Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Gaia for studying Milky Way star clusters

Abstract We review the implications of the Gaia Data Release 2 catalogue for studying the dynamics of Milky Way globular clusters, focusing on two separate topics. The first one is the analysis of the full 6-dimensional phase-space distribution of the entire population of Milky Way globular clusters: their mean proper motions (PM) can be measured with an exquisite precision (down to 0.05 mas yr−1, including systematic errors). Using these data, and a suitable ansatz for the steady-state distribution function (DF) of the cluster population, we then determine simultaneously the best-fit parameters of this DF and the total Milky Way potential. We also discuss possible correlated structures in the space of integrals of motion. The second topic addresses the internal dynamics of a few dozen of the closest and richest globular clusters, again using the Gaia PM to measure the velocity dispersion and internal rotation, with a proper treatment of spatially correlated systematic errors. Clear rotation signatures are detected in 10 clusters, and a few more show weaker signatures at a level ∼0.05 mas yr−1. PM dispersion profiles can be reliably measured down to 0.1 mas yr−1, and agree well with the line-of-sight velocity dispersion profiles from the literature.
Evolution of relativistic thin discs with a finite ISCO stress – I. Stalled accretion

We present solutions to the relativistic thin disc evolutionary equation using an α-model for the turbulent stress tensor. Solutions with a finite stress at the innermost stable circular orbit (ISCO) give rise to bolometric light curves with a shallow power-law time dependence, in good agreement with those observed in tidal disruption events. A self-similar model based on electron scattering opacity, for example, yields a power-law index of −11/14, as opposed to −19/16 for the case of zero ISCO stress. These solutions correspond to an extended period of relaxation of the evolving disc which, like the light curves they produce, is not sustainable indefinitely. Cumulative departures from the approximation of exact circular orbits cause the power-law index to evolve slowly with time, leading eventually to the steeper fall-off associated with traditional zero ISCO stress models. These modified solutions are discussed in detail in a companion paper.
Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes

Policy gradient methods are among the most effective methods in challenging reinforcement learning problems with large state and/or action spaces. However, little is known about even their most basic theoretical convergence properties, including: if and how fast they converge to a globally optimal solution (say with a sufficiently rich policy class); how they cope with approximation error due to using a restricted class of parametric policies; or their finite sample behavior. Such characterizations are important not only to compare these methods to their approximate value function counterparts (where such issues are relatively well understood, at least in the worst case), but also to help with more principled approaches to algorithm design. This work provides provable characterizations of computational, approximation, and sample size issues with regards to policy gradient methods in the context of discounted Markov Decision Processes (MDPs). We focus on both: 1) "tabular" policy parameterizations, where the optimal policy is contained in the class and where we show global convergence to the optimal policy, and 2) restricted policy classes, which may not contain the optimal policy and where we provide agnostic learning results. One insight of this work is in formalizing the importance how a favorable initial state distribution provides a means to circumvent worst-case exploration issues. Overall, these results place policy gradient methods under a solid theoretical footing, analogous to the global convergence guarantees of iterative value function based algorithms.
Local analysis of the clustering, velocities, and accelerations of particles settling in turbulence

Using 3D Vorono\text{i} analysis, we explore the local dynamics of small, settling, inertial particles in isotropic turbulence using Direct Numerical Simulations (DNS). We independently vary the Taylor Reynolds number $R_\lambda \in[90,398]$, Froude number $Fr\equiv a_\eta/g\in[0.052,\infty]$ (where $a_\eta$ is the Kolmogorov acceleration, and $g$ is the acceleration due to gravity), and Kolmogorov scale Stokes number $St\equiv\tau_p/\tau_\eta\in[0,3]$. In agreement with previous results using global measures of particle clustering, such as the Radial Distribution Function (RDF), we find that for small Vorono\text{i} volumes (corresponding to the most clustered particles), the behavior is strongly dependent upon $St$ and $Fr$, but only weakly dependent upon $R_\lambda$, unless $St>1$. However, larger Vorono\text{i} volumes (void regions) exhibit a much stronger dependence on $R_\lambda$, even when $St\leq 1$, and we show that this, rather than the behavior at small volumes, is the cause of the sensitivity of the standard deviation of the Vorono\text{i} volumes that has been previously reported. We also show that the largest contribution to the particle settling velocities is associated with increasingly larger Vorono\text{i} volumes as the settling parameter $Sv\equiv St/Fr$ is increased. Our local analysis of the acceleration statistics of settling inertial particles shows that clustered particles experience a net acceleration in the direction of gravity, while particles in void regions experience the opposite. The particle acceleration variance, however, is a convex function of the Vorono\text{i} volumes, with or without gravity, which seems to indicate a non-trivial relationship between the Vorono\text{i} volumes and the sizes of the turbulent flow scales. Results for the variance of the fluid acceleration at the inertial particle ". "
Instability of twisted magnetar magnetospheres

