cssi/SciSciGPT-SciSciNet huggingface dataset:
A Direct Test of Legislative Gatekeeping

Tests of legislative gatekeeping theories have been hampered by the absence of status quo estimates, making these tests vulnerable to selection bias. I overcome this problem with a novel data set on positions by private interests in Iowa, Nebraska, and Wisconsin, because these states' legislatures record organizations' positions on lobbied bills irrespective of whether the bills receive floor consideration. This permits an estimation of the ideological locations of status quo policies for bills with and without floor consideration, and in turn rigorous empirical tests of agenda control theories. The data provide substantial evidence of partisan and nonpartisan gatekeeping, and can adjudicate among the two models of gatekeeping in specific circumstances. In particular, they corroborate partisan gatekeeping in the Iowa House and the Wisconsin Assembly, and cannot distinguish between the two accounts in the other chambers. Moreover, the results show that strong partisan institutions need not result in predominantly partisan gatekeeping.
Rapid micro-immunohistochemistry.

We present a new and versatile implementation of rapid and localized immunohistochemical staining of tissue sections. Immunohistochemistry (IHC) comprises a sequence of specific biochemical reactions and allows the detection of specific proteins in tissue sections. For the rapid implementation of IHC, we fabricated horizontally oriented microfluidic probes (MFPs) with functionally designed apertures to enable square and circular footprints, which we employ to locally expose a tissue to time-optimized sequences of different biochemicals. We show that the two main incubation steps of IHC protocols can be performed on MDAMB468-1510A cell block sections in less than 30 min, compared to incubation times of an hour or more in standard protocols. IHC analysis on the timescale of tens of minutes could potentially be applied during surgery, enabling clinicians to react in more dynamically and efficiently. Furthermore, this rapid IHC implementation along with conservative tissue usage has strong potential for the implementation of multiplexed assays, allowing the exploration of optimal assay conditions with a small amount of tissue to ensure high-quality staining results for the remainder of the sample. A new microfluidic device enables immunohistochemistry analysis of tissue within minutes. Immunohistochemistry is a quantitative approach for the analysis of antigens in tissue sections, such as for the detection of cancer. Antibodies are introduced to the tissue that bind to specific antigens, enabling their detection. However, speeding up the diagnosis process, or detecting multiple antigens at one time, is challenging due to the complexity of antibody reactions with antigens. Here, a team from IBM Research Europe report an improved microfluidic process for immunohistochemistry. By using a horizontally oriented microfluidic probe they are able to speed-up reaction rates for the assay and switch between different processing liquids. This allows them to reduce the main incubation step time from an hour to less than 30 minutes.
Discrete Hamilton–Jacobi Theory

We develop a discrete analogue of Hamilton–Jacobi theory in the framework of discrete Hamiltonian mechanics. The resulting discrete Hamilton–Jacobi equation is discrete only in time. We describe a discrete analogue of Jacobi's solution and also prove a discrete version of the geometric Hamilton–Jacobi theorem. The theory applied to discrete linear Hamiltonian systems yields the discrete Riccati equation as a special case of the discrete Hamilton–Jacobi equation. We also apply the theory to discrete optimal control problems, and recover some well-known results, such as the Bellman equation (discrete-time HJB equation) of dynamic programming and its relation to the costate variable in the Pontryagin maximum principle. This relationship between the discrete Hamilton–Jacobi equation and Bellman equation is exploited to derive a generalized form of the Bellman equation that has controls at internal stages.
Low-shear three-dimensional equilibria in a periodic cylinder

We carry out expansions of non-symmetric toroidal ideal magnetohydrodynamic (MHD) equilibria with nested flux surfaces about a periodic cylinder, in which physical quantities are periodic of period in the cylindrical angle and . The cross-section of a flux surface at a constant toroidal angle is assumed to be approximately circular, and data are given on the cylindrical flux surface . Furthermore, we assume that the magnetic field lines are closed on the lowest-order flux surface, and the magnetic shear is relatively small. We extend earlier work in a flat torus by Weitzner (Phys. Plasmas, vol. 23, 2016, 062512) and demonstrate that a power series expansion can be carried out to all orders using magnetic flux as an expansion parameter. The cylindrical metric introduces certain new features to the expansions compared to the flat torus. However, the basic methodology of dealing with resonance singularities remains the same. The results, even though lacking convergence proofs, once again support the possibility of smooth, low-shear non-symmetric toroidal MHD equilibria.
Fivebranes and 3-manifold homology

Motivated by physical constructions of homological knot invariants, we study their analogs for closed 3-manifolds. We show that fivebrane compactifications provide a universal description of various old and new homological invariants of 3-manifolds. In terms of 3d/3d correspondence, such invariants are given by the Q-cohomology of the Hilbert space of partially topologically twisted 3d N=2 theory T[M_3] on a Riemann surface with defects. We demonstrate this by concrete and explicit calculations in the case of monopole/Heegaard Floer homology and a 3-manifold analog of Khovanov-Rozansky link homology. The latter gives a categorification of Chern-Simons partition function. Some of the new key elements include the explicit form of the S-transform and a novel connection between categorification and a previously mysterious role of Eichler integrals in Chern-Simons theory.
Arithmetic representations of fundamental groups I

