cssi/SciSciGPT-SciSciNet huggingface dataset:
Investor confidence: Are you your own worst enemy?

Are overconfident investors more apt to make risky choices, which could erode investor returns? With confidence levels that exceed knowledge levels, investors may unknowingly expose themselves to risk. This paper shows that in terms of investing, overconfidence is associated with increased optimism as well as additional risk‐taking through focused investment strategies. Specifically, overconfident individuals are more likely to be overoptimistic about their individual performance as well as overall market performance; more likely to have confidence in market regulations; less likely to seek the advice of an adviser; more likely to trade on margin; more likely to trade commodities, futures, and options; and more likely to have whole life insurance. Overconfidence may help explain why investor returns are consistently lower than investment returns. These findings are particularly relevant for financial advisers, as they serve the important role of providing feedback and sharing in the decision process. Full Text Available Here: https://doi.org/10.1002/cfp2.1092
Memory Organization for Energy-Efficient Learning and Inference in Digital Neuromorphic Accelerators

The energy efficiency of neuromorphic hardware is greatly affected by the energy of storing, accessing, and updating synaptic parameters. Various methods of memory organisation targeting energy-efficient digital accelerators have been investigated in the past, however, they do not completely encapsulate the energy costs at a system level. To address this shortcoming and to account for various overheads, we synthesize the controller and memory for different encoding schemes and extract the energy costs from these synthesized blocks. Additionally, we introduce functional encoding for structured connectivity such as the connectivity in convolutional layers. Functional encoding offers a 58% reduction in the energy to implement a backward pass and weight update in such layers compared to existing index-based solutions. We show that for a 2 layer spiking neural network trained to retain a spatio-temporal pattern, bitmap (PB-BMP) based organization can encode the sparser networks more efficiently. This form of encoding delivers a 1.37× improvement in energy efficiency coming at the cost of a 4% degradation in network retention accuracy as measured by the van Rossum distance.
Mape_Maker: A Scenario Creator

We describe algorithms for creating probabilistic scenarios for renewables power production. Our approach allows for tailoring of forecast uncertainty, such that scenarios can be constructed to capture the situation where the underlying forecast methodology is more (or less) accurate than it has been historically. Such scenarios can be used in studies that extend into the future and may need to consider the possibility that forecast technology will improve. Our approach can also be used to generate alternative realizations of renewable energy production that are consistent with historical forecast accuracy, in effect serving as a method for creating families of realistic alternatives—which are often critical in simulation-based analysis methodologies. We illustrate the methods using real data for day-ahead wind forecasts.
Giving syphilis and gonorrhea to friends: using in-person friendship networks to find additional cases of gonorrhea and syphilis.

Syphilis and gonorrhea reached an all-time high in 2018. The resurgence of syphilis and gonorrhea requires innovative methods of sexual contact tracing that encourage disclosure of same-sex sexual contacts that might otherwise be suppressed. Over 75% of Grindr mobile phone application users report seeking “friendship,” so this study asked people diagnosed with syphilis and gonorrhea to identify their friends. Patients at the two Baltimore sexually transmitted infection (STI) clinics and the Baltimore City Health Department were asked 12 questions to elicit members of their friendship networks before eliciting sexual networks. The study included 353 index cases and 172 friendship contacts, yielding a friendship network of 331 non-isolates (n = 331) and sexual-only network of 140 non-isolates. The data were plotted and analyzed using exponential family random graph analysis. Eliciting respondents’ in-person social contacts yielded 12 syphilis cases and 6 gonorrhea cases in addition to the 16 syphilis cases and 4 gonorrhea cases that would have been found with sexual contacts alone. Syphilis is clustered within sexual (odds ratio = 2.2, 95% confidence interval (1.36, 3.66)) and social contacts (OR = 1.31, 95% CI (1.02, 1.68)). Gonorrhea is clustered within reported social (OR = 1.56, 95% CI (1.22, 2.00)) but not sexual contacts (OR = 0.98, 95% CI (0.62, 1.53)). Eliciting friendship networks of people diagnosed with syphilis and gonorrhea may find members of their sexual networks, drug use networks, or people of similar STI risk. Friendship networks include more diagnosed cases of syphilis and gonorrhea than sexual networks alone, especially among populations with many non-disclosing men who have sex with men (MSM) and women who have sex with women (WSW). Future research should evaluate whether this friendship network method of contact tracing can be implemented by adapting automated mobile phone COVID-19 contact tracing protocols, if these COVID-19 contact tracing methods are able to maintain anonymity and public trust.
Surface Brightness Profiles of Dwarf Galaxies: II. Color Trends and Mass Profiles

