cssi/SciSciGPT-SciSciNet huggingface dataset:
THE PRODUCTION RATE OF SN Ia EVENTS IN GLOBULAR CLUSTERS

In globular clusters, dynamical evolution produces luminous X-ray emitting binaries at a rate about 200 times greater than in the field. If globular clusters also produce SN Ia at a high rate, it would account for many of the SN Ia production in early-type galaxies and provide insight into their formation. Here we use archival Hubble Space Telescope (HST) images of nearby galaxies that have hosted an SN Ia to examine the rate at which globular clusters produce these events. The location of the SN Ia is registered on an HST image obtained before the event or after the supernova (SN) faded. Of the 36 nearby galaxies examined, 21 had sufficiently good data to search for globular cluster hosts. None of the 21 SNe have a definite globular cluster counterpart, although there are some ambiguous cases. This places an upper limit to the enhancement rate of SN Ia production in globular clusters of about 42 at the 95% confidence level, which is an order of magnitude lower than the enhancement rate for luminous X-ray binaries. Even if all of the ambiguous cases are considered as having a globular cluster counterpart, the upper bound for the enhancement rate is 82 at the 95% confidence level, still a factor of several below that needed to account for half of the SN Ia events. Barring unforeseen selection effects, we conclude that globular clusters are not responsible for producing a significant fraction of the SN Ia events in early-type galaxies.
Severe Challenges in Gravity Theories

Gravity is specifically the attractive force between two masses separated at a distance. Is this force a derived or a fundamental interaction? We believe that all fundamental interactions are quantum in nature but a derived interaction may be classical. Severe challenges have appeared in many quantum theories of gravity. None of these theories has thus far attained its goal in quantizing gravity and some have met remarkable defeat. We are led to ponder whether gravitation is intrinsically classical and that there would exist a deeper and structurally different underlying theory which would give rise to classical gravitation, in the sense that statistical mechanics, quantum or classical, provides the underlying theory of classical thermodynamics.
Coherent Vortex Structures and 3D Enstrophy Cascade

Existence of 2D enstrophy cascade in a suitable mathematical setting, and under suitable conditions compatible with 2D turbulence phenomenology, is known both in the Fourier and in the physical scales. The goal of this paper is to show that the same geometric condition preventing the formation of singularities – $${\frac{1}{2}}$$ -Holder coherence of the vorticity direction – coupled with a suitable condition on a modified Kraichnan scale, and under a certain modulation assumption on evolution of the vorticity, leads to existence of 3D enstrophy cascade in physical scales of the flow.
Optimal detection of sparse principal components in high dimension

We perform a finite sample analysis of the detection levels for sparse principal components of a high-dimensional covariance matrix. Our minimax optimal test is based on a sparse eigenvalue statistic. Alas, computing this test is known to be NP-complete in general, and we describe a computationally efficient alternative test using convex relaxations. Our relaxation is also proved to detect sparse principal components at near optimal detection levels, and it performs well on simulated datasets. Moreover, using polynomial time reductions from theoretical computer science, we bring significant evidence that our results cannot be improved, thus revealing an inherent trade off between statistical and computational performance.
Homotopy theoretic models of identity types

Quillen [17] introduced model categories as an abstract framework for homotopy theory which would apply to a wide range of mathematical settings. By all accounts this program has been a success and—as, e.g., the work of Voevodsky on the homotopy theory of schemes [15] or the work of Joyal [11, 12] and Lurie [13] on quasicategories seem to indicate—it will likely continue to facilitate mathematical advances. In this paper we present a novel connection between model categories and mathematical logic, inspired by the groupoid model of (intensional) Martin–Lof type theory [14] due to Hofmann and Streicher [9]. In particular, we show that a form of Martin–Lof type theory can be soundly modelled in any model category. This result indicates moreover that any model category has an associated “internal language” which is itself a form of Martin-Lof type theory. This suggests applications both to type theory and to homotopy theory. Because Martin–Lof type theory is, in one form or another, the theoretical basis for many of the computer proof assistants currently in use, such as Coq and Agda (cf. [3] and [5]), this promise of applications is of a practical, as well as theoretical, nature.
Wavepackets in Inhomogeneous Periodic Media: Propagation Through a One-Dimensional Band Crossing

We consider a model of an electron in a crystal moving under the influence of an external electric field: Schrodinger’s equation in one spatial dimension with a potential which is the sum of a periodic function V and a smooth function W. We assume that the period of V is much shorter than the scale of variation of W and denote the ratio of these scales by $${\epsilon}$$ . We consider the dynamics of semiclassical wavepacket asymptotic (in the limit $${\epsilon\downarrow 0)}$$ solutions which are spectrally localized near to a crossing of two Bloch band dispersion functions of the periodic operator $${-\frac{1}{2} \partial^{2}_ {z} +V(z)}$$ . We show that the dynamics is qualitatively different from the case where bands are well-separated: at the time the wavepacket is incident on the band crossing, a second wavepacket is ‘excited’ which has opposite group velocity to the incident wavepacket. We then show that our result is consistent with the solution of a ‘Landau–Zener’-type model.
Semi-local quantum criticality and the instability of extremal planar horizons