Let X be a normal algebraic variety over a finitely generated field k of characteristic zero, and let $$\ell $$ be a prime. Say that a continuous $$\ell $$ -adic representation $$\rho $$ of $$\pi _1^{\acute{\mathrm{e}}\text {t}}(X_{\bar{k}})$$ is arithmetic if there exists a finite extension $$k'$$ of k, and a representation $$\tilde{\rho }$$ of $$\pi _1^{\acute{\mathrm{e}}\text {t}}(X_{k'})$$ , with $$\rho $$ a subquotient of $$\tilde{\rho }|_{\pi _1(X_{\bar{k}})}$$ . We show that there exists an integer $$N=N(X, \ell )$$ such that every nontrivial, semisimple arithmetic representation of $$\pi _1^{\acute{\mathrm{e}}\text {t}}(X_{\bar{k}})$$ is nontrivial mod $$\ell ^N$$ . As a corollary, we prove that any nontrivial $$\ell $$ -adic representation of $$\pi _1^{\acute{\mathrm{e}}\text {t}}(X_{\bar{k}})$$ which arises from geometry is nontrivial mod $$\ell ^N$$ .
A Resolution Study of Magnetically Arrested Disks

We investigate numerical convergence in simulations of magnetically arrested disks around spinning black holes. Using the general-relativistic magnetohydrodynamics code Athena++, we study the same system at four resolutions (up to an effective 512 × 256 × 512 cells) and with two different spatial reconstruction algorithms. The accretion rate and general large-scale structure of the flow agree across the simulations. This includes the amount of magnetic flux accumulated in the saturated state and the ensuing suppression of the magnetorotational instability from the strong field. The energy of the jet and the efficiency with which spin energy is extracted via the Blandford–Znajek process also show convergence. However the spatial structure of the jet shows variation across the set of grids employed, as do the Lorentz factors. Small-scale features of the turbulence, as measured by correlation lengths, are not fully converged. Despite convergence of a number of aspects of the flow, modeling of synchrotron emission shows that variability is not converged and decreases with increasing resolution even at our highest resolutions.
Experimental Calibration of a Cahn-Hilliard Phase-Field Model for Phase Transformations in Li-Sn Electrodes

Experiments, numerical simulations, and analytical calculations are used to calibrate a diffuse-interface Cahn-Hilliard model of Li-Sn thin film electrodes that experience a transformation from Sn to Li2Sn5. It is shown that a concentration-gradient dependent mobility can be used in the Cahn-Hilliard equation to give the interface a finite mobility and capture its nonequilibrium behavior. Comparing experiments and simulations, the free-energy of Li-Sn, diffusivity of Li in Sn and Li2Sn5, the exchange current density for the surface reaction, and the mobility of the Sn/Li2Sn5 interface are extracted. The implications of finite interface mobility for practical battery electrodes are discussed.
Fomenko–Mischenko Theory, Hessenberg Varieties, and Polarizations

The symmetric algebra \({S(\mathfrak{g})}\) over a Lie algebra \({\mathfrak{g}}\) has the structure of a Poisson algebra. Assume \({\mathfrak{g}}\) is complex semisimple. Then results of Fomenko–Mischenko (translation of invariants) and Tarasov construct a polynomial subalgebra \({{\mathcal {H}} = {\mathbb C}[q_1,\ldots,q_b]}\) of \({S(\mathfrak{g})}\) which is maximally Poisson commutative. Here b is the dimension of a Borel subalgebra of \({\mathfrak{g}}\). Let G be the adjoint group of \({\mathfrak{g}}\) and let l = rank \({\mathfrak{g}}\). Using the Killing form, identify \({\mathfrak{g}}\) with its dual so that any G-orbit O in \({\mathfrak{g}}\) has the structure (KKS) of a symplectic manifold and \({S(\mathfrak{g})}\) can be identified with the affine algebra of \({\mathfrak{g}}\). An element \({x\in \mathfrak{g}}\) will be called strongly regular if \({\{({\rm d}q_i)_x\},\,i=1,\ldots,b}\), are linearly independent. Then the set \({\mathfrak{g}^{\rm{sreg}}}\) of all strongly regular elements is Zariski open and dense in \({\mathfrak{g}}\) and also \({\mathfrak{g}^{\rm{sreg}}\subset \mathfrak{g}^{\rm{ reg}}}\) where \({\mathfrak{g}^{\rm{reg}}}\) is the set of all regular elements in \({\mathfrak{g}}\). A Hessenberg variety is the b-dimensional affine plane in \({\mathfrak{g}}\), obtained by translating a Borel subalgebra by a suitable principal nilpotent element. Such a variety was introduced in Kostant (Am J Math 85:327–404, 1963). Defining Hess to be a particular Hessenberg variety, Tarasov has shown that \({{\rm{Hess}}\subset \mathfrak{g}^{\rm{sreg}}}\). Let R be the set of all regular G-orbits in \({\mathfrak{g}}\). Thus if \({O\in R}\), then O is a symplectic manifold of dimension 2n where n = b − l. For any \({O\in R}\) let \({O^{\rm{sreg}} = \mathfrak{g}^{\rm{sreg}} \cap O}\). One shows that Osreg is Zariski open and dense in O so that Osreg is again a symplectic manifold of dimension 2n. For any \({O\in R}\) let \({{\rm{Hess}}(O) = {\rm{Hess}}\cap O}\). One proves that Hess(O) is a Lagrangian submanifold of Osreg and that $${\rm{Hess}} = \sqcup_{O\in R}{\rm{Hess}}(O).$$ The main result of this paper is to show that there exists simultaneously over all \({O\in R}\), an explicit polarization (i.e., a “fibration” by Lagrangian submanifolds) of Osreg which makes Osreg simulate, in some sense, the cotangent bundle of Hess(O).
Four-dimensional reflection groups and electrostatics

