cssi/SciSciGPT-SciSciNet huggingface dataset:
DFTpy: An efficient and object-oriented platform for orbital-free DFT simulations

In silico materials design is hampered by the computational complexity of Kohn-Sham DFT, which scales cubically with the system size. Owing to the development of new-generation kinetic energy density functionals (KEDFs), orbital-free DFT (OFDFT, a linear-scaling method) can now be successfully applied to a large class of semiconductors and such finite systems as quantum dots and metal clusters. In this work, we present DFTpy, an open source software implementing OFDFT written entirely in Python 3 and outsourcing the computationally expensive operations to third-party modules, such as NumPy and SciPy. When fast simulations are in order, DFTpy exploits the fast Fourier transforms (FFTs) from PyFFTW. New-generation, nonlocal and density-dependent-kernel KEDFs are made computationally efficient by employing linear splines and other methods for fast kernel builds. We showcase DFTpy by solving for the electronic structure of a million-atom system of aluminum metal which was computed on a single CPU. The Python 3 implementation is object-oriented, opening the door to easy implementation of new features. As an example, we present a time-dependent OFDFT implementation (hydrodynamic DFT) which we use to compute the spectra of small metal cluster recovering qualitatively the time-dependent Kohn-Sham DFT result. The Python code base allows for easy implementation of APIs. We showcase the combination of DFTpy and ASE for molecular dynamics simulations (NVT) of liquid metals. DFTpy is released under the MIT license.
Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages.

We train neural machine translation (NMT) models from English to six target languages, using NMT encoder representations to predict ancestor constituent labels of source language words. We find that NMT encoders learn similar source syntax regardless of NMT target language, relying on explicit morphosyntactic cues to extract syntactic features from source sentences. Furthermore, the NMT encoders outperform RNNs trained directly on several of the constituent label prediction tasks, suggesting that NMT encoder representations can be used effectively for natural language tasks involving syntax. However, both the NMT encoders and the directly-trained RNNs learn substantially different syntactic information from a probabilistic context-free grammar (PCFG) parser. Despite lower overall accuracy scores, the PCFG often performs well on sentences for which the RNN-based models perform poorly, suggesting that RNN architectures are constrained in the types of syntax they can learn.
T Helper Plasticity Is Orchestrated by STAT3, Bcl6, and Blimp-1 Balancing Pathology and Protection in Malaria.

Summary Hybrid Th1/Tfh cells (IFN-γ+IL-21+CXCR5+) predominate in response to several persistent infections. In Plasmodium chabaudi infection, IFN-γ+ T cells control parasitemia, whereas antibody and IL-21+Bcl6+ T cells effect final clearance, suggesting an evolutionary driver for the hybrid population. We found that CD4-intrinsic Bcl6, Blimp-1, and STAT3 coordinately regulate expression of the Th1 master regulator T-bet, supporting plasticity of CD4 T cells. Bcl6 and Blimp-1 regulate CXCR5 levels, and T-bet, IL-27Rα, and STAT3 modulate cytokines in hybrid Th1/Tfh cells. Infected mice with STAT3 knockout (KO) T cells produced less antibody and more Th1-like IFN-γ+IL-21−CXCR5lo effector and memory cells and were protected from re-infection. Conversely, T-bet KO mice had reduced Th1-bias upon re-infection and prolonged secondary parasitemia. Therefore, each feature of the CD4 T cell population phenotype is uniquely regulated in this persistent infection, and the cytokine profile of memory T cells can be modified to enhance the effectiveness of the secondary response.
The P387 thrombospondin-4 variant promotes accumulation of macrophages in atherosclerotic lesions

Thrombospondin-4 (TSP4) is a pro-angiogenic protein that has been implicated in tissue remodeling and local vascular inflammation. TSP4 and, in particular, its SNP variant, P387 TSP4, have been associated with cardiovascular disease. Macrophages are central to initiation and resolution of inflammation and development of atherosclerotic lesions, but the effects of the P387 TSP4 on macrophages remain essentially unknown. We examined the effects of the P387 TSP4 variant on macrophages in cell culture and in vivo in a murine model of atherosclerosis. Furthermore, the levels and distributions of the two TSP4 variants were assessed in human atherosclerotic arteries. In ApoE- /- /P387-TSP4 knock-in mice, lesions size measured by Oil Red O did not change, but the lesions accumulated more macrophages than lesions bearing A387 TSP4. The levels of inflammatory markers were increased in lesions of ApoE- / - /P387-TSP4 knock-in mice compared to ApoE- / - mice. Lesions in human arteries from individuals carrying the P387 variant had higher levels of TSP4 and higher macrophage accumulation. P387 TSP4 was more active in supporting adhesion of cultured human and mouse macrophages in experiments using recombinant TSP4 variants and in cells derived from P387-TSP4 knock-in mice. TSP4 supports the adhesion of macrophages and their accumulation in atherosclerotic lesions without changing the size of lesions. P387 TSP4 is more active in supporting these pro-inflammatory events in the vascular wall, which may contribute to the increased association of P387 TSP4 with cardiovascular disease.
Congruence classes and maximal nonbases

The set A is an asymptotic nonbasis of order h for an additive abelian semigroup X if there are infinitely many elements of X not in the h-fold sumset hA. For all $$h \geq 2$$ , this paper constructs new classes of asymptotic nonbases of order h for Z and for N0 that are not subsets of maximal asymptotic nonbases.
Mountain stoneflies may tolerate warming streams: Evidence from organismal physiology and gene expression.

