cssi/SciSciGPT-SciSciNet huggingface dataset:
USING LAGRANGIAN PERTURBATION THEORY FOR PRECISION COSMOLOGY

We explore the Lagrangian perturbation theory (LPT) at one-loop order with Gaussian initial conditions. We present an expansion method to approximately compute the power spectrum LPT. Our approximate solution has good convergence in the series expansion and enables us to compute the power spectrum in LPT accurately and quickly. Non-linear corrections in this theory naturally satisfy the law of conservation of mass because the relation between matter density and the displacement vector of dark matter corresponds to the conservation of mass. By matching the one-loop solution in LPT to the two-loop solution in standard perturbation theory, we present an approximate solution of the power spectrum which has higher order corrections than the two-loop order in standard perturbation theory with the conservation of mass satisfied. With this approximation, we can use LPT to compute a non-linear power spectrum without any free parameters, and this solution agrees with numerical simulations at k = 0.2 h Mpc–1 and z = 0.35 to better than 2%.
Reachability-Based Safety and Goal Satisfaction of Unmanned Aerial Platoons on Air Highways

Recently, there has been immense interest in using unmanned aerial vehicles for civilian operations. As a result, unmanned aerial systems traffic management is needed to ensure the safety and goal ...
A Conformally Invariant Gap Theorem in Yang–Mills Theory

We show a sharp conformally invariant gap theorem for Yang–Mills connections in dimension 4 by exploiting an associated Yamabe-type problem.
Piecewise quantile autoregressive modeling for nonstationary time series

We develop a new methodology for the fitting of nonstationary time series that exhibit nonlinearity, asymmetry, local persistence and changes in location scale and shape of the underlying distribution. In order to achieve this goal, we perform model selection in the class of piecewise stationary quantile autoregressive processes. The best model is defined in terms of minimizing a minimum description length criterion derived from an asymmetric Laplace likelihood. Its practical minimization is done with the use of genetic algorithms. If the data generating process follows indeed a piecewise quantile autoregression structure, we show that our method is consistent for estimating the break points and the autoregressive parameters. Empirical work suggests that the proposed method performs well in finite samples.
Sequence-Level Mixed Sample Data Augmentation

Despite their empirical success, neural networks still have difficulty capturing compositional aspects of natural language. This work proposes a simple data augmentation approach to encourage compositional behavior in neural models for sequence-to-sequence problems. Our approach, SeqMix, creates new synthetic examples by softly combining input/output sequences from the training set. We connect this approach to existing techniques such as SwitchOut and word dropout, and show that these techniques are all essentially approximating variants of a single objective. SeqMix consistently yields approximately 1.0 BLEU improvement on five different translation datasets over strong Transformer baselines. On tasks that require strong compositional generalization such as SCAN and semantic parsing, SeqMix also offers further improvements.
S-TYPE AND P-TYPE HABITABILITY IN STELLAR BINARY SYSTEMS: A COMPREHENSIVE APPROACH. II. ELLIPTICAL ORBITS

In the first paper of this series, a comprehensive approach has been provided for the study of S-type and P-type habitable regions in stellar binary systems, which was, however, restricted to circular orbits of the stellar components. Fortunately, a modest modification of the method also allows for the consideration of elliptical orbits, which of course entails a much broader range of applicability. This augmented method is presented here, and numerous applications are conveyed. In alignment with Paper I, the selected approach considers a variety of aspects, which comprise the consideration of a joint constraint including orbital stability and a habitable region for a possible system planet through the stellar radiative energy fluxes ("radiative habitable zone"; RHZ). The devised method is based on a combined formalism for the assessment of both S-type and P-type habitability; in particular, mathematical criteria are deduced for which kinds of systems S-type and P-type habitable zones are realized. If the RHZs are truncated by the additional constraint of orbital stability, the notation of ST-type and PT-type habitability applies. In comparison to the circular case, it is found that in systems of higher eccentricity, the range of the RHZs is significantly reduced. Moreover, for a considerable number of models, the orbital stability constraint also reduces the range of S-type and P-type habitability. Nonetheless, S-, P-, ST-, and PT-type habitability is identified for a considerable set of system parameters. The method as presented is utilized for BinHab, an online code available at The University of Texas at Arlington.
Does the SYK model have a spin glass phase

We argue that the Sachdev-Ye-Kitaev model has no spin glass phase, based on calculations involving both the nearly-conformal limit and the strongly-coupled Schwarzian limit of the model. This conclusion is supported by numerical computations of eigenvalue statistics with up to 46 Majorana fermions. In addition, we find numerically that the distribution of the ground state energy is Gaussian.
Inverse semigroup spectral analysis for partially ranked data