Abstract We present a new class of electrostatics problems that are exactly solvable by adding finitely many image charges. Given a charge at some location inside a cavity bounded by up to four conducting grounded segments of spheres: if the spheres have a symmetry derived via a stereographic projection from a 4D finite reflection group, then this is a solvable generalization of the familiar problem of a charge inside a spherical cavity. There are 19 three-parametric families of finite groups formed by inversions relative to at most four spheres, each member of each family giving a solvable problem. We solve a sample problem that derives from the reflection group D 4 and requires 191 image charges.
A p-adic Eisenstein measure for vector-weight automorphic forms

We construct a p-adic Eisenstein measure with values in the space of vector-weight p-adic automorphic forms on certain unitary groups. This measure allows us to p-adically interpolate special values of certain vector-weight C∞ automorphic forms, including Eisenstein series, as their weights vary. This completes a key step toward the construction of certain p-adic L-functions. We also explain how to extend our methods to the case of Siegel modular forms and how to recover Nicholas Katz’s p-adic families of Eisenstein series for Hilbert modular forms.
Black Holes with Short Hair

We present spherically symmetric black hole solutions for Einstein gravity coupled to anisotropic matter. We show that these black holes have arbitrarily short hair, and argue for stability by showing that they can arise from dynamical collapse. We also show that a recent "no short hair" theorem does not apply to these solutions.
Representing uncertainty on model analysis plots

Model analysis provides a mechanism for representing student learning as measured by standard multiple-choice surveys. The model plot contains information regarding both how likely students in a particular class are to choose the correct answer and how likely they are to choose an answer consistent with a well-documented conceptual model. Unfortunately Bao's original presentation of the model plot did not include a way to represent uncertainty in these measurements. I present details of a method to add error bars to model plots by expanding the work of Sommer and Lindell. I also provide a template for generating model plots with error bars.
Combining Harmonic Generation and Laser Chirping to Achieve High Spectral Density in Compton Sources

Recently various laser-chirping schemes have been investigated with the goal of reducing or eliminating ponderomotive line broadening in Compton or Thomson scattering occurring at high laser intensities. As a next level of detail in the spectrum calculations, we have calculated the line smoothing and broadening expected due to incident beam energy spread within a one-dimensional plane wave model for the incident laser pulse, both for compensated (chirped) and unchirped cases. The scattered compensated distributions are treatable analytically within three models for the envelope of the incident laser pulses: Gaussian, Lorentzian, or hyperbolic secant. We use the new results to demonstrate that the laser chirping in Compton sources at high laser intensities: (i) enables the use of higher order harmonics, thereby reducing the required electron beam energies; and (ii) increases the photon yield in a small frequency band beyond that possible with the fundamental without chirping. This combination of chirping and higher harmonics can lead to substantial savings in the design, construction and operational costs of the new Compton sources. This is of particular importance to the widely popular laser-plasma accelerator based Compton sources, as the improvement in their beam quality enters the regime where chirping is most effective.
ESG preferences, risk and return

There are two primary factors that affect expected returns for companies with high ESG (environmental, social and governance) ratings—investor preferences and risk. Although investor preferences for highly rated ESG companies can lower the cost of capital, the flip side of the coin is lower expected returns for investors. Regarding risk, the jury remains out on whether there is an ESG‐related risk factor. However, to the extent, ESG is a risk factor it also points towards lower expected returns for investments in highly rated companies. Though ESG investing may have social benefits, higher expected returns for investors are not among them.
Modeling solid-state dewetting of a single-crystal binary alloy thin films

Dewetting of a binary alloy thin film is studied using a continuum many-parameter model that accounts for the surface and bulk diffusion, the bulk phase separation, the surface segregation, and the particle formation. An analytical solution is found for the quasistatic equilibrium concentration of a surface-segregated atomic species. This solution is factored into the nonlinear and coupled evolution partial differential equations (PDEs) for the bulk composition and surface morphology. The stability of a planar film surface with respect to small perturbations of shape and composition is analyzed, revealing the dependence of the particle size on major physical parameters. The computations show various scenarios of the particle formation and the redistribution of the alloy components inside the particles and on their surface. In most situations, for the alloy film composed initially of 50% A and 50% B atoms, core-shell particles are formed, and they are located atop a wetting layer that is modestly rich in t...
Multimodal Sensing and Interaction for a Robotic Hand Orthosis

