cssi/SciSciGPT-SciSciNet huggingface dataset:
On the Turaev-Viro endomorphism and the colored Jones polynomial

By applying a variant of the TQFT constructed by Blanchet, Habegger, Masbaum and Vogel and using a construction of Ohtsuki, we define a module endomorphism for each knot K by using a tangle obtained from a surgery presentation of K . We show that it is strong shift equivalent to the Turaev‐Viro endomorphism associated to K . Following Viro, we consider the endomorphisms that one obtains after coloring the meridian and the longitude of the knot. We show that the traces of these endomorphisms encode the same information as the colored Jones polynomials of K at a root of unity. Most of the discussion is carried out in the more general setting of infinite cyclic covers of 3‐manifolds. 57M25, 57M27, 57R56
Magnetic Boron Nitride Nanoribbons with Tunable Electronic Properties

We present theoretical evidence, based on total-energy first-principles calculations, of the existence of spin-polarized states well localized at and extended along the edges of bare zigzag boron nitride nanoribbons. Our calculations predict that all the magnetic configurations studied in this work are thermally accessible at room temperature and present an energy gap. In particular, we show that the high spin state, with a magnetic moment of 1 μB at each edge atom, presents a rich spectrum of electronic behaviors as it can be controlled by applying an external electric field in order to obtain metallic ↔ semiconducting ↔ half-metallic transitions.
Quantitative Mode Stability for the Wave Equation on the Kerr Spacetime

We give a quantitative refinement and simple proofs of mode stability type statements for the wave equation on Kerr backgrounds in the full sub-extremal range (|a| < M). As an application, we are able to quantitatively control the energy flux along the horizon and null infinity and establish integrated local energy decay for solutions to the wave equation in any bounded-frequency regime.
THE MEASUREMENT, TREATMENT, AND IMPACT OF SPECTRAL COVARIANCE AND BAYESIAN PRIORS IN INTEGRAL-FIELD SPECTROSCOPY OF EXOPLANETS

The recovery of an exoplanet's atmospheric parameters from its spectrum requires accurate knowledge of the spectral errors and covariances. Unfortunately, the complex image processing used in high-contrast integral-field spectrograph (IFS) observations generally produces spectral covariances that are poorly understood and often ignored. In this work, we show how to measure the spectral errors and covariances and include them self-consistently in parameter retrievals. By combining model exoplanet spectra with a realistic noise model generated from GPI early science data, we show that ignoring spectral covariance in high-contrast IFS data can both bias inferred parameters and lead to unreliable confidence regions on those parameters. This problem is made worse by the common practice of scaling the $\chi^2$ per degree of freedom to unity; the input parameters then fall outside the $95\%$ confidence regions in as many as ${\sim}80\%$ of noise realizations. The biases we observe can approach the typical levels of precision achieved in high-contrast spectroscopy. Accounting for realistic priors in fully Bayesian retrievals can also have a significant impact on the inferred parameters. Plausible priors on effective temperature and surface gravity can vary by an order of magnitude across the confidence regions appropriate for objects with weak age constraints; priors for objects with good age constraints are dominated by modeling uncertainties. Our methods are directly applicable to existing high-contrast IFSs including GPI and SPHERE, as well as upcoming instruments like CHARIS and, ultimately, WFIRST-AFTA.
On the symplectic cohomology of log Calabi–Yau surfaces

We study the symplectic cohomology of affine algebraic surfaces that admit a compactification by a normal crossings anticanonical divisor. Using a toroidal structure near the compactification divisor, we describe the complex computing symplectic cohomology, and compute enough differentials to identify a basis for the degree zero part of the symplectic cohomology. This basis is indexed by integral points in a certain integral affine manifold, providing a relationship to the theta functions of Gross, Hacking and Keel. Included is a discussion of wrapped Floer cohomology of Lagrangian submanifolds and a description of the product structure in a special case. We also show that, after enhancing the coefficient ring, the degree zero symplectic cohomology defines a family degenerating to a singular surface obtained by gluing together several affine planes.
Microscopic diagonal entropy and its connection to basic thermodynamic relations

The author acknowledges helpful discussions with R. Barankov on earlier stages of this work. The author also thanks C. Gogolin for sharing the proof of Eq. (24) and for many valuable comments. It is also a pleasure to acknowledge E. Altman, S. Girvin, V. Gritsev, V. Gurarie, D. Huse, Y. Kafri, W. Zwerger for helpful discussions related to this work. This work was supported by NSF (DMR-0907039), AFOSR YIP, AFOSR FA9550-10-1-0110, and Sloan Foundation. (DMR-0907039 - NSF; AFOSR YIP; FA9550-10-1-0110 - AFOSR; Sloan Foundation)
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores

The increased use of algorithmic predictions in sensitive domains has been accompanied by both enthusiasm and concern. To understand the opportunities and risks of these technologies, it is key to study how experts alter their decisions when using such tools. In this paper, we study the adoption of an algorithmic tool used to assist child maltreatment hotline screening decisions. We focus on the question: Are humans capable of identifying cases in which the machine is wrong, and of overriding those recommendations? We first show that humans do alter their behavior when the tool is deployed. Then, we show that humans are less likely to adhere to the machine's recommendation when the score displayed is an incorrect estimate of risk, even when overriding the recommendation requires supervisory approval. These results highlight the risks of full automation and the importance of designing decision pipelines that provide humans with autonomy.
Experiments with a LoRaWAN-Based Remote ID System for Locating Unmanned Aerial Vehicles (UAVs)

Federal Aviation Administration (FAA) of the United States is considering Remote ID systems for unmanned aerial vehicles (UAVs). These systems act as license plates used on automobiles, but they transmit information using radio waves. To be useful, the transmissions in such systems need to reach long distances to minimize the number of ground stations to capture these transmissions. LoRaWAN is designed as a cheap long-range technology to be used for long-range communication for the Internet of Things. Several manufacturers make LoRaWAN modules, which are readily available on the market and are, therefore, ideal for the UAVs Remote IDs at a low cost. In this paper, we present our experiences in using LoRaWAN technology as a communication technology. Our experiments to identify and locate the UAV systems uncovered several issues of using LoRaWAN in such systems that are documented in this paper. Using several ground stations, we can determine the location of a UAV equipped with a LoRaWAN module that transmits the UAV Remote ID. Hence, it can help identify UAVs that unintentionally, or intentionally, fly into restricted zones.
NOISE CORRUPTION OF EMPIRICAL MODE DECOMPOSITION AND ITS EFFECT ON INSTANTANEOUS FREQUENCY

Huang's Empirical Mode Decomposition (EMD) is an algorithm for analyzing nonstationary data that provides a localized time-frequency representation by decomposing the data into adaptively defined modes. EMD can be used to estimate a signal's instantaneous frequency (IF) but suffers from poor performance in the presence of noise. To produce a meaningful IF, each mode of the decomposition must be nearly monochromatic, a condition that is not guaranteed by the algorithm and fails to be met when the signal is corrupted by noise. In this work, the extraction of modes containing both signal and noise is identified as the cause of poor IF estimation. The specific mechanism by which such "transition" modes are extracted is detailed and builds on the observation of Flandrin and Goncalves that EMD acts in a filter bank manner when analyzing pure noise. The mechanism is shown to be dependent on spectral leak between modes and the phase of the underlying signal. These ideas are developed through the use of simple signals and are tested on a synthetic seismic waveform.
Neutrinos from Fallback onto Newly Formed Neutron Stars

In the standard supernova picture, Type Ib/c and Type II supernovae are powered by the potential energy released in the collapse of the core of a massive star. In studying supernovae, we primarily focus on the ejecta that makes it beyond the potential well of the collapsed core. But, as we shall show in this paper, in most supernova explosions a tenth of a solar mass or more of the ejecta is decelerated enough that it does not escape the potential well of that compact object. This material falls back onto the proto-neutron star within the first 10-15 s after the launch of the explosion, releasing more than 1052 erg of additional potential energy. Most of this energy is emitted in the form of neutrinos and we must understand this fallback neutrino emission if we are to use neutrino observations to study the behavior of matter at high densities. Here we present both a one-dimensional study of fallback using energy-injected, supernova explosions and a first study of neutrino emission from fallback using a suite of two-dimensional simulations.
COLOR SYSTEMATICS OF COMETS AND RELATED BODIES

Most comets are volatile-rich bodies that have recently entered the inner solar system following long-term storage in the Kuiper belt and the Oort cloud reservoirs. These reservoirs feed several distinct, short-lived “small body” populations. Here, we present new measurements of the optical colors of cometary and comet-related bodies including long-period (Oort cloud) comets, Damocloids (probable inactive nuclei of long-period comets) and Centaurs (recent escapees from the Kuiper belt and precursors to the Jupiter family comets). We combine the new measurements with published data on short-period comets, Jovian Trojans and Kuiper belt objects to examine the color systematics of the comet-related populations. We find that the mean optical colors of the dust in short-period and long-period comets are identical within the uncertainties of measurement, as are the colors of the dust and of the underlying nuclei. These populations show no evidence for scattering by optically small particles or for compositional gradients, even at the largest distances from the Sun, and no evidence for ultrared matter. Consistent with earlier work, ultrared surfaces are common in the Kuiper belt and on the Centaurs, but not in other small body populations, suggesting that this material is hidden or destroyed upon entry to the inner solar system. The onset of activity in the Centaurs and the disappearance of the ultrared matter in this population begin at about the same perihelion distance (∼10 AU), suggesting that the two are related. Blanketing of primordial surface materials by the fallback of sub-orbital ejecta, for which we calculate a very short timescale, is the likely mechanism. The same process should operate on any mass-losing body, explaining the absence of ultrared surface material in the entire comet population.
INTEGRAL FIELD SPECTROSCOPY OF AGN ABSORPTION OUTFLOWS: MRK 509 AND IRAS F04250–5718