Abstract Motivated by the notion of symmetric group spectral analysis developed by Diaconis, we introduce the notion of spectral analysis on the rook monoid (also called the symmetric inverse semigroup), characterize its output in terms of symmetric group spectral analysis, and provide an application to the statistical analysis of partially ranked (voting) data. We also discuss generalizations to arbitrary finite inverse semigroups. This paper marks the first non-group semigroup development of spectral analysis.
THE TRENDS HIGH-CONTRAST IMAGING SURVEY. II. DIRECT DETECTION OF THE HD 8375 TERTIARY

We present the direct imaging detection of a faint tertiary companion to the single-lined spectroscopic binary HD 8375 AB. Initially noticed as an 53 m s^–1 yr^–1 Doppler acceleration by Bowler et al., we have obtained high-contrast adaptive optics observations at Keck using NIRC2 that spatially resolve HD 8375 C from its host(s). Astrometric measurements demonstrate that the companion shares a common proper-motion. We detect orbital motion in a clockwise direction. Multiband relative photometry measurements are consistent with an early M-dwarf spectral type (~M1V). Our combined Doppler and imaging observations place a lower-limit of m ≥ 0.297 M_☉ on its dynamical mass. We also provide a refined orbit for the inner pair using recent radial velocity measurements obtained with the High Resolution Echelle Spectrometer. HD 8375 is one of many triple-star systems that are apparently missing in the solar neighborhood.
On the Origin of the Scatter in the Red Sequence: An Analysis of Four CLASH Clusters

In clusters of galaxies, the red sequence is believed to be a consequence of a correlation between stellar mass and chemical abundances, with more massive galaxies being more metal-rich and, as a consequence, redder. However, there is a color scatter around the red sequence that holds even with precision photometry, implying that the galaxy population is more complicated than as described by a mass-metallicity relation. We use precision photometry from the Cluster Lensing and Supernova survey with Hubble (CLASH) to investigate what drives this scatter. In four CLASH clusters at $z=0.355 \pm 0.007$, we find that the optical-IR galaxy colors confirm the previously known trend of metallicity along the red sequence but also show a strong connection between stellar age and red sequence offset, with ages ranging from 3 to 8 Gyr. Starting with fixed-age color-magnitude relations motivated by the mass-metallicity correlations of CLASH cluster galaxies, and by adjusting galaxy colors through stellar population models to put them all at the age of our red sequence, we are able to reduce the, e.g., F625W $-$ F814W scatter from 0.051 mag to 0.026 mag with median photometric errors of 0.029 mag. While we will extend this analysis to the full CLASH sample, in four clusters our technique already provides a color precision in near-total-light apertures to resolve the spread in stellar population formation ages that drives the scatter in the red sequence.
Protection of Accelerator Hardware: RF systems

The radio-frequency (RF) system is the key element that generates electric fields for beam acceleration. To keep the system reliable, a highly sophisticated protection scheme is required, which also should be designed to ensure a good balance between beam availability and machine safety. Since RF systems are complex, incorporating high-voltage and high-power equipment, a good portion of machine downtime typically comes from RF systems. Equipment and component damage in RF systems results in long and expensive repairs. Protection of RF system hardware is one of the oldest machine protection concepts, dealing with the protection of individual highpower RF equipment from breakdowns. As beam power increases in modern accelerators, the protection of accelerating structures from beam-induced faults also becomes a critical aspect of protection schemes. In this article, an overview of the RF system is given, and selected topics of failure mechanisms and examples of protection requirements are introduced.
Loops, polytopes and splines

We uncover an unexpected connection between the physics of loop integrals and the mathematics of spline functions. One loop integrands are Laplace transforms of splines. This clarifies the geometry of the associated loop integrals, since a n-node spline has support on a n-vertex polyhedral cone. One-loop integrals are integrals of splines on a hyperbolic slice of the cone, yielding polytopes in AdS space. Splines thus give a geometrical counterpart to the rational function identities at the level of the integrand. Spline technology also allows for a clear, simple, algebraic decomposition of higher point loop integrals in lower dimensional kinematics in terms of lower point integrals — e.g. an hexagon integral in 2d kinematics can be written as a sum of scalar boxes. Higher loops can also be understood directly in terms of splines — they map onto spline convolutions, leading to an intriguing representation in terms of hyperbolic simplices integrated over other hyperbolic simplices. We finish with speculations on the interpretation of one-loop integrals as partition functions, inspired by the use of splines in counting points in polytopes.
Non-commutativity and Supersymmetry

We study the extent to which the gauge symmetry of abelian Yang-Mills can be deformed under two conditions: first, that the deformation depend on a two-form scale. Second, that the deformation preserve supersymmetry. We show that (up to a single parameter) the only allowed deformation is the one determined by the star product. We then consider the supersymmetry algebra satisfied by NCYM expressed in commutative variables. The algebra is peculiar since the supercharges are not gauge-invariant. However, the action, expressed in commutative variables, appears to be quadratic in fermions to all orders in θ.
An overview of (selected) recent results in finite-temperature lattice QCD