In this second paper of a series, we explore the B-V, U-B, and FUV-NUV radial color trends from a multi-wavelength sample of 141 dwarf disk galaxies. Like spirals, dwarf galaxies have three types of radial surface brightness profiles: (I) single exponential throughout the observed extent (the minority), (II) down-bending (the majority), and (III) up-bending. We find that colors of (1) Type I dwarfs generally become redder with increasing radius unlike spirals that have a blueing trend that flattens beyond ~1.5 disk scale lengths, (2) Type II dwarfs come in six different "flavors," one of which mimics the "U" shape of spirals, and (3) Type III dwarfs have a stretched "S" shape where central colors are flattish, become steeply redder to the surface brightness break, then remain roughly constant beyond, similar to spiral TypeIII color profiles, but without the central outward bluing. Faint (-9 > M_B > -14) Type II dwarfs tend to have continuously red or "U" shaped colors and steeper color slopes than bright (-14 > M_B > -19) Type II dwarfs, which additionally have colors that become bluer or remain constant with increasing radius. Sm dwarfs and BCDs tend to have at least some blue and red radial color trend, respectively. Additionally, we determine stellar surface mass density (Sigma) profiles and use them to show that the break in Sigma generally remains in Type II dwarfs (unlike Type II spirals) but generally disappears in Type III dwarfs (unlike Type III spirals). Moreover, the break in Sigma is strong, intermediate, and weak in faint dwarfs, bright dwarfs, and spirals, respectively, indicating that Sigma may straighten with increasing galaxy mass. Lastly, the average stellar surface mass density at the surface brightness break is roughly 1-2 M_S/pc^2 for Type II dwarfs but higher at 5.9 M_S/pc^2 or 27 M_S/pc^2 for Type III BCDs and dIms, respectively.
On Hydrodynamic Equations at the Limit of Infinitely Many Molecules

We show that the weak convergence of point measures and (2 + ∈)-moment conditions imply hydrodynamic equations at the limit of infinitely many interacting molecules. The conditions are satisfied whenever the solutions of the classical equations for N interacting molecules obey uniform in N bounds. As an example, we show that this holds when the initial conditions are bounded and the molecule interaction, a certain N-rescaling of potentials that include all r −p for 1 < p, is weak enough at the initial time. In this case, the hydrodynamic equations coincide with the macroscopic Maxwell equations. Bibliography: 23 titles.
Broadband Optical Detection Using the Spin Seebeck Effect

Utilizing spin in condensed matter is an important means to create or enhance technologically important phenomena. However, this route has rarely been used to produce relevant functional advantages for the generation, detection, or manipulation of light. This work shows that the spin Seebeck effect (SSE), in which a pure spin current is generated from magnetization and a thermal gradient, can detect light in Pt/Y${}_{3}$Fe${}_{5}$O${}_{12}$ devices at wavelengths from ultraviolet to near-infrared. The extremely flat, broadband responsivity of these SSE devices paves the way for a generation of spin-based optical detectors.
Markov Chain Lifting and Distributed ADMM

The time to converge to the steady state of a finite Markov chain can be greatly reduced by a lifting operation, which creates a new Markov chain on an expanded state space. For a class of quadratic objectives, we show an analogous behavior where a distributed alternating direction method of multipliers (ADMM) algorithm can be seen as a lifting of gradient descent. This provides a deep insight for its faster convergence rate under optimal parameter tuning. We conjecture that this gain is always present, as opposed to the lifting of a Markov chain, which sometimes only provides a marginal speedup.
Existence of valuations with smallest normalized volume

Li introduced the normalized volume of a valuation due to its relation to K-semistability. He conjectured that over a Kawamata log terminal (klt) singularity there exists a valuation with smallest normalized volume. We prove this conjecture and give an explicit example to show that such a valuation need not be divisorial.
Mass Accretion and its Effects on the Self-Similarity of Gas Profiles in the Outskirts of Galaxy Clusters

Galaxy clusters exhibit remarkable self-similar behavior which allows us to establish simple scaling relationships between observable quantities and cluster masses, making galaxy clusters useful cosmological probes. Recent X-ray observations suggested that self-similarity may be broken in the outskirts of galaxy clusters. In this work, we analyze a mass-limited sample of massive galaxy clusters from the Omega500 cosmological hydrodynamic simulation to investigate the self-similarity of the diffuse X-ray emitting intracluster medium (ICM) in the outskirts of galaxy clusters. We find that the self-similarity of the outer ICM profiles is better preserved if they are normalized with respect to the mean density of the universe, while the inner profiles are more self-similar when normalized using the critical density. However, the outer ICM profiles as well as the location of accretion shock around clusters are sensitive to their mass accretion rate, which causes the apparent breaking of self-similarity in cluster outskirts. We also find that the collisional gas does not follow the distribution of collisionless dark matter (DM) perfectly in the infall regions of galaxy clusters, leading to 10% departures in the gas-to-DM density ratio from the cosmic mean value. Our results have a number implications for interpreting observations of galaxy clusters in X-ray and through the Sunyaev?Zel?dovich effect, and their applications to cosmology.
Diffusive shock re-acceleration