Rapid glacier recession is altering the physical conditions of headwater streams. Stream temperatures are predicted to rise and become increasingly variable, putting entire meltwater-associated biological communities at risk of extinction. Thus, there is a pressing need to understand how thermal stress affects mountain stream insects, particularly where glaciers are likely to vanish on contemporary timescales. In this study, we measured the critical thermal maximum (CTMAX ) of stonefly nymphs representing multiple species and a range of thermal regimes in the high Rocky Mountains, USA. We then collected RNA-sequencing data to assess how organismal thermal stress translated to the cellular level. Our focal species included the meltwater stonefly, Lednia tumana, which was recently listed under the U.S. Endangered Species Act due to climate-induced habitat loss. For all study species, critical thermal maxima (CTMAX > 20°C) far exceeded the stream temperatures mountain stoneflies experience (<10°C). Moreover, while evidence for a cellular stress response was present, we also observed constitutive expression of genes encoding proteins known to underlie thermal stress (i.e., heat shock proteins) even at low temperatures that reflected natural conditions. We show that high-elevation aquatic insects may not be physiologically threatened by short-term exposure to warm temperatures and that longer-term physiological responses or biotic factors (e.g., competition) may better explain their extreme distributions.
A Generative Approach to Titling and Clustering Wikipedia Sections

We evaluate the performance of transformer encoders with various decoders for information organization through a new task: generation of section headings for Wikipedia articles. Our analysis shows that decoders containing attention mechanisms over the encoder output achieve high-scoring results by generating extractive text. In contrast, a decoder without attention better facilitates semantic encoding and can be used to generate section embeddings. We additionally introduce a new loss function, which further encourages the decoder to generate high-quality embeddings.
Separating overlapped intervals on a line

Given n intervals on a line l, we consider the problem of moving these intervals on l such that after the movement no two intervals overlap and the maximum moving distance of the intervals is minimized. The difficulty for solving the problem lies in determining the order of the intervals in an optimal solution. By interesting observations, we show that it is sufficient to consider at most n “candidate” lists of ordered intervals. Further, although explicitly maintaining these lists takes Ω(n^2) time and space, by more observations and a pruning technique, we present an algorithm that can compute an optimal solution in O(n log n) time and O(n) space. We also prove an Ω(n log n) time lower bound for solving the problem, which implies the optimality of our algorithm.
Supernilpotent Taylor algebras are nilpotent

We develop the theory of the higher commutator for Taylor varieties. A new higher commutator operation called the hypercommutator is defined using a type of invariant relation called a higher dimensional congruence. The hypercommutator is shown to be symmetric and satisfy an inequality relating nested terms. For a Taylor algebra the term condition higher commutator and the hypercommutator are equal when evaluated at a constant tuple, and it follows that every supernilpotent Taylor algebra is nilpotent. We end with a characterization of congruence meet-semidistributive varieties in terms of the neutrality of the higher commutator.
Compressed-Sensing based Beam Detection in 5G NR Initial Access

To support millimeter wave (mmWave) frequency bands in cellular communications, both the base station and the mobile platform utilize large antenna arrays to steer narrow beams towards each other to compensate the path loss and improve communication performance. The time-frequency resource allocated for initial access, however, is limited, which gives rise to need for efficient approaches for beam detection. For hybrid analog-digital beamforming (HB) architectures, which are used to reduce power consumption, we propose a compressed sensing (CS) based approach for 5G initial access beam detection that is for a HB architecture and that is compliant with the 3GPP standard. The CS-based approach is compared with the exhaustive search in terms of beam detection accuracy and by simulation is shown to outperform. Up to 256 antennas are considered, and the importance of a careful codebook design is reaffirmed.
Representative bureaucracy in challenging environments: Gender representation, education, and India

A bureaucracy representative of disadvantaged groups in a society has been linked to better outcomes for those groups in a wide variety of policy areas. Most of the empirical work identifying this ...
How to succeed at Witten diagram recursions without really trying

Witten diagrams are basic objects for studying dynamics in AdS space, and also play key roles in the analytic functional bootstrap. However, these diagrams are notoriously hard to evaluate, making it extremely difficult to search for recursion relations among them. In this note, we present simple methods to obtain recursion relations for exchange Witten diagrams from conformal block recursion relations. We discover a variety of new relations, including the dimensional reduction formulae for exchange Witten diagrams. In particular, we find a five-term recursion relation relating exchange Witten diagrams in d and d − 2 dimensions. This gives the holographic analogue of a similar formula for conformal blocks due to Parisi-Sourlas supersymmetry. We also extend the analysis to two-point functions in CFTs with conformal boundaries, and obtain similar results.
Deep fiducial inference