I discuss recent results on the lattice with the main emphasis on the thermodynamics of the crossover region, restoration of the chiral symmetry and fluctuations of conserved charges as an indicator of deconfinement, that may also be used to determine the chemical freeze-out conditions in heavy-ion collision experiments.
Successive Convexification of Non-Convex Optimal Control Problems with State Constraints

Abstract This paper presents a Successive Convexification (SCvx) algorithm to solve a class of non-convex optimal control problems with certain types of state constraints. Sources of non-convexity may include nonlinear dynamics and non-convex state/control constraints. To tackle the challenge posed by non-convexity, first we utilize exact penalty function to handle the nonlinear dynamics. Then the proposed algorithm successively convexifies the problem via a project-and-linearize procedure. Thus a finite dimensional convex programming subproblem is solved at each succession, which can be done efficiently with fast Interior Point Method (IPM) solvers. Global convergence to a local optimum is demonstrated with certain convexity assumptions, which are satisfied in a broad range of optimal control problems. The proposed algorithm is particularly suitable for solving trajectory planning problems with collision avoidance constraints. Through numerical simulations, we demonstrate that the algorithm converges reliably after only a few successions. Thus with powerful IPM based custom solvers, the algorithm can be implemented onboard for real-time autonomous control applications.
Infinite subsets of random sets of integers

There is an infinite subset of a Martin-L\"of random set of integers that does not compute any Martin-L\"of random set of integers. To prove this, we show that each real of positive effective Hausdorff dimension computes an infinite subset of a Martin-L\"of random set of integers, and apply a result of Miller.
TRANSIENT ASTROPHYSICAL PULSES AND QUANTUM GRAVITY

Searches for transient astrophysical pulses could open an exciting new window into the fundamental physics of quantum gravity. In particular, an evaporating primordial black hole in the presence of an extra dimension can produce a detectable transient pulse. Observations of such a phenomenon can in principle explore the electroweak energy scale, indicating that astrophysical probes of quantum gravity can successfully complement the exciting new physics expected to be discovered in the near future at the Large Hadron Collider.
The Nonlinear Schrödinger Equation on Z and R with Bounded Initial Data: Examples and Conjectures

We study the nonlinear Schrodinger equation (NLS) with bounded initial data which does not vanish at infinity. Examples include periodic, quasi-periodic and random initial data. On the lattice we prove that solutions are polynomially bounded in time for any bounded data. In the continuum, local existence is proved for real analytic data by a Newton iteration scheme. Global existence for NLS with a regularized nonlinearity follows by analyzing a local energy norm.
Domain walls and massive gauged supergravity potentials

We point out that massive gauged supergravity potentials, for example those arising due to the massive breathing mode of sphere reductions in M-theory or string theory, allow for supersymmetric (static) domain-wall solutions which are a hybrid of a Randall-Sundrum domain wall on one side, and a dilatonic domain wall with a runaway dilaton on the other side. On the anti-de Sitter (AdS) side, these walls have a repulsive gravity with an asymptotic region corresponding to the Cauchy horizon, while on the other side the runaway dilaton approaches the weak-coupling regime and a non-singular attractive gravity, with the asymptotic region corresponding to the boundary of spacetime. We contrast these results with the situation for gauged supergravity potentials for massless scalar modes, whose supersymmetric AdS extrema are generically maxima, and there the asymptotic regime transverse to the wall corresponds to the boundary of the AdS spacetime. We also comment on the possibility that the massive breathing mode may, in the case of fundamental domain-wall sources, stabilize such walls via a Goldberger-Wise mechanism.
AN ARECIBO SURVEY FOR ZEEMAN SPLITTING IN OH MEGAMASER GALAXIES

We present the results of a comprehensive survey using the Arecibo Observatory for Zeeman splitting of OH lines in OH megamasers (OHMs). A total of 77 sources were observed with the Arecibo telescope. Of these, maser emission could not be detected for eight sources, and two sources were only ambiguously detected. Another 27 sources were detected at low signal-to-noise ratios or with interference that prevented placing any useful limits on the presence of magnetic fields. In 26 sources, it was possible to place upper limits on the magnitude of magnetic fields, typically between 10 and 30 mG. For 14 sources, the Stokes V spectra exhibit features consistent with Zeeman splitting. Eleven of these 14 are new detections, and the remaining three are re-detections of Stokes V detections in Robishaw et al. Among confident new detections, we derive magnetic fields associated with maser regions with magnitudes ranging from 6.1 to 27.6 mG. The distribution of magnetic field strengths suggests the magnetic fields in OH masing clouds in OHMs are larger than those in Galactic OH masers. The results are consistent with magnetic fields playing a dynamically important role in OH masing clouds in OHMs.
Artificial Neural Networks in Fluid Dynamics: A Novel Approach to the Navier-Stokes Equations