We have performed two-dimensional hybrid simulations of non-relativistic collisionless shocks in the presence of pre-existing energetic particles (‘seeds’); such a study applies, for instance, to the re-acceleration of galactic cosmic rays (CRs) in supernova remnant (SNR) shocks and solar wind energetic particles in heliospheric shocks. Energetic particles can be effectively reflected and accelerated regardless of shock inclination via a process that we call diffusive shock re-acceleration. We find that re-accelerated seeds can drive the streaming instability in the shock upstream and produce effective magnetic field amplification. This can eventually trigger the injection of thermal protons even at oblique shocks that ordinarily cannot inject thermal particles. We characterize the current in reflected seeds, finding that it tends to a universal value , where is the seed charge density and is the shock velocity. When applying our results to SNRs, we find that the re-acceleration of galactic CRs can excite the Bell instability to nonlinear levels in less than , thereby providing a minimum level of magnetic field amplification for any SNR shock. Finally, we discuss the relevance of diffusive shock re-acceleration also for other environments, such as heliospheric shocks, galactic superbubbles and clusters of galaxies.
Advances in macromolecular data storage

We propose to develop a new method of information storage to replace magnetic hard disk drives and other instruments of secondary/backup data storage. The proposed method stores petabytes of user-data in a sugar cube (1 cm3), and can read/write that information at hundreds of megabits/sec. Digital information is recorded and stored in the form of a long macromolecule consisting of at least two bases, &#119860; and &#119861;. (This would be similar to DNA strands constructed from the four nucleic acids &#119866;, &#119862;, &#119860;, &#119879;.) The macromolecules initially enter the system as blank slates. A macromolecule with, say, 10,000 identical bases in the form of &#119860;&#119860;&#119860;&#119860;&#119860;. . . . &#119860;&#119860;&#119860; may be used to record a kilobyte block of user-data (including modulation and error-correction coding), although, in this blank state, it can only represent the null sequence 00000....000. Suppose this blank string of &#119860;’s is dragged before an atomically-sharp needle of a scanning tunneling microscope (STM). When electric pulses are applied to the needle in accordance with the sequence of 0s and 1s of a 1 &#119896;&#119861; block of user-data, selected &#119860; molecules will be transformed into &#119861; molecules (e.g., a fraction of &#119860; will be broken off and discarded). The resulting string now encodes the user-data in the form of &#119860;&#119860;&#119861;&#119860;&#119861;&#119861;&#119860;. . . &#119861;&#119860;&#119861;. The same STM needle can subsequently read the recorded information, as &#119860; and &#119861; would produce different electric signals when the strand passes under the needle. The macromolecule now represents a data block to be stored in a “parking lot” within the sugar cube, and later brought to a read station on demand. Millions of parking spots and thousands of Read/Write stations may be integrated within the micro-fabricated sugar cube, thus providing access to petabytes of user-data in a scheme that benefits from the massive parallelism of thousands of Read/Write stations within the same three-dimensionally micro-structured device.
Wide-Field Imaging of the Hubble Deep Field-South Region. II. The Evolution of Galaxy Clustering at z < 1

We present the galaxy-galaxy angular correlations as a function of photometric redshift in a deep, wide galaxy survey centered on the Hubble Deep Field-South (HDF-S). Images were obtained with the Big Throughput Camera on the Blanco 4 m telescope at CTIO, of square degree in broadband uBVRI, reaching ~24 mag. Approximately 40,000 galaxies are detected in the survey. We determine photometric redshifts using galaxy template fitting to the photometry. Monte Carlo simulations show that redshifts from these data should be reliable out to z ~ 1, where the 4000 A break shifts into the I band. The inferred redshift distribution, n(z), shows good agreement with the distribution of galaxies measured in the Hubble Deep Field-North (HDF-N) and the Canada-France Redshift Survey. After assigning galaxies to redshift bins with width Δz = 0.33, we determine the two-point angular correlation function in each bin. We find that the amplitude of the correlation, Aw, drops across the three bins to redshift z ~ 1. Simple models of clustering evolution fit this result, with the best agreement for = 0. Hierarchical cold dark matter models best fit in a low-density, Λ-dominated universe.
Topological Approximate Dynamic Programming under Temporal Logic Constraints

In this paper, we develop a model-free approximate dynamic programming method for stochastic systems modeled as Markov decision processes to maximize the probability of satisfying high-level system specifications expressed in a subclass of temporal logic formulas—syntactically co-safe linear temporal logic. Our proposed method includes two steps: First, we decompose the planning problem into a sequence of sub-problems based on the topological property of the task automaton which is translated from a temporal logic formula. Second, we extend a model-free approximate dynamic programming method to solve value functions, one for each state in the task automaton, in an order reverse to the causal dependency. Particularly, we show that the run-time of the proposed algorithm does not grow exponentially with the size of specifications. The correctness and efficiency of the algorithm are demonstrated using a robotic motion planning example.
Pressure determinations for incompressible fluids and magnetofluids