Ultravoilet (UV) absorption lines provide abundant spectroscopic information enabling the probe of the physical conditions in AGN outflows, but the outflow radii (and the energetics consequently) can only be determined indirectly. In this paper, we present the first direct test of these determinations using integral field unit (IFU) spectroscopy. We have conducted Gemini IFU mapping of the ionized gas nebulae surrounding two AGNs, whose outflow radii have been constrained by UV absorption line analyses. In Mrk 509, we find a quasi-spherical outflow with a radius of 1.2 kpc and a velocity of $\sim290$ km s$^{-1}$, while IRAS F04250$-$5718 is driving a biconical outflow extending out to 2.9 kpc, with a velocity of $\sim580$ km s$^{-1}$ and an opening angle of $\sim70^{\circ}$. The derived mass flow rate is $\sim5$ and $>1$ M$_{\odot}$ yr$^{-1}$, respectively, and the kinetic luminosity is $\gtrsim1\times10^{41}$ erg s$^{-1}$ for both. Adopting the outflow radii and geometric parameters measured from IFU, absorption line analyses would yield mass flow rates and kinetic luminosities in agreement with the above results within a factor of $\sim2$. We conclude that the spatial locations, kinematics and energetics revealed by this IFU emission-line study are consistent with pre-existing UV absorption line analyses, providing a long-awaited direct confirmation of the latter as an effective approach for characterizing outflow properties.
Shift in Critical Temperature for Random Spatial Permutations with Cycle Weights

We examine a phase transition in a model of random spatial permutations which originates in a study of the interacting Bose gas. Permutations are weighted according to point positions; the low-temperature onset of the appearance of arbitrarily long cycles is connected to the phase transition of Bose-Einstein condensates. In our simplified model, point positions are held fixed on the fully occupied cubic lattice and interactions are expressed as Ewens-type weights on cycle lengths of permutations. The critical temperature of the transition to long cycles depends on an interaction-strength parameter α. For weak interactions, the shift in critical temperature is expected to be linear in α with constant of linearity c. Using Markov chain Monte Carlo methods and finite-size scaling, we find c=0.618±0.086. This finding matches a similar analytical result of Ueltschi and Betz. We also examine the mean longest cycle length as a fraction of the number of sites in long cycles, recovering an earlier result of Shepp and Lloyd for non-spatial permutations.
The Phase Transition in Statistical Models Defined on Farey Fractions

We consider several statistical models defined on the Farey fractions. Two of these models may be regarded as “spin chains,” with long-range interactions, while another arises in the study of multifractals associated with chaotic maps exhibiting intermittency. We prove that these models all have the same free energy. Their thermodynamic behavior is determined by the spectrum of the transfer operator (Ruelle–Perron–Frobenius operator), which is defined using the maps (presentation functions) generating the Farey “tree.” The spectrum of this operator was completely determined by Prellberg. It follows that these models have a second-order phase transition with a specific heat divergence of the form C ∼ [∈ ln2∈]−1. The spin chain models are also rigorously known to have a discontinuity in the magnetization at the phase transition.
Semiclassical Soliton Ensembles for the Three-Wave Resonant Interaction Equations

The three-wave resonant interaction equations are a non-dispersive system of partial differential equations with quadratic coupling describing the time evolution of the complex amplitudes of three resonant wave modes. Collisions of wave packets induce energy transfer between different modes via pumping and decay. We analyze the collision of two or three packets in the semiclassical limit by applying the inverse-scattering transform. Using WKB analysis, we construct an associated semiclassical soliton ensemble, a family of reflectionless solutions defined through their scattering data, intended to accurately approximate the initial data in the semiclassical limit. The map from the initial packets to the soliton ensemble is explicit and amenable to asymptotic and numerical analysis. Plots of the soliton ensembles indicate the space–time plane is partitioned into regions containing either quiescent, slowly varying, or rapidly oscillatory waves. This behavior resembles the well-known generation of dispersive shock waves in equations such as the Korteweg–de Vries and nonlinear Schrodinger equations, although the physical mechanism must be different in the absence of dispersion.
Convergence of random zeros on complex manifolds

We show that the zeros of random sequences of Gaussian systems of polynomials of increasing degree almost surely converge to the expected limit distribution under very general hypotheses. In particular, the normalized distribution of zeros of systems of m polynomials of degree N, orthonormalized on a regular compact set K ⊂ ℂ m , almost surely converge to the equilibrium measure on K as N → ∞.
Milky Way tomography with K and M dwarf stars: The vertical structure of the galactic disk

