cssi/SciSciGPT-SciSciNet huggingface dataset:
IRIS-FGM: an integrative single-cell RNA-Seq interpretation system for functional gene module analysis

Motivation Single-cell RNA-Seq (scRNA-Seq) data is useful in discovering cell heterogeneity and signature genes in specific cell populations in cancer and other complex diseases. Specifically, the investigation of condition-specific functional gene modules (FGM) can help to understand interactive gene networks and complex biological processes in different cell clusters. QUBIC2 is recognized as one of the most efficient and effective biclustering tools for condition-specific FGM identification from scRNA-Seq data. However, its limited availability to a C implementation restricted its application to only a few downstream analysis functionalities. We developed an R package named IRIS-FGM (Integrative scRNA-Seq Interpretation System for Functional Gene Module analysis) to support the investigation of FGMs and cell clustering using scRNA-Seq data. Empowered by QUBIC2, IRIS-FGM can effectively identify condition-specific FGMs, predict cell types/clusters, uncover differentially expressed genes, and perform pathway enrichment analysis. It is noteworthy that IRIS-FGM can also take Seurat objects as input, facilitating easy integration with the existing analysis pipeline. Availability and implementation IRIS-FGM is implemented in the R environment (as of version 3.6) with the source code freely available at https://github.com/BMEngineeR/IRISFGM. Supplementary information Supplementary data are available at Bioinformatics online.
Relativistic winds from compact gamma-ray sources. II. Pair loading and radiative acceleration in gamma-ray bursts

We consider the effects of rapid pair creation by an intense pulse of γ-rays propagating ahead of a relativistic shock. Sidescattered photons colliding with the main γ-ray beam amplify the density of scattering charges. The acceleration rate of the pair-loaded medium is calculated and its limiting bulk Lorentz factor related to the spectrum and compactness of the photon source. One obtains, as a result, a definite prediction for the relative inertia in baryons and pairs. The deceleration of a relativistic shock in the moving medium and the resulting synchrotron emissivity are compared with existing results for a static medium. The radiative efficiency is increased dramatically by pair loading. When the initial ambient density exceeds a critical value, the scattering depth traversed by the main γ-ray pulse rises above unity and the pulse is broadened. This sets an upper limit to the preburst mass-loss rate of ~10-5 M☉ per year and places significant constraints on γ-ray burst progenitors. An anisotropic γ-ray flux (on an angular scale Γ-1 or larger) drives a large velocity shear that greatly increases the energy in the seed magnetic field forward of the propagating shock.
NUCLEATION AND STABILIZATION OF CARBON-RICH STRUCTURES IN INTERSTELLAR MEDIA

We study the conditions under which carbon clusters of different sizes form and stabilize. We describe the approach to equilibrium by simulating tenuous carbon gas dynamics to long times. First, we use reactive molecular dynamics simulations to describe the nucleation of long chains, large clusters, and complex cage structures in carbon- and hydrogen-rich interstellar gas phases. We study how temperature, particle density, the presence of hydrogen, and carbon inflow affect the nucleation of molecular moieties with different characteristics, in accordance with astrophysical conditions. We extend the simulations to densities that are orders of magnitude lower than current laboratory densities, to temperatures that are relevant to circumstellar environments of planetary nebulae, and microsecond formation times. We correlate cluster size distributions from the simulations with thermodynamic equilibrium at low temperatures and gas densities, where entropy plays a significant role.
On the rigidity of mean convex self-shrinkers

Self-shrinkers model singularities of the mean curvature flow; they are defined as the special solutions that contract homothetically under the flow. Colding-Ilmanen-Minicozzi showed that cylindrical self-shrinkers are rigid in a strong sense - that is, any self-shrinker that is mean convex with uniformly bounded curvature on a large, but compact, set must be a round cylinder. Using this result, Colding and Minicozzi were able to establish uniqueness of blowups at cylindrical singularities, and provide a detailed description of the singular set of generic mean curvature flows. In this paper, we show that the bounded curvature assumption is unnecessary for the rigidity of the cylinder if either n is at most 6, or if the mean curvature is bounded below by a positive constant. These results follow from curvature estimates that we prove for strictly mean convex self-shrinkers. We also obtain a rigidity theorem in all dimensions for graphical self-shrinkers, and curvature estimates for translators of the mean curvature flow.
On the Automatic Generation of Medical Imaging Reports

Medical imaging is widely used in clinical practice for diagnosis and treatment. Report-writing can be error-prone for unexperienced physicians, and time-consuming and tedious for experienced physicians. To address these issues, we study the automatic generation of medical imaging reports. This task presents several challenges. First, a complete report contains multiple heterogeneous forms of information, including findings and tags. Second, abnormal regions in medical images are difficult to identify. Third, the reports are typically long, containing multiple sentences. To cope with these challenges, we (1) build a multi-task learning framework which jointly performs the prediction of tags and the generation of paragraphs, (2) propose a co-attention mechanism to localize regions containing abnormalities and generate narrations for them, (3) develop a hierarchical LSTM model to generate long paragraphs. We demonstrate the effectiveness of the proposed methods on two publicly available dataset.
Lattice charge overlap: towards the elastic limit