Certain unresolved ambiguities surround pressure determinations for incompressible flows: both Navier-Stokes and magnetohydrodynamic (MHD) For uniform-density fluids with standard Newtonian viscous terms, taking the divergence of the equation of motion leaves a Poisson equation for the pressure to be solved. But Poisson equations require boundary conditions. For the case of rectangular periodic boundary conditions, pressures determined in this way are unambiguous. But in the presence of no-slip' rigid walls, the equation of motion can be used to infer both Dirichlet and Neumann boundary conditions on the pressure P. and thus amounts to an over-determination. This has occasionally been recognized as a problem, and numerical treatments of wall-bounded shear flows usually have built in some relatively ad hoc dynamical recipe for dealing with it - often one that appears to work' satisfactorily. Here we consider a class of solenoidal velocity fields that vanish at no-slip walls, have all spatial derivatives, but are simple enough that explicit analytical solutions for P can be given. Satisfying the two boundary conditions separately gives two pressures, a Neumann pressure' and a Dirichlet pressure', which differ non-trivially at the initial instant, even before any dynamics are implemented. We compare the two pressures, and find that, in particular, they lead to different volume forces near the walls. This suggests a reconsideration of no-slip boundary eonditions, in which the vanishing of the tangential velocity at a noslip wall is replaced by a local wall-friction term in the equation of motion.
Dating COVID-Induced Recession in the U.S

The COVID-induced recession began in March 2020 for the United States. We identify this turning point by applying a Bayesian sequential quickest detection method to a real-time index of economic ac...
Entanglement in Theory Space

We propose a new concept of entanglement for quantum systems: entanglement in theory space. This is defined by decomposing a theory into two by an un-gauging procedure. We provide two examples where this newly introduced entanglement is closely related to conventional geometric entropies: deconstruction and AGT-type correspondence.
Cosmic Reionization On Computers. Properties of the Post-reionization IGM

United States Department of Energy [DE-AC02-07CH11359]; NSF [AST-1211190]; Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence "Origin and Structure of the Universe"; DOE Office of Science User Facility [DE-AC02-06CH11357]
IB2d Reloaded: A more powerful Python and MATLAB implementation of the immersed boundary method

The immersed boundary method (IB) is an elegant way to fully couple the motion of a fluid and deformations of an immersed elastic structure. In that vein, the IB2d software allows for expedited explorations of fluid-structure interaction for beginners and veterans to the field of computational fluid dynamics (CFD). While most open source CFD codes are written in low level programming environments, IB2d was specifically written in high- level programming environments to make its accessibility extend beyond scientists with vast programming experience. Although introduced previously by Battista et al. 2015, many improvements and additions have been made to the software to allow for even more robust models of material properties for the elastic structures, including a data analysis package for both the fluid and immersed structure data, an improved time-stepping scheme for higher accuracy solutions, and functionality for modeling slight fluid density variations as given by the Boussinesq approximation.
Transient current in a quantum dot asymmetrically coupled to metallic leads

The time-dependent non-crossing approximation is used to study the transient current in a single-electron transistor attached asymmetrically to two leads following a sudden change in the energy of the dot level. We show that for asymmetric coupling, sharp features in the density of states of the leads can induce oscillations in the current through the dot. These oscillations persist to much longer timescales than the timescale for charge fluctuations. The amplitude of the oscillations increases as the temperature or source–drain bias across the dot is reduced and saturates for values below the Kondo temperature. We discuss the microscopic origin of these oscillations and comment on the possibility for their experimental detection.
The Square Kilometre Array: a new probe of cosmic magnetism

Magnetic fields are a fundamental part of many astrophysical phenomena, but the evolution, structure and origin of magnetic fields are still unresolved problems in physics and astrophysics. When and how were the first fields generated? Are present-day magnetic fields the result of standard dynamo action, or do they represent rapid or recent field amplification through other processes? What role do magnetic fields play in turbulence, cosmic ray acceleration and structure formation? I explain how the Square Kilometre Array (SKA), a next-generation radio telescope, can deliver stunning new data-sets that will address these currently unanswered issues. The foundation for these experiments will be an all-sky survey of rotation measures, in which Faraday rotation toward > 107 background sources will provide a dense grid for probing magnetism in the Milky Way, nearby galaxies, and in distant galaxies, clusters and protogalaxies. Using these data, we can map out the evolution of magnetized structures from redshifts z > 3 to the present, can distinguish between different origins for seed magnetic fields in galaxies, and can develop a detailed model of the magnetic field geometry of the intergalactic medium and of the overall Universe. In addition, the SKA will certainly discover new magnetic phenomena beyond what we can currently predict or imagine. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Principal Component Analysis with Noisy and/or Missing Data

We present a method for performing principal component analysis (PCA) on noisy datasets with missing values. Estimates of the measurement error are used to weight the input data such that the resulting eigenvectors, when compared to classic PCA, are more sensitive to the true underlying signal variations rather than being pulled by heteroskedastic measurement noise. Missing data are simply limiting cases of weight = 0. The underlying algorithm is a noise weighted expectation maximization (EM) PCA, which has additional benefits of implementation speed and flexibility for smoothing eigenvectors to reduce the noise contribution. We present applications of this method on simulated data and QSO spectra from the Sloan Digital Sky Survey (SDSS).
Understanding Dwarf Galaxies in Order to Understand Dark Matter

