Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Third Order Adams-Bashforth Time Stepping Scheme for 2D Extended Boussinesq Equations

We develop the third-order adaptive Adams-Bashforth time stepping scheme and the second-order finite difference discretization equation for variable time steps. We incorporate these schemes in the Celeris Advent software to discretize and solve the extended Boussinesq equations. This software uses a hybrid finite volume - finite difference scheme and leverages GPU to solve the equations faster than real-time as well to concurrently visualize them. We simulate several benchmarks using the adaptive time stepping scheme of Celeris Advent and demonstrate the capability of the software in modeling wave-breaking, wave runup, irregular waves, and rip currents. The adaptive scheme significantly improves the robustness of the model without slowing it down.
JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR Video

Joint learning of super-resolution (SR) and inverse tone-mapping (ITM) has been explored recently, to convert legacy low resolution (LR) standard dynamic range (SDR) videos to high resolution (HR) high dynamic range (HDR) videos for the growing need of UHD HDR TV/broadcasting applications. However, previous CNN-based methods directly reconstruct the HR HDR frames from LR SDR frames, and are only trained with a simple L2 loss. In this paper, we take a divide-and-conquer approach in designing a novel GAN-based joint SR-ITM network, called JSI-GAN, which is composed of three task-specific subnets: an image reconstruction subnet, a detail restoration (DR) subnet and a local contrast enhancement (LCE) subnet. We delicately design these subnets so that they are appropriately trained for the intended purpose, learning a pair of pixel-wise 1D separable filters via the DR subnet for detail restoration and a pixel-wise 2D local filter by the LCE subnet for contrast enhancement. Moreover, to train the JSI-GAN effectively, we propose a novel detail GAN loss alongside the conventional GAN loss, which helps enhancing both local details and contrasts to reconstruct high quality HR HDR results. When all subnets are jointly trained well, the predicted HR HDR results of higher quality are obtained with at least 0.41 dB gain in PSNR over those generated by the previous methods.
A LOFAR-IRAS cross-match study: the far-infrared radio correlation and the 150 MHz luminosity as a star-formation rate tracer

Aims. We aim to study the far-infrared radio correlation (FIRC) at 150 MHz in the local Universe (at a median redshift ⟨z⟩∼0.05) and improve the use of the rest-frame 150 MHz luminosity, L150, as a star-formation rate (SFR) tracer, which is unaffected by dust extinction. Methods. We cross-match the 60 μm selected Revised IRAS Faint Source Survey Redshift (RIFSCz) catalogue and the 150 MHz selected LOFAR value-added source catalogue in the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) Spring Field. We estimate L150 for the cross-matched sources and compare it with the total infrared (IR) luminosity, LIR, and various SFR tracers. Results. We find a tight linear correlation between log L150 and log LIR for star-forming galaxies, with a slope of 1.37. The median qIR value (defined as the logarithm of the LIR to L150 ratio) and its rms scatter of our main sample are 2.14 and 0.34, respectively. We also find that log L150 correlates tightly with the logarithm of SFR derived from three different tracers, i.e., SFRHα based on the Hα line luminosity, SFR60 based on the rest-frame 60 μm luminosity and SFRIR based on LIR, with a scatter of 0.3 dex. Our best-fit relations between L150 and these SFR tracers are, log L150 (L⊙) = 1.35(±0.06) × log SFRHα (M⊙ yr−1) + 3.20(±0.06), log L150 (L⊙) = 1.31(±0.05) × log SFR60 (M⊙ yr−1) + 3.14(±0.06), and log L150 (L⊙) = 1.37 (±0.05) × log SFRIR (M⊙ yr−1) + 3.09(±0.05), which show excellent agreement with each other.
Studying the Solar system dynamics using pulsar timing arrays and the LINIMOSS dynamical model

Pulsar timing arrays (PTAs) can be used to study the Solar system ephemeris (SSE), the errors of which can lead to correlated timing residuals and significantly contribute to the PTA noise budget. Most Solar system studies with PTAs assume the dominance of the term from the shift of the Solar system barycentre (SSB). However, it is unclear to which extent this approximation can be valid, since the perturbations on the planetary orbits may become important as data precision keeps increasing. To better understand the effects of SSE uncertainties on pulsar timing, we develop the linimoss dynamical model of the Solar system, based on the SSE of Guangyu Li. Using the same input parameters as DE435, the calculated planetary positions by linimoss are compatible with DE435 at centimetre level over a 20 yr timespan, which is sufficiently precise for pulsar-timing applications. We utilize linimoss to investigate the effects of SSE errors on pulsar timing in a fully dynamical way, by perturbing one SSE parameter per trial and examining the induced timing residuals. For the outer planets, the timing residuals are dominated by the SSB shift, as assumed in previous work. For the inner planets, the variations in the orbit of the Earth are more prominent, making previously adopted assumptions insufficient. The power spectra of the timing residuals have complex structures, which may introduce false signals in the search of gravitational waves. We also study how to infer the SSE parameters using PTAs, and calculate the accuracy of parameter estimation.
Surrogate-based Optimization using Mutual Information for Computer Experiments (optim-MICE)