Neural networks have been used to solve different types of large data related problems in many different fields. This project takes a novel approach to solving the Navier-Stokes Equations for turbulence by training a neural network using Bayesian Cluster and SOM neighbor weighting to map ionospheric velocity fields based on 3-dimensional inputs. Parameters used in this problem included the velocity, Reynold's number, Prandtl number, and temperature. In this project data was obtained from Johns-Hopkins University to train the neural network using MATLAB. The neural network was able to map the velocity fields within a 67% accuracy of the validation data used. Further studies will focus on higher accuracy and solving further non-linear differential equations using convolutional neural networks.
Finite-size effects on periodic arrays of nanostructures

Arrays of nanostructures have emerged as exceptional tools for the manipulation and control of light. Oftentimes, despite the fact that real implementations of nanostructure arrays must be finite, these systems are modeled as perfectly periodic, and therefore infinite. Here, we investigate the legitimacy of this approximation by studying the evolution of the optical response of finite arrays of nanostructures as their number of elements is increased. We find that the number of elements necessary to reach the infinite array limit is determined by the strength of the coupling between them, and that, even when that limit is reached, the individual responses of the elements may still display significant variations. In addition, we show that, when retardation is negligible, the resonance frequency for the infinite array is always redshifted compared to the single particle. However, in the opposite situation, there could be either a blue- or a redshift. We also study the effects of inhomogeneity in size and position of the elements on the optical response of the array. This work advances the understanding of the behavior of finite and infinite arrays of nanostructures, and therefore provides guidance to design applications that utilize these systems.
Limited-View and Sparse Photoacoustic Tomography for Neuroimaging with Deep Learning.

Photoacoustic tomography (PAT) is a non-ionizing imaging modality capable of acquiring high contrast and resolution images of optical absorption at depths greater than traditional optical imaging techniques. Practical considerations with instrumentation and geometry limit the number of available acoustic sensors and their “view” of the imaging target, which result in image reconstruction artifacts degrading image quality. Iterative reconstruction methods can be used to reduce artifacts but are computationally expensive. In this work, we propose a novel deep learning approach termed pixel-wise deep learning (Pixel-DL) that first employs pixel-wise interpolation governed by the physics of photoacoustic wave propagation and then uses a convolution neural network to reconstruct an image. Simulated photoacoustic data from synthetic, mouse-brain, lung, and fundus vasculature phantoms were used for training and testing. Results demonstrated that Pixel-DL achieved comparable or better performance to iterative methods and consistently outperformed other CNN-based approaches for correcting artifacts. Pixel-DL is a computationally efficient approach that enables for real-time PAT rendering and improved image reconstruction quality for limited-view and sparse PAT.
Cosmo-Particle Searches for Supersymmetry at the Collider Detector at Fermilab

Some theories of particle physics are so compelling that it is worth doing a comprehensive and systematic set of experimental searches to see if they are realized in nature. Supersymmetry is one such theory. This review focuses on the motivation for a broad set of cosmology-inspired search strategies at the Tevatron and on their implementation and results at the Collider Detector at Fermilab (CDF) with the first few fb-1 of integrated luminosity of data.
Specifying Angular Momentum and Center of Mass for Vacuum Initial Data Sets

We show that it is possible to perturb arbitrary vacuum asymptotically flat spacetimes to new ones having exactly the same energy and linear momentum, but with center of mass and angular momentum equal to any preassigned values measured with respect to a fixed affine frame at infinity. This is in contrast to the axisymmetric situation where a bound on the angular momentum by the mass has been shown to hold for black hole solutions. Our construction involves changing the solution at the linear level in a shell near infinity, and perturbing to impose the vacuum constraint equations. The procedure involves the perturbation correction of an approximate solution which is given explicitly.
Multi-wavelength Photometry of the T Tauri Binary V582 Mon (KH 15D): a New Epoch of Occultations

We present multi-wavelength (VRIJHK) observations of KH 15D obtained in 2012/2013, as well as a master table of standard photometry spanning the years 1967 to 2013. The system is a close, eccentric T Tauri binary embedded in an inclined precessing circumbinary (CB) ring. The most recent data show the continued rise of star B with respect to the trailing edge of the occulting horizon as the system's maximum brightness steadily increases. The wealth of data in time and wavelength domains allows us to track the long-term CCD color evolution of KH 15D. We find that the V – I behavior is consistent with direct and scattered light from the composite color of two stars with slightly different temperatures. There is no evidence for any reddening or bluing associated with extinction or scattering by interstellar-medium-size dust grains. Furthermore, we probe the system's faint phase behavior at near-infrared wavelengths in order to investigate extinction properties of the ring and signatures of a possible shepherding planet sometimes invoked to confine the CB ring at ~5 AU. The wavelength independence of eclipse depth at second contact is consistent with the ring material being fully opaque to 2.2 μm. The color-magnitude diagrams demonstrate excess flux in J and H at low light levels, which may be due to the presence of a hot, young Jupiter-mass planet.
A Nonthermal Radio Filament Connected to the Galactic Black Hole