We use the number density distributions of K and M dwarf stars with vertical height from the Galactic disk, determined using observations from the Sloan Digital Sky Survey, to probe the structure of the Milky Way disk across the survey's footprint. Using photometric parallax as a distance estimator we analyze a sample of several million disk stars in matching footprints above and below the Galactic plane, and we determine the location and extent of vertical asymmetries in the number counts in a variety of thin- and thick-disk subsamples in regions of some 200 square degrees within 2 kpc in vertical distance from the Galactic disk. These disk asymmetries present wave-like features as previously observed on other scales and at other distances from the Sun. We additionally explore the scale height of the disk and the implied offset of the Sun from the Galactic plane at different locations, noting that the scale height of the disk can differ significantly when measured using stars only above or only below the plane. Moreover, we compare the shape of the number density distribution in the north for different latitude ranges with a fixed range in longitude and find the shape to be sensitive to the selected latitude window. We explain why this may be indicative of a change in stellar populations in the latitude regions compared, possibly allowing access to the systematic metallicity difference between thin- and thick-disk populations through photometry.
Almost sure convergence in quantum spin glasses

Recently, Keating, Linden, and Wells [Markov Processes Relat. Fields 21(3), 537-555 (2015)] showed that the density of states measure of a nearest-neighbor quantum spin glass model is approximately Gaussian when the number of particles is large. The density of states measure is the ensemble average of the empirical spectral measure of a random matrix; in this paper, we use concentration of measure and entropy techniques together with the result of Keating, Linden, and Wells to show that in fact the empirical spectral measure of such a random matrix is almost surely approximately Gaussian itself with no ensemble averaging. We also extend this result to a spherical quantum spin glass model and to the more general coupling geometries investigated by Erdős and Schroder [Math. Phys., Anal. Geom. 17(3-4), 441–464 (2014)].
A damage model for fracking

Injections of large volumes of water into tight shale reservoirs allow the extraction of oil and gas not previously accessible. This large volume “super” fracking induces damage that allows the oil...
Scaling configuration of energy harvesting sensors with reinforcement learning

With the advent of the Internet of Things (IoT), an increasing number of energy harvesting methods are being used to supplement or supplant battery based sensors. Energy harvesting sensors need to be configured according to the application, hardware, and environmental conditions to maximize their usefulness. As of today, the configuration of sensors is either manual or heuristics based, requiring valuable domain expertise. Reinforcement learning (RL) is a promising approach to automate configuration and efficiently scale IoT deployments, but it is not yet adopted in practice. We propose solutions to bridge this gap: reduce the training phase of RL so that nodes are operational within a short time after deployment and reduce the computational requirements to scale to large deployments. We focus on configuration of the sampling rate of indoor solar panel based energy harvesting sensors. We created a simulator based on 3 months of data collected from 5 sensor nodes subject to different lighting conditions. Our simulation results show that RL can effectively learn energy availability patterns and configure the sampling rate of the sensor nodes to maximize the sensing data while ensuring that energy storage is not depleted. The nodes can be operational within the first day by using our methods. We show that it is possible to reduce the number of RL policies by using a single policy for nodes that share similar lighting conditions.
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo

Sampling from a log-concave distribution function is one core problem that has wide applications in Bayesian statistics and machine learning. While most gradient free methods have slow convergence rate, the Langevin Monte Carlo (LMC) that provides fast convergence requires the computation of gradients. In practice one uses finite-differencing approximations as surrogates, and the method is expensive in high-dimensions. A natural strategy to reduce computational cost in each iteration is to utilize random gradient approximations, such as random coordinate descent (RCD) or simultaneous perturbation stochastic approximation (SPSA). We show by a counter-example that blindly applying RCD does not achieve the goal in the most general setting. The high variance induced by the randomness means a larger number of iterations are needed, and this balances out the saving in each iteration. We then introduce a new variance reduction approach, termed Randomized Coordinates Averaging Descent (RCAD), and incorporate it with both overdamped and underdamped LMC. The methods are termed RCAD-O-LMC and RCAD-U-LMC respectively. The methods still sit in the random gradient approximation framework, and thus the computational cost in each iteration is low. However, by employing RCAD, the variance is reduced, so the methods converge within the same number of iterations as the classical overdamped and underdamped LMC. This leads to a computational saving overall.
NOTHING TO HIDE: AN X-RAY SURVEY FOR YOUNG STELLAR OBJECTS IN THE PIPE NEBULA

We have previously analyzed sensitive mid-infrared observations to establish that the Pipe Nebula (PiN) has a very low star formation efficiency. That study focused on young stellar objects (YSOs) with excess infrared emission (i.e., protostars and pre-main-sequence stars with disks), however, and could have missed a population of more evolved pre-main-sequence stars or Class III objects (i.e., young stars with dissipated disks that no longer show excess infrared emission). Evolved pre-main-sequence stars are X-ray bright, so we have used ROSAT All-Sky Survey data to search for diskless pre-main-sequence stars throughout the PiN. We have also analyzed archival XMM-Newton observations of three prominent areas within the Pipe: Barnard 59 (B 59), containing a known cluster of YSOs; Barnard 68, a dense core that has yet to form stars; and the Pipe molecular ring, a high-extinction region in the bowl of the Pipe. We also characterize the X-ray properties of YSOs in B 59. The ROSAT and XMM-Newton data provide no indication of a significant population of more evolved pre-main-sequence stars within the Pipe, reinforcing our previous measurement of the Pipe's very low star formation efficiency.
Intradomain phase transitions in flexible block copolymers with self-aligning segments