The computational burden of running a complex computer model can make optimization impractical. Gaussian Processes (GPs) are statistical surrogates (also known as emulators) that alleviate this issue since they cheaply replace the computer model. As a result, the exploration vs. exploitation trade-off strategy can be accelerated by building a GP surrogate. In this paper, we propose a new surrogate-based optimization scheme that minimizes the number of evaluations of the computationally expensive function. Taking advantage of parallelism of the evaluation of the unknown function, the uncertain regions are explored simultaneously, and a batch of input points is chosen using Mutual Information for Computer Experiments (MICE), a sequential design algorithm which maximizes the information theoretic Mutual Information over the input space. The computational efficiency of interweaving the optimization scheme with MICE (optim-MICE) is examined and demonstrated on test functions. Optim-MICE is compared with state-of-the-art heuristics such as Efficient Global Optimization (EGO) and GP-Upper Confidence Bound (GP-UCB). We demonstrate that optim-MICE outperforms these schemes on a large range of computational experiments.
A self-consistent dynamical system with multiple absolutely continuous invariant measures

In this paper we study a class of \emph{self-consistent dynamical systems}, self-consistent in the sense that the discrete time dynamics is different in each step depending on current statistics. The general framework admits popular examples such as coupled map systems. Motivated by an example of M. Blank, we concentrate on a special case where the dynamics in each step is a $\beta$-map with some $\beta \geq 2$. Included in the definition of $\beta$ is a parameter $\varepsilon > 0$ controlling the strength of self-consistency. We show such a self-consistent system which has a unique absolutely continuous invariant measure (acim) for $\varepsilon=0$, but at least two for any $\varepsilon > 0$. With a slight modification, we transform this system into one which produces a phase transition-like behavior: it has a unique acim for $0< \varepsilon < \varepsilon^*$, and multiple for sufficiently large values of $\varepsilon$. We discuss the stability of the invariant measures by the help of computer simulations employing the numerical representation of the self-consistent transfer operator.
Knowledge Enhanced Contextual Word Representations

Contextual word representations, typically trained on unstructured, unlabeled text, do not contain any explicit grounding to real world entities and are often unable to remember facts about those entities. We propose a general method to embed multiple knowledge bases (KBs) into large scale models, and thereby enhance their representations with structured, human-curated knowledge. For each KB, we first use an integrated entity linker to retrieve relevant entity embeddings, then update contextual word representations via a form of word-to-entity attention. In contrast to previous approaches, the entity linkers and self-supervised language modeling objective are jointly trained end-to-end in a multitask setting that combines a small amount of entity linking supervision with a large amount of raw text. After integrating WordNet and a subset of Wikipedia into BERT, the knowledge enhanced BERT (KnowBert) demonstrates improved perplexity, ability to recall facts as measured in a probing task and downstream performance on relationship extraction, entity typing, and word sense disambiguation. KnowBert’s runtime is comparable to BERT’s and it scales to large KBs.
TMA: Tera‐MACs/W neural hardware inference accelerator with a multiplier‐less massive parallel processor

Computationally intensive inference tasks of deep neural networks have brought about a revolution in accelerator architecture, aiming to reduce power consumption as well as latency. The key figure‐of‐merit in hardware inference accelerators is the number of multiply‐and‐accumulation operations per watt (MACs/W); the state‐of‐ the‐art MACs/W, so far, has been several hundreds Giga‐MACs/W. We propose a Tera‐ MACS/W neural hardware inference accelerator (TMA) with 8‐bit activations and scalable integer weights less than 1‐byte. The architecture's main feature is a configurable neural processing element for matrix‐vector operations. The proposed neural processing element uses a multiplier‐less massive parallel processor that works without multipliers, which makes it attractive for energy efficient high‐performance neural network applications. We benchmark our system's latency, power, and performance using Alexnet trained on ImageNet. Finally, we compared our accelerator's throughput and power consumption to that of the prior works. The proposed accelerator outperforms the state‐of‐the‐art counterparts, in terms of the energy and area efficiency, achieving 2.3 TMACs/W@1.0 V on a 28‐nm Virtex‐7 FPGA chip.
Bootstrap percolation in Ore-type graphs