Since the mid-2000s, there has been a resurrection of interest in modern modifications of fiducial inference. To date, the main computational tool to extract a generalized fiducial distribution is Markov chain Monte Carlo (MCMC). We propose an alternative way of computing a generalized fiducial distribution that could be used in complex situations. In particular, to overcome the difficulty when the unnormalized fiducial density (needed for MCMC), we design a fiducial autoencoder (FAE). The fitted autoencoder is used to generate generalized fiducial samples of the unknown parameters. To increase accuracy, we then apply an approximate fiducial computation (AFC) algorithm, by rejecting samples that when plugged into a decoder do not replicate the observed data well enough. Our numerical experiments show the effectiveness of our FAE-based inverse solution and the excellent coverage performance of the AFC corrected FAE solution.
The initial structure of chondrule dust rims II: Charged grains

Abstract In order to characterize the early growth of fine-grained dust rims (FGRs) that commonly surround chondrules, we simulate the growth of FGRs through direct accretion of monomers of various sizes onto the chondrule surfaces. Dust becomes charged to varying degrees in the radiative plasma environment of the solar nebula (SN), and the resulting electrostatic force alters the trajectories of colliding dust grains, influencing the structure of the dust rim as well as the time scale of rim formation. We compare the growth of FGRs in protoplanetary disks (PPD) with different turbulence strengths and plasma conditions to previous models which assumed neutral dust grains (Xiang, C., Carballido, A., Hanna, R.D., Matthews, L.S., Hyde, T.W., 2019). We use a combination of a Monte Carlo method and an N-body code to simulate the collision of dust monomers of radii 0.5– 10 μ m with chondrules whose radii are between 500 and 1000 μ m: a Monte Carlo algorithm is used to randomly select dust particles that will collide with the chondrule as well as determine the elapsed time interval between collisions; at close approach, the detailed collision process is modeled using an N-body algorithm, Aggregate Builder (AB), to determine the collision outcome, as well as any restructuring of the chondrule rim. For computational expediency, we limit accretion of dust monomers to a small patch of the chondrule surface. The collisions are driven by Brownian motion and coupling to turbulent gas motion in the protoplanetary disk. The charge distribution of the dust rim is modeled, used to calculate the trajectories of dust grains, and then analyze the resulting morphology of the dust rim. In a weakly turbulent region, the decreased relative velocity between charged particles causes small grains to be repelled from the chondrule, causing dust rims to grow more slowly and be composed of larger monomers, which results in a more porous structure. In a highly turbulent region, the presence of charge mainly affects the porosity of the rim by causing dust particles to deviate from the extremities of the rim and reducing the amount of restructuring caused by high-velocity collisions.
Trauma Center Drive Time Distances and Fatal Outcomes among Gunshot Wound Victims

Despite nation-wide decreases in crime, urban gun violence remains a serious and pressing issue in many cities. Victim survival in these incidents is often contingent on the speed and quality of care provided. Increasingly, new research has identified the role that specialized trauma care plays in victim survival from firearm-related injuries. Using nearly four years of data on shooting victimizations in Philadelphia we test whether distance to the nearest level 1 trauma center is associated with victim survival. We employ different distance measures based on straight-line Euclidian distance, street network distances, and drive-time estimates—comparing the predictive accuracy of each. Our results find that victims who are shot farther from trauma centers have an increased likelihood of death, and drive time distances provide the most accurate predictions. We discuss the practical implications of this research as it applies to urban public health.
Epitaxial niobium nitride superconducting nanowire single-photon detectors

Superconducting nanowires used in single-photon detectors have been realized on amorphous or poly-crystalline films. Here, we report the first use of single-crystalline NbN thin films for superconducting nanowire single-photon detectors (SNSPDs). Grown by molecular beam epitaxy (MBE) at high temperature on nearly lattice-matched AlN-on-sapphire substrates, the NbN films exhibit a high degree of uniformity and homogeneity. Even with relatively thick films, the fabricated nanowire detectors show saturated internal efficiency at near-IR wavelengths, demonstrating the potential of MBE-grown NbN for realizing large arrays of on-chip SNSPDs and their integration with AlN-based χ ( 2 ) quantum photonic circuits.
The Economics of the Fed Put

Since the mid-1990s, negative stock returns comove with downgrades to the Fed’s growth expectations and predict policy accommodations. Textual analysis of FOMC documents reveals that policy makers pay attention to the stock market. The primary mechanism is their concern with the consumption wealth effect, with a secondary role for the market predicting the economy. We find little evidence of the Fed overreacting to the market in an ex post sense (reacting beyond the market’s effect on growth expectations). Although policy makers are aware that the Fed put could induce risk-taking, moral hazard considerations appear not to significantly affect their decision-making ex ante.
Unsupervised Learning of Interpretable Dialog Models

Recently several deep learning based models have been proposed for end-to-end learning of dialogs. While these models can be trained from data without the need for any additional annotations, it is hard to interpret them. On the other hand, there exist traditional state based dialog systems, where the states of the dialog are discrete and hence easy to interpret. However these states need to be handcrafted and annotated in the data. To achieve the best of both worlds, we propose Latent State Tracking Network (LSTN) using which we learn an interpretable model in unsupervised manner. The model defines a discrete latent variable at each turn of the conversation which can take a finite set of values. Since these discrete variables are not present in the training data, we use EM algorithm to train our model in unsupervised manner. In the experiments, we show that LSTN can help achieve interpretability in dialog models without much decrease in performance compared to end-to-end approaches.
Histopathology of Third Trimester Placenta from SARS-CoV-2-Positive Women.