We present 3D force-free electrodynamics simulations of magnetar magnetospheres that demonstrate the instability of certain degenerate, high energy equilibrium solutions of the Grad–Shafranov equation. This result indicates the existence of an unstable branch of twisted magnetospheric solutions and allows us to formulate an instability criterion. The rearrangement of magnetic field lines as a consequence of this instability triggers the dissipation of up to 30 per cent of the magnetospheric energy on a thin layer above the magnetar surface. During this process, we predict an increase of the mechanical stresses on to the stellar crust, which can potentially result in a global mechanical failure of a significant fraction of it. We find that the estimated energy release and the emission properties are compatible with the observed giant flare events. The newly identified instability is a candidate for recurrent energy dissipation, which could explain part of the phenomenology observed in magnetars.
Cluster counts

The Lambda cold dark matter (ΛCDM) concordance model is very successful at describing our Universe with high accuracy and only a few parameters. Despite its successes, a few tensions persist; most notably, the best-fit ΛCDM model, as derived from the Planck cosmic microwave background (CMB) data, largely overpredicts the abundance of Sunyaev–Zel’dovich (SZ) clusters when using their standard mass calibration. Whether this is the sign of an incorrect calibration or the need for new physics remains a matter of debate. In this study, we examined two simple extensions of the standard model and their ability to release the aforementioned tension: massive neutrinos and a simple modified gravity model via a non-standard growth index γ. We used both the Planck CMB power spectra and SZ cluster counts as datasets, alone and in combination with local X-ray clusters. In the case of massive neutrinos, the cluster-mass calibration (1 − b) is constrained to 0.585+0.031−0.037 (68% limits), more than 5σ away from its standard value (1 − b)∼0.8. We found little correlation between neutrino masses and cluster calibration, corroborating previous conclusions derived from X-ray clusters; massive neutrinos do not alleviate the cluster-CMB tension. With our simple γ model, we found a large correlation between the calibration and the growth index γ, but contrary to local X-ray clusters, SZ clusters are able to break the degeneracy between the two parameters thanks to their extended redshift range. The calibration (1 − b) was then constrained to 0.602+0.053−0.065, leading to an interesting constraint on γ = 0.60 ± 0.13. When both massive neutrinos and modified gravity were allowed, preferred values remained centred on standard ΛCDM values, but a calibration (1 − b)∼0.8 was allowed (though only at the 2σ level) provided ∑mν ∼ 0.34 eV and γ ∼ 0.8. We conclude that massive neutrinos do not relieve the cluster-CMB tension, and that a calibration close to the standard value (1 − b)∼0.8 would call for new physics in the gravitational sector.
Heavy-hole band splitting observed in mobility spectrum of p-type InAs grown on GaAs substrate.

High quality berylium doped InAs layer grown by MBE on GaAs substrate has been examined via magnetotransport measurements and high resolution quantitative mobility spectrum analysis in the range from 5 to 300 K and up to 15 T magnetic field. The layer homogenity and dopant concentration has been proofed via HR-SIMS. The results shew four channel conductivity and essential splitting of the most populated holelike channel below 55 K. The multilayer model concluded from the QMSA results has been compared with nextnano simulation.
Learning to Denoise and Decode: A Novel Residual Neural Network Decoder for Polar Codes

Polar codes have been adopted as the control channel coding scheme in the fifth generation new radio (5G NR) standard due to its capacity-achievable property. Traditional polar decoding algorithms such as successive cancellation (SC) suffer from high latency problem because of their sequential decoding nature. Neural network decoder (NND) has been proved to be a candidate for polar decoder since it is capable of one-shot decoding and parallel computing. In his paper, we propose a residual neural network decoder (RNND) for polar codes. Different from previous works which directly use neural network for decoding symbols received from the channel, the proposed RNND introduces a denoising module based on residual learning before NND. The proposed residual learning denoiser is able to remove remarkable amount of noise from received signals. Numerical results show that on one hand our proposed RNND outperforms traditional NND with regard to the BER performance under comparable latency. On the other hand, although the proposed scheme is a little inferior to the traditional successive cancellation list decoder when the BER performance is under consideration, it reduces significant decoding latency with the aid of the parallel structure of neural network and modern graphical processing units.
Modelling and Simulation of of high efficiency GaAs PIN-Solar Cell