Using the Very Large Array, we have investigated a nonthermal radio filament (NTF) recently found very near the Galactic black hole and its radio counterpart, Sgr A*. While this NTF—the Sgr A West Filament (SgrAWF)—shares many characteristics with the population of NTFs occupying the central few hundred parsecs of the Galaxy, the SgrAWF has the distinction of having an orientation and sky location that suggest an intimate physical connection to Sgr A*. We present 3.3 and 5.5 cm images constructed using an innovative methodology that yields a very high dynamic range, providing an unprecedentedly clear picture of the SgrAWF. While the physical association of the SgrAWF with Sgr A* is not unambiguous, the images decidedly evoke this interesting possibility. Assuming that the SgrAWF bears a physical relationship to Sgr A*, we examine the potential implications. One is that Sgr A* is a source of relativistic particles constrained to diffuse along ordered local field lines. The relativistic particles could also be fed into the local field by a collimated outflow from Sgr A*, perhaps driven by the Poynting flux accompanying the black hole spin in the presence of a magnetic field threading the event horizon. Second, we consider the possibility that the SgrAWF is the manifestation of a low-mass-density cosmic string that has become anchored to the black hole. The simplest form of these hypotheses would predict that the filament be bi-directional, whereas the SgrAWF is only seen on one side of Sgr A*, perhaps because of the dynamics of the local medium.
Exactly Computing the Local Lipschitz Constant of ReLU Networks

The local Lipschitz constant of a neural network is a useful metric with applications in robustness, generalization, and fairness evaluation. We provide novel analytic results relating the local Lipschitz constant of nonsmooth vector-valued functions to a maximization over the norm of the generalized Jacobian. We present a sufficient condition for which backpropagation always returns an element of the generalized Jacobian, and reframe the problem over this broad class of functions. We show strong inapproximability results for estimating Lipschitz constants of ReLU networks, and then formulate an algorithm to compute these quantities exactly. We leverage this algorithm to evaluate the tightness of competing Lipschitz estimators and the effects of regularized training on the Lipschitz constant.
Learning Physical Constraints with Neural Projections

We propose a new family of neural networks to predict the behaviors of physical systems by learning their underpinning constraints. A neural projection operator lies at the heart of our approach, composed of a lightweight network with an embedded recursive architecture that interactively enforces learned underpinning constraints and predicts the various governed behaviors of different physical systems. Our neural projection operator is motivated by the position-based dynamics model that has been used widely in game and visual effects industries to unify the various fast physics simulators. Our method can automatically and effectively uncover a broad range of constraints from observation point data, such as length, angle, bending, collision, boundary effects, and their arbitrary combinations, without any connectivity priors. We provide a multi-group point representation in conjunction with a configurable network connection mechanism to incorporate prior inputs for processing complex physical systems. We demonstrated the efficacy of our approach by learning a set of challenging physical systems all in a unified and simple fashion including: rigid bodies with complex geometries, ropes with varying length and bending, articulated soft and rigid bodies, and multi-object collisions with complex boundaries.
The Oblique Orbit of WASP-107b from K2 Photometry

Observations of nine transits of WASP-107 during the K2 mission reveal three separate occasions when the planet crossed in front of a starspot. The data confirm the stellar rotation period to be 17 days—approximately three times the planet's orbital period—and suggest that large spots persist for at least one full rotation. If the star had a low obliquity, at least two additional spot crossings should have been observed. They were not observed, giving evidence for a high obliquity. We use a simple geometric model to show that the obliquity is likely in the range 40°–140°, i.e., both spin–orbit alignment and anti-alignment can be ruled out. WASP-107 thereby joins the small collection of relatively low-mass stars with a high obliquity. Most such stars have been observed to have low obliquities; all of the exceptions, including WASP-107, involve planets with relatively wide orbits ("warm Jupiters," with ). This demonstrates a connection between stellar obliquity and planet properties, in contradiction to some theories for obliquity excitation.
Information Dynamics at a Phase Transition

We propose a new way of investigating phase transitions in the context of information theory. We use an information-entropic measure of spatial complexity known as configurational entropy (CE) to quantify both the storage and exchange of information in a lattice simulation of a Ginzburg–Landau model with a scalar order parameter coupled to a heat bath. The CE is built from the Fourier spectrum of fluctuations around the mean-field and reaches a minimum at criticality. In particular, we investigate the behavior of CE near and at criticality, exploring the relation between information and the emergence of ordered domains. We show that as the temperature is increased from below, the CE displays three essential scaling regimes at different spatial scales: scale free, turbulent, and critical. Together, they offer an information-entropic characterization of critical behavior where the storage and fidelity of information processing is maximized at criticality.
WFIRST-AFTA Coronagraph Science Yield Modeling with EXOSIMS