Much progress has been made in recent years by the galaxy simulation community in making realistic galaxies, mostly by more accurately capturing the effects of baryons on the structural evolution of dark matter halos at high resolutions. This progress has altered theoretical expectations for galaxy evolution within a Cold Dark Matter (CDM) model, reconciling many earlier discrepancies between theory and observations. Despite this reconciliation, CDM may not be an accurate model for our Universe. Much more work must be done to understand the predictions for galaxy formation within alternative dark matter models.
Large U(1) charges in F-theory

We show that massless fields with large abelian charges (up to at least q = 21) can be constructed in 6D F-theory models with a U(1) gauge group. To show this, we explicitly construct F-theory Weierstrass models with nonabelian gauge groups that can be broken to U(1) theories with a variety of large charges. Determining the maximum abelian charge allowed in such a theory is key to eliminating what seems currently to be an infinite swampland of apparently consistent U(1) supergravity theories with large charges.
Empirical-likelihood-based confidence interval for the mean with a heavy-tailed distribution

Empirical-likelihood-based confidence intervals for a mean were introduced by Owen [Biometrika 75 (1988) 237–249], where at least a finite second moment is required. This excludes some important distributions, for example, those in the domain of attraction of a stable law with index between 1 and 2. In this article we use a method similar to Qin and Wong [Scand. J. Statist. 23 (1996) 209–219] to derive an empirical-likelihood-based confidence interval for the mean when the underlying distribution has heavy tails. Our method can easily be extended to obtain a confidence interval for any order of moment of a heavy-tailed distribution.
Do Explicit Alignments Robustly Improve Multilingual Encoders

Multilingual BERT (mBERT), XLM-RoBERTa (XLMR) and other unsupervised multilingual encoders can effectively learn cross-lingual representation. Explicit alignment objectives based on bitexts like Europarl or MultiUN have been shown to further improve these representations. However, word-level alignments are often suboptimal and such bitexts are unavailable for many languages. In this paper, we propose a new contrastive alignment objective that can better utilize such signal, and examine whether these previous alignment methods can be adapted to noisier sources of aligned data: a randomly sampled 1 million pair subset of the OPUS collection. Additionally, rather than report results on a single dataset with a single model run, we report the mean and standard derivation of multiple runs with different seeds, on four datasets and tasks. Our more extensive analysis finds that, while our new objective outperforms previous work, overall these methods do not improve performance with a more robust evaluation framework. Furthermore, the gains from using a better underlying model eclipse any benefits from alignment training. These negative results dictate more care in evaluating these methods and suggest limitations in applying explicit alignment objectives.
Threshold phenomena for symmetric decreasing solutions of reaction-diffusion equations

We study the long time behavior of solutions of the Cauchy problem for nonlinear reaction-diffusion equations in one space dimension with the nonlinearity of bistable, ignition or monostable type. We prove a one-to-one relation between the long time behavior of the solution and the limit value of its energy for symmetric decreasing initial data in L2 under minimal assumptions on the nonlinearities. The obtained relation allows to establish sharp threshold results between propagation and extinction for monotone families of initial data in the considered general setting.
A Bound from Below on the Temperature for the Navier--Stokes--Fourier System

We give a uniform bound from below on the temperature for a variant of the compressible Navier-Stokes--Fourier system, under suitable hypotheses. This system of equations forms a mathematical model of the motion of a compressible fluid subject to heat conduction. Building upon the work of [A. Mellet and A. Vasseur, Monatsh. Math., 157 (2009), pp. 143--161], we identify a class of weak solutions satisfying a localized form of the entropy inequality (adapted to measure the set where the temperature becomes small) and use a form of the De Giorgi argument for $L^\infty$ bounds of solutions to elliptic equations with bounded measurable coefficients.
The fixed-point theory of strictly contracting functions on generalized ultrametric semilattices

We introduce a new class of abstract structures, which we call generalized ultrametric semilattices, and in which the meet operation of the semilattice coexists with a generalized distance function in a tightly coordinated way. We prove a constructive fixed-point theorem for strictly contracting functions on directed-complete generalized ultrametric semilattices, and introduce a corresponding induction principle. We cite examples of application in the semantics of logic programming and timed computation, where, until now, the only tool available has been the non-constructive fixed-point theorem of Priess-Crampe and Ribenboim for strictly contracting functions on spherically complete generalized ultrametric semilattices.
HIGH-LUNDQUIST NUMBER SCALING IN THREE-DIMENSIONAL SIMULATIONS OF PARKER'S MODEL OF CORONAL HEATING