Wearable robotic hand rehabilitation devices can allow greater freedom and flexibility than their workstation-like counterparts. However, the field is generally lacking effective methods by which the user can operate the device: such controls must be effective, intuitive, and robust to the wide range of possible impairment patterns. Even when focusing on a specific condition, such as stroke, the variety of encountered upper limb impairment patterns means that a single sensing modality, such as electromyography (EMG), might not be sufficient to enable controls for a broad range of users. To address this significant gap, we introduce a multimodal sensing and interaction paradigm for an active hand orthosis. In our proof-of-concept implementation, EMG is complemented by other sensing modalities, such as finger bend and contact pressure sensors. We propose multimodal interaction methods that utilize this sensory data as input and show they can enable tasks for stroke survivors who exhibit different impairment patterns. We believe that robotic hand orthoses developed as multimodal sensory platforms with help address some of the key challenges in physical interaction with the user.
Near-infrared Structure of Fast and Slow-rotating Disk Galaxies

We investigate the stellar disk structure of six nearby edge-on spiral galaxies using high-resolution JHK {sub s}-band images and three-dimensional radiative transfer models. To explore how mass and environment shape spiral disks, we selected galaxies with rotational velocities between 69 km s{sup –1} 150 km s{sup –1}) galaxies, only NGC 4013 has the super-thin+thin+thick nested disk structure seen in NGC 891 and the Milky Way, albeit with decreased oblateness, while NGC 1055, a disturbed massive spiral galaxy, contains disks with h{sub z} ≲ 200 pc. NGC 4565, another fast-rotator, contains a prominent ring at a radius ∼5 kpc but no super-thin disk. Despite these differences, all fast-rotating galaxies in our sample have inner truncations in at least one of their disks. These truncations lead to Freeman Type II profiles when projected face-on. Slow-rotating galaxies are less complex, lacking inner disk truncations and requiring fewer disk components to reproduce their light distributions. Super-thin disk components in undisturbed disks contribute ∼25% of the total K {sub s}-band light, up to that of the thin-disk contribution. The presence of super-thin disks correlates with infrared flux ratios; galaxies with super-thin disks have f{sub K{sub s}}/f{sub 60} {sub μm}≤0.12 for integrated light, consistent with super-thinmore » disks being regions of ongoing star-formation. Attenuation-corrected vertical color gradients in (J – K {sub s}) correlate with the observed disk structure and are consistent with population gradients with young-to-intermediate ages closer to the mid-plane, indicating that disk heating—or cooling—is a ubiquitous phenomenon.« less
SOFIA FIFI-LS Observations of Sgr B1: Ionization Structure and Sources of Excitation

The current paradigm of Galactic Center (GC) gas motions and star formation envisions sequential star formation in streams of gas as they pass near the supermassive black hole, Sgr A*. This is based on the relative positions of dense molecular clouds, the very young star-forming region Sgr B2, the much older region Sgr C, and the several Myr old Arches and Quintuplet Clusters. Because Sgr B1 is found with Sgr B2 in a common envelope of molecular gas and far-infrared emission, the two sources are thought to be physically related, even though there are indicators of a significantly greater age for Sgr B1. To clarify the status of Sgr B1, we have mapped it with the FIFI-LS spectrometer on SOFIA in the far-infrared lines of [O III] 52 and 88 micron. From the ratios of these lines and lines measured with the Spitzer Infrared Spectrograph, we find that there are at least eight separate sub-regions that must contain the stars that excite the gas. We infer spectral energy distributions (SEDs) of the ionizing sources from models and find they are in agreement only with SEDs of late O stars augmented at the highest frequencies with interstellar X-rays from fast shocks. We suggest that although the gas, from its velocity structure, must be part of the very young Sgr B2 complex, the stars that are ionizing the gas were not formed there but are the remnants of a previous generation of star formation in the GC.
Complexity of Quantum Impurity Problems

We give a quasi-polynomial time classical algorithm for estimating the ground state energy and for computing low energy states of quantum impurity models. Such models describe a bath of free fermions coupled to a small interacting subsystem called an impurity. The full system consists of n fermionic modes and has a Hamiltonian $${H=H_0+H_{imp}}$$ , where H 0 is quadratic in creation–annihilation operators and H imp is an arbitrary Hamiltonian acting on a subset of O(1) modes. We show that the ground energy of H can be approximated with an additive error $${2^{-b}}$$ in time $${n^3 \exp{[O(b^3)]}}$$ . Our algorithm also finds a low energy state that achieves this approximation. The low energy state is represented as a superposition of $${\exp{[O(b^3)]}}$$ fermionic Gaussian states. To arrive at this result we prove several theorems concerning exact ground states of impurity models. In particular, we show that eigenvalues of the ground state covariance matrix decay exponentially with the exponent depending very mildly on the spectral gap of H 0. A key ingredient of our proof is Zolotarev’s rational approximation to the $${\sqrt{x}}$$ function. We anticipate that our algorithms may be used in hybrid quantum-classical simulations of strongly correlated materials based on dynamical mean field theory. We implemented a simplified practical version of our algorithm and benchmarked it using the single impurity Anderson model.
Neutrino Astronomy in the Ice

The South Pole is an optimal location for hosting astrophysical observatories. The status of the construction of the IceCube Observatory and some selected physics results will be discussed. Moreover prospects for detection of Ultra-High Energy cosmogenic neutrinos and techniques that can address this energy region will be considered.
High Throughput Quantitative Metallography for Complex Microstructures Using Deep Learning: A Case Study in Ultrahigh Carbon Steel.