Abstract A numerical investigation of time-separated charge overlap measurements is carried out for the pion in the context of lattice QCD using smeared Wilson fermions. The evolution of the charge distribution function is examined and the expected asymptotic time behavior ∼exp[−(Eq−mπt], where t represents the charge density relative time separation, is clearly visible in the Fo urier transform. Values of the pion form factor are extracted using point-to-smeared correlation functions and are seen to be consistent with the expected monopole form from vector dominance. The implications of these results for hadron structure calculations is briefly discussed.
Two-Black-Hole Bound States

The quantum mechanics of N slowly-moving BPS black holes in five dimensions is considered. A divergent continuum of states describing arbitrarily closely bound black holes with arbitrarily small excitation energies is found. A superconformal structure appears at low energies and can be used to define an index counting the weighted number of supersymmetric bound states. It is shown that the index is determined from the dimensions of certain cohomology classes on the symmetric product of N copies of 4. An explicit computation for the case of N = 2 with no angular momentum yields a finite nonzero result.
A generating set for the palindromic Torelli group

A palindrome in a free group Fn is a word on some fixed free basis of Fn that reads the same backwards as forwards. The palindromic automorphism group ΠAn of the free group Fn consists of automorphisms that take each member of some fixed free basis of Fn to a palindrome; the group ΠAn has close connections with hyperelliptic mapping class groups, braid groups, congruence subgroups of GL(n,Z), and symmetric automorphisms of free groups. We obtain a generating set for the subgroup of ΠAn consisting of those elements that act trivially on the abelianisation of Fn, the palindromic Torelli group PIn. The group PIn is a free group analogue of the hyperelliptic Torelli subgroup of the mapping class group of an oriented surface. We obtain our generating set by constructing a simplicial complex on which PIn acts in a nice manner, adapting a proof of Day–Putman [11]. The generating set leads to a finite presentation of the principal level 2 congruence subgroup of GL(n,Z).
Operationalizing the AAPT Learning Goals for the Lab

Calls for reform to instructional labs mean many instructors and departments are facing the daunting task of identifying goals for their introductory lab courses. Fortunately, the American Association of Physics Teachers (AAPT) released a set of recommendations for learning goals for the lab to support lab redevelopment. Here we outline the process we have undergone to identify a set of learning goals for the labs that operationalize those provided by the AAPT. We also provide two examples of newly developed lab activities that aim to meet those goals to demonstrate this operationalization. We aim to provide departments and instructors with a few ideas of a procedure that they can follow or a set of goals that they can use to align lab instruction with the AAPT learning goals.
Quantum mechanics on York slices

For some time the York time parameter has been identified as a candidate for a physically meaningful time in cosmology. An associated Hamiltonian may be found by solving the Hamiltonian constraint for the momentum conjugate to the York time variable, although an explicit solution can only be found in highly symmetric cases. The Poisson structure of the remaining variables is not canonical. Here we quantise this dynamics in an anisotropic minisuperspace model via a natural extension of canonical quantisation. The resulting quantum theory has no momentum representation. Instead the position basis takes a fundamental role. We illustrate how the quantum theory and the modified representation of its momentum operators lead to a consistent theory in the presence of the constraints that arose during the Hamiltonian reduction. The quantised reduced Hamiltonian is Hermitian, although the momentum operators are not, the causes and implications of which we discuss. We are able to solve for the eigenspectrum of the Hamiltonian. Finally we discuss how far the results of this model extend to the general non-homogeneous case, in particular perturbation theory with York time.
Spectral proper orthogonal decomposition and its relationship to dynamic mode decomposition and resolvent analysis

We consider the frequency domain form of proper orthogonal decomposition (POD), called spectral proper orthogonal decomposition (SPOD). Spectral POD is derived from a space–time POD problem for statistically stationary flows and leads to modes that each oscillate at a single frequency. This form of POD goes back to the original work of Lumley (Stochastic Tools in Turbulence, Academic Press, 1970), but has been overshadowed by a space-only form of POD since the 1990s. We clarify the relationship between these two forms of POD and show that SPOD modes represent structures that evolve coherently in space and time, while space-only POD modes in general do not. We also establish a relationship between SPOD and dynamic mode decomposition (DMD); we show that SPOD modes are in fact optimally averaged DMD modes obtained from an ensemble DMD problem for stationary flows. Accordingly, SPOD modes represent structures that are dynamic in the same sense as DMD modes but also optimally account for the statistical variability of turbulent flows. Finally, we establish a connection between SPOD and resolvent analysis. The key observation is that the resolvent-mode expansion coefficients must be regarded as statistical quantities to ensure convergent approximations of the flow statistics. When the expansion coefficients are uncorrelated, we show that SPOD and resolvent modes are identical. Our theoretical results and the overall utility of SPOD are demonstrated using two example problems: the complex Ginzburg–Landau equation and a turbulent jet.
Modifying quantum walks: a scattering theory approach