We study a model of flexible block copolymers (BCPs) in which there is an enlthalpic preference for orientational order, or local alignment, among like-block segments. We describe a generalization of the self-consistent field theory of flexible BCPs to include inter-segment orientational interactions via a Landau-de Gennes free energy associated with a polar or nematic order parameter for segments of one component of a diblock copolymer. We study the equilibrium states of this model numerically, using a pseudo-spectral approach to solve for chain conformation statistics in the presence of a self-consistent torque generated by inter-segment alignment forces. Applying this theory to the structure of lamellar domains composed of symmetric diblocks possessing a single block of "self-aligning" polar segments, we show the emergence of spatially complex segment order parameters (segment director fields) within a given lamellar domain. Because BCP phase separation gives rise to spatially inhomogeneous orientation order of segments even in the absence of explicit intra-segment aligning forces, the director fields of BCPs, as well as thermodynamics of lamellar domain formation, exhibit a highly non-linear dependence on both the inter-block segregation (χN) and the enthalpy of alignment (e). Specifically, we predict the stability of new phases of lamellar order in which distinct regions of alignment coexist within the single mesodomain and spontaneously break the symmetries of the lamella (or smectic) pattern of composition in the melt via in-plane tilt of the director in the centers of the like-composition domains. We further show that, in analogy to Freedericksz transition confined nematics, the elastic costs to reorient segments within the domain, as described by the Frank elasticity of the director, increase the threshold value e needed to induce this intra-domain phase transition.
Monopole Bubbling via String Theory

In this paper, we propose a string theory description of generic ’t Hooft defects in $$ \mathcal{N}=2 $$ SU(N) supersymmetric gauge theories. We show that the space of supesrsymmetric ground states is given by the moduli space of singular monopoles and that in this setting, Kronheimer’s correspondence is realized as T-duality. We conjecture that this brane configuration can be used to study the full dynamics of monopole bubbling.
DETECTION OF A DISTINCT METAL-POOR STELLAR HALO IN THE EARLY-TYPE GALAXY NGC 3115*

We present the resolved stellar populations in the inner and outer halo of the nearby lenticular galaxy NGC 3115. Using deep Hubble Space Telescope observations, we analyze stars 2 mag fainter than the tip of the red giant branch (TRGB). We study three fields along the minor axis of this galaxy, 19, 37, and 54 kpc from its center—corresponding to 7, 14, and 21 effective radii (re ). Even at these large galactocentric distances, all of the fields are dominated by a relatively enriched population, with the main peak in the metallicity distribution decreasing with radius from [Z/H] ~ –0.5 to –0.65. The fraction of metal-poor stars ([Z/H] < –0.95) increases from 17% at 16-37 kpc to 28% at ~54 kpc. We observe a distinct low-metallicity population (peaked at [Z/H] ~ –1.3 and with total mass 2 × 1010 M ☉ ~ 14% of the galaxy's stellar mass) and argue that this represents the detection of an underlying low-metallicity stellar halo. Such halos are generally predicted by galaxy formation theories and have been observed in several late-type galaxies, including the Milky Way and M31. The metallicity and spatial distribution of the stellar halo of NGC 3115 are consistent with the galaxy's globular cluster system, which has a similar low-metallicity population that becomes dominant at these large radii. This finding supports the use of globular clusters as bright chemodynamical tracers of galaxy halos. These data also allow us to make a precise measurement of the magnitude of the TRGB, from which we derive a distance modulus of NGC 3115 of 30.05 ± 0.05 ± 0.10sys (10.2 ± 0.2 ± 0.5sys Mpc).
On the interplay between exposure misclassification and informative cluster size

In this paper we study the impact of exposure misclassification when cluster size is potentially informative (i.e., related to outcomes) and when misclassification is differential by cluster size. First, we show that misclassification in an exposure related to cluster size can induce informativeness when cluster size would otherwise be non-informative. Second, we show that misclassification that is differential by informative cluster size can not only attenuate estimates of exposure effects but even inflate or reverse the sign of estimates. To correct for bias in estimating marginal parameters, we propose two frameworks: (i) an observed likelihood approach for joint marginalized models of cluster size and outcomes and (ii) an expected estimating equations approach. Although we focus on estimating marginal parameters, a corollary is that the observed likelihood approach permits valid inference for conditional parameters as well. Using data from the Nurses Health Study II, we compare the results of the proposed correction methods when applied to motivating data on the multigenerational effect of in-utero diethylstilbestrol exposure on attention-deficit/hyperactivity disorder in 106,198 children of 47,450 nurses.
Characterizing the Stability of NISQ Devices