This study aims to investigate whether maternal SARS-CoV-2 status affects placental pathology. Methods: A retrospective case-control study was conducted by reviewing charts and slides of placentas ...
Democratic Party Control Reduces Gender Inequality

Women earn less than men who work in the same job with the same level of experience. We know much about this gender wage gap but relatively little about its political or partisan sources. In this article, we examine the effects of party control of state government on gender inequality in income, wages, unemployment, and poverty. Employing both a regression discontinuity design and a dynamic difference-in-difference analysis, we find that electing a Democratic majority to the state house leads to substantial improvement in women’s incomes, wages, and unemployment relative to men – especially in recent years. We also show that greater female representation in office and more liberal policy-making on policies related to women’s rights could be driving that process. We find, however, fewer clear effects on poverty and less robust results for partisan control of the governor’s office or the state senate. Parties and politics matter, but not always.
Adversarial T-shirt! Evading Person Detectors in A Physical World

It is known that deep neural networks (DNNs) are vulnerable to adversarial attacks. The so-called physical adversarial examples deceive DNN-based decision makers by attaching adversarial patches to real objects. However, most of the existing works on physical adversarial attacks focus on static objects such as glass frames, stop signs and images attached to cardboard. In this work, we propose Adversarial T-shirts, a robust physical adversarial example for evading person detectors even if it could undergo non-rigid deformation due to a moving person’s pose changes. To the best of our knowledge, this is the first work that models the effect of deformation for designing physical adversarial examples with respect to non-rigid objects such as T-shirts. We show that the proposed method achieves 74% and 57% attack success rates in the digital and physical worlds respectively against YOLOv2. In contrast, the state-of-the-art physical attack method to fool a person detector only achieves 18% attack success rate. Furthermore, by leveraging min-max optimization, we extend our method to the ensemble attack setting against two object detectors YOLO-v2 and Faster R-CNN simultaneously.
SQUIRREL: Testing Database Management Systems with Language Validity and Coverage Feedback

Fuzzing is an increasingly popular technique for verifying software functionalities and finding security vulnerabilities. However, current mutation-based fuzzers cannot effectively test database management systems (DBMSs), which strictly check inputs for valid syntax and semantics. Generation-based testing can guarantee the syntax correctness of the inputs, but it does not utilize any feedback, like code coverage, to guide the path exploration. In this paper, we develop Squirrel, a novel fuzzing framework that considers both language validity and coverage feedback to test DBMSs. We design an intermediate representation (IR) to maintain SQL queries in a structural and informative manner. To generate syntactically correct queries, we perform type-based mutations on IR, including statement insertion, deletion and replacement. To mitigate semantic errors, we analyze each IR to identify the logical dependencies between arguments, and generate queries that satisfy these dependencies. We evaluated Squirrel on four popular DBMSs: SQLite, MySQL, PostgreSQL and MariaDB. Squirrel found 51 bugs in SQLite, 7 in MySQL and 5 in MariaDB. 52 of the bugs are fixed with 12 CVEs assigned. In our experiment, Squirrel achieves 2.4×-243.9× higher semantic correctness than state-of-the-art fuzzers, and explores 2.0×-10.9× more new edges than mutation-based tools. These results show that Squirrel is effective in finding memory errors of database management systems.
An Analytical Portrait of Binary Mergers in Hierarchical Triple Systems

With better statistics and precision, eccentricity could prove to be a useful tool for understanding the origin and environment of binary black holes. Hierarchical triples in particular, which might be abundant in globular clusters and galactic nuclei, could generate observably large eccentricity at LIGO and future gravitational wave detectors. Measuring the eccentricity distribution accurately could help us probe the background and the formation of the mergers. In this paper we continue our previous investigation and improve our semianalytical description of the eccentricity distribution of mergers of hierarchical triple systems. Our result, which further reduces the reliance on numerical simulations, could be useful for statistically distinguishing different formation channels of observed binary mergers.
DEGREE PROFILE OF m-ARY SEARCH TREES: A VEHICLE FOR DATA STRUCTURE COMPRESSION

We revisit the random m-ary search tree and study a finer profile of its node outdegrees with the purpose of exploring possibilities of data structure compression. The analysis is done via Polya urns. The analysis shows that the number of nodes of each individual node outdegree has a phase transition: Up to m = 26, the number of nodes of outdegree k, for k = 0, 1, …, m, is asymptotically normal; that behavior changes at m = 27. Based on the analysis, we propose a compact m-ary tree that offers significant space saving.
DYNAMICAL CAPTURE BINARY NEUTRON STAR MERGERS