Parker's model is one of the most discussed mechanisms for coronal heating and has generated much debate. We have recently obtained new scaling results in a two-dimensional (2D) version of this problem suggesting that the heating rate becomes independent of resistivity in a statistical steady state. Our numerical work has now been extended to 3D by means of large-scale numerical simulations. Random photospheric footpoint motion is applied for a time much longer than the correlation time of the motion to obtain converged average coronal heating rates. Simulations are done for different values of the Lundquist number to determine scaling. In the high-Lundquist number limit, the coronal heating rate obtained so far is consistent with a trend that is independent of the Lundquist number, as predicted by previous analysis as well as 2D simulations. In the same limit the average magnetic energy built up by the random footpoint motion tends to have a much weaker dependence on the Lundquist number than that in the 2D simulations, due to the formation of strong current layers and subsequent disruption when the equilibrium becomes unstable. We will present scaling analysis showing that when the dissipation time is comparable or larger than the correlation time of the random footpoint motion, the heating rate tends to become independent of Lundquist number, and that the magnetic energy production is also reduced significantly.
Normal modes for N identical particles: A study of the evolution of collective behavior from few-body to many-body

Abstract Normal mode dynamics are ubiquitous in nature underlying the motions of diverse interacting systems from the behavior of rotating stars to the vibration of crystal structures. These behaviors are composed of simple collective motions of the N interacting particles which move with the same frequency and phase, thus encapsulating many-body effects into simple dynamic motions. In this study, I investigate the evolution of collective motion as a function of N for five types of normal modes previously obtained from an L = 0 group theoretic solution of a general Hamiltonian for confined, identical particles. I show using simple analytic forms for the N -body normal modes that the collective behavior of few-body systems, which have the well known motions of molecular equivalents such as ammonia and methane, evolves smoothly as N increases to the collective motions expected for large N ensembles (breathing, center of mass, particle–hole radial and angular excitations and phonon). Furthermore, the transition from few-body behavior (symmetric stretch, symmetric bend, asymmetric stretch, asymmetric bend and the opening and closing of alternative interparticle angles) to large N behavior occurs at quite low values of N . I extend this investigation to a Hamiltonian known to support collective behavior, the Hamiltonian for Fermi gases in the unitary regime. This analysis reveals two phenomena that could contribute to the viability of collective behavior. With the recent success using normal modes to describe the emergence of collective behavior in the form of superfluidity in ultracold Fermi gases in the unitary regime, understanding the character of these normal modes and the evolution of their behavior as a function of N has become of some interest due to the possibility of offering insight into the dynamics of regimes supporting collective behavior. In this study, I investigate both the macroscopic behavior associated with these N -body normal modes, as well as the microscopic motions underlying this behavior, and study the evolution of their collective behavior as a function of N .
VARIATIONS ON A THEOREM OF DAVENPORT CONCERNING ABUNDANT NUMBERS

DOI: Let \(\sigma(n)\) denote the sum of the positive divisors of \(N\). In 1933, Davenport showed that \(n/\sigma(n)\) possesses a continuous distribution function. We study the behavior of analogous weighted distributions involving certain complex-valued multiplicative functions. Our results cover many of the more frequently encountered functions, including \(\sigma(n)\), \(\tau(n)\) and \(\mu(n)\). They also apply to the representation function for sums of two squares, leading again to a continuous distribution function. 10.1017/S0004972713000695
Mining parametric temporal logic properties in model-based design for cyber-physical systems

One of the advantages of adopting a model-based development process is that it enables testing and verification at early stages of development. However, it is often desirable to not only verify/falsify certain formal system specifications, but also to automatically explore the properties that the system satisfies. In this work, we present a framework that enables property exploration for cyber-physical systems. Namely, given a parametric specification with multiple parameters, our solution can automatically infer the ranges of parameters for which the property does not hold on the system. In this paper, we consider parametric specifications in metric or Signal Temporal Logic (MTL or STL). Using robust semantics for MTL, the parameter mining problem can be converted into a Pareto optimization problem for which we can provide an approximate solution by utilizing stochastic optimization methods. We include algorithms for the exploration and visualization of multi-parametric specifications. The framework is demonstrated on an industrial size, high-fidelity engine model as well as examples from related literature.
Stellar Archaeology — Exploring the Universe with Metal-Poor Stars

The abundance patterns of the most metal-poor stars in the Galactic halo and small dwarf galaxies provide us with a wealth of information about the early Universe. In particular, these old survivors allow us to study the nature of the firs t stars and supernovae, the relevant nucleosynthesis processes responsible for the formation and evolution of the elements, early star- and galaxy formation processes, as well as the assembly process of the stellar halo from dwarf galaxies a long time ago. This review presents the current state of the field o f “stellar archaeology” ‐ the diverse use of metal-poor star s to explore the high-redshift Universe and its constituents. I n particular, the conditions for early star formation are di scussed, how these ultimately led to a chemical evolution, and what the role of the most iron-poor stars is for learning about Population III supernovae yields. Rapid neutron-capture signatures found in metal-poor stars can be used to obtain stellar ages, but also to constrain this complex nucleosynthesis process with observational measurements. Moreover, chemical abundances of extremely metal-poor stars in different types of dwarf galaxies can be used to infer details on the formation scenario of the halo. and the role of dwarf galaxies as Galactic building blocks. I conclude with an outlook as to where this field may be heading within the next decade. A table of � 1000 metal-poor stars and their abundances as collected from the literature is provided in electronic format.
Ambipolar Black Phosphorus MOSFETs With Record n-Channel Transconductance