We show that the Aretakis instability of compact extremal horizons persists in the planar case of interest to holography and discuss its connection with the emergence of “semi-local quantum criticality” in the field theory dual. In particular, the spatially localized power-law decay of this critical phase corresponds to spatially localized power-law growth of stress-energy on the horizon. For near-extremal black holes these phenomena occur transiently over times of order the inverse temperature. The boundary critical phase is characterized by an emergent temporal conformal symmetry, and the bulk instability seems to be essential to preserving the symmetry in the presence of interactions. We work primarily in the solvable example of charged scalar perturbations of five-dimensional (near-)extremal planar Reissner-Nordstrom anti-de Sitter spacetime and argue that the conclusions hold more generally.
Neutrinos and supermassive stars: Prospects for neutrino emission and detection

We calculate the luminosity and energy spectrum of the neutrino emission from electron-positron pair annihilation during the collapse of a supermassive star (M 5 × 104 M☉). We then estimate the cumulative flux and energy spectrum of the resulting neutrino background as a function of the abundance and redshift of supermassive stars and the efficiency of these objects in converting gravitational energy into neutrino energy. We estimate the expected signal in some of the new generation of astrophysical neutrino detectors from both a cumulative background of supermassive stars and single collapse events associated with these objects.
Segregation models for density-bidisperse granular flows

A kinetic-theory-based model of granular flow which predicts the depth-varying segregation velocities of rising and sinking particles in density-bidisperse mixtures is presented. The segregation velocity results from a balance between the buoyant force, due to particle density and concentration, and the interspecies drag force from kinetic theory, which depends on interparticle friction and local flow conditions.
Curvature Bounds for Surfaces in Hyperbolic 3-Manifolds

A triangulation of a hyperbolic 3-manifold is -thick if each tetrahedron having all vertices in the thick part of is -bilipschitz diffeomorphic to the standard Euclidean tetrahedron. We show that there exists a fixed constant such that every complete hyperbolic 3-manifold has an -thick geodesic triangulation. We use this to prove the existence of universal bounds on the principal curvatures of -injective surfaces and strongly irreducible Heegaard surfaces in hyperbolic 3-manifolds.
PICS: SIMULATIONS OF STRONG GRAVITATIONAL LENSING IN GALAXY CLUSTERS

Gravitational lensing has become one of the most powerful tools available for investigating the 'dark side' of the universe. Cosmological strong gravitational lensing, in particular, probes the properties of the dense cores of dark matter halos over decades in mass and offers the opportunity to study the distant universe at flux levels and spatial resolutions otherwise unavailable. Studies of strongly-lensed variable sources offer yet further scientific opportunities. One of the challenges in realizing the potential of strong lensing is to understand the statistical context of both the individual systems that receive extensive follow-up study, as well as that of the larger samples of strong lenses that are now emerging from survey efforts. Motivated by these challenges, we have developed an image-simulation pipeline, PICS (Pipeline for Images of Cosmological Strong lensing) to generate realistic strong gravitational lensing signals from group and cluster scale lenses. PICS uses a low-noise and unbiased density estimator based on (resampled) Delaunay Tessellations to calculate the density field; lensed images are produced by ray-tracing images of actual galaxies from deep Hubble Space Telescope observations. Other galaxies, similarly sampled, are added to fill in the light cone. The pipeline further adds cluster-member galaxies and foreground stars into the lensed images. The entire image ensemble is then observed using a realistic point spread function which includes appropriate detector artifacts for bright stars. Noise is further added, including such non-Gaussian elements as noise window-paning from mosaiced observations, residual bad pixels, and cosmic rays. The aim is to produced simulated images that appear identical - to the eye (expert or otherwise) - to real observations in various imaging surveys.
Efficient Point-to-Subspace Query in $\ell^1$ with Application to Robust Object Instance Recognition

Motivated by vision tasks such as robust face and object recognition, we consider the following general problem: given a collection of low-dimensional linear subspaces in a high-dimensional ambient (image) space, and a query point (image), efficiently determine the nearest subspace to the query in $\ell^1$ distance. In contrast to the naive exhaustive search which entails large-scale linear programs, we show that the computational burden can be cut down significantly by a simple two-stage algorithm: (1) projecting the query and database subspaces into lower-dimensional space by random Cauchy matrix and solving small-scale distance evaluations (linear programs) in the projection space to locate the nearest candidates; (2) with few candidates upon independent repetition of (1), getting back to the high-dimensional space and performing exhaustive search. To preserve the identity of the nearest subspace with nontrivial probability, the projection dimension typically is a low-order polynomial of the subspace d...
Relaxation oscillations in an idealized ocean circulation model