In this study, we focus on the question of stability of NISQ devices. The parameters that define the device stability profile are motivated by the work of DiVincenzo in [9] where the requirements for physical implementation of quantum computing are discussed. We develop the metrics and theoretical framework to quantify the DiVincenzo requirements and study the stability of those key metrics. The basis of our assessment is histogram similarity (in time and space). For identical experiments, devices which produce reproducible histograms in time, and similar histograms in space, are considered more reliable. To investigate such reliability concerns robustly, we propose a moment-based distance (MBD) metric. We illustrate our methodology using data collected from IBM's Yorktown device. Two types of assessments are discussed: spatial stability and temporal stability.
Why Conventional Design Rules for C–H Activation Fail for Open-Shell Transition-Metal Catalysts

The design of selective and active C–H activation catalysts for direct methane-to-methanol conversion is challenging. Bioinspired complexes that form high-valent metal–oxo intermediates capable of ...
Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of .
Strongly refuting all semi-random Boolean CSPs

We give an efficient algorithm to strongly refute \emph{semi-random} instances of all Boolean constraint satisfaction problems. The number of constraints required by our algorithm matches (up to polylogarithmic factors) the best-known bounds for efficient refutation of fully random instances. Our main technical contribution is an algorithm to strongly refute semi-random instances of the Boolean $k$-XOR problem on $n$ variables that have $\widetilde{O}(n^{k/2})$ constraints. (In a semi-random $k$-XOR instance, the equations can be arbitrary and only the right-hand sides are random.) One of our key insights is to identify a simple combinatorial property of random XOR instances that makes spectral refutation work. Our approach involves taking an instance that does not satisfy this property (i.e., is \emph{not} pseudorandom) and reducing it to a partitioned collection of $2$-XOR instances. We analyze these subinstances using a carefully chosen quadratic form as a proxy, which in turn is bounded via a combination of spectral methods and semidefinite programming. The analysis of our spectral bounds relies only on an off-the-shelf matrix Bernstein inequality. Even for the purely random case, this leads to a shorter proof compared to the ones in the literature that rely on problem-specific trace-moment computations.
Nonconvex Regularization for Network Slimming: Compressing CNNs Even More

In the last decade, convolutional neural networks (CNNs) have evolved to become the dominant models for various computer vision tasks, but they cannot be deployed in low-memory devices due to its high memory requirement and computational cost. One popular, straightforward approach to compressing CNNs is network slimming, which imposes an \(\ell _1\) penalty on the channel-associated scaling factors in the batch normalization layers during training. In this way, channels with low scaling factors are identified to be insignificant and are pruned in the models. In this paper, we propose replacing the \(\ell _1\) penalty with the \(\ell _p\) and transformed \(\ell _1\) (T\(\ell _1\)) penalties since these nonconvex penalties outperformed \(\ell _1\) in yielding sparser satisfactory solutions in various compressed sensing problems. In our numerical experiments, we demonstrate network slimming with \(\ell _p\) and T\(\ell _1\) penalties on VGGNet and Densenet trained on CIFAR 10/100. The results demonstrate that the nonconvex penalties compress CNNs better than \(\ell _1\). In addition, T\(\ell _1\) preserves the model accuracy after channel pruning, and \(\ell _{1/2, 3/4}\) yield compressed models with similar accuracies as \(\ell _1\) after retraining.
An approximate Bayesian inference on propensity score estimation under unit nonresponse

Nonresponse weighting adjustment using the response propensity score is a popular tool for handling unit nonresponse. Statistical inference after the nonresponse weighting adjustment is complicated because the effect of estimating the propensity model parameter needs to be incorporated. In this paper, we propose an approximate Bayesian approach to handle unit nonresponse with parametric model assumptions on the response probability, but without model assumptions for the outcome variable. The proposed Bayesian method is calibrated to the frequentist inference in that the credible region obtained from the posterior distribution asymptotically matches to the frequentist confidence interval obtained from the Taylor linearization method. Unlike the frequentist approach, however, the proposed method does not involve Taylor linearization. The proposed method can be extended to handle over-identified cases in which there are more estimating equations than the parameters. Besides, the proposed method can also be modified to handle nonignorable nonresponse. Results from two simulation studies confirm the validity of the proposed methods, which are then applied to data from a Korean longitudinal survey.
Differentially Private Formation Control

As multi-agent systems proliferate, there is in-creasing demand for coordination protocols that protect agents’ sensitive information while allowing them to collaborate. To help address this need, this paper presents a differentially private formation control framework. Agents’ state trajectories are protected using differential privacy, which is a statistical notion of privacy that protects data by adding noise to it. We provide a private formation control implementation and analyze the impact of privacy upon the system. Specifically, we quantify tradeoffs between privacy level, system performance, and connectedness of the network’s communication topology. These tradeoffs are used to develop guidelines for calibrating privacy in terms of control theoretic quantities, such as steady-state error, without requiring in-depth knowledge of differential privacy. Additional guidelines are also developed for treating privacy levels and network topologies as design parameters to tune the network’s performance. Simulation results illustrate these tradeoffs and show that strict privacy is inherently compatible with strong system performance.
HIFiRE-5b Boundary-Layer Transition Length and Turbulent Overshoot