We show how to construct discrete-time quantum walks on directed, Eulerian graphs. These graphs have tails on which the particle making the walk propagates freely, and this makes it possible to analyze the walks in terms of scattering theory. The probability of entering a graph from one tail and leaving from another can be found from the scattering matrix of the graph. We show how the scattering matrix of a graph that is an automorphic image of the original is related to the scattering matrix of the original graph, and we show how the scattering matrix of the reverse graph is related to that of the original graph. Modifications of graphs and the effects of these modifications are then considered. In particular we show how the scattering matrix of a graph is changed if we remove two tails and replace them with an edge or cut an edge and add two tails. This allows us to combine graphs, that is if we connect two graphs we can construct the scattering matrix of the combined graph from those of its parts. Finally, using these techniques, we show how two graphs can be compared by constructing a larger graph in which the two original graphs are in parallel, and performing a quantum walk on the larger graph. This is a kind of quantum walk interferometry.
Global Analysis of Quasilinear Wave Equations on Asymptotically Kerr-de Sitter Spaces

We consider quasilinear wave equations on manifolds for which infinity has a structure generalizing that of Kerr-de Sitter space; in particular the trapped geodesics form a normally hyperbolic invariant manifold. We prove the global existence and decay, to constants for the actual wave equation, of solutions. The key new ingredient compared to earlier work by the authors in the semilinear case [33] and by the first author in the non-trapping quasilinear case [30] is the use of the Nash-Moser iteration in our framework.
Fast FPGA emulation of analog dynamics in digitally-driven systems

In this paper, we propose an architecture for FPGA emulation of mixed-signal systems that achieves high accuracy at a high throughput. We represent the analog output of a block as a superposition of step responses to changes in its analog input, and the output is evaluated only when needed by the digital subsystem. Our architecture is therefore intended for digitally-driven systems; that is, those in which the inputs of analog dynamical blocks change only on digital clock edges. We implemented a high-speed link transceiver design using the proposed architecture on a Xilinx FPGA. This design demonstrates how our approach breaks the link between simulation rate and time resolution that is characteristic of prior approaches. The emulator is flexible, allowing for the real-time adjustment of analog dynamics, clock jitter, and various design parameters. We demonstrate that our architecture achieves 1% accuracy while running 3 orders of magnitude faster than a comparable high-performance CPU simulation.
ON MACHINE-LEARNED CLASSIFICATION OF VARIABLE STARS WITH SPARSE AND NOISY TIME-SERIES DATA

With the coming data deluge from synoptic surveys, there is a need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly observed variables based on small numbers of time-series measurements. In this paper, we introduce a methodology for variable-star classification, drawing from modern machine-learning techniques. We describe how to homogenize the information gleaned from light curves by selection and computation of real-numbered metrics (features), detail methods to robustly estimate periodic features, introduce tree-ensemble methods for accurate variable-star classification, and show how to rigorously evaluate a classifier using cross validation. On a 25-class data set of 1542 well-studied variable stars, we achieve a 22.8% error rate using the random forest (RF) classifier; this represents a 24% improvement over the best previous classifier on these data. This methodology is effective for identifying samples of specific science classes: for pulsational variables used in Milky Way tomography we obtain a discovery efficiency of 98.2% and for eclipsing systems we find an efficiency of 99.1%, both at 95% purity. The RF classifier is superior to other methods in terms of accuracy, speed, and relative immunity to irrelevant features; the RF can also be used to estimate the importance of each feature in classification. Additionally, we present the first astronomical use of hierarchical classification methods to incorporate a known class taxonomy in the classifier, which reduces the catastrophic error rate from 8% to 7.8%. Excluding low-amplitude sources, the overall error rate improves to 14%, with a catastrophic error rate of 3.5%.
Unsupervised Domain Adaptation Using Regularized Hyper-Graph Matching

Domain adaptation (DA) addresses the real-world image classification problem of discrepancy between training (source) and testing (target) data distributions. We propose an unsupervised DA method that considers the presence of only unlabelled data in the target domain. Our approach centers on finding matches between samples of the source and target domains. The matches are obtained by treating the source and target domains as hyper-graphs and carrying out a class-regularized hyper-graph matching using first-, second-and third-order similarities between the graphs. We have also developed a computationally efficient algorithm by initially selecting a subset of the samples to construct a graph and then developing a customized optimization routine for graph-matching based on Conditional Gradient and Alternating Direction Multiplier Method. This allows the proposed method to be used widely. We also performed a set of experiments on standard object recognition datasets to validate the effectiveness of our framework over previous approaches.
Inverse problems for general second order hyperbolic equations with time-dependent coefficients