We apply a deep convolutional neural network segmentation model to enable novel automated microstructure segmentation applications for complex microstructures typically evaluated manually and subjectively. We explore two microstructure segmentation tasks in an openly available ultrahigh carbon steel microstructure dataset: segmenting cementite particles in the spheroidized matrix, and segmenting larger fields of view featuring grain boundary carbide, spheroidized particle matrix, particle-free grain boundary denuded zone, and Widmanstatten cementite. We also demonstrate how to combine these data-driven microstructure segmentation models to obtain empirical cementite particle size and denuded zone width distributions from more complex micrographs containing multiple microconstituents. The full annotated dataset is available on materialsdata.nist.gov.
Enabling Pedestrian Safety Using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash

Human lives are important. The decision to allow self-driving vehicles operate on our roads carries great weight. This has been a hot topic of debate between policy-makers, technologists and public safety institutions. The recent Uber Inc. self-driving car crash, resulting in the death of a pedestrian, has strengthened the argument that autonomous vehicle technology is still not ready for deployment on public roads. In this work, we analyze the Uber car crash and shed light on the question, “Could the Uber Car Crash have been avoided?”. We apply state-of-the-art Computer Vision models to this highly practical scenario. More generally, our experimental results are an evaluation of various image enhancement and object recognition techniques for enabling pedestrian safety in low-lighting conditions using the Uber crash as a case study.
Single-Molecule Nanomagnets

Single-molecule magnets straddle the classical and quantum mechanical worlds, displaying many fascinating phenomena. They may have important technological applications in information storage and quantum computation. We review the physical properties of two prototypical molecular nanomagnets, Mn12-acetate and Fe8: Each behaves as a rigid, spin-10 object and exhibits tunneling between up and down directions. As temperature is lowered, the spin-reversal process evolves from thermal activation to pure quantum tunneling. At low temperatures, magnetic avalanches occur in which the magnetization of an entire sample rapidly reverses. We discuss the important role that symmetry-breaking fields play in driving tunneling and in producing Berry-phase interference. Recent experimental advances indicate that quantum coherence can be maintained on timescales sufficient to allow a meaningful number of quantum computing operations to be performed. Efforts are under way to create monolayers and to address and manipulate in...
Constraining Formation Models of Binary Black Holes with Gravitational-wave Observations

Gravitational waves (GWs) from binary black hole (BBH) mergers provide a new probe of massive-star evolution and the formation channels of binary compact objects. By coupling the growing sample of BBH systems with population synthesis models, we can begin to constrain the parameters of such models and glean unprecedented knowledge about the inherent physical processes that underpin binary stellar evolution. In this study, we apply a hierarchical Bayesian model to mass measurements from a synthetic GW sample to constrain the physical prescriptions in population models and the relative fraction of systems generated from various channels. We employ population models of two canonical formation scenarios in our analysis—isolated binary evolution involving a common-envelope phase and dynamical formation within globular clusters—with model variations for different black hole natal kick prescriptions. We show that solely with chirp mass measurements, it is possible to constrain natal kick prescriptions and the relative fraction of systems originating from each formation channel with of confident detections. This framework can be extended to include additional formation scenarios, model parameters, and measured properties of the compact binary.
General Requirements on Matter Power Spectrum Predictions for Cosmology with Weak Lensing Tomography

Forthcoming projects such as DES, LSST, WFIRST, and Euclid aim to measure weak lensing shear correlations with unprecedented precision, constraining the dark energy equation of state at the percent level. Reliance on photometrically-determined redshifts constitutes a major source of uncertainty for these surveys. Additionally, interpreting the weak lensing signal requires a detailed understanding of the nonlinear physics of gravitational collapse. We present a new analysis of the stringent calibration requirements for weak lensing analyses of future imaging surveys that addresses both photo-z uncertainty and errors in the calibration of the matter power spectrum. We find that when photo-z uncertainty is taken into account the requirements on the level of precision in the prediction for the matter power spectrum are more stringent than previously thought. Including degree-scale galaxy clustering statistics in a joint analysis with weak lensing not only strengthens the survey's constraining power by ~ 20%, but can also have a profound impact on the calibration demands, decreasing the degradation in dark energy constraints with matter power spectrum uncertainty by a factor of 2-5. Similarly, using galaxy clustering information significantly relaxes the demands on photo-z calibration. We compare these calibration requirements to the contemporary state-of-the-art in photometric redshift estimation and predictions of the power spectrum and suggest strategies to utilize forthcoming data optimally.
A drift‐kinetic method for obtaining gradients in plasma properties from single‐point distribution function data