This work is motivated by a desire to understand transitions between stable equilibria observed in Stommel’s 1961 thermohaline circulation model. We adapt the model, including a forcing parameter as a dynamic slow variable. The resulting model is a piecewise-smooth, three time-scale system. The model is analyzed using geometric singular perturbation theory to demonstrate the existence of attracting periodic orbits. The system is capable of producing classical relaxation oscillations as expected, but there is also a parameter regime in which the model exhibits small amplitude oscillations known as canard cycles. Forcing the model with obliquity variations from the last 100,000 years produces oscillations that are modulated in amplitude and frequency. The output shows similarities with important features of the climate proxy data of the same period.
Outbursts, state transitions, and periodicities observed with the RXTE all-sky monitor

Abstract Results from the All-Sky Monitor (ASM) on the Rossi X-ray Timing Explorer are reviewed. A number of recurrent transient sources have been detected, while only a few previously unreported sources have been discovered. The ASM light curves show a wide variety of phenomena in general, and, in particular, those of transient sources show a wide range of properties. Examples are used to illustrate that the distinction between persistent and transient sources may be very unclear. The results of searches for periodicities in the ASM light curves are summarized, and other astrophysical investigations using ASM light curves are suggested. The latter include investigations of the possible causes of long-term quasiperiodic and chaotic variability, and comparative studies on the basis of the observed variability.
On random quadratic forms: supports of potential local maxima

The selection model in population genetics is a dynamic system on the set of the probability distributions 𝒑=(p1,…,pn) of the alleles A1…,An, with pi(t+1) proportional to pi(t) multiplied by ∑jfi,jpj(t), and fi,j=fj,i interpreted as a fitness of the gene pair (Ai,Aj). It is known that 𝒑 is a locally stable equilibrium if and only if 𝒑 is a strict local maximum of the quadratic form 𝒑T𝒇𝒑. Usually, there are multiple local maxima and lim𝒑(t) depends on 𝒑(0). To address the question of a typical behavior of {𝒑(t)}, John Kingman considered the case when the fi,j are independent and [0,1]-uniform. He proved that with high probability (w.h.p.) no local maximum may have more than 2.49n1∕2 positive components, and reduced 2.49 to 2.14 for a nonbiological case of exponentials on [0,∞). We show that the constant 2.14 serves a broad class of smooth densities on [0,1] with the increasing hazard rate. As for a lower bound, we prove that w.h.p. for all k≤2n1∕3, there are many k-element subsets of [n] that pass a partial test to be a support of a local maximum. Still, it may well be that w.h.p. the actual supports are much smaller. In that direction, we prove that w.h.p. a support of a local maximum, which does not contain a support of a local equilibrium, is very unlikely to have size exceeding ⅔log2n and, for the uniform fitnesses, there are super-polynomially many potential supports free of local equilibriums of size close to ½log2n.
Dispersing Nanoparticles in a Polymer Film via Solvent Evaporation

Large-scale molecular dynamics simulations are used to study the dispersion of nanoparticles (NPs) in a polymer film during solvent evaporation. As the solvent evaporates, a dense polymer-rich skin layer forms at the liquid/vapor interface, which is either NP rich or poor depending on the strength of the NP/polymer interaction. When the NPs are strongly wet by the polymer, the NPs accumulate at the interface and form layers. However, when the NPs are only partially wet by the polymer, most NPs are uniformly distributed in the bulk of the polymer film, with the dense skin layer serving as a barrier to prevent the NPs from moving to the interface. Our results point to a possible route to employ less favorable NP/polymer interactions and fast solvent evaporation to uniformly disperse NPs in a polymer film, contrary to the common belief that strong NP/polymer attractions are needed to make NPs well dispersed in polymer nanocomposites.
RELATIONS BETWEEN VARIOUS BOUNDARIES OF RELATIVELY HYPERBOLIC GROUPS

Suppose a group G is relatively hyperbolic with respect to a collection ℙ of its subgroups and also acts properly, cocompactly on a CAT(0) (or δ-hyperbolic) space X. The relatively hyperbolic structure provides a relative boundary ∂(G, ℙ). The CAT(0) structure provides a different boundary at infinity ∂X. In this paper, we examine the connection between these two spaces at infinity. In particular, we show that ∂(G, ℙ) is G-equivariantly homeomorphic to the space obtained from ∂X by identifying the peripheral limit points of the same type.
On the boundary coupling of topological Landau-Ginzburg models

I propose a general form for the boundary coupling of B-type topological Landau-Ginzburg models. In particular, I show that the relevant background in the open string sector is a (generally non-abelian) superconnection of type (0,1) living in a complex superbundle defined on the target space, which I allow to be a non-compact Calabi-Yau manifold. This extends and clarifies previous proposals. Generalizing an argument due to Witten, I show that BRST invariance of the partition function on the worldsheet amounts to the condition that the (0, ≤ 2) part of the superconnection's curvature equals a constant endomorphism plus the Landau-Ginzburg potential times the identity section of the underlying superbundle. This provides the target space equations of motion for the open topological model.
Fundamental Properties of Co-moving Stars Observed by Gaia