We study the inverse problems for the second order hyperbolic equations of general form with time-dependent coefficients assuming that the boundary data are given on a part of the boundary. The main result of this paper is the determination of the time-dependent Lorentzian metric by the boundary measurements. This is achieved by the adaptation of a variant of the boundary control method developed by Eskin (Inverse Probl 22(3):815–833, 2006; Inverse Probl 23:2343–2356, 2007).
Nebular Continuum and Line Emission in Stellar Population Synthesis Models

Accounting for nebular emission when modeling galaxy spectral energy distributions (SEDs) is important, as both line and continuum emission can contribute significantly to the total observed flux. In this work, we present a new nebular emission model integrated within the Flexible Stellar Population Synthesis code that computes the total line and continuum emission for complex stellar populations using the photoionization code Cloudy. The self-consistent coupling of the nebular emission to the matched ionizing spectrum produces emission line intensities that correctly scale with the stellar population as a function of age and metallicity. This more complete model of galaxy SEDs will improve estimates of global gas properties derived with diagnostic diagrams, star formation rates based on H$\alpha$, and stellar masses derived from NIR broadband photometry. Our models agree well with results from other photoionization models and are able to reproduce observed emission from H II regions and star-forming galaxies. Our models show improved agreement with the observed H II regions in the Ne III/O II plane and show satisfactory agreement with He II emission from $z=2$ galaxies when including rotating stellar models. Models including post-asymptotic giant branch stars are able to reproduce line ratios consistent with low-ionization emission regions (LIERs).
Propagation of correlations in local random quantum circuits

We derive a dynamical bound on the propagation of correlations in local random quantum circuits--lattice spin systems where piecewise quantum operations--in space and time--occur with classical probabilities. Correlations are quantified by the Frobenius norm of the commutator of two positive operators acting on disjoint regions of a one-dimensional circular chain of length L. For a time $$t=O(L)$$t=O(L), correlations spread ballistically to spatial distances $$\mathcal {D}=t$$D=t, growing at best, diffusively with time for any distance within that radius with extensively suppressed distance- dependent corrections. For $$t=\varOmega (L^2)$$t=Ω(L2), all parts of the system get almost equally correlated with exponentially suppressed distance- dependent corrections and approach the maximum amount of correlations that may be established asymptotically.
Prediction with dimension reduction of multiple molecular data sources for patient Survival

Predictive modeling from high-dimensional genomic data is often preceded by a dimension reduction step, such as principal component analysis (PCA). However, the application of PCA is not straightforward for multisource data, wherein multiple sources of 'omics data measure different but related biological components. In this article, we use recent advances in the dimension reduction of multisource data for predictive modeling. In particular, we apply exploratory results from Joint and Individual Variation Explained (JIVE), an extension of PCA for multisource data, for prediction of differing response types. We conduct illustrative simulations to illustrate the practical advantages and interpretability of our approach. As an application example, we consider predicting survival for patients with glioblastoma multiforme from 3 data sources measuring messenger RNA expression, microRNA expression, and DNA methylation. We also introduce a method to estimate JIVE scores for new samples that were not used in the initial dimension reduction and study its theoretical properties; this method is implemented in the R package R.JIVE on CRAN, in the function jive.predict.
RG Decimations and Confinement

We outline the steps in a derivation of the statement that the SU(2) gauge theory is in a confining phase for all values of the coupling, 0 β a . The approach employed is to obtain both upper and lower bounds for the partition function and the 'twisted' partition function in terms of approximate decimation transformations. The behavior of the exact quantities is thus constrained by that of the easily computable bounding decimations.
Optimizing Neural Networks via Koopman Operator Theory

Koopman operator theory, a powerful framework for discovering the underlying dynamics of nonlinear dynamical systems, was recently shown to be intimately connected with neural network training. In this work, we take the first steps in making use of this connection. As Koopman operator theory is a linear theory, a successful implementation of it in evolving network weights and biases offers the promise of accelerated training, especially in the context of deep networks, where optimization is inherently a non-convex problem. We show that Koopman operator theoretic methods allow for accurate predictions of weights and biases of feedforward, fully connected deep networks over a non-trivial range of training time. During this window, we find that our approach is >10x faster than various gradient descent based methods (e.g. Adam, Adadelta, Adagrad), in line with our complexity analysis. We end by highlighting open questions in this exciting intersection between dynamical systems and neural network theory. We highlight additional methods by which our results could be expanded to broader classes of networks and larger training intervals, which shall be the focus of future work.
Autonomous Hybrid Ground/Aerial Mobility in Unknown Environments

Hybrid ground and aerial vehicles can possess distinct advantages over ground-only or flight-only designs in terms of energy savings and increased mobility. In this work we outline our unified framework for controls, planning, and autonomy of hybrid ground/air vehicles. Our contribution is three-fold: 1) We develop a control scheme for the control of passive two-wheeled hybrid ground/aerial vehicles. 2) We present a unified planner for both rolling and flying by leveraging differential flatness mappings. 3) We conduct experiments leveraging mapping and global planning for hybrid mobility in unknown environments, showing that hybrid mobility uses up to five times less energy than flying only1.1Video at https://youtu.be/nlGfYehTLpg
DECONSTRUCTING THE KINETIC SZ POWER SPECTRUM

