriate loss weighting scheme mitigates this effect and allows convergence to the desired solution.
Stochastic games and related topics : in honor of Professor L.S. Shapley

Stochastic games - an overview. - A brief summary of the papers in the volume. - Contributed Papers. - 1 Models for the Game of Liar's dice. - 2 A Discrete Search Game. - 3 Algorithms for Stochastic Games. - 4 On the Algorithm of Pollatschek and Avi-Itzhak. - 5 Semi-infinite Stochastic Games. Indian Statistical Institute. - 6 Easy Initial States in Stochastic Games. - 7 Big Match with Lack of Information on One Side (III). - 8 Stochastic Games with Lack of Information on One Side and Positive Stop Probabilities. - 9 Positive Stochastic Games and a Theorem of Ornstein. - 10 Existence of Correlated Weak Equilibria in Discounted Stochastic Games with General State Space. - 11 Nonzero-Sum Stochastic Games. - 12 On Stochastic Games with Uncountable State and Action Spaces. - 13 Non-Cooperative Dynamic Games with General Utility Functions. - 14 Symmetric Stochastic Games of Resource Extraction: The Existence of Non-Randomized Stationary Equilibrium. - 15 Robustness of Uncertain Dynamical Systems with Delay in the Absence of Matching Assumptions. - Ancestral Papers. - Ancestral papers Stochastic Games, Proc. Nat. Acad. Sciences, U.S.A. , 39, 1095-1100. - On Games of Survival, Ann. Math. Studies, 39, 15-45, Princeton University Press.
Labor informality and monetary and multidimensional poverty in Bogotá and the Metropolitan Area

Labor informality, associated with low income, increases a household’s likelihood of being poor and experiencing precarious living conditions. The aim of this article is to study the relationship between labor informality and both monetary and multidimensional poverty in Bogotá, the capital of Colombia, and its Metropolitan Area (MA). Based on the Multipurpose Survey, the article estimates levels of labor informality and pay gaps, as well as indicators of monetary and multidimensional poverty. This article also simulated various scenarios to identify the levels of poverty reduction as a result of a potential formalization and closing of gaps by segmentation, highlighting the heterogeneities between areas of Bogotá and its Metropolitan Area (MA).
Towards deriving the AdS/CFT correspondence

I present the sketch of a "physicist's" derivation of the AdS/CFT correspondence for the original pair, string theory in $AdS_5\times S^5$ vs. ${\cal N}=4$ SYM, based on the pp wave limit, and deviations from it. I show that one can reverse the logic, and derive the action of ${\cal N}=4$ SYM, as kinetic terms plus vertices, as well as the elements of its path integral, from string theory on the pp wave. One can also treat consistently deviations from the "strings on the pp wave" limit, starting from the SYM side, and a priori reconstruct the full $AdS_5\times S^5$ geometry perturbatively, as well as full perturbative string theory on it.
Identification and informative sample size

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Midtropospheric frontogenesis associated with antecedent indirect precipitation ahead of tropical cyclones over the Korean Peninsula

On the Korean Peninsula (KP), heavy rainfall often precedes the landfall of a tropical cyclone (TC). This rainfall is called antecedent indirect precipitation (AIP), because it occurs well beyond the effective radius of the TC. The present study examines the statistical characteristics and physical mechanism of the AIP produced by TCs that influenced the KP during the period 1993–2004. Composite analyses demonstrate that the AIP events were accompanied by midtropospheric frontogenesis due to the TC-mid-latitude environment interaction. When an approaching TC encountered an approaching mid-latitude upper-level trough, this encounter resulted in confluent and deformed flows at the mid-level by the combination of westerlies from the trough and southerlies from the TC. The delicate balance of horizontal winds related to the two systems at the mid-level led to the midtropospheric frontogenesis to the north of the KP. The frontogenetic feature related to the AIP was in marked contrast to those of the remote rainfall event over the KP and the predecessor rainfall event over the United States suggested by previous studies. Quasi-geostrophic analysis demonstrates that the midtropospheric front induced thermally direct circulation, which led to ascending motion over the KP. Consequently, the midtropospheric front helped to intensify the AIP, together with the convective instability that was amplified by the transport of warm and moist air along the conduit between the TC and subtropical high.
Improving the Efficiency of the PC Algorithm by Using Model-Based Conditional Independence Tests

Learning causal structure is useful in many areas of artificial intelligence, including planning, robotics, and explanation. Constraint-based structure learning algorithms such as PC use conditional independence (CI) tests to infer causal structure. Traditionally, constraint-based algorithms perform CI tests with a preference for smaller-sized conditioning sets, partially because the statistical power of conventional CI tests declines rapidly as the size of the conditioning set increases. However, many modern conditional independence tests are model-based, and these tests use well-regularized models that maintain statistical power even with very large conditioning sets. This suggests an intriguing new strategy for constraint-based algorithms which may result in a reduction of the total number of CI tests performed: Test variable pairs with large conditioning sets first, as a pre-processing step that finds some conditional independencies quickly, before moving on to the more conventional strategy that favors small conditioning sets. We propose such a pre-processing step for the PC algorithm which relies on performing CI tests on a few randomly selected large conditioning sets. We perform an empirical analysis on directed acyclic graphs (DAGs) that correspond to real-world systems and both empirical and theoretical analyses for Erd\H{o}s-Renyi DAGs. Our results show that Pre-Processing Plus PC (P3PC) performs far fewer CI tests than the original PC algorithm, between 0.5% to 36%, and often less than 10%, of the CI tests that the PC algorithm alone performs. The efficiency gains are particularly significant for the DAGs corresponding to real-world systems.
EdMSM: Multi-Scalar-Multiplication for recursive SNARKs and more

The bottleneck in the proving algorithm of most of elliptic-curve-based SNARK proof systems is the Multi-Scalar-Multiplication (MSM) algorithm. In this paper we give an overview of a variant of the Pippenger MSM algorithm together with a set of optimizations tailored for curves that admit a twisted Edwards form. This is the case for SNARK-friendly chains and cycles of elliptic curves, which are useful for recursive constructions. Accelerating the MSM over these curves on mobile devices is critical for deployment of recursive proof systems on mobile applications. This work is implemented in Go and uses hand-written arm64 assembly for accelerating the ﬁnite ﬁeld arithmetic ( bigint ). This work was implemented as part of a submission to the ZPrize competition in the open division “Accelerating MSM on Mobile” ( https://www.zprize.io/ ). We achieved a 78% speedup over the ZPrize baseline implementation in Rust.
Experimental Comparison of Ansätze for Quantum Natural Language Processing

The DisCoCat model of natural language is a framework which serves as the foundation for several contemporary experiments in Quantum Natural Language Processing (QNLP). In this model, sentences are represented as string diagrams which compose the meaning of the entire sentence from the meaning of each word. An essential step in performing QNLP tasks is converting DisCoCat string diagrams into quantum circuits, through a mapping known as an ansatz. While several ansätze have been studied in the broader quantum machine learning literature, no comparative study of ansätze exists for the specific case of QNLP models. In this work, we implement multiple ansätze and compare their performance on a variety of QNLP tasks. In doing so, the first experimental results for a QNLP model applied to the paraphrase identification task are presented. We propose a novel approach to overcome the out-of-vocabulary problem faced by contemporary QNLP models, and demonstrate that our proposed method outperforms naive approaches by a significant margin. Further, experimental results relating to the barren plateau phenomenon in quantum machine learning are provided. We present evidence suggesting that circuits derived from DisCoCat string diagrams for binary classification tasks are no more susceptible to the barren plateau problem than regular quantum machine learning circuits.