We have estimated fundamental parameters for a sample of co-moving stars observed by $Gaia$ and identified by Oh et al. (2017). We matched the $Gaia$ observations to the 2MASS and WISE catalogs and fit MIST isochrones to the data, deriving estimates of the mass, radius, [Fe/H], age, distance and extinction to 9,754 stars in the original sample of 10,606 stars. We verify these estimates by comparing our new results to previous analyses of nearby stars, examining fiducial cluster properties, and estimating the power-law slope of the local present-day mass function. A comparison to previous studies suggests that our mass estimates are robust, while metallicity and age estimates are increasingly uncertain. We use our calculated masses to examine the properties of binaries in the sample, and show that separation of the pairs dominates the observed binding energies and expected lifetimes.
Floer homology and surface decompositions

Sutured Floer homology, denoted by SFH, is an invariant of balanced sutured manifolds previously defined by the author. In this paper we give a formula that shows how this invariant changes under surface decompositions. In particular, if (M,γ)⇝(M′,γ′) is a sutured manifold decomposition then SFH(M′,γ′) is a direct summand of SFH(M,γ). To prove the decomposition formula we give an algorithm that computes SFH(M,γ) from a balanced diagram defining (M,γ) that generalizes the algorithm of Sarkar and Wang. As a corollary we obtain that if (M,γ) is taut then SFH(M,γ)≠0. Other applications include simple proofs of a result of Ozsvath and Szabo that link Floer homology detects the Thurston norm, and a theorem of Ni that knot Floer homology detects fibred knots. Our proofs do not make use of any contact geometry. Moreover, using these methods we show that if K is a genus g knot in a rational homology 3–sphere Y whose Alexander polynomial has leading coefficient ag≠0 and if rkHFK(Y,K,g)<4 then Y∖N(K) admits a depth ≤2 taut foliation transversal to ∂N(K).
Droplet phases in non-local Ginzburg-Landau models with Coulomb repulsion in two dimensions

We establish the behavior of the energy of minimizers of non-local Ginzburg-Landau energies with Coulomb repulsion in two space dimensions near the onset of multi-droplet patterns. Under suitable scaling of the background charge density with vanishing surface tension the non-local Ginzburg-Landau energy becomes asymptotically equivalent to a sharp interface energy with screened Coulomb interaction. Near the onset the minimizers of the sharp interface energy consist of nearly identical circular droplets of small size separated by large distances. In the limit the droplets become uniformly distributed throughout the domain. The precise asymptotic limits of the bifurcation threshold, the minimal energy, the droplet radii, and the droplet density are obtained.
Hyperbolic manifolds containing high topological index surfaces

If a graph is in bridge position in a 3-manifold so that the graph complement is irreducible and boundary irreducible, we generalize a result of Bachman and Schleimer to prove that the complexity of a surface properly embedded in the complement of the graph bounds the graph distance of the bridge surface. We use this result to construct, for any natural number $n$, a hyperbolic manifold containing a surface of topological index $n$.
Observables of String Field Theory

We study gauge invariant operators of open string field theory and find a precise correspondence with on-shell closed strings. We provide a detailed proof of the gauge invariance of the operators and a heuristic interpretation of their correlation functions in terms of on-shell scattering amplitudes of closed strings. We also comment on the implications of these operators to vacuum string field theory.
Constraining the Rate of Relativistic Jets from Tidal Disruptions Using Radio Surveys

Tidal disruptions of stars by massive black holes produce transient accretion flows that flare at optical, UV, and X-ray wavelengths. At late times, these accretion flows may launch relativistic jets that can be detected through the interaction of the jet with the dense interstellar medium of the galaxy. We present an upper limit for the flux density of a radio counterpart to a tidal disruption event detected by GALEX that is a factor of six below theoretical predictions. We also examine existing radio surveys for transients with a timescale of 1 yr and use these to set a 2σ upper limit on the rate of tidal disruption events producing relativistic jets of ~14 × 10–7 Mpc-3 yr–1. This rate is an order of magnitude lower than the highest values from theoretical models and is consistent with detection rates from optical and X-ray surveys.
RNNs can generate bounded hierarchical languages with optimal memory

Recurrent neural networks empirically generate natural language with high syntactic fidelity. However, their success is not well-understood theoretically. We provide theoretical insight into this success, proving in a finite-precision setting that RNNs can efficiently generate bounded hierarchical languages that reflect the scaffolding of natural language syntax. We introduce Dyck-$(k,m)$, the language of well-nested brackets (of $k$ types) and $m$-bounded nesting depth, reflecting the bounded memory needs and long-distance dependencies of natural language syntax. The best known results use $O(k^{\frac{m}{2}})$ memory (hidden units) to generate these languages. We prove that an RNN with $O(m \log k)$ hidden units suffices, an exponential reduction in memory, by an explicit construction. Finally, we show that no algorithm, even with unbounded computation, can suffice with $o(m \log k)$ hidden units.
Strong self-induced nonreciprocal transmission by using nonlinear PT-symmetric epsilon-near-zero metamaterials