In this paper, we derive a new drift-kinetic method for estimating gradients in the plasma properties through a velocity space distribution at a single point. The gradients are intrinsically related to agyrotropic features of the distribution function. This method predicts the gradients in the magnetized distribution function, and can predict gradients of arbitrary moments of the gyrotropic background distribution function. The method allows for estimates on density and pressure gradients on the scale of a Larmor radius, proving to resolve smaller scales than any method currently available to spacecraft. The model is verified with a set of fully-kinetic VPIC particle-in-cell simulations.
Occlusion-Aware Risk Assessment for Autonomous Driving in Urban Environments

Navigating safely in urban environments remains a challenging problem for autonomous vehicles. Occlusion and limited sensor range can pose significant challenges to safely navigate among pedestrians and other vehicles in the environment. Enabling vehicles to quantify the risk posed by unseen regions allows them to anticipate future possibilities, resulting in increased safety and ride comfort. This letter proposes an algorithm that takes advantage of the known road layouts to forecast, quantify, and aggregate risk associated with occlusions and limited sensor range. This allows us to make predictions of risk induced by unobserved vehicles even in heavily occluded urban environments. The risk can then be used either by a low-level planning algorithm to generate better trajectories, or by a high-level one to plan a better route. The proposed algorithm is evaluated on intersection layouts from real-world map data with up to five other vehicles in the scene, and verified to reduce collision rates by $4.8\times$ comparing to a baseline method while improving driving comfort.
A Spectral Sequence of the Floer Cohomology of Symplectomorphisms of Trivial Polarization Class

Let $M$ be an exact symplectic manifold equal to a symplectization near infinity and having stably trivializable tangent bundle, and $\phi$ be an exact symplectomorphism of $M$ which, near infinity, is equal to either the identity or the symplectization of a contactomorphism $\hat{\phi}$ such that neither $\hat{\phi}$ nor $\hat{\phi}^2$ has fixed points. We give conditions under which Seidel and Smith's localization theorem for Lagrangian Floer cohomology implies the existence of a spectral sequence from $\mathit{HF}(\phi^2)\otimes \mathbb Z_2((\theta))$ to $\mathit{HF}(\phi)\otimes \mathbb Z_2((\theta))$.
Weakly supervised classification in high energy physics

As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations. This paper presents a new approach called weakly supervised classification in which class proportions are the only input into the machine learning algorithm. Using one of the most challenging binary classification tasks in high energy physics — quark versus gluon tagging — we show that weakly supervised classification can match the performance of fully supervised algorithms. Furthermore, by design, the new algorithm is insensitive to any mis-modeling of discriminating features in the data by the simulation. Weakly supervised classification is a general procedure that can be applied to a wide variety of learning problems to boost performance and robustness when detailed simulations are not reliable or not available.
Empirical Non-Parametric Estimation of the Fisher Information

The Fisher information matrix (FIM) is a foundational concept in statistical signal processing. The FIM depends on the probability distribution, assumed to belong to a smooth parametric family. Traditional approaches to estimating the FIM require estimating the probability distribution function (PDF), or its parameters, along with its gradient or Hessian. However, in many practical situations the PDF of the data is not known but the statistician has access to an observation sample for any parameter value. Here we propose a method of estimating the FIM directly from sampled data that does not require knowledge of the underlying PDF. The method is based on non-parametric estimation of an $f$ -divergence over a local neighborhood of the parameter space and a relation between curvature of the $f$ -divergence and the FIM. Thus we obtain an empirical estimator of the FIM that does not require density estimation and is asymptotically consistent. We empirically evaluate the validity of our approach using two experiments.
Applications of machine learning in cryptography: a survey

Machine learning techniques have had a long list of applications in recent years. However, the use of machine learning in information and network security is not new. Machine learning and cryptography have many things in common. The most apparent is the processing of large amounts of data and large search spaces. In its varying techniques, machine learning has been an interesting field of study with massive potential for application. In the past three decades, machine learning techniques, whether supervised or unsupervised, have been applied in cryptographic algorithms, cryptanalysis, steganography, among other data-security-related applications. This paper presents an updated survey of applications of machine learning techniques in cryptography and cryptanalysis. The paper summarizes the research done in these areas and provides suggestions for future directions in research.
The Early Evolution of Massive Black Holes

Massive black holes (MBHs) are nowadays believed to reside in most local galaxies. Studies have also established a number of relations between the MBH mass and properties of the host galaxy such as bulge mass and velocity dispersion. These results suggest that central MBHs, while much less massive than their hosts (~ 0.1%), are linked to the evolution of galactic structure. When did it all start? In hierarchical cosmologies, a single big galaxy today can be traced back to the stage when it was split up in hundreds of smaller components. Did MBH seeds form with the same efficiency in small proto-galaxies, or did their formation have to await the buildup of substantial galaxies with deeper potential wells? I briefly review here some of the physical processes that are conducive to the evolution of the massive black hole population. I will discuss black hole formation processes for “seed” black holes that are likely to take place at early cosmic epochs, and possible observational tests of these scenarios.
Thermodynamic stabilization of precipitates through interface segregation: Chemical effects