Ambipolar black phosphorus MOSFETs with record n-channel extrinsic transconductance are reported. The devices consist of multilayer black phosphorus aligned to a local back-gate electrode with 10-nm-thick HfO2 gate dielectric. Before passivation, devices with 0.3- $\mu \text{m}$ gate length behaved as p-MOSFETs with peak extrinsic transconductance, $g_{m}$ , of 282 $\mu \text{S}/\mu \text{m}$ at $V_{\textrm {DS}}=- 2$ V. After passivation, the same devices displayed the ambipolar behavior, and when tested as n-MOSFETs, had peak $g_{m} =66~\mu \text{S}/\mu \text{m}$ at $V_{\textrm {DS}} = +2$ V, and similar devices on the same wafer had $g_{m}$ as high as 80 $\mu \text{S}/\mu \text{m}$ . These results are an important step toward the realization of high-performance black phosphorus complementary logic circuits.
QUASI-SYMMETRIC FUNCTIONS AND MOD p MULTIPLE HARMONIC SUMS

We present a number of results about (finite) multiple harmonic sums modulo a prime, which provide interesting parallels to known results about multiple zeta values (i.e., infinite multiple harmonic series). In particular, we prove a “duality” result for mod p harmonic sums similar to (but distinct from) that for multiple zeta values. We also exploit the Hopf algebra structure of the quasi-symmetric functions to do calculations with multiple harmonic sums mod p, and obtain, for each weight n ≤ 9, a set of generators for the space of weight-n multiple harmonic sums mod p.
Potential envelope theory and the local energy theorem

We consider a one-particle bound quantum mechanical system governed by a Schrodinger operator H=−Δ+v f(r), where f(r) is an attractive central potential and v > 0 is a coupling parameter. If ϕ∈D(H) is a “trial function,” the local energy theorem tells us that the discrete energies of H are bounded by the extreme values of (H ϕ)/ϕ, as a function of r. We suppose that f(r) is a smooth transformation of the form f = g(h), where g is monotone increasing with definite convexity and h(r) is a potential for which the eigenvalues Hn(u) of the operator H=−Δ+u h(r), for appropriate u > 0, are known. It is shown that the eigenfunctions of H provide local-energy trial functions ϕ which necessarily lead to finite eigenvalue approximations that are either lower or upper bounds. This is used to extend the local energy theorem to the case of upper bounds for the excited-state energies when the trial function is chosen to be an eigenfunction of such an operator H. Moreover, we prove that the local-energy approximations obtained are identical to “envelope bounds,” which can be obtained directly from the spectral data Hn(u) without explicit reference to the trial wave functions.We consider a one-particle bound quantum mechanical system governed by a Schrodinger operator H=−Δ+v f(r), where f(r) is an attractive central potential and v > 0 is a coupling parameter. If ϕ∈D(H) is a “trial function,” the local energy theorem tells us that the discrete energies of H are bounded by the extreme values of (H ϕ)/ϕ, as a function of r. We suppose that f(r) is a smooth transformation of the form f = g(h), where g is monotone increasing with definite convexity and h(r) is a potential for which the eigenvalues Hn(u) of the operator H=−Δ+u h(r), for appropriate u > 0, are known. It is shown that the eigenfunctions of H provide local-energy trial functions ϕ which necessarily lead to finite eigenvalue approximations that are either lower or upper bounds. This is used to extend the local energy theorem to the case of upper bounds for the excited-state energies when the trial function is chosen to be an eigenfunction of such an operator H. Moreover, we prove that the local-energy approximations ob...
A Short-term Intervention for Long-term Fairness in the Labor Market

The persistence of racial inequality in the U.S. labor market against a general backdrop of formal equality of opportunity is a troubling phenomenon that has significant ramifications on the design of hiring policies. In this paper, we show that current group disparate outcomes may be immovable even when hiring decisions are bound by an input-output notion of "individual fairness." Instead, we construct a dynamic reputational model of the labor market that illustrates the reinforcing nature of asymmetric outcomes resulting from groups» divergent accesses to resources and as a result, investment choices. To address these disparities, we adopt a dual labor market composed of a Temporary Labor Market (TLM), in which firms» hiring strategies are constrained to ensure statistical parity of workers granted entry into the pipeline, and a Permanent Labor Market (PLM), in which firms hire top performers as desired. Individual worker reputations produce externalities for their group; the corresponding feedback loop raises the collective reputation of the initially disadvantaged group via a TLM fairness intervention that need not be permanent. We show that such a restriction on hiring practices induces an equilibrium that, under particular market conditions, Pareto-dominates those arising from strategies that statistically discriminate or employ a "group-blind" criterion. The enduring nature of equilibria that are both inequitable and Pareto suboptimal suggests that fairness interventions beyond procedural checks of hiring decisions will be of critical importance in a world where machines play a greater role in the employment process.
Cosmological physics with black holes (and possibly white dwarfs)