Nonreciprocal transmission is the fundamental process behind unidirectional wave propagation phenomena. In our work, a compact and practical parity-time (PT) symmetric metamaterial is designed based on two Silicon Carbide (SiC) media separated by an air gap and photonically doped with gain and loss defects. We demonstrate that an exceptional point (EP) is formed in this PT-symmetric system when SiC operates as a practical epsilon-near-zero (ENZ) material and by taking into account its moderate optical loss. Furthermore and even more importantly, strong self-induced nonreciprocal transmission is excited due to the nonlinear Kerr effect at a frequency slightly shifted off the EP but without breaking the PT-symmetric phase. The transmittance from one direction is exactly unity while the transmittance from the other direction is decreased to very low values, achieving very high optical isolation. The proposed active nonlinear metamaterial overcomes the fundamental physical bounds on nonreciprocity compared with a passive nonlinear nonreciprocal resonator. The strong self-induced nonreciprocal transmission arises from the extreme asymmetric field distribution achieved upon excitation from opposite incident directions. The significant enhancement of the electric field in the defects effectively decreases the required optical power to trigger the presented nonlinear response. This work can have a plethora of applications, such as nonreciprocal ultrathin coatings for the protection of sources or other sensitive equipment from external pulsed signals, circulators, and isolators.
Nitric Oxide in Climatological Global Energy Budget During 1982–2013

Over the past decades, temperature and density of the upper atmosphere show negative trends and decrease of the upper atmospheric temperature is attributed to the declining neutral density. Specifically, nitric oxide (NO) and carbon dioxide (CO2) govern thermospheric cooling at 5.3 and 15 micron, respectively. While a lot of efforts have focused on the CO2 effects on the long-term trends, relatively less attention has been paid to the impacts by NO, which responds to solar and geomagnetic activities dynamically. In this study, we investigate the role of NO in climatological global energy budget for the recent three solar cycles using the Global Ionosphere Thermosphere Model. From 1982 to 2013, the F10.7 and Ap indices showed a decadal decrease of ~8% and ~20%, respectively. By imposing temporal-varying F10.7 and Ap values in the simulations, we find a decadal change of -0.28x1011 W or -17.3% in total NO cooling power, which agrees well with that (-0.34x1011 W or -17.2%) from the empirical Thermosphere Climate Index derived from the TIMED/SABER data. Neutral density decreases by 10-20% at 200-450km and Tex decreases by 25.3 K per decade. The deduced-decadal change of NO cooling reaches ~25% of the sum of total heating at ~130 km and its significance decreases with altitude.
The signature of the Seiberg-Witten surface

The Seiberg-Witten family of elliptic curves defines a Jacobian rational elliptic surface $\Z$ over $\mathbb{C}\mathrm{P}^1$. We show that for the $\bar{\partial}$-operator along the fiber the logarithm of the regularized determinant $-1/2 \log \det' (\bar\partial^* \bar\partial)$ satisfies the anomaly equation of the one-loop topological string amplitude derived in Kodaira-Spencer theory. We also show that not only the determinant line bundle with the Quillen metric but also the $\bar{\partial}$-operator itself extends across the nodal fibers of $\mathrm{Z}$. The extension introduces current contributions to the curvature of the determinant line bundle at the points where the fibration develops nodal fibers. The global anomaly of the determinant line bundle then determines the signature of $\mathrm{Z}$ which equals minus the number of hypermultiplets.
BINARY DISRUPTION BY MASSIVE BLACK HOLES: HYPERVELOCITY STARS, S STARS, AND TIDAL DISRUPTION EVENTS

We examine whether disrupted binary stars can fuel black hole growth. In this mechanism, tidal disruption produces a single hypervelocity star (HVS) ejected at high velocity and a former companion star bound to the black hole. After a cluster of bound stars forms, orbital diffusion allows the black hole to accrete stars by tidal disruption at a rate comparable to the capture rate. In the Milky Way, HVSs and the S star cluster imply similar rates of 10{sup -5} to 10{sup -3} yr{sup -1} for binary disruption. These rates are consistent with estimates for the tidal disruption rate in nearby galaxies and imply significant black hole growth from disrupted binaries on 10 Gyr timescales.
Twisted index theory on good orbifolds. II. Fractional quantum numbers

This paper uses techniques in noncommutative geometry as developed by Alain Connes [Co2], in order to study the twisted higher index theory of elliptic operators on orbifold covering spaces of compact good orbifolds, which are invariant under a projective action of the orbifold fundamental group, continuing our earlier work [MM]. We also compute the range of the higher cyclic traces on K-theory for cocompact Fuchsian groups, which is then applied to determine the range of values of the Connes–Kubo Hall conductance in the discrete model of the quantum Hall effect on the hyperbolic plane, generalizing earlier results in [Bel+E+S], [CHMM]. The new phenomenon that we observe in our case is that the Connes–Kubo Hall conductance has plateaux at integral multiples of a fractional valued topological invariant, namely the orbifold Euler characteristic. Moreover the set of possible fractions has been determined, and is compared with recently available experimental data. It is plausible that this might shed some light on the mathematical mechanism responsible for fractional quantum numbers.
Stability conditions and branes at singularities