We present and discuss the design details of an extensible, modular, open-source software framework called EXOSIMS (Exoplanet Open-Source Imaging Mission Simulator), which creates end-to-end simulations of space-based exoplanet imaging missions. We motivate the development and baseline implementation of the component parts of this software with models of the wide-field infrared survey telescope-astrophysics focused telescope assets (WFIRST-AFTA) coronagraph and present initial results of mission simulations for various iterations of the WFIRST-AFTA coronagraph design. We present and discuss two sets of simulations. The first compares the science yield of completely different instruments in the form of early competing coronagraph designs for WFIRST-AFTA. The second set of simulations evaluates the effects of different operating assumptions, specifically the assumed postprocessing capabilities and telescope vibration levels. We discuss how these results can guide further instrument development and the expected evolution of science yields.
Viscous Flow Past a Body Translating by Time-Periodic Motion with Zero Average

We study the existence, uniqueness, regularity and asymptotic spatial behavior of a Navier–Stokes flow past a body, $${\mathscr {B}}$$, moving by a time-periodic translational motion of period T, and with zero average. For example, $${\mathscr {B}}$$ moves in an oscillating fashion. We then show that the flow is also time-periodic with same period T. However, sufficiently “far” from the body, the oscillatory component decays faster than the averaged component, so that the flow shows there a distinctive steady-state character. This provides a rigorous interpretation of the “steady streaming” phenomenon.
New Maser Emission from Nonmetastable Ammonia in NGC 7538. IV. Coincident Masers in Adjacent States of Para-ammonia

We present the first detection of para-ammonia masers in NGC 7538: multiple epochs of observation of the {sup 14}NH{sub 3} (J, K) = (10, 8) and (9,8) lines. We detect both thermal absorption and nonthermal emission in the (10,8) and (9,8) transitions and the absence of a maser in the (11,8) transition. The (9,8) maser is observed to increase in intensity by 40% over six months. Using interferometric observations with a synthesized beam of 0.''25, we find that the (10,8) and (9,8) masers originate at the same sky position near IRS 1. With strong evidence that the (10,8) and (9,8) masers arise in the same volume, we discuss the application of pumping models for the simultaneous excitation of nonmetastable (J > K) para-ammonia states having the same value of K and consecutive values of J. We also present detections of thermal absorption in rotational states ranging in energy from E/k{sub B} ∼ 200 K to 2000 K, and several non-detections in higher-energy states. In particular, we describe the populations in eight adjacent rotational states with K = 6, including two maser transitions, along with the implications for ortho-ammonia pumping models. An existing torus model for molecular gas in the environmentmore » of IRS 1 has been applied to the masers; a variety of maser species are shown to agree with the model. Historical and new interferometric observations of {sup 15}NH{sub 3} (3,3) masers in the region indicate a precession of the rotating torus at a rate comparable to continuum-emission-based models of the region. We discuss the general necessity of interferometric observations for diagnosing the excitation state of the masers and for determining the geometry of the molecular environment.« less
Multifractality at non-Anderson disorder-driven transitions in Weyl semimetals and other systems

Abstract Systems with the power-law quasiparticle dispersion ϵ k ∝ k α exhibit non-Anderson disorder-driven transitions in dimensions d > 2 α , as exemplified by Weyl semimetals, 1D and 2D arrays of ultracold ions with long-range interactions, quantum kicked rotors, and semiconductor models in high dimensions. We study the wavefunction structure in such systems and demonstrate that at these transitions they exhibit fractal behaviour with an infinite set of multifractal exponents. The multifractality persists even when the wavefunction localisation is forbidden by symmetry or topology and occurs as a result of elastic scattering between all momentum states in the band on length scales shorter than the mean free path. We calculate explicitly the multifractal spectra in semiconductors and Weyl semimetals using one-loop and two-loop renormalisation-group approaches slightly above the marginal dimension d = 2 α .
Synthetic foundations of cevian geometry, III: the generalized orthocenter

In this paper, the third in the series, we study the properties of the generalized orthocenter H corresponding to a point P, defined to be the unique point for which the lines HA, HB, HC are parallel, respectively, to QD, QE, QF, where DEF is the cevian triangle of P and \({Q = K \circ \iota(P)}\) is the isotomcomplement of P, both with respect to a given triangle ABC. We characterize the center Z of the cevian conic \({\mathcal{C}_P}\) on the 5 points ABCPQ as the center of the affine map \({\Phi_{P} = T_{P} \circ K^{-1} \circ T_{P'} \circ K^{-1}}\), where TP is the unique affine map for which TP(ABC) = DEF; TP' is defined similarly for the isotomic conjugate \({P' = \iota(P)}\) of P; and K is the complement map. The point Z is the point where the nine-point conic \({\mathcal{N}_H}\) for the quadrangle ABCH and the inconic \({\mathcal{I}}\) of ABC, tangent to the sides at D, E, F, touch. This theorem generalizes the classical Feuerbach theorem.
Cluster pinch-point densities in polygons

In a statistical cluster or loop model such as percolation, or more generally the Potts models or O(n) models, a pinch point is a single bulk point where several distinct clusters or loops touch. In a polygon P harboring such a model in its interior and with 2N sides exhibiting free/fixed side-alternating boundary conditions, boundary clusters anchor to the fixed sides of P. At the critical point and in the continuum limit, the density (i.e. frequency of occurrence) of pinch-points between s distinct boundary clusters at a bulk point w ∈ P is proportional to � ψ c
Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