Solar energy is the most convenient and reliable energy source among all renewable energy resources and an efficient photovoltaic device is required to convert this energy into utilizable energy. Different types of solar cells (SC) are commercially available. However, various parameters need to be optimized to get maximum efficiency from a SC. In this study we have presented a SC model in which dependence of quantum efficiency (QE) on various parameters has been investigated. The mobility of the carriers has been varied with wide range along with the carrier life time (LT). Results show that maximum efficiencies can be achieved up to 11.10% and 10.81% keeping the electron and hole mobility to be 1500 cm2V-1s-1 and 300 cm2V-1s-1 respectively with electron and hole carrier LT to be 3ns and 7ns respectively. The effect of surface recombination velocity (SRV) has also been brought under observation and the maximum efficiency is found to be 13.75% at electron and hole SRV equal to be 103ms-1. Results shows that the higher photovoltaic efficiencies can be achieved by increasing the mobility and carrier LT while decreasing the surface recombination velocities.
Equilibrium states for non-uniformly hyperbolic systems: Statistical properties and analyticity

We consider a wide family of non-uniformly expanding maps and hyperbolic H\"older continuous potentials. We prove that the unique equilibrium state associated to each element of this family is given by the eigenfunction of the transfer operator and the eigenmeasure of the dual operator (both having the spectral radius as eigenvalue). We show that the transfer operator has the spectral gap property in some space of H\"older continuous observables and from this we obtain an exponential decay of correlations and a central limit theorem for the equilibrium state. Moreover, we establish the analyticity with respect to the potential of the equilibrium state as well as that of other thermodynamical quantities. Furthermore, we derive similar results for the equilibrium state associated to a family of non-uniformly hyperbolic skew products and hyperbolic H\"older continuous potentials.
Observations of the Ultra-compact X-Ray Binary 4U 1543-624 in Outburst with NICER, INTEGRAL, Swift, and ATCA

We report on X-ray and radio observations of the ultra-compact X-ray binary 4U 1543−624 taken in August 2017 during an enhanced accretion episode. We obtained Neutron Star Interior Composition Explorer (NICER) monitoring of the source over a ∼10 day period during which target-of-opportunity observations were also conducted with Swift, INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL), and the Australia Telescope Compact Array. Emission lines were measured in the NICER X-ray spectrum at ∼0.64 keV and ∼6.4 keV that correspond to O and Fe, respectively. By modeling these line components, we are able to track changes in the accretion disk throughout this period. The innermost accretion flow appears to move inwards from hundreds of gravitational radii (Rg = GM/c2) at the beginning of the outburst to <8.7 Rg at peak intensity. We do not detect the source in radio, but are able to place a 3σ upper limit on the flux density at 27 μJy beam−1. Comparing the radio and X-ray luminosities, we find that the source lies significantly away from the range typical of black holes in the – plane, suggesting a neutron star primary. This adds to the evidence that neutron stars (NSs) do not follow a single track in the – plane, limiting its use in distinguishing between different classes of NSs based on radio and X-ray observations alone.
KiloGrams: Very Large N-Grams for Malware Classification

N-grams have been a common tool for information retrieval and machine learning applications for decades. In nearly all previous works, only a few values of $n$ are tested, with $n > 6$ being exceedingly rare. Larger values of $n$ are not tested due to computational burden or the fear of overfitting. In this work, we present a method to find the top-$k$ most frequent $n$-grams that is 60$\times$ faster for small $n$, and can tackle large $n\geq1024$. Despite the unprecedented size of $n$ considered, we show how these features still have predictive ability for malware classification tasks. More important, large $n$-grams provide benefits in producing features that are interpretable by malware analysis, and can be used to create general purpose signatures compatible with industry standard tools like Yara. Furthermore, the counts of common $n$-grams in a file may be added as features to publicly available human-engineered features that rival efficacy of professionally-developed features when used to train gradient-boosted decision tree models on the EMBER dataset.
The Widefield Arecibo Virgo Extragalactic Survey. I. New Structures in the ALFALFA Virgo 7 Cloud Complex and an Extended Tail on NGC 4522

We are carrying out a sensitive blind survey for neutral hydrogen (H i) in the Virgo cluster and report here on the first 5° × 1° area covered, which includes two optically dark gas features: the five-cloud ALFALFA Virgo 7 complex and the stripped tail of NGC 4522. We discover a sixth cloud and low-velocity gas that extends the velocity range of the complex to over 450 km s−1, find that around half of the total H i flux comes from extended emission rather than compact clouds, and see around 150% more gas, raising the total H i mass from 5.1 × 108 M⊙ to 1.3 × 109 M⊙. This makes the identification of NGC 4445 and NGC 4424 by Kent et al. as possible progenitors of the complex less likely, as it would require an unusually high fraction of the gas removed to have been preserved in the complex. We also identify a new component to the gas tail of NGC 4522 extending to ∼200 km s−1 below the velocity range of the gas in the galaxy, pointing toward the eastern end of the complex. We consider the possibility that NGC 4522 may be the parent galaxy of the complex, but the large velocity separation (∼1800 km s−1) leads us to rule this out. We conclude that, in the absence of any better candidate, NGC 4445 remains the most likely parent galaxy, although this requires it to have been particularly gas-rich prior to the event that removed its gas into the complex.
Optimization-Based Control for Bearing-Only Target Search With a Mobile Vehicle