I use Bridgeland's definition of a stability condition on a triangulated category to investigate the stability of D-branes on Calabi-Yau cones given by the canonical line bundle over a del Pezzo surface. In this context, I prove the existence of the decay of a D3-brane into a set of fractional branes. This is an important aspect of the derivation of quiver gauge theories from branes at singularities via the technique of equivalences of categories. Some important technical aspects of this equivalence are discussed. I also prove that the representations corresponding to skyscraper sheaves supported off the zero section are simple.
Robustness of a bisimulation-type faster-than preorder

TACS is an extension of CCS where upper time bounds for delays can be specified. Luettgen and Vogler defined three variants of bismulation-type faster-than relations and showed that they all three lead to the same preorder, demonstrating the robustness of their approach. In the present paper, the operational semantics of TACS is extended; it is shown that two of the variants still give the same preorder as before, underlining robustness. An explanation is given why this result fails for the third variant. It is also shown that another variant, which mixes old and new operational semantics, can lead to smaller relations that prove the same preorder.
Minimum energy configurations in the N -body problem and the celestial mechanics of granular systems

Minimum energy configurations in Celestial Mechanics are investigated. It is shown that this is not a well defined problem for point-mass celestial mechanics but well-posed for finite density distributions. This naturally leads to a granular mechanics extension of usual Celestial Mechanics questions such as relative equilibria and stability. This paper specifically studies and finds all relative equilibria and minimum energy configurations for N = 1, 2, 3 and develops hypotheses on the relative equilibria and minimum energy configurations for N ≫ 1 bodies.
Confidence sets for network structure

Latent variable models are frequently used to identify structure in dichotomous network data, in part, because they give rise to a Bernoulli product likelihood that is both well understood and consistent with the notion of exchangeable random graphs. In this article, we propose conservative confidence sets that hold with respect to these underlying Bernoulli parameters as a function of any given partition of network nodes, enabling us to assess estimates of residual network structure, that is, structure that cannot be explained by known covariates and thus cannot be easily verified by manual inspection. We demonstrate the proposed methodology by analyzing student friendship networks from the National Longitudinal Survey of Adolescent Health that include race, gender, and school year as covariates. We employ a stochastic expectation-maximization algorithm to fit a logistic regression model that includes these explanatory variables as well as a latent stochastic blockmodel component and additional node-specific effects. Although maximum-likelihood estimates do not appear consistent in this context, we are able to evaluate confidence sets as a function of different blockmodel partitions, which enables us to qualitatively assess the significance of estimated residual network structure relative to a baseline, which models covariates but lacks block structure. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 461–469, 2011 © 2011 Wiley Periodicals, Inc.
STANDING SHOCK INSTABILITY IN ADVECTION-DOMINATED ACCRETION FLOWS

Depending on the values of the energy and angular momentum per unit mass in the gas supplied at large radii, inviscid advection-dominated accretion flows can display velocity profiles with either preshock deceleration or preshock acceleration. Nakayama has shown that these two types of flow configurations are expected to have different stability properties. By employing the Chevalier & Imamura linearization method and the Nakayama instability boundary conditions, we discover that there are regions of parameter space where disks/shocks with outflows can be stable or unstable. In regions of instability, we find that preshock deceleration is always unstable to the zeroth mode with zero frequency of oscillation, but is always stable to the fundamental mode and overtones. Furthermore, we also find that preshock acceleration is always unstable to the zeroth mode and that the fundamental mode and overtones become increasingly less stable as the shock location moves away from the horizon when the disk half-height expands above ~12 gravitational radii at the shock radius. In regions of stability, we demonstrate the zeroth mode to be stable for the velocity profiles that exhibit preshock acceleration and deceleration. Moreover, for models that are linearly unstable, our model suggests the possible existence of quasi-periodic oscillations (QPOs) with ratios 2:3 and 3:5. These ratios are believed to occur in stellar and supermassive black hole candidates, for example, in GRS 1915+105 and Sgr A*, respectively. We expect that similar QPO ratios also exist in regions of stable shocks.
Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets

Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking the neuron, or the synapse functionality. While memristive devices have been proposed to emulate biological synapses, spintronic devices have proved to be efficient at performing the thresholding operation of the neuron at ultra-low currents. In this work, we propose an All-Spin Artificial Neural Network where a single spintronic device acts as the basic building block of the system. The device offers a direct mapping to synapse and neuron functionalities in the brain while inter-layer network communication is accomplished via CMOS transistors. To the best of our knowledge, this is the first demonstration of a neural architecture where a single nanoelectronic device is able to mimic both neurons and synapses. The ultra-low voltage operation of low resistance magneto-metallic neurons enables the low-voltage operation of the array of spintronic synapses, thereby leading to ultra-low power neural architectures. Device-level simulations, calibrated to experimental results, was used to drive the circuit and system level simulations of the neural network for a standard pattern recognition problem. Simulation studies indicate energy savings by $\sim\!\! 100\times$ in comparison to a corresponding digital/analog CMOS neuron implementation.
Uncertainty quantification in first-principles predictions of phonon properties and lattice thermal conductivity