Data science models, although successful in a number of commercial domains, have had limited applicability in scientific problems involving complex physical phenomena. Theory-guided data science (TGDS) is an emerging paradigm that aims to leverage the wealth of scientific knowledge for improving the effectiveness of data science models in enabling scientific discovery. The overarching vision of TGDS is to introduce scientific consistency as an essential component for learning generalizable models. Further, by producing scientifically interpretable models, TGDS aims to advance our scientific understanding by discovering novel domain insights. Indeed, the paradigm of TGDS has started to gain prominence in a number of scientific disciplines such as turbulence modeling, material discovery, quantum chemistry, bio-medical science, bio-marker discovery, climate science, and hydrology. In this paper, we formally conceptualize the paradigm of TGDS and present a taxonomy of research themes in TGDS. We describe several approaches for integrating domain knowledge in different research themes using illustrative examples from different disciplines. We also highlight some of the promising avenues of novel research for realizing the full potential of theory-guided data science.
A Note on Low Energy Scattering for Homogeneous Long-Range Potentials

We explicitly calculate the scattering matrix at energy zero for attractive, radial and homogeneous long-range potentials. This proves a conjecture by Derezinski and Skibsted.
Stability of gapped ground state phases of spins and fermions in one dimension

We investigate the persistence of spectral gaps of one-dimensional frustration free quantum lattice systems under weak perturbations and with open boundary conditions. Assuming that the interactions of the system satisfy a form of local topological quantum order, we prove explicit lower bounds on the ground state spectral gap and higher gaps for spin and fermion chains. By adapting previous methods using the spectral flow, we analyze the bulk and edge dependence of lower bounds on spectral gaps.
Distributed Constrained Recursive Nonlinear Least-Squares Estimation: Algorithms and Asymptotics

This paper focuses on recursive nonlinear least-squares parameter estimation in multiagent networks, where the individual agents observe sequentially over time an independent and identically distributed time-series consisting of a nonlinear function of the true but unknown parameter corrupted by noise. A distributed recursive estimator of the consensus+innovations type, namely $\mathcal {CIWNLS}$ , is proposed, in which the agents update their parameter estimates at each observation sampling epoch in a collaborative way by simultaneously processing the latest locally sensed information (innovations) and the parameter estimates from other agents (consensus) in the local neighborhood conforming to a prespecified interagent communication topology. Under rather weak conditions on the connectivity of the interagent communication and a global observability criterion, it is shown that, at every network agent, $\mathcal {CIWNLS}$ leads to consistent parameter estimates. Furthermore, under standard smoothness assumptions on the local observation functions, the distributed estimator is shown to yield order-optimal convergence rates, i.e., as far as the order of pathwise convergence is concerned, the local parameter estimates at each agent are as good as the optimal centralized nonlinear least-squares estimator that requires access to all the observations across all the agents at all times. To benchmark the performance of the $\mathcal {CIWNLS}$ estimator with that of the centralized nonlinear least-squares estimator, the asymptotic normality of the estimate sequence is established, and the asymptotic covariance of the distributed estimator is evaluated.
An End-to-End Conversational Style Matching Agent

We present an end-to-end voice-based conversational agent that is able to engage in naturalistic multi-turn dialogue and align with the interlocutor's conversational style. The system uses a series of deep neural network components for speech recognition, dialogue generation, prosodic analysis and speech synthesis to generate language and prosodic expression with qualities that match those of the user. We conducted a user study (N=30) in which participants talked with the agent for 15 to 20 minutes, resulting in over 8 hours of natural interaction data. Users with high consideration conversational styles reported the agent to be more trustworthy when it matched their conversational style. Whereas, users with high involvement conversational styles were indifferent. Finally, we provide design guidelines for multi-turn dialogue interactions using conversational style adaptation.
Intersections of Multiplicative Translates of 3-Adic Cantor Sets II: Two Infinite Families

ABSTRACTThis article studies the structure of finite intersections of general multiplicative translates for integers 1 ⩽ M1 < M2 < ⋅⋅⋅ < Mn, in which denotes the 3-adic Cantor set (of 3-adic integers whose expansions omit the digit 2), which has Hausdorff dimension log 32 ≈ 0.630929. This study was motivated by questions concerning the discrete dynamical system on the 3-adic integers given by multiplication by 2. The exceptional set is defined to be the set of all elements of whose forward orbits under this action intersect the 3-adic Cantor set infinitely many times. It is conjectured that it has Hausdorff dimension 0. An earlier article showed that upper bounds on the Hausdorff dimension of the exceptional set can be extracted from knowing Hausdorff dimensions of sets of the kind above, in cases where all Mi are powers of 2. These intersection sets were shown to be fractals whose points have 3-adic expansions describable by labeled paths in a finite automaton, whose Hausdorff dimension is exactly comput...
Cloning Hubble Deep Fields. I. A Model-independent Measurement of Galaxy Evolution