We study dynamical capture binary neutron star mergers as may arise in dense stellar regions such as globular clusters. Using general-relativistic hydrodynamics, we find that these mergers can result in the prompt collapse to a black hole or in the formation of a hypermassive neutron star, depending not only on the neutron star equation of state but also on impact parameter. We also find that these mergers can produce accretion disks of up to a tenth of a solar mass and unbound ejected material of up to a few percent of a solar mass. We comment on the gravitational radiation and electromagnetic transients that these sources may produce.
Contextual Reserve Price Optimization in Auctions via Mixed Integer Programming

We study the problem of learning a linear model to set the reserve price in an auction, given contextual information, in order to maximize expected revenue from the seller side. First, we show that it is not possible to solve this problem in polynomial time unless the \emph{Exponential Time Hypothesis} fails. Second, we present a strong mixed-integer programming (MIP) formulation for this problem, which is capable of exactly modeling the nonconvex and discontinuous expected reward function. Moreover, we show that this MIP formulation is ideal (i.e. the strongest possible formulation) for the revenue function of a single impression. Since it can be computationally expensive to exactly solve the MIP formulation in practice, we also study the performance of its linear programming (LP) relaxation. Though it may work well in practice, we show that, unfortunately, in the worst case the optimal objective of the LP relaxation can be O(number of samples) times larger than the optimal objective of the true problem. Finally, we present computational results, showcasing that the MIP formulation, along with its LP relaxation, are able to achieve superior in- and out-of-sample performance, as compared to state-of-the-art algorithms on both real and synthetic datasets. More broadly, we believe this work offers an indication of the strength of optimization methodologies like MIP to exactly model intrinsic discontinuities in machine learning problems.
On Lipschitz retraction of finite subsets of normed spaces

If X is a metric space, then its finite subset spaces X(n) form a nested sequence under natural isometric embeddings X = X(1) ⊂ X(2) ⊂ ・ ・ ・. It was previously established, by Kovalev when X is a Hilbert space and by Bacak and Kovalev when X is a CAT(0) space, that this sequence admits Lipschitz retractions X(n) → X(n − 1) for all n ≥ 2. We prove that when X is a normed space, the above sequence admits Lipschitz retractions X(n) → X, X(n) → X(2), as well as concrete retractions X(n) → X(n − 1) that are Lipschitz if n = 2,3 and Holder-continuous on bounded sets if n > 3. We also prove that if X is a geodesic metric space, then each X(n) is a 2-quasiconvex metric space. These results are relevant to certain questions in the aforementioned previous work which asked whether Lipschitz retractions X(n) → X(n − 1), n ≥ 2, exist for X in more general classes of Banach spaces.
Distances to the High Galactic Latitude Molecular Clouds G192–67 and MBM 23-24

We report on distance determinations for two high-Galactic latitude cloud complexes, G192-67 and MBM 23-24. No distance determination exists in the literature for either cloud. Thirty-four early-type stars were observed toward the two clouds, more than half of which have parallaxes measured by the Hipparcos satellite. For the remaining stars, we have made spectroscopic distance estimates. The data consist of high-resolution echelle spectra centered on the Na I D lines and were obtained over six nights at the Coude Feed telescope at Kitt Peak National Observatory. Interstellar absorption lines were detected toward some of the stars, which enabled estimates of the distances to the clouds of 109±14 pc for G192-67 and 139±33 pc for MBM 23-24. We discuss the relationship of these clouds to other ISM features such as the Local Hot Bubble and the local cavity in neutral hydrogen.
Bergman Subspaces and Subkernels: Degenerate $$L^p$$ Mapping and Zeroes

Regularity and irregularity of the Bergman projection on \(L^p\) spaces is established on a natural family of bounded, pseudoconvex domains. The family is parameterized by a real variable \(\gamma \). A surprising consequence of the analysis is that, whenever \(\gamma \) is irrational, the Bergman projection is bounded only for \(p=2\).
Pileup Mitigation with Machine Learning (PUMML)

Pileup involves the contamination of the energy distribution arising from the primary collision of interest (leading vertex) by radiation from soft collisions (pileup). We develop a new technique for removing this contamination using machine learning and convolutional neural networks. The network takes as input the energy distribution of charged leading vertex particles, charged pileup particles, and all neutral particles and outputs the energy distribution of particles coming from leading vertex alone. The PUMML algorithm performs remarkably well at eliminating pileup distortion on a wide range of simple and complex jet observables. We test the robustness of the algorithm in a number of ways and discuss how the network can be trained directly on data.
Group Strategyproof Pareto-Stable Marriage with Indifferences via the Generalized Assignment Game

We study the variant of the stable marriage problem in which the preferences of the agents are allowed to include indifferences. We present a mechanism for producing Pareto-stable matchings in stable marriage markets with indifferences that is group strategyproof for one side of the market. Our key technique involves modeling the stable marriage market as a generalized assignment game. We also show that our mechanism can be implemented efficiently. These results can be extended to the college admissions problem with indifferences.
Magnetospheric Scattering and Emission in Millisecond Pulsars

We model the formation of magnetospheric components of millisecond pulsar light curves, deriving an approximate model for the curved space, "swept-back" dipole field and following photon emission, propagation, and scattering. Magnetospheric pulse components are strongly affected by rapid rotation and Schwarzschild effects.
Exponential Stellar Disks in Low Surface Brightness Galaxies: A Critical Test of Viscous Evolution