We present a framework for quantifying the uncertainty that results from the choice of exchange-correlation (XC) functional in predictions of phonon properties and thermal conductivity that use density functional theory to calculate the atomic force constants. The energy ensemble capabilities of the Bayesian error estimation functional with van der Waals correlation XC functional are first applied to determine an ensemble of interatomic force constants, which are then used as inputs to lattice dynamics calculations and a solution of the Boltzmann transport equation. The framework is applied to isotopically pure silicon. We find that the uncertainty estimates bound property predictions (e.g., phonon dispersions, specific heat, thermal conductivity) from other XC functionals and experiments. We distinguish between properties in silicon that are correlated with the predicted thermal conductivity [e.g., the transverse-acoustic branch sound speed (squared Pearson correlation coefficient, ${R}^{2}$, of 0.89) and average Gr\"uneisen parameter (${R}^{2}=0.85$)] and those that are not [e.g., longitudinal-acoustic branch sound speed (${R}^{2}=0.23$) and specific heat (${R}^{2}=0.00$)]. We find that differences in ensemble predictions of thermal conductivity are correlated with the behavior of transverse-acoustic phonons with mean free paths between 100 and 300 nm. The framework systematically accounts for XC uncertainty in phonon calculations and should be used whenever it is suspected that the choice of XC functional is influencing physical interpretations.
Data-Driven Distributionally Robust Optimal Power Flow for Distribution Systems

Increasing penetration of distributed energy resources complicate operations of electric power distribution systems by amplifying volatility of nodal power injections. On the other hand, these resources can provide additional control means to the distribution system operator (DSO). In this work we develop a data-driven distributionally robust decision-making framework in the DSO’s perspective to overcome the uncertainty of these injections and its impact on the distribution system operations. We develop an ac optimal power flow formulation for radial distribution systems based on the LinDistFlow ac power flow approximation and exploit distributionally robust optimization to immunize the optimized decisions against uncertainty in the probabilistic models of forecast errors obtained from the available observations. The model is reformulated to be computationally tractable and tested on multiple IEEE distribution test systems. We also release the code supplement that implements the proposed model in Julia and can be used to reproduce our numerical results.
Coherent x rays with tunable time-dependent polarization

We describe a method for producing high power, coherent x-ray pulses from a free electron laser with femtosecond scale periodic temporal modulation of the polarization vector. This approach relies on the generation of a temporal intensity modulation after self seeding either by modulating the seed intensity or the beam current. After generating a coherent temporally modulated $s$-polarization pulse, the electron beam is delayed by half a modulation period and sent into a short orthogonally oriented undulator, serving as a $p$-polarization afterburner. We provide simulations of three configurations for realizing this polarization switching, namely, enhanced self seeding with an intensity modulation generated by 2 color self seeding, enhanced self seeding of a current modulated bunch, and regular self seeding of a current modulated bunch. Start to end simulations for the Linac Coherent Light Source-II are provided for the latter.
Real-Time Investigation of a Large Nosocomial Influenza A Outbreak Informed by Genomic Epidemiology.

BACKGROUND Nosocomial respiratory virus outbreaks represent serious public health challenges. Rapid and precise identification of cases and tracing of transmission chains is critical to end outbreaks and to inform prevention measures. METHODS We combined conventional surveillance with influenza A virus (IAV) genome sequencing to identify and contain a large IAV outbreak in a metropolitan healthcare system. A total of 381 individuals, including 91 inpatients and 290 health care workers (HCWs), were included in the investigation. RESULTS During a 12-day period in early 2019, infection preventionists identified 89 HCWs and 18 inpatients as cases of influenza-like illness (ILI), using an amended definition without the requirement for fever. Sequencing of IAV genomes from available nasopharyngeal (NP) specimens identified 66 individuals infected with a nearly identical strain of influenza A H1N1pdm09 (43 HCWs, 17 inpatients, and 6 with unspecified affiliation). All HCWs infected with the outbreak strain had received the seasonal influenza virus vaccination. Characterization of five representative outbreak viral isolates did not show antigenic drift. In conjunction with IAV genome sequencing, mining of electronic records pinpointed the origin of the outbreak as a single patient and a few interactions in the emergency department that occurred one day prior to the index ILI cluster. CONCLUSIONS We used precision surveillance to delineate a large nosocomial IAV outbreak, mapping the source of the outbreak to a single patient rather than HCWs as initially assumed based on conventional epidemiology. These findings have important ramifications for more effective prevention strategies to curb nosocomial respiratory virus outbreaks.
Deep Learning for Reactive Power Control of Smart Inverters under Communication Constraints