Precipitation hardening, which relies on a high density of intermetallic precipitates, is a commonly utilized technique for strengthening structural alloys. At high temperatures, however, the precipitates often coarsen to reduce the excess energy of the interface, resulting in a significant reduction in the strengthening achieved. In certain ternary alloys, secondary solute segregation to the interface has been observed to result in the formation of a high density of nanosized precipitates that provide enhanced strength and are resistant to coarsening. To understand the chemical effects involved, and to identify such segregating systems, we develop a thermodynamic model using the framework of the regular nanocrystalline solution model. For various global compositions, temperatures, and thermodynamic parameters, we evaluate equilibrium configurations of a Mg-Sn-Zn alloy by minimizing the Gibbs free energy function with respect to region-specific (bulk solid solution, interface, and precipitate) concentrations and sizes. The results show that ${\mathrm{Mg}}_{2}\mathrm{Sn}$ precipitates can be stabilized to nanoscale sizes through Zn segregation to the $\mathrm{Mg}/{\mathrm{Mg}}_{2}\mathrm{Sn}$ interface, and the precipitates can be stabilized against coarsening at high temperatures through strong Mg-Zn interface interaction. Together with the inclusion of elastic strain energy effects, kinetic contributions, and the input of computationally informed interface parameters in the future, the model is expected to provide a more realistic prediction of segregation and precipitate stabilization in ternary alloys of structural importance.
Constrained dynamics: generalized Lie symmetries, singular Lagrangians, and the passage to Hamiltonian mechanics

Guided by the symmetries of the Euler-Lagrange equations of motion, a study of the constrained dynamics of singular Lagrangians is presented. We find that these equations of motion admit a generalized Lie symmetry, and on the Lagrangian phase space the generators of this symmetry lie in the kernel of the Lagrangian two-form. Solutions of the energy equation—called second-order, Euler-Lagrange vector fields (SOELVFs)—with integral flows that have this symmetry are determined. Importantly, while second-order, Lagrangian vector fields are not such a solution, it is always possible to construct from them a SOELVF that is. All SOELVFs are projectable to the Hamiltonian phase space, as are all the dynamical structures in the Lagrangian phase space needed for their evolution. In particular, the primary Hamiltonian constraints can be constructed from vectors in the kernel of the Lagrangian two-form, and with this construction, we show that the Lagrangian constraint algorithm for the SOELVF is equivalent to the stability analysis of the total Hamiltonian. Importantly, the end result of the stability analysis gives a Hamiltonian vector field that is the projection of the SOELVF obtained from the Lagrangian constraint algorithm.
A personal account of the discovery of hyperbolic structures on some knot complements

Abstract I give my view of the early history of the discovery of hyperbolic structures on knot complements from my early work on representations of knot groups into matrix groups to my meeting with William Thurston in 1976.
Prediction of many-electron wavefunctions using atomic potentials: Refinements and extensions to transition metals and large systems.

For a given many-electron molecule, it is possible to define a corresponding one-electron Schrodinger equation, using potentials derived from simple atomic densities, whose solution predicts fairly accurate molecular orbitals for single-determinant and multideterminant wavefunctions for the molecule. The energy is not predicted and must be evaluated by calculating Coulomb and exchange interactions over the predicted orbitals. Transferable potentials for first-row atoms and transition metal oxides that can be used without modification in different molecules are reported. For improved accuracy, molecular wavefunctions can be refined by slightly scaling nuclear charges and by introducing potentials optimized for functional groups. The accuracy is further improved by a single diagonalization of the Fock matrix constructed from the predicted orbitals. For a test set of 20 molecules representing different bonding environments, the transferable potentials with scaling give wavefunctions with energies that deviate from exact self-consistent field or configuration interaction energies by less than 0.05 eV and 0.02 eV per bond or valence electron pair, respectively. On diagonalization of the Fock matrix, the corresponding errors are reduced by a factor of three to less than 0.016 eV and 0.006 eV, respectively. Applications to the ground and excited states of a Ti18O36 nanoparticle and chlorophyll-a are reported.
Basis function method for numerical loop quantum cosmology: the Schwarzschild black hole interior

Loop quantum cosmology is a symmetry-reduced application of loop quantum gravity that has led to the resolution of classical singularities such as the big bang, and those at the center of black holes. This can be seen through numerical simulations involving the quantum Hamiltonian constraint that is a partial difference equation. The equation allows one to study the evolution of sharply-peaked Gaussian wave packets that generically exhibit a quantum "bounce" or a non-singular passage through the classical singularity, thus offering complete singularity resolution. In addition, von-Neumann stability analysis of the difference equation -- treated as a stencil for a numerical solution that steps through the triad variables -- yields useful constraints on the model and the allowed space of states. In this paper, we develop a new method for the numerical solution of loop quantum cosmology models using a set of basis functions that offer a number of advantages over computing a solution by stepping through the triad variables. We use the Corichi and Singh model for the Schwarzschild interior as the main case study in this effort. The main advantage of this new method is computational efficiency and the ease of parallelization. In addition, we also discuss how the stability analysis appears in the context of this new approach.
PHYSICAL PARAMETERS OF ASTEROIDS ESTIMATED FROM THE WISE 3-BAND DATA AND NEOWISE POST-CRYOGENIC SURVEY