This article aims to design an optimization-based controller for a discrete-time Dubins vehicle to approach a target with unknown position as fast as possible by only using bearing measurements. To this end, we propose a bi-objective optimization problem, which jointly considers the performance of estimating the unknown target position and controlling the mobile vehicle to a known position, and then adopt a weighted sum method with normalization to solve it. The controller is given based on the solution of the optimization problem in ties with a least-square estimate of the target position. Moreover, the controller does not need the vehicle’s global position information. Finally, the simulation results are included to validate the effectiveness of the proposed controller.
Correlations and dynamics of tunnel-coupled one-dimensional Bose gases

We present a series of experiments performed with two ultracold one-dimensional Bose gases (rubidium atoms) in a double well potential. Employing matter-wave interference, we can measure the spatially resolved phase difference between the two gases and consequently investigate spatial correlations. By investigating whether higher order correlation functions can be factorized into correlations of lower order, we can investigate the interaction properties of the system. For a non-interacting system, all correlation functions with orders greater than two factorize and one observes Gaussian fluctuations. Here, we present the measurement of non-factorizing fourth-order correlation functions, leading to an experimental characterization of the interactions between the collective excitations of the quantum many-body system. The degree of non-factorizibility, i.e., the degree of non-Gaussianity of the phase fluctuations, depends on the tuneable tunneling strength between the wells. Starting from such a non-Gaussian state, we are able to observe the dynamical evolution towards a state with factorizing correlation functions (Gaussian fluctuations). We start in a double well with tunneling and then abruptly decouple the two subsystems. Subsequently, we observe how the initially non-Gaussian phase fluctuations become Gaussian. Moreover, we discuss the dynamical emergence of phase coherence in a double well potential with tunneling. We experimentally investigate the evolution starting from two different initial states. In one case, we split a cloud of atoms into two and trigger global oscillations in their relative phase. The oscillations subsequently damp and phase coherence sets in. In the other case, two independent clouds are suddenly coupled by tunneling. Again, phase coherence emerges between the two subsystems.
The origin of metal-poor and metal-rich globular clusters in E-MOSAICS

Abstract It has been a long-standing open question why observed globular cluster (GC) populations of different metallicities differ in their ages and spatial distributions, with metal-poor GCs being the older and radially more extended of the two. We use the suite of 25 Milky Way-mass cosmological zoom-in simulations from the E-MOSAICS project, which self-consistently model the formation and evolution of stellar clusters and their host galaxies, to understand the properties of observed GC populations. We find that the different ages and spatial distributions of metal-poor and metal-rich GCs are the result of regular cluster formation at high redshift in the context of hierarchical galaxy assembly. We also find that metallicity on its own is not a good tracer of accretion, and other properties, such as kinematics, need to be considered.
A Unified Point-Based Framework for 3D Segmentation

3D point cloud segmentation remains challenging for structureless and textureless regions. We present a new unified point-based framework for 3D point cloud segmentation that effectively optimizes pixel-level features, geometrical structures and global context priors of an entire scene. By back-projecting 2D image features into 3D coordinates, our network learns 2D textural appearance and 3D structural features in a unified framework. In addition, we investigate a global context prior to obtain a better prediction. We evaluate our framework on ScanNet online benchmark and show that our method outperforms several state-of-theart approaches. We explore synthesizing camera poses in 3D reconstructed scenes for achieving higher performance. In-depth analysis on feature combinations and synthetic camera pose verify that features from different modalities benefit each other and dense camera pose sampling further improves the segmentation results.
A three-dimensional map of the Milky Way using classical Cepheid variable stars

Cepheids help to map the Galaxy Cepheid variable stars pulsate, which allows their distances to be determined from the periodic variations in brightness. Skowron et al. constructed a catalog of thousands of Cepheids covering a large fraction of the Milky Way. They combined optical and infrared data to determine the stars' pulsation periods and mapped the distribution of Cepheids and the associated young stellar populations across the Galaxy. Their three-dimensional map demonstrates the warping of the Milky Way's disc. A simple model of star formation in the spiral arms reproduced the positions and ages of the Cepheid population. Science, this issue p. 478 Mapping the Milky Way in three dimensions using Cepheid variable stars shows the Galaxy’s warped disk. The Milky Way is a barred spiral galaxy, with physical properties inferred from various tracers informed by the extrapolation of structures seen in other galaxies. However, the distances of these tracers are measured indirectly and are model-dependent. We constructed a map of the Milky Way in three dimensions, based on the positions and distances of thousands of classical Cepheid variable stars. This map shows the structure of our Galaxy’s young stellar population and allows us to constrain the warped shape of the Milky Way’s disk. A simple model of star formation in the spiral arms reproduces the observed distribution of Cepheids.