We present a detailed investigation of the impact of astrophysical processes on the shape and amplitude of the kinetic SZ (kSZ) power spectrum from the post-reionization epoch. This is achieved by constructing a new model of the kSZ power spectrum which we calibrate to the results of hydrodynamic simulations. By construction, our method accounts for all relevant density and velocity modes and so is unaffected by the limited box size of our simulations. We find that radiative cooling and star formation can reduce the amplitude of the kSZ power spectrum by up to 33% or 1 μK2 at l = 3000. This is driven by a decrease in the mean gas density in groups and clusters due to the conversion of gas into stars. Variations in the redshifts at which helium reionization occurs can effect the amplitude by a similar fraction, while current constraints on cosmological parameters (namely σ8) translate to a further ±15% uncertainty on the kSZ power spectrum. We demonstrate how the models presented in this work can be constrained—reducing the astrophysical uncertainty on the kSZ signal—by measuring the redshift dependence of the signal via kSZ tomography. Finally, we discuss how the results of this work can help constrain the duration of reionization via measurements of the kSZ signal sourced by inhomogeneous (or patchy) reionization.
Sequential Covariance Calculation for Exoplanet Image Processing

Direct imaging of exoplanets involves the extraction of very faint signals from highly noisy data sets, with noise that often exhibits significant spatial, spectral, and temporal correlations. As a result, a large number of post-processing algorithms have been developed in order to optimally decorrelate the signal from the noise. In this paper, we explore four such closely related algorithms, all of which depend heavily on the calculation of covariances between large data sets of imaging data. We discuss the similarities and differences between these methods, and demonstrate how the use sequential calculation techniques can significantly improve their computational efficiencies.
FINITE VORONOI DECOMPOSITIONS OF INFINITE VERTEX TRANSITIVE GRAPHS

In this paper, we consider the Voronoi decompositions of an arbitrary infinite vertex-transitive graph G. In particular, we are interested in the following question: what is the largest number of Voronoi cells that must be infinite, given sufficiently (but finitely) many Voronoi sites which are sufficiently far from each other? We call this number the survival number s(G). The survival number of a graph has an alternative characterization in terms of the number of balls of radius r-1 required to cover a sphere of radius r. The survival number is not a quasi-isometry invariant, but it remains open whether finiteness of s(G) is. We show that all vertex-transitive graphs with polynomial growth have finite s(G); vertex-transitive graphs with infinitely many ends have infinite s(G); the lamplighter graph LL(Z), which has exponential growth, has finite s(G); and the lamplighter graph LL(Z2), which is Liouville, has infinite s(G).
Modeling the initiation of the 2006 December 13 coronal mass ejection in AR 10930: The structure and dynamics of the erupting flux rope

We carry out a 3D magnetohydrodynamic simulation to model the initiation of the coronal mass ejection (CME) on 2006 December 13 in the emerging δ-sunspot active region NOAA 10930. The setup of the simulation is similar to a previous simulation by Fan, but with a significantly widened simulation domain to accommodate the wide CME. The simulation shows that the CME can result from the emergence of a east–west oriented twisted flux rope whose positive, following emerging pole corresponds to the observed positive rotating sunspot emerging against the southern edge of the dominant pre-existing negative sunspot. The erupting flux rope in the simulation accelerates to a terminal speed that exceeds 1500 km s−1 and undergoes a counter-clockwise rotation of nearly 180° such that its front and flanks all exhibit southward directed magnetic fields, explaining the observed southward magnetic field in the magnetic cloud impacting the Earth. With continued driving of flux emergence, the source region coronal magnetic field also shows the reformation of a coronal flux rope underlying the flare current sheet of the erupting flux rope, ready for a second eruption. This may explain the build up for another X-class eruptive flare that occurred the following day from the same region.
Optimal smoothing for N-body codes

In any collisionless N -body code, there is an optimal choice for the smoothing parameter that minimizes the average error in the force evaluations. We show how to compute the optimal softening length in a direct-summation code and demonstrate that it varies roughly as N.
Is the Milky Way's Hot Halo Convectively Unstable?