Enhancements to the science data processing pipeline of NASA's Wide-field Infrared Survey Explorer (WISE) mission, collectively known as NEOWISE, resulted in the detection of >158,000 minor planets in four infrared wavelengths during the fully cryogenic portion of the mission. Following the depletion of its cryogen, NASA's Planetary Science Directorate funded a four-month extension to complete the survey of the inner edge of the Main Asteroid Belt and to detect and discover near-Earth objects (NEOs). This extended survey phase, known as the NEOWISE Post-Cryogenic Survey, resulted in the detection of ~6500 large Main Belt asteroids and 86 NEOs in its 3.4 and 4.6 μm channels. During the Post-Cryogenic Survey, NEOWISE discovered and detected a number of asteroids co-orbital with the Earth and Mars, including the first known Earth Trojan. We present preliminary thermal fits for these and other NEOs detected during the 3-Band Cryogenic and Post-Cryogenic Surveys.
ASYMMETRIES IN SN 2014J NEAR MAXIMUM LIGHT REVEALED THROUGH SPECTROPOLARIMETRY

National Aeronautics and Space Administration; VizieR catalog access tool, CDS, Strasbourg, France; NSF [AST-1009571, AST-1210311, AST-1210599, AST-1210372]
Enhanced Twitter Sentiment Classification Using Contextual Information

The rise in popularity and ubiquity of Twitter has made sentiment analysis of tweets an important and well-covered area of research. However, the 140 character limit imposed on tweets makes it hard to use standard linguistic methods for sentiment classification. On the other hand, what tweets lack in structure they make up with sheer volume and rich metadata. This metadata includes geolocation, temporal and author information. We hypothesize that sentiment is dependent on all these contextual factors. Different locations, times and authors have different emotional valences. In this paper, we explored this hypothesis by utilizing distant supervision to collect millions of labelled tweets from different locations, times and authors. We used this data to analyse the variation of tweet sentiments across different authors, times and locations. Once we explored and understood the relationship between these variables and sentiment, we used a Bayesian approach to combine these variables with more standard linguistic features such as n-grams to create a Twitter sentiment classifier. This combined classifier outperforms the purely linguistic classifier, showing that integrating the rich contextual information available on Twitter into sentiment classification is a promising direction of research.
Cascades and Dissipative Anomalies in Nearly Collisionless Plasma Turbulence

A new exact theory for plasma turbulence could lead to new insights into plasma environments and simplifications of the complex equations used to describe them.
QUANTUM GRAVITY AND DARK MATTER

We propose a connection between global physics and local galactic dynamics via quantum gravity. The salient features of cold dark matter (CDM) and modified Newtonian dynamics (MOND) are combined into a unified scheme by introducing the concept of MONDian dark matter which behaves like CDM at cluster and cosmological scales but emulates MOND at the galactic scale.
Proton light yield in organic scintillators using a double time-of-flight technique

Recent progress in the development of novel organic scintillators necessitates modern characterization capabilities. As the primary means of energy deposition by neutrons in these materials is n-p elastic scattering, knowledge of the proton light yield is paramount. This work establishes a new model-independent method to continuously measure the proton light yield in organic scintillators over a broad energy range. Using a deuteron breakup neutron source at the 88-in. Cyclotron at Lawrence Berkeley National Laboratory and an array of organic scintillators, the proton light yield of EJ-301 and EJ-309, commercially available organic liquid scintillators from Eljen Technology, was measured via a double time-of-flight technique. The light yield was determined using a kinematically over-constrained system in the proton energy range of 1–20 MeV. The effect of the pulse integration length on the magnitude and shape of the proton light yield relation was also explored. This work enables accurate simulation of the performance of advanced neutron detectors and supports the development of next-generation neutron imaging systems.
Connecting the Sun's High-resolution Magnetic Carpet to the Turbulent Heliosphere

The solar wind is connected to the Sun's atmosphere by flux tubes that are rooted in an ever-changing pattern of positive and negative magnetic polarities on the surface. Observations indicate that the magnetic field is filamentary and intermittent across a wide range of spatial scales. However, we do not know to what extent the complex flux-tube topology seen near the Sun survives as the wind expands into interplanetary space. In order to study the possible long-distance connections between the corona and the heliosphere, we developed new models of turbulence-driven solar wind acceleration along empirically constrained field lines. We used a potential field model of the quiet Sun to trace field lines into the ecliptic plane with unprecedented spatial resolution at their footpoints. For each flux tube, a one-dimensional model was created with an existing wave/turbulence code that solves equations of mass, momentum, and energy conservation from the photosphere to 4 AU. To take account of stream-stream interactions between flux tubes, we used those models as inner boundary conditions for a time-steady magnetohydrodynamic description of radial and longitudinal structure in the ecliptic. Corotating stream interactions smear out much of the smallest-scale variability, making it difficult to see how individual flux tubesmore » on granular or supergranular scales can survive out to 1 AU. However, our models help clarify the level of ''background'' variability with which waves and turbulent eddies should be expected to interact. Also, the modeled fluctuations in magnetic field magnitude were seen to match measured power spectra quite well.« less