The $r$-neighbour bootstrap process describes an infection process on a graph, where we start with a set of initially infected vertices and an uninfected vertex becomes infected as soon as it has $r$ infected neighbours. An inital set of infected vertices is called percolating if at the end of the bootstrap process all vertices are infected. We give Ore-type conditions that guarantee the existence of a small percolating set of size $l\leq 2r-2$ if the number of vertices $n$ of our graph is sufficiently large: if $l\geq r$ and satisfies $2r \geq l+2 \lfloor \sqrt{2(l-r)+0.25}+2.5 \rfloor-1$ then there exists a percolating set of size $l$ for every graph in which any two non-adjacent vertices $x$ and $y$ satisfy $deg(x)+deg(y) \geq n+4r-2l-2\lfloor\sqrt{2(l-r)+0.25}+2.5 \rfloor-1$ and if $l$ is larger with $l\leq 2r-2$ there exists a percolating set of size $l$ if $deg(x)+deg(y) \geq n+2r-l-2$. Our results extend the work of Gunderson, who showed that a graph with minimum degree $\lfloor n/2 \rfloor+r-3$ has a percolating set of size $r \geq 4$. We also give bounds for arbitrarily large $l$ in the minimum degree setting.
Universality driven analytic structure of the QCD crossover: Radius of convergence in the baryon chemical potential

Recent lattice QCD calculations show strong indications that the chiral crossover of QCD at zero baryon chemical potential \mu_B is a remnant of the second order chiral phase transition. Furthermore, the non-universal parameters needed to map temperature T and \mu_B to the universal properties of the second order chiral phase transition have been determined recently. Motivated by these observations, first, we determine the analytic structure of the partition function -- the so-called Yang-Lee edge singularity -- in the QCD crossover regime, solely based on universal properties. Next, utilizing the lattice QCD results for non-universal parameters we map this singularity to the real T and complex \mu_B plane, leading to the determination of the radius of convergence in \mu_B in the QCD crossover regime. These universality- and QCD-based results provide tight constraints on the range of validity of the lattice QCD calculations at \mu_B>0. Implication of this result on the location of the conjectured QCD critical point is discussed.
Modular Block-diagonal Curvature Approximations for Feedforward Architectures

We propose a modular extension of backpropagation for the computation of block-diagonal approximations to various curvature matrices of the training objective (in particular, the Hessian, generalized Gauss-Newton, and positive-curvature Hessian). The approach reduces the otherwise tedious manual derivation of these matrices into local modules, and is easy to integrate into existing machine learning libraries. Moreover, we develop a compact notation derived from matrix differential calculus. We outline different strategies applicable to our method. They subsume recently-proposed block-diagonal approximations as special cases, and are extended to convolutional neural networks in this work.
Gas accretion and galactic fountain flows in the Auriga cosmological simulations: angular momentum and metal redistribution

Using a set of 15 high-resolution magnetohydrodynamic cosmological simulations of Milky Way formation, we investigate the origin of the baryonic material found in stars at redshift zero. We find that roughly half of this material originates from subhalo/satellite systems and half is smoothly accreted from the intergalactic medium. About $90 {{\ \rm per\ cent}}$ of all material has been ejected and re-accreted in galactic winds at least once. The vast majority of smoothly accreted gas enters into a galactic fountain that extends to a median galactocentric distance of ∼20 kpc with a median recycling time-scale of ∼500 Myr. We demonstrate that, in most cases, galactic fountains acquire angular momentum via mixing of low angular momentum, wind-recycled gas with high angular momentum gas in the circumgalactic medium (CGM). Prograde mergers boost this activity by helping to align the disc and CGM rotation axes, whereas retrograde mergers cause the fountain to lose angular momentum. Fountain flows that promote angular momentum growth are conducive to smooth evolution on tracks quasi-parallel to the disc sequence of the stellar mass-specific angular momentum plane, whereas retrograde minor mergers, major mergers, and bar-driven secular evolution move galaxies towards the bulge sequence. Finally, we demonstrate that fountain flows act to flatten and narrow the radial metallicity gradient and metallicity dispersion of disc stars, respectively. Thus, the evolution of galactic fountains depends strongly on the cosmological merger history and is crucial for the chemodynamical evolution of Milky-Way-sized disc galaxies.
ALMA Observations of Giant Molecular Clouds in M33. I. Resolving Star Formation Activities in the Giant Molecular Filaments Possibly Formed by a Spiral Shock

We report molecular line and continuum observations toward one of the most massive giant molecular clouds (GMCs), GMC-16, in M33 using ALMA with an angular resolution of 0. ″44 × 0. ″27 (∼2 pc × 1 pc). We have found that the GMC is composed of several filamentary structures in 12CO and 13CO(J = 2–1). The typical length, width, and total mass are ∼50–70 pc, ∼5–6 pc, and ∼105 M⊙, respectively, which are consistent with those of giant molecular filaments (GMFs) as seen in the Galactic GMCs. The elongations of the GMFs are roughly perpendicular to the direction of the galaxy’s rotation, and several H ii regions are located at the downstream side relative to the filaments with an offset of ∼10–20 pc. These observational results indicate that the GMFs are considered to be produced by a galactic spiral shock. The 1.3 mm continuum and C18O(J = 2–1) observations detected a dense clump with the size of ∼2 pc at the intersection of several filamentary clouds, which is referred to as the “hub filament,” possibly formed by a cloud–cloud collision. A strong candidate for protostellar outflow in M33 has also been identified at the center of the clump. We have successfully resolved the parsec-scale local star formation activity in which the galactic scale kinematics may induce the formation of the parental filamentary clouds.
Measles and rubella misdiagnosed in infants as exanthem subitum (roseola infantum)