We investigate the convective stability of two popular types of model of the gas distribution in the hot Galactic halo. We first consider models in which the halo density and temperature decrease exponentially with height above the disk. These halo models were created to account for the fact that, on some sight lines, the halo's X-ray emission lines and absorption lines yield different temperatures, implying that the halo is non-isothermal. We show that the hot gas in these exponential models is convectively unstable if γ < 3/2, where γ is the ratio of the temperature and density scale heights. Using published measurements of γ and its uncertainty, we use Bayes' theorem to infer posterior probability distributions for γ, and hence the probability that the halo is convectively unstable for different sight lines. We find that, if these exponential models are good descriptions of the hot halo gas, at least in the first few kiloparsecs from the plane, the hot halo is reasonably likely to be convectively unstable on two of the three sight lines for which scale height information is available. We also consider more extended models of the halo. While isothermal halo models are convectively stable if the density decreases with distance from the Galaxy, a model of an extended adiabatic halo in hydrostatic equilibrium with the Galaxy's dark matter is on the boundary between stability and instability. However, we find that radiative cooling may perturb this model in the direction of convective instability. If the Galactic halo is indeed convectively unstable, this would argue in favor of supernova activity in the Galactic disk contributing to the heating of the hot halo gas.
FINITE TEMPERATURE DYNAMICS NEAR QUANTUM PHASE TRANSITIONS

We review the non-zero temperature relaxational dynamics of quantum systems near a zero temperature, second-order phase transition. We begin with the quantum Ising chain, for which universal and exact results for the relaxation rates can be obtained in all the distinct limiting regimes of the phase diagram. Next, we describe the crossovers in the electron spectral function near a transition involving a change in the pairing symmetry of BCS superconductors in two dimensions. Finally, we consider dynamic spin models which may provide a mean-field description of magnetic ordering transitions in the heavy fermion compounds.
Nuclear response in a finite-temperature relativistic framework

A thermal extension of the relativistic nuclear field theory is formulated for the nuclear response. The Bethe-Salpeter equation (BSE) with the time-dependent kernel for the particle-hole response is treated within the Matsubara Green’s function formalism. We show that, with the help of a temperature-dependent projection operator on the subspace of the imaginary time (time blocking), it is possible to reduce the BSE for the nuclear response function to a single frequency variable equation also at finite temperature. The approach is implemented self-consistently in the framework of quantum hadrodynamics based on the meson-nucleon Lagrangian. The method is applied to the monopole, dipole and quadrupole response of 48Ca and to the dipole response of the tin isotopes 100, 120, 132Sn, in particular, to a study of the evolution of nuclear collective oscillations with temperature. The article is dedicated to the memory of Pier Francesco Bortignon and devoted to the developments related to his pioneering ideas.
A PRECESSING JET IN THE CH Cyg SYMBIOTIC SYSTEM

Jets have been detected in only a few symbiotic binaries to date, and CH Cyg is one of them. In 2001, a non-relativistic jet was detected in CH Cyg for the first time in X-rays. We carried out coordinated Chandra, Hubble Space Telescope (HST), and VLA observations in 2008 to study the propagation of this jet and its interaction with the circumbinary medium. We detected the jet with Chandra and HST and determined that the apex has expanded to the south from {approx}300 AU to {approx}1400 AU, with the shock front propagating with velocity <100 km s{sup -1}. The shock front has significantly slowed down since 2001. Unexpectedly, we also discovered a powerful jet in the NE-SW direction, in the X-ray, optical and radio. This jet has a multi-component structure, including an inner jet and a counterjet at {approx}170 AU, and a SW component ending in several clumps extending out to {approx}750 AU. The structure of the jet and the curvature of the outer portion of the SW jet suggest an episodically powered precessing jet or a continuous precessing jet with occasional mass ejections or pulses. We carried out detailed spatial mapping of the X-ray emission and correlation with themore » optical and radio emission. X-ray spectra were extracted from the central source, inner NE counterjet, and the brightest clump at a distance of {approx}500 AU from the central source. We discuss the initial results of our analyses, including the multi-component spectral fitting of the jet components and of the central source.« less
Proof of the path localization conjecture for directed polymers

It is a well-known open problem in the literature on random polymers to show that a directed polymer in random environment localizes around a favorite path at low temperature. A precise statement of this conjecture is formulated and proved in this article.
A globalization for non-complete but geodesic spaces

I show that if a geodesic space has curvature bounded below locally in the sense of Alexandrov then its completion has the same lower curvature bound globally.
Tachyon condensation in the D0/D4 system

The D0-D4 system with a Neveu-Schwarz B-field in the spatial directions of the D4-brane has a tachyon in the spectrum of the (0,4) strings. The tachyon signals the instability of the system to form a bound state of the D0-brane with the D4-brane. We use the Wess-Zumino-Witten like open superstring field theory formulated by Berkovits to study the tachyon potential for this system. The tachyon potential lies outside the universality class of the D-brane anti-D-brane system. It is a function of the B-field. We calculate the tachyon potential at the zeroth level approximation. The minimum of the tachyon potential in this case is expected to reproduce the mass defect involved in the formation of the D0-D4 bound state. We compare the minimum of the tachyon potential with the mass defect in three cases. For small values of the B-field we obtain 70% of the expected mass defect. For large values of the B-field with Pf(2πα'B) > 0 the potential reduces to that of the D-brane anti-D-brane reproducing 62% of the expected mass defect. For large values of the B-field with Pf(2πα'B) < 0 the minimum of the tachyon potential gives 25% of the expected mass defect. At the tachyon condensate we show that the (0,4) strings decouple from the low energy dynamics.
Gravitational fields of the magnetic-type