Hypersonic International Flight Research Experimentation 5 (HIFiRE-5) is a hypersonic flight-test experiment designed to investigate the aerothermodynamics of a 3-D geometry. The vehicle is an elli...
Ultrafast thermal modification of strong coupling in an organic microcavity

There is growing interest in using strongly coupled organic microcavities to tune molecular dynamics, including the electronic and vibrational properties of molecules. However, very little attention has been paid to the utility of cavity polaritons as sensors for out-of-equilibrium phenomena, including thermal excitations. Here, we demonstrate that non-resonant infrared excitation of an organic microcavity system induces a transient response in the visible spectral range near the cavity polariton resonances. We show how these optical responses can be understood in terms of ultrafast heating of electrons in the metal cavity mirror, which modifies the effective refractive index and subsequently the strong coupling conditions. The temporal dynamics of the microcavity are strictly determined by carriers in the metal, including the cooling of electrons via electron–phonon coupling and excitation of propagating coherent acoustic modes in the lattice. We rule out multiphoton excitation processes and verify that no real polariton population exists despite their strong transient features. These results suggest the cavity polaritons to be promising as sensitive probes of non-equilibrium phenomena.
A Theory of Endogenous Institutional Change

This paper asks (a) why and how institutions change, (b) how an institution persists in a changing environment, and (c) how processes that it unleashes lead to its own demise. The paper shows that the game-theoretic notion of self-enforcing equilibrium and the historical institutionalist focus on process are both inadequate to answer these questions. Building on a game-theoretic foundation, but responding to the critique of it by historical institutionalists, the paper introduces the concepts of quasi-parameters and self reinforcement. With these concepts, and building on repeated game theory, a dynamic approach to institutions is offered, one that can account for endogenous change (and stability) of institutions. Contextual accounts of formal governing institutions in early modern Europe and the informal institution of cleavage structure in the contemporary world provide illustrations of the approach.
Rights, Privileges, and Access to Information

Protecting property rights in creative works represent a classic institutional approach to a specific economic problem of non-rivalness and non-excludability of information. By providing the copyright owner with an enforceable right against nonpaying members of society, copyright laws encourage the production and dissemination of literary and artistic works to society for the purposes of learning. Implicit in the grant of property rights is the assumption that commercial incentives foster creative activity and productivity. In recent years, literary and artistic works have increasingly become the subject matter of exclusive property rights and control, particularly as new technologies emerge to provide users of creative works with greater access to informational goods. As a result of expanding property rights in literary and artistic works, society’s access to, and use of, information has, however, been severely restricted by increasing access costs despite the development of enabling technologies to facilitate greater access. This Article examines the general social claim to a right of access to information for the purposes of furthering the constitutional goals of promoting progress, and proposes that the question of access to information is a question of sustainable resource use that should not evoke the exclusionary rights of a strict property rule. The rights under copyright laws protect economic privileges in information and govern society’s use of informational resources. They do not provide copyright owners with a general right to exclude socially beneficial uses of informational works, are specifically tailored to increase social welfare, and must be distinguished from a property right to exclude others from use of a thing. Exclusionary property rights in creative works, arise, if at all, to protect an author’s creative integrity, validate the importance of authentic authorship, and provide personal and moral incentives for authors to produce creative works of social value. Property rights and economic privileges, this Article proposes, encourage the production of informational goods and are necessary to ensure the advancement of science and the useful arts in accordance with the Constitutional goals of the copyright system.
The Neuroscience Behind the Stock Market's Reaction to Corporate Earnings News

ABSTRACT: Using functional magnetic resonance imaging, we capture neural activity in the ventral striatum—a key area in the human brain's reward processing circuit—of 35 adult investors learning t...
Influence of the UV Environment on the Synthesis of Prebiotic Molecules.