Human herpesvirus-6 is widespread throughout human populations, with primary infection usually occurring in infants aged 40-60 weeks.1 Primary infection may be asymptomatic but where there is disease the classic presentation is of the common childhood illness exanthem subitum (roseola infantum). 2 This begins with a sudden fever of about 40°C perhaps accompanied by febrile convulsions; the child appears surprisingly well with few other clinical findings apart from leucopenia. The fever resolves after three to five days coincident with the sudden appearance of a finely macular rose rash that may be transient but usually persists for two days. The exanthem is prominent over the thighs and buttocks, where each macule is sometimes surrounded by a fine halo. Despite detailed descriptions, however, exanthem subitum tends to be confused with measles and rubella.3 Two recent studies have shown that measles and rubella are themselves commonly misdiagnosed,4 5 with only 11% of clinical cases …
Mathematical modeling for 2D light-sheet fluorescence microscopy image reconstruction

We study an inverse problem for light sheet fluorescence microscopy (LSFM), where the density of fluorescent molecules needs to be reconstructed. Our first step is to present a mathematical model to describe the measurements obtained by an optic camera during an LSFM experiment. Two meaningful stages are considered: excitation and fluorescence. We propose a paraxial model to describe the excitation process which is directly related with the Fermi pencil-beam equation. For the fluorescence stage, we use the transport equation to describe the transport of photons towards the detection camera. For the mathematical inverse problem that we obtain after the modeling, we present a uniqueness result, recasting the problem as the recovery of the initial condition for the heat equation in R×(0,∞) from measurements in a space–time curve. Additionally, we present numerical experiments to recover the density of the fluorescent molecules by discretizing the proposed model and facing this problem as the solution of a large and sparse linear system. Some iterative and regularized methods are used to achieve this objective. The results show that solving the inverse problem achieves better reconstructions than the direct acquisition method that is currently used.
Investigating the completeness and omission roads of OpenStreetMap data in Hubei, China by comparing with Street Map and Street View

Abstract. OpenStreetMap (OSM) is a free map of the world which can be edited by global volunteers. Existing studies have showed that completeness of OSM road data in some developing countries (e.g. China) is much lower, resulting in concern in utilizing the data in various applications. But very few have focused on investigating what types of road are still poorly mapped. This study aims not only to investigate the completeness of OSM road datasets in China but also to investigate what types of road (called omission roads) have not been mapped, which is achieved by referring to both Street Map and Street View. Sixteen prefecture-level divisions in the urban areas of Hubei (China) were used as study areas. Results showed that: (1) the completeness for most prefecture-level divisions was at a low-to-medium level; most roads (in the Street Map), however, with traffic conditions had already been mapped well. (2) Most of the omission OSM roads were either private roads, or public roads not having yet been named and with only one single lane, indicating their minor importance in the urban road network. We argue that although the OSM road datasets in China are incomplete, they may still be used for several applications such as traffic flow analysis, road map representation, and backbone structure detection.
Octagons II: Strong Coupling

The octagon function is the fundamental building block yielding correlation functions of four large BPS operators in N=4 super Yang-Mills theory at any value of the 't Hooft coupling and at any genus order. Here we compute the octagon at strong coupling, and discuss various interesting limits and implications, both at the planar and non-planar level.
Faraday and Resonant Waves in Dipolar Cigar-Shaped Bose-Einstein Condensates

Faraday and resonant density waves emerge in Bose-Einstein condensates as a result of harmonic driving of the system. They represent nonlinear excitations and are generated due to the interaction-induced coupling of collective oscillation modes and the existence of parametric resonances. Using a mean-field variational and a full numerical approach, we studied density waves in dipolar condensates at zero temperature, where breaking of the symmetry due to anisotropy of the dipole-dipole interaction (DDI) plays an important role. We derived variational equations of motion for the dynamics of a driven dipolar system and identify the most unstable modes that correspond to the Faraday and resonant waves. Based on this, we derived the analytical expressions for spatial periods of both types of density waves as functions of the contact and the DDI strength. We compared the obtained variational results with the results of extensive numerical simulations that solve the dipolar Gross-Pitaevskii equation in 3D, and found a very good agreement.