Local conformal symmetry introduces the conformal curvature (Weyl tensor) that gets split into its (gravito-) electric and magnetic (tensor) parts. Newtonian tidal forces are expected from the grav...
The EFT of Large Scale Structures at All Redshifts: Analytical Predictions for Lensing

We study the prediction of the Effective Field Theory of Large Scale Structures (EFTofLSS) for the matter power spectrum at different redshifts. In previous work, we found that the two-loop prediction can match the nonlinear power spectrum measured from N-body simulations at redshift zero within approximately 2% up to k~ 0.6 h Mpc-1 after fixing a single free parameter, the so-called "speed of sound". We determine the time evolution of this parameter by matching the EFTofLSS prediction to simulation output at different redshifts, and find that it is well-described by a fitting function that only includes one additional parameter. After the two free parameters are fixed, the prediction agrees with nonlinear data within approximately 2% up to at least k~ 1 h Mpc-1 at z≥ 1, and also within approximately 5% up to k~ 1.2 h Mpc-1 at z=1 and k~ 2.3 h Mpc-1 at z=3, a major improvement with respect to other perturbative techniques. We also develop an accurate way to estimate where the EFTofLSS predictions at different loop orders should fail, based on the sizes of the next-order terms that are neglected, and find agreement with the actual comparisons to data. Finally, we use our matter power spectrum results to perform analytical calculations of lensing potential power spectra corresponding to both CMB and galaxy lensing. This opens the door to future direct applications of the EFTofLSS to observations of gravitational clustering on cosmic scales.
Random billiards with wall temperature and associated Markov chains

By a random billiard we mean a billiard system in which the standard rule of specular reflection is replaced with a Markov transition probabilities operator P that gives, at each collision of the billiard particle with the boundary of the billiard domain, the probability distribution of the post-collision velocity for a given pre-collision velocity. A random billiard with microstructure, or RBM for short, is a random billiard for which P is derived from a choice of geometric/mechanical structure on the boundary of the billiard domain, as explained in the text. Such systems provide simple and explicit mechanical models of particle–surface interaction that can incorporate thermal effects and permit a detailed study of thermostatic action from the perspective of the standard theory of Markov chains on general state spaces. The main focus of this paper is on the operator P itself and how it relates to the mechanical and geometric features of the microstructure, such as mass ratios, curvatures, and potentials. The main results are as follows: (1) we give a characterization of the stationary probabilities (equilibrium states) of P and show how standard equilibrium distributions studied in classical statistical mechanics such as the Maxwell–Boltzmann distribution and the Knudsen cosine law arise naturally as generalized invariant billiard measures; (2) we obtain some of the more basic functional theoretic properties of P, in particular that P is under very general conditions a self-adjoint operator of norm 1 on a Hilbert space to be defined below, and show in a simple but somewhat typical example that P is a compact (Hilbert–Schmidt) operator. This leads to the issue of relating the spectrum of eigenvalues of P to the geometric/mechanical features of the billiard microstructure; (3) we explore the latter issue, both analytically and numerically in a few representative examples. Additionally, (4) a general algorithm for simulating the Markov chains is given based on a geometric description of the invariant volumes of classical statistical mechanics. Our description of these volumes may have independent interest.
A mixed effects model for longitudinal relational and network data, with applications to international trade and conflict

The focus of this paper is an approach to the modeling of longitudinal social network or relational data. Such data arise from measurements on pairs of objects or actors made at regular temporal intervals, resulting in a social network for each point in time. In this article we represent the network and temporal dependencies with a random effects model, resulting in a stochastic process defined by a set of stationary covariance matrices. Our approach builds upon the social relations models of Warner, Kenny and Stoto [Journal of Personality and Social Psychology 37 (1979) 1742–1757] and Gill and Swartz [Canad. J. Statist. 29 (2001) 321–331] and allows for an intra- and inter-temporal representation of network structures. We apply the methodology to two longitudinal data sets: international trade (continuous response) and militarized interstate disputes (binary response).
MAESTROeX: A Massively Parallel Low Mach Number Astrophysical Solver

Author(s): Fan, Duoming; Nonaka, Andrew; Almgren, Ann S; Harpole, Alice; Zingale, Michael | Abstract: We present MAESTROeX, a massively parallel solver for low Mach number astrophysical flows. The underlying low Mach number equation set allows for efficient, long-time integration for highly subsonic flows compared to compressible approaches. MAESTROeX is suitable for modeling full spherical stars as well as well as planar simulations of dynamics within localized regions of a star, and can robustly handle several orders of magnitude of density and pressure stratification. Previously, we have described the development of the predecessor of MAESTROeX, called MAESTRO, in a series of papers. Here, we present a new, greatly simplified temporal integration scheme that retains the same order of accuracy as our previous approaches. We also explore the use of alternative spatial mapping of the one-dimensional base state onto the full Cartesian grid. The code leverages the new AMReX software framework for block-structured adaptive mesh refinement (AMR) applications, allowing for scalability to large fractions of leadership-class machines. Using our previous studies on the convective phase of single-degenerate progenitor models of Type Ia supernovae as a guide, we characterize the performance of the code and validate the new algorithmic features. Like MAESTRO, MAESTROeX is fully open source.
Verifiable Round-Robin Scheme for Smart Homes