Abstract The notion that microparsec-scale black holes can be used to probe gigaparsec-scale physics may seem counterintuitive, at first. Yet, the gravitational observatory LISA will detect cosmologically-distant coalescing pairs of massive black holes, accurately measure their luminosity distance and help identify an electromagnetic counterpart or a host galaxy. A wide variety of new black hole studies and a gravitational version of Hubble’s diagram become possible, if host galaxies are successfully identified. Furthermore, if dark energy is a manifestation of large-scale modified gravity, deviations from general relativistic expectations could become apparent in a gravitational signal propagated over cosmological scales, especially when compared to the electromagnetic signal from a same source. Finally, since inspirals of white dwarfs into massive black holes at cosmological distances may permit pre-merger localizations, we suggest that careful monitoring of these events and any associated electromagnetic counterpart could lead to high-precision cosmological measurements with LISA.
Simple Current Extensions and Mapping Class Group Representations

The conjecture of Fuchs, Schellekens and Schweigert on the relation of mapping class group representations and fixed point resolution in simple current extensions is investigated, and a cohomological interpretation of the untwisted stabilizer is given.
A 3D-Printed Wheel with Constant Mass and Variable Moment of Inertia for Lab and Demonstration

We present a versatile experimental apparatus for exploring rotational motion through the interplay between the moment of inertia, torque, and rotational kinetic energy of a wheel. The heart of this experiment uses a 3D-printed wheel along with easily accessible stock components that allow for the adjustment of the moment of inertia while keeping the total mass of the wheel constant. The wheel can act as a massive pulley of variable moment of inertia that allows students to measure the moment of inertia of the bare wheel by applying a constant torque to the system. The wheel can also be used to explore rotational kinetic energy in the form of races down ramps. The 3D-printed aspect of this wheel allows anyone with access to a 3D printer to create, explore, and modify this wheel at a low cost, allowing for more flexibility and accessibility for student and instructor exploration and modification. In the study of linear kinematics, it is easy to investigate how systems evolve with variable mass. With rotational motion the situation is more complicated due to the fact that the moment of inertia depends not only on the mass, but also on the distribution of the mass. This can be demonstrated in the form of massive pulleys in Atwood machines and in a rolling race of objects of varying mass and moment of inertia. For lab explorations it is best to isolate a single variable that can be changed. For rotational motion it is difficult to find a wheel with constant mass but different moments of inertia. There do exist examples that solve this problem, but they require workshop access and cannot act as pulleys. To address this issue we have designed a wheel whose moment of inertia can easily be created and manipulated while the mass of the system remains constant, providing an accessible, flexible, and robust apparatus to explore the interplay between moment of inertia and torque and rotational kinetic energy.
How Polarized Have We Become? A Multimodal Classification of Trump Followers and Clinton Followers

Polarization in American politics has been extensively documented and analyzed for decades, and the phenomenon became all the more apparent during the 2016 presidential election, where Trump and Clinton depicted two radically different pictures of America. Inspired by this gaping polarization and the extensive utilization of Twitter during the 2016 presidential campaign, in this paper we take the first step in measuring polarization in social media and we attempt to predict individuals’ Twitter following behavior through analyzing ones’ everyday tweets, profile images and posted pictures. As such, we treat polarization as a classification problem and study to what extent Trump followers and Clinton followers on Twitter can be distinguished, which in turn serves as a metric of polarization in general. We apply LSTM to processing tweet features and we extract visual features using the VGG neural network. Integrating these two sets of features boosts the overall performance. We are able to achieve an accuracy of 69%, suggesting that the high degree of polarization recorded in the literature has started to manifest itself in social media as well.
JET RESULTS AND JET RECONSTRUCTION TECHNIQUES IN p+p AND THEIR PROSPECTS IN Pb+Pb COLLISIONS IN CMS

Copious production of very energetic jets is expected at the LHC due to the large increase in collision energy. Jet reconstruction at these high center of mass energies will provide crucial leverage to map out the QCD evolution of parton energy loss and a unique insight into the nature of the hot QCD matter. This article presents jet reconstruction techniques and the preliminary jet results in p+p collisions at collected by the CMS experiment at the LHC. Jet reconstruction prospects for the heavy ion collisions are also discussed.
SELF-TRAPPING AT THE LIQUID-VAPOR CRITICAL POINT

Experiments suggest that localization via self-trapping plays a central role in the behavior of equilibrated low mass particles in both liquids and in supercritical fluids. In the latter case, the behavior is dominated by the liquid-vapor critical point which is difficult to probe, both experimentally and theoretically. Here, for the first time, we present the results of path-integral computations of the characteristics of a self-trapped particle at the critical point of a Lennard-Jones fluid for a positive particle-atom scattering length. We investigate the influence of the range of the particle-atom interaction on trapping properties, and the pick-off decay rate for the case where the particle is ortho-positronium. We find that, at the critical point, the transition from the self-trapped inhomogeneity to the density of the surrounding fluid is more gradual than in the liquid, or dense gas, away from the critical point. In addition the "shell structure" in fluid density surrounding the droplet is effaced.