Viscous redistribution of mass in Milky Way-type galactic disks is an appealing way of generating an exponential stellar profile over many scale lengths, almost independent of initial conditions, requiring only that the viscous timescale and star formation timescale are approximately equal. However, galaxies with solid-body rotation curves cannot undergo viscous evolution. Low surface brightness (LSB) galaxies have exponential surface brightness profiles, yet have slowly rising, nearly solid-body rotation curves. Because of this, viscous evolution may be inefficient in LSB galaxies: the exponential profiles, instead, would give important insight into initial conditions for galaxy disk formation. Using star formation laws from the literature and tuning the efficiency of viscous processes to reproduce an exponential stellar profile in Milky Way-type galaxies, I test the role of viscous evolution in LSB galaxies. Under the conservative and not unreasonable condition that LSB galaxies are gravitationally unstable for at least a part of their lives, I find that it is impossible to rule out a significant role for viscous evolution. This type of model still offers an attractive way of producing exponential disks, even in LSB galaxies with slowly rising rotation curves.
A Deep X-Ray View of the Synchrotron-dominated Supernova Remnant G330.2+1.0

We present moderately deep (125 ks) XMM-Newton observations of supernova remnant G330.2+1.0. This remnant is one of only a few known that fall into the "synchrotron-dominated" category, with the emission almost entirely dominated by a nonthermal continuum. Previous X-ray observations could only characterize the spectra of a few regions. Here, we examine the spectra from 14 regions surrounding the entire rim, finding that the spectral properties of the nonthermal emission do not vary significantly in any systematic way from one part of the forward shock to another, unlike several other remnants of this class. We confirm earlier findings that the power-law index, Γ, ranges from about 2.1-2.5, while the absorbing column density is generally between (2.0-2.6) × 10(exp 22) cm(exp -2). Fits with the srcut model find values of the roll-off frequency in the range of 10(exp 17.1)-10(exp 17.5) Hz, implying energies of accelerated electrons of approximately 100 TeV. These values imply a high shock velocity of approximately 4600 km s(exp -1), favoring a young age of the remnant. Diffuse emission from the interior is nonthermal in origin as well, and fits to these regions yield similar values to those along the rim, also implying a young age. Thermal emission is present in the east, and the spectrum is consistent with approximately 650 km s(exp -1) shock wave encountering interstellar or circumstellar material with a density of approximately 1 cm(exp -3).
Modelling magnetically dominated and radiatively cooling jets

Using 3D-MHD Eulerian-grid numerical simulations, we study the formation and evolution of rising magnetic towers propagating into an ambient medium. The towers are gener- ated from a localized injection of pure magnetic energy. No rotation is imposed on the plasma. We compare the evolution of a radiatively cooling tower with an adiabatic one, and find that both bend due to pinch instabilities. Collimation is stronger in the radiative cooling case; the adiabatic tower tends to expand radially. Structural similarities are found between these towers and the millimeter scale magnetic towers produced in laboratory experiments.
Resolving the source populations that contribute to the X-ray background: The 2 Ms Chandra Deep Field-North Survey

With ≈ 2 Ms of exposure, the Chandra Deep Field-North (CDF-N) survey provides the deepest view of the Universe in the 0.5–8.0 keV band. Five hundred and three (503) X-ray sources are detected down to on-axis 0.5–2.0 keV and 2–8 keV flux limits of ≈ 1.5 × 10–17 erg cm–2 s–1 and ≈ 1.0 × 10–16 erg cm–2 s–1, respectively. These flux limits correspond to L0.5–8.0 keV≈ 3 × 1041 erg s–1 at z = 1 and L0.5–8.0 keV≈ 2 × 1043 erg s–1 at z = 6; thus this survey is sensitive enough to detect starburst galaxies out to moderate redshift and Seyfert galaxies out to high redshift.We present the X-ray observations, describe the broad diversity of X-ray selected sources, and review the prospects for deeper exposures.
Dislocation-Induced Anomalous Softening of Solid Helium

The classical motion of gliding dislocation lines in slip planes of crystalline solid helium leads to plastic deformation even at temperatures far below the Debye temperature and can affect elastic properties. In this work we propose that the gliding of dislocations and plasticity may be the origin of many observed elastic anomalies in solid 4He, which have been argued to be connected to supersolidity. We present a dislocation motion model that describes the stress-strain τ–e curves and work-hardening rate dτ/de of a shear experiment performed at constant strain rate in solid helium. The calculated dτ/de exhibits strong softening with increasing temperature owing to the motion of dislocations, which mimics anomalous softening of the elastic shear modulus μ. In the same temperature region the motion of dislocations causes dissipation with a prominent peak.
Gluon Vortices and Induced Magnetic Field in Compact Stars

The natural candidates for the realization of color superconductivity are the extremely dense cores of compact stars, many of which have very large magnetic fields, especially the so called magnetars. In this paper we discuss how a color superconducting core can serve to generate and enhance the stellar magnetic field without appealing to a magnetohydrodynamic dynamo mechanism.
A Survey for New Members of Taurus from Stellar to Planetary Masses