Advances in sensing, networking, and actuation technologies have resulted in the IoT wave that is expected to revolutionize all aspects of modern society. This paper focuses on the new challenges of privacy that arise in IoT in the context of smart homes. Specifically, the paper focuses on preventing the user's privacy via inferences through channel and in-home device activities. We propose a method for securely scheduling the devices while decoupling the device and channels activities. The proposed solution avoids any attacks that may reveal the coordinated schedule of the devices, and hence, also, assures that inferences that may compromise individual's privacy are not leaked due to device and channel level activities. Our experiments also validate the proposed approach, and consequently, an adversary cannot infer device and channel activities by just observing the network traffic.
Involutive Heegaard Floer homology

Using the conjugation symmetry on Heegaard Floer complexes, we define a 3-manifold invariant called involutive Heegaard Floer homology, which is meant to correspond to Z4-equivariant Seiberg–Witten Floer homology. Further, we obtain two new invariants of homology cobordism, d and d¯, and two invariants of smooth knot concordance, V0 and V¯0. We also develop a formula for the involutive Heegaard Floer homology of large integral surgeries on knots. We give explicit calculations in the case of L-space knots and thin knots. In particular, we show that V0 detects the nonsliceness of the figure-eight knot. Other applications include constraints on which large surgeries on alternating knots can be homology-cobordant to other large surgeries on alternating knots.
Radiation Transport for Explosive Outflows: Opacity Regrouping

Implicit Monte Carlo (IMC) and Discrete Diffusion Monte Carlo (DDMC) are methods used to stochastically solve the radiative transport and diffusion equations, respectively. These methods combine into a hybrid transport-diffusion method we refer to as IMC-DDMC. We explore a multigroup IMC-DDMC scheme that in DDMC, combines frequency groups with sufficient optical thickness. We term this procedure ''opacity regrouping''. Opacity regrouping has previously been applied to IMC-DDMC calculations for problems in which the dependence of the opacity on frequency is monotonic. We generalize opacity regrouping to non-contiguous groups and implement this in SuperNu, a code designed to do radiation transport in high-velocity outflows with non-monotonic opacities. We find that regrouping of non-contiguous opacity groups generally improves the speed of IMC-DDMC radiation transport. We present an asymptotic analysis that informs the nature of the Doppler shift in DDMC groups and summarize the derivation of the Gentile-Fleck factor for modified IMC-DDMC. We test SuperNu using numerical experiments including a quasi-manufactured analytic solution, a simple 10 group problem, and the W7 problem for Type Ia supernovae. We find that opacity regrouping is necessary to make our IMC-DDMC implementation feasible for the W7 problem and possibly Type Ia supernova simulations in general. We compare themore » bolometric light curves and spectra produced by the SuperNu and PHOENIX radiation transport codes for the W7 problem. The overall shape of the bolometric light curves are in good agreement, as are the spectra and their evolution with time. However, for the numerical specifications we considered, we find that the peak luminosity of the light curve calculated using SuperNu is ∼10% less than that calculated using PHOENIX.« less
OH as an Alternate Tracer for Molecular Gas: Quantity and Structure of Molecular Gas in W5

We report column densities of molecular gas in the W5 star-forming region as traced with OH 18-cm emission in a grid survey using the Green Bank Telescope. OH appears to trace a greater column density than does CO in 8 out of 15 cases containing OH emission detections; the two molecules trace the same column densities for the other 7 cases. OH and CO trace a similar morphology of molecular gas with a nearly one-to-one correspondence. The mass of molecular gas traced by OH in the portion of the survey containing OH emission is $1.7$ (+ 0.6 or - 0.2) $\times 10^4 M_{\odot}$, whereas the corresponding CO detections trace $9.9 \times 10^3 M_{\odot} (\pm 0.7) \times 10^3$. We find that for lines observed in absorption, calculations assuming uniform gas and continuum distributions underestimate column density values by 1 to 2 orders of magnitude, making them unreliable for our purposes. Modeling of this behavior in terms of OH cloud structure on a scale smaller than telescopic resolution leads us to estimate that the filling factor of OH gas is a few to 10 percent. Consideration of filling factor effects also results in a method of constraining the excitation temperature values. The total molecular gas content of W5 may be approximately two to three times what we report from direct measurement, because we excluded absorption line detections from the mass estimate.