We present a model-independent method of quantifying galaxy evolution in high-resolution images, a method which we apply to the Hubble Deep Field (HDF). Our procedure is to k-correct all pixels belonging to the images of a complete set of bright galaxies and then to replicate each galaxy image to higher redshift by the product of its space density, 1/Vmax, and the cosmological volume. The set of bright galaxies is itself selected from the HDF, because presently the HDF provides the highest quality UV images of a redshift-complete sample of galaxies (31 galaxies with I 24) are much smaller, more numerous, and less regular than our no-evolution extrapolation, for any interesting geometry. A higher proportion of HDF galaxies "dropout" in both U and B, indicating that some galaxies are brighter at higher redshifts than our "cloned" z ~ 0.5 population.
Interpretable Entity Representations through Large-Scale Typing

In standard methodology for natural language processing, entities in text are typically embedded in dense vector spaces with pre-trained models. The embeddings produced this way are effective when fed into downstream models, but they require end-task fine-tuning and are fundamentally difficult to interpret. In this paper, we present an approach to creating entity representations that are human readable and achieve high performance on entity-related tasks out of the box. Our representations are vectors whose values correspond to posterior probabilities over fine-grained entity types, indicating the confidence of a typing model’s decision that the entity belongs to the corresponding type. We obtain these representations using a fine-grained entity typing model, trained either on supervised ultra-fine entity typing data (Choi et al. 2018) or distantly-supervised examples from Wikipedia. On entity probing tasks involving recognizing entity identity, our embeddings used in parameter-free downstream models achieve competitive performance with ELMo- and BERT-based embeddings in trained models. We also show that it is possible to reduce the size of our type set in a learning-based way for particular domains. Finally, we show that these embeddings can be post-hoc modified through a small number of rules to incorporate domain knowledge and improve performance.
Engineering dissipation with phononic spectral hole burning

Optomechanics, nano-electromechanics, and integrated photonics have brought about a renaissance in phononic device physics and technology. Central to this advance are devices and materials supporting ultra-long-lived photonic and phononic excitations that enable novel regimes of classical and quantum dynamics based on tailorable photon-phonon coupling. Silica-based devices have been at the forefront of such innovations for their ability to support optical excitations persisting for nearly 1 billion cycles, and for their low optical nonlinearity. While acoustic phonon modes can persist for a similar number of cycles in crystalline solids at cryogenic temperatures, it has not been possible to achieve such performance in silica, as silica becomes acoustically opaque at low temperatures. We demonstrate that these intrinsic forms of phonon dissipation are greatly reduced (by >90%) by nonlinear saturation using continuous drive fields of disparate frequencies. The result is a form of steady-state phononic spectral hole burning that produces a wideband transparency window with optically generated phonon fields of modest (nW) powers. We developed a simple model that explains both dissipative and dispersive changes produced by phononic saturation. Our studies, conducted in a microscale device, represent an important step towards engineerable phonon dynamics on demand and the use of glasses as low-loss phononic media.
Optimizing pilot overhead for ultra-reliable short-packet transmission

In this paper we optimize the pilot overhead for ultra-reliable short-packet transmission and investigate the dependence of this overhead on packet size and error probability. In particular, we consider a point-to-point communication in which one sensor sends messages to a central node, or base-station, over AWGN with Rayleigh fading channel. We formalize the optimization in terms of approximate achievable rates at a given block length, pilot length, and error probability. This leads to more accurate pilot overhead optimization. Simulation results show that it is important to take into account the packet size and the error probability when optimizing the pilot overhead.
Optimal Strategy in "Guess Who?": Beyond Binary Search

“Guess Who?” is a popular two player game where players ask “Yes”/“No” questions to search for their opponent's secret identity from a pool of possible candidates. This is modeled as a simple stochastic game. Using this model, the optimal strategy is explicitly found. Contrary to popular belief, performing a binary search is not always optimal. Instead, the optimal strategy for the player who trails is to make certain bold plays in an attempt catch up. This is discovered by first analyzing a continuous version of the game where players play indefinitely and the winner is never decided after finitely many rounds.
Torsion in one-term distributive homology

The one-term distributive homology was introduced by J.H.Przytycki as an atomic replacement of rack and quandle homology, which was first introduced and developed by R.Fenn, C.Rourke and B.Sanderson, and J.S.Carter, S.Kamada and M.Saito. This homology was initially suspected to be torsion-free, but we show in this paper that the one-term homology of a finite spindle can have torsion. We carefully analyze spindles of block decomposition of type (n,1) and introduce various techniques to compute their homology precisely. In addition, we show that any finite group can appear as the torsion subgroup of the first homology of some finite spindle. Finally, we show that if a shelf satisfies a certain, rather general, condition then the one-term homology is trivial.