NASA [80NSSC18 K0444, NNH14CK55B]; NASA; University of Texas at Austin McDonald Observatory; Pennsylvania State University; Department of Astronomy; National Development and Reform Commission; NSF; Alfred P. Sloan Foundation; U.S. Department of Energy; Japanese Monbukagakusho; Max Planck Society; Higher Education Funding Council for England; American Museum of Natural History; Astrophysical Institute Potsdam; University of Basel; University of Cambridge; Case Western Reserve University; University of Chicago; Drexel University; Fermilab; Institute for Advanced Study; Japan Participation Group; Johns Hopkins University; Joint Institute for Nuclear Astrophysics; Kavli Institute for Particle Astrophysics and Cosmology; Korean Scientist Group; Chinese Academy of Sciences; Los Alamos National Laboratory; Max-Planck-Institute for Astronomy; Max-Planck-Institute for Astrophysics; Ohio State University; University of Pittsburgh; University of Portsmouth; Princeton University; United States Naval Observatory; University of Washington; National Aeronautics and Space Administration [NNX08AR22G]; NSF [AST-1238877]; Eberly College of Science; Pennsylvania Space Grant Consortium; New Mexico State University; [U/17B/UA05]; [GN-2017B-Q-8]; [GN-2018B-Q-114]; [GN-2018B-FT-205]; [GN-2018B-FT-207]
Classification of Some Solvable Leibniz Algebras

Leibniz algebras are certain generalization of Lie algebras. In this paper we give classification of non-Lie solvable (left) Leibniz algebras of dimension ≤ 8 with one dimensional derived subalgebra. We use the canonical forms for the congruence classes of matrices of bilinear forms to obtain our result. Our approach can easily be extended to classify these algebras of higher dimensions. We also revisit the classification of three dimensional non-Lie solvable (left) Leibniz algebras.
Gravity darkening and brightening in binaries

We apply a von Zeipel gravity darkening model to corotating binaries to obtain a simple, analytical expression for the emergent radiative flux from a tidally distorted primary orbiting a point-mass secondary. We adopt a simple Roche model to determine the envelope structure of the primary, assumed massive and centrally condensed, and use the results to calculate the flux. As for single rotating stars, gravity darkening reduces the flux along the stellar equator of the primary, but, unlike for rotating stars, we find that gravity brightening enhances the flux in a region around the stellar poles. We identify a critical limiting separation beyond which hydrostatic equilibrium no longer is possible, whereby the flux vanishes at the point on the stellar equator of the primary facing the companion. For equal-mass binaries, the total luminosity is reduced by about 13% when this limiting separation is reached.
Observation of a ferro-rotational order coupled with second-order nonlinear optical fields

Ferroic orders can be classified by the symmetry of their order parameters, and ferroelectric, ferromagnetic and ferro-toroidal orders have already been observed. The ferro-rotational order1–3, whose order parameter is an axial vector invariant under both time-reversal and spatial-inversion operations, is the final ferroic to be identified and has a vector order parameter. This order is closely related to a number of phenomena such as polar vortices4, giant magnetoelectric coupling5 and spin-helicity-driven ferroelectricity6, but it has received little attention so far. Here, using high-sensitivity rotational-anisotropy second-harmonic generation, we have exploited the electric quadrupole contribution to the second-harmonic generation to directly couple to this centrosymmetric ferro-rotational order in an archetype of type-II multiferroics, RbFe(MoO4)2. We found that two domain states with opposite ferro-rotational vectors emerge with distinct populations at the critical temperature Tc ≈ 195 K and gradually evolve to reach an even ratio at lower temperatures. Moreover, we have identified the ferro-rotational order phase transition as weakly first order and have revealed its coupling field as a unique combination of the induced electric quadrupole second-harmonic generation and the incident fundamental electric fields. The authors use optical spectroscopy to show that RbFe(MoO4)2 hosts a ferro-rotational phase. This is the final form of ferroic order to be observed.
Non-Gaussian Mode Coupling and the Statistical Cosmological Principle

Local-type primordial non-Gaussianity couples statistics of the curvature perturbation ζ on vastly different physical scales. Because of this coupling, statistics (i.e. the polyspectra) of ζ in our Hubble volume may not be representative of those in the larger universe — that is, they may be biased. The bias depends on the local background value of ζ, which includes contributions from all modes with wavelength kH0 and is therefore enhanced if the entire post-inflationary patch is large compared with our Hubble volume. We study the bias to locally-measured statistics for general local-type non-Gaussianity. We consider three examples in detail: (i) the usual fNL, gNL model, (ii) a strongly non-Gaussian model with ζ ~ ζGp, and (iii) two-field non-Gaussian initial conditions. In each scenario one may generate statistics in a Hubble-size patch that are weakly Gaussian and consistent with observations despite the fact that the statistics in the larger, post-inflationary patch look very different.
A unified and improved Chebotarev density theorem