Abstract Ultraviolet radiation is common to most planetary environments and could play a key role in the chemistry of molecules relevant to abiogenesis (prebiotic chemistry). In this work, we explore the impact of UV light on prebiotic chemistry that might occur in liquid water on the surface of a planet with an atmosphere. We consider effects including atmospheric absorption, attenuation by water, and stellar variability to constrain the UV input as a function of wavelength. We conclude that the UV environment would be characterized by broadband input, and wavelengths below 204 nm and 168 nm would be shielded out by atmospheric CO2 and water, respectively. We compare this broadband prebiotic UV input to the narrowband UV sources (e.g., mercury lamps) often used in laboratory studies of prebiotic chemistry and explore the implications for the conclusions drawn from these experiments. We consider as case studies the ribonucleotide synthesis pathway of Powner et al. (2009) and the sugar synthesis pathway of...
Surgery on a knot in (Surface x I)

Suppose F is a compact orientable surface, K is a knot in F × I, and (F × I)surg is the 3-manifold obtained by some non-trivial surgery on K. If F × {0} compresses in (F × I)surg , then there is an annulus in F × I with one end K and the other end an essential simple closed curve in F ×{0}. Moreover, the end of the annulus at K determines the surgery slope. An application: suppose M is a compact orientable 3-manifold that fibers over the circle. If surgery on K ⊂M yields a reducible manifold, then either • the projection K ⊂M → S1 has non-trivial winding number, • K lies in a ball, • K lies in a fiber, or • K is cabled The study of Dehn surgery on knots in 3-manifolds has a long and rich history, interacting in a deep way with • sophisticated combinatorics ([GL], [CGLS]), • the theory of character varieties ([CGLS], [BGZ]), and • sutured manifold theory ([Ga1], [Sch]) It is pleasing then to find a result that is simple to state, easy to understand and yet has so far escaped explicit notice. Yi Ni has pointed out that there is at least implicit overlap of our results with [Ni, Theorem 1.4 and Section 3]. Theorem 0.1. Suppose F is a compact orientable surface, K is a knot in F × I, and (F × I)surg is the 3-manifold obtained by some non-trivial surgery on K. If F ×{0} compresses in (F × I)surg, then K is parallel to an essential simple closed curve in F × {0}. Moreover, the annulus that describes the parallelism determines the slope of the surgery. An important precursor to this theorem is [BGZ, Proposition 4.6]. This proposition examines the same sort of question, but restricted to the case in which F is closed, and concludes that the slope of the surgery on K must be integral. It does not directly comment on the position of the knot in F × I, though the proof itself comes close: the proof of that proposition offers our conclusion (that the complement F × I− η(K) of a tubular neighborhood η(K) of K is what the authors call a “hollow product”) as one of two possibilities. Our argument is independent of this result, resting entirely on central sutured manifold results from [Ga2], [Ga3] and [Sch]. First some notation: Date: August 10, 2009.
The Nature of Precautionary Wealth

Abstract This paper uses the Panel Study of Income Dynamics to provide some of the first direct evidence that wealth is systematically higher for consumers with predictably greater income uncertainty. However, the apparent pattern of precautionary wealth is not consistent with a standard parameterization of the life cucle model in which consumers are patient enough to begin saving for retirement early in life; wealth is estimated to be far less sensitive to uncertainty than implied by that model. Instead, our results suggest that over most of their working life time, consumers behave in accordance with the ‘buffer-stock’ models of saving described in Carroll (1992, 1997) or Deaton (1991), in which consumers hold wealth principally to insulate consumption against near-term fluctuations in income.
The optimal level of experimentation

We assume that an impatient decision maker (DM) runs variable-size experiments at an increasing, strictly convex cost before choosing an irreversible action. We introduce and solve a tractable continuous time version of this problem --- a control of variance of a diffusion with uncertain mean. Assuming two states and two actions, we prove: (a) the optimal experimentation level rises in the Bellman value; and deduce testable implications, like (b) experimentation costs drift up; and (c) a more impatient decision maker may experiment more, given lump-sum final payoffs. We show that (a) and (b) are robust to finitely many states and actions, and we also extend an R&D interpretation of the model, where experimentation is monotonic not only in the value, but also in beliefs. Our intuition for our key monotonicity finding (a) is very economic. There are two decisions at each instant: stop or experiment, and then at what level n. The second choice equates the marginal costs and benefits of information: c'(n) = MB(n). In our diffusion setting, the marginal benefit of experimentation is constant, and so the total benefit TB is linear in the level: TB = n*MB = nc'(n). So the DM acts like a neoclassic competitive firm, producing information at an increasing marginal cost and selling it to himself at the fixed price c'(n). Since postponing the final decision entails a discounting cost, optimal stopping demands that the DM equate his producer surplus from experimentation nc'(n)-c(n) to the delay cost rV (given the interest rate r). Intuitively, the DM closes down his information firm (i.e. acts) when he cannot generate profits (producer surplus) to justify his capital rental (his deferred action). Since this surplus rises in quantity with convex costs, greater experimentation is needed to generate the higher surplus for a higher value V.
The World Trade Model: Revised estimates

Abstract This article presents updated and revised estimates for the International Monetary Fund's (IMF) World Trade Model (WTM). The model estimates import and export price and volume relationships for each of three types of merchandise trade—manufactures, raw material, and agricultural—for 14 of the largest industrial countries. The extended data set has generally resulted in estimated price and volume equations that fit the data better than previous versions of the model. In addition, the simulation properties of the model have been enhanced by imposing long-run activity elasticities of unity on the activity terms in the demand for imported manufactures equations.