Aiming for the median solution between cyber-intensive optimal power flow (OPF) solutions and subpar local control, this work advocates deciding inverter injection setpoints using deep neural networks (DNNs). Instead of fitting OPF solutions in a black-box manner, inverter DNNs are naturally integrated with the feeder model and trained to minimize a grid-wide objective subject to inverter and network constraints enforced on the average over uncertain grid conditions. Learning occurs in a quasi-stationary fashion and is posed as a stochastic OPF, handled via stochastic primal-dual updates acting on grid data scenarios. Although trained as a whole, the proposed DNN is operated in a master-slave architecture. Its master part is run at the utility to output a condensed control signal broadcast to all inverters. Its slave parts are implemented by inverters and are driven by the utility signal along with local inverter readings. This novel DNN structure uniquely addresses the small-big data conundrum where utilities collect detailed smart meter readings yet on an hourly basis, while in real time inverters should be driven by local inputs and minimal utility coordination to save on communication. Numerical tests corroborate the efficacy of this physics-aware DNN-based inverter solution over an optimal control policy.
Lie 2-algebras of vector fields

We show that the category of vector fields on a geometric stack has the structure of a Lie 2-algebra. This proves a conjecture of R.~Hepworth. The construction uses a Lie groupoid that presents the geometric stack. We show that the category of vector fields on the Lie groupoid is equivalent to the category of vector fields on the stack. The category of vector fields on the Lie groupoid has a Lie 2-algebra structure built from known (ordinary) Lie brackets on multiplicative vector fields of Mackenzie and Xu and the global sections of the Lie algebroid of the Lie groupoid. After giving a precise formulation of Morita invariance of the construction, we verify that the Lie 2-algebra structure defined in this way is well-defined on the underlying stack.
Nematic topological semimetal and insulator in magic-angle bilayer graphene at charge neutrality

This work explores the possible interacting ground states of magic angle twisted bilayer graphene at charge neutrality, emphasizing the role of three-fold lattice rotation symmetry.
Diverse viral proteases activate the NLRP1 inflammasome.

The immune system recognizes disease-causing microbes, such as bacteria and viruses, and removes them from the body before they can cause harm. When the immune system first detects these foreign invaders, a multi-part structure known as the inflammasome launches an inflammatory response to help fight the microbes off. Several sensor proteins can activate the inflammasome, including one in mice called NLRP1B. This protein has evolved a specialized site that can be cut by a bacterial toxin. Once cleaved, this region acts like a biological tripwire and sparks NLRP1B into action, allowing the sensor to activate the inflammasome system. Humans have a similar protein called NLRP1, but it is unclear whether this protein has also evolved a tripwire region that can sense microbial proteins. To answer this question, Tsu, Beierschmitt et al. set out to find whether NLRP1 can be activated by viruses in the Picornaviridae family, which are responsible for diseases like polio, hepatitis A, and the common cold. This revealed that NLRP1 contains a cleavage site for enzymes produced by some, but not all, of the viruses in the picornavirus family. Further experiments confirmed that when a picornavirus enzyme cuts through this region during a viral infection, it triggers NLRP1 to activate the inflammasome and initiate an immune response. The enzymes from different viruses were also found to cleave human NLRP1 at different sites, and the protein’s susceptibility to cleavage varied between different animal species. For instance, Tsu, Beierschmitt et al. discovered that NLRP1B in mice is also able to sense picornaviruses, and that different enzymes activate and cleave NLRP1B and NLRP1 to varying degrees: this affected how well the two proteins are expected to be able to sense specific viral infections. This variation suggests that there is an ongoing evolutionary arms-race between viral proteins and the immune system: as viral proteins change and new ones emerge, NLRP1 rapidly evolves new tripwire sites that allow it to sense the infection and launch an inflammatory response. What happens when NLRP1B activates the inflammasome during a viral infection is still an open question. The discovery that mouse NLRP1B shares features with human NLRP1 could allow the development of animal models to study the role of the tripwire in antiviral defenses and the overactive inflammation associated with some viral infections. Understanding the types of viruses that activate the NLRP1 inflammasome, and the outcomes of the resulting immune response, may have implications for future treatments of viral infections.
Simplifying Weinstein Morse functions

We prove that the minimum number of critical points of a Weinstein Morse function on a Weinstein domain of dimension at least six is at most two more than the minimum number of critical points of a smooth Morse function on that domain; if the domain has nonzero middle-dimensional homology, these two numbers agree. There is also an upper bound on the number of gradient trajectories between critical points in smoothly trivial Weinstein cobordisms. As an application, we show that the number of generators for the Grothendieck group of the wrapped Fukaya category is at most the number of generators for singular cohomology and hence vanishes for any Weinstein ball. We also give a topological obstruction to the existence of finite-dimensional representations of the Chekanov–Eliashberg DGA for Legendrians.