We establish an unconditional effective Chebotarev density theorem that improves uniformly over the well-known result of Lagarias and Odlyzko. As a consequence, we give a new asymptotic form of the Chebotarev density theorem that can count much smaller primes with arbitrary log-power savings, even in the case where a Landau–Siegel zero is present. Our main theorem also interpolates the strongest unconditional upper bound for the least prime ideal with a given Artin symbol as well as the Chebotarev analogue of the Brun–Titchmarsh theorem proved by the authors.
Rényi’s parking problem revisited

Renyi’s parking problem (or 1D sequential interval packing problem) dates back to 1958, when Renyi studied the following random process: Consider an interval I of length x, and sequentially and randomly pack disjoint unit intervals in I until the remaining space prevents placing any new segment. The expected value of the measure of the covered part of I is M(x), so that the ratio M(x)/x is the expected filling density of the random process. Following recent work by Gargano et al. [4], we studied the discretized version of the above process by considering the packing of the 1D discrete lattice interval {1, 2,…,n + 2k − 1} with disjoint blocks of (k + 1) integers but, as opposed to the mentioned [4] result, our exclusion process is symmetric, hence more natural. Furthermore, we were able to obtain useful recursion formulas for the expected number of r-gaps (0 ≤ r ≤ k) between neighboring blocks. We also provided very fast converging series and extensive computer simulations for these expected numbers, so that the limiting filling density of the long line segment (as n →∞) is Renyi’s famous parking constant, 0.7475979203….
Scattered results in 2D string theory

The nonperturbative 1→N tachyon scattering amplitude in 2D type 0A string theory is computed. The probability that N particles are produced is a monotonically decreasing function of N whenever N is large enough that statistical methods apply. The results are compared with expectations from black hole thermodynamics.
A flexible high-performance simulator for verifying and benchmarking quantum circuits implemented on real hardware

Here we present qFlex, a flexible tensor network-based quantum circuit simulator. qFlex can compute both the exact amplitudes, essential for the verification of the quantum hardware, as well as low-fidelity amplitudes, to mimic sampling from Noisy Intermediate-Scale Quantum (NISQ) devices. In this work, we focus on random quantum circuits (RQCs) in the range of sizes expected for supremacy experiments. Fidelity f simulations are performed at a cost that is 1/f lower than perfect fidelity ones. We also present a technique to eliminate the overhead introduced by rejection sampling in most tensor network approaches. We benchmark the simulation of square lattices and Google’s Bristlecone QPU. Our analysis is supported by extensive simulations on NASA HPC clusters Pleiades and Electra. For our most computationally demanding simulation, the two clusters combined reached a peak of 20 Peta Floating Point Operations per Second (PFLOPS) (single precision), i.e., 64% of their maximum achievable performance, which represents the largest numerical computation in terms of sustained FLOPs and the number of nodes utilized ever run on NASA HPC clusters. Finally, we introduce a novel multithreaded, cache-efficient tensor index permutation algorithm of general application.
The tame-wild principle for discriminant relations for number fields

Consider tuples (K1;:::;Kr) of separable algebras over a com- mon local or global number eld F , with the Ki related to each other by specied resolvent constructions. Under the assumption that all ramication is tame, simple group-theoretic calculations give best possible divisibility re- lations among the discriminants of Ki=F. We show that for many resolvent constructions, these divisibility relations continue to hold even in the presence of wild ramication.
The Structure of Cooling Fronts in Accretion Disks

Recent work has shown that the speed of the cooling front in soft X-ray transients may be an important clue in understanding the nature of accretion disk viscosity. In a previous paper (Vishniac & Wheeler), we derived the scaling law for the cooling front speed. Here we derive a similarity solution for the hot inner part of disks undergoing cooling. This solution is exact in the limit of a thin disk, power-law opacities, and a minimum hot state column density, which is an infinitesimal fraction of the maximum cold state density. For a disk of finite thickness, the largest error is in the ratio of the mass flow across the cooling front to the mass flow at small radii. Comparison to the numerical simulations of Cannizzo et al. indicates that the errors in other parameters do not exceed (csF/rFΩF)q, that is, the ratio of the sound speed at the disk midplane to its orbital velocity, evaluated at the cooling front, to the qth power. Here q ≈ ½. Its precise value is determined by the relevant hot state opacity law and the functional form of the dimensionless viscosity.
Cohomology for infinitesimal unipotent algebraic and quantum groups

In this paper we study the structure of cohomology spaces for the Frobenius kernels of unipotent and parabolic algebraic group schemes and of their quantum analogs. Given a simple algebraic group G, a parabolic subgroup PJ, and its unipotent radical UJ, we determine the ring structure of the cohomology ring H•((UJ)1, k). We also obtain new results on computing H•((PJ)1, L(λ)) as an LJ-module where L(λ) is a simple G-module with highest weight λ in the closure of the bottom p-alcove. Finally, we provide generalizations of all our results to small quantum groups at a root of unity.
On the self-intersections of curves deep in the lower central series of a surface group

We give various estimates of the minimal number of self-intersections of a nontrivial element of the kth term of the lower central series and derived series of the fundamental group of a surface. As an application, we obtain a new topological proof of the fact that free groups and fundamental groups of closed surfaces are residually nilpotent. Along the way, we prove that a nontrivial element of the kth term of the lower central series of a nonabelian free group has to have word length at least k in a free generating set.