cssi/SciSciGPT-SciSciNet huggingface dataset:
Distributed Feedback Controllers for Stable Cooperative Locomotion of Quadrupedal Robots: A Virtual Constraint Approach*

This paper aims to develop distributed feedback control algorithms that allow cooperative locomotion of quadrupedal robots which are coupled to each other by holonomic constraints. These constraints can arise from collaborative manipulation of objects during locomotion. In addressing this problem, the complex hybrid dynamical models that describe collaborative legged locomotion are studied. The complex periodic orbits (i.e., gaits) of these sophisticated and high-dimensional hybrid systems are investigated. We consider a set of virtual constraints that stabilizes locomotion of a single agent. The paper then generates modified and local virtual constraints for each agent that allow stable collaborative locomotion. Optimal distributed feedback controllers, based on nonlinear control and quadratic programming, are developed to impose the local virtual constraints. To demonstrate the power of the analytical foundation, an extensive numerical simulation for cooperative locomotion of two quadrupedal robots with robotic manipulators is presented. The numerical complex hybrid model has 64 continuous-time domains, 192 discrete-time transitions, 96 state variables, and 36 control inputs.
The Role of the Mean State on MJO Simulation in CESM2 Ensemble Simulation

This study examines the role of the mean state in the propagation of the Madden-Julian Oscillation (MJO) over the Maritime Continent (MC). We use an ensemble of simulations made with a single model...
An Efficient Algorithm for Designing Optimal CRCs for Tail-Biting Convolutional Codes

Cyclic redundancy check (CRC) codes combined with convolutional codes yield a powerful concatenated code that can be efficiently decoded using list decoding. To help design such systems, this paper presents an efficient algorithm for identifying the distance-spectrum-optimal (DSO) CRC polynomial for a given tail-biting convolutional code (TBCC) when the target undetected error rate (UER) is small. Lou et al. found that the DSO CRC design for a given zero-terminated convolutional code under low UER is equivalent to maximizing the undetected minimum distance (the minimum distance of the concatenated code). This paper applies the same principle to design the DSO CRC for a given TBCC under low target UER. Our algorithm is based on partitioning the tail-biting trellis into several disjoint sets of tail-biting paths that are closed under cyclic shifts. This paper shows that the tail-biting path in each set can be constructed by concatenating the irreducible error events (IEEs) and circularly shifting the resultant path. This motivates an efficient collection algorithm that aims at gathering IEEs, and a search algorithm that reconstructs the full list of error events with bounded distance of interest, which can be used to find the DSO CRC. Simulation results show that DSO CRCs can significantly outperform suboptimal CRCs in the low UER regime.
Nitrogen doping and infusion in SRF cavities: A review

Abstract Advances in SRF technology over the last 40 years allowed achieving accelerating gradients ~50 ​MV/m corresponding to peak surface magnetic fields close to the theoretical limit of niobium. However, the quality factor decreases significantly with increasing accelerating gradient. This decrease is expected since increasing the rf field increases the number of quasiparticles and therefore the rf losses. Recently, a new phenomenon of increase in quality factor with an accelerating gradient has been observed when SRF cavities are doped with certain non-magnetic impurities. In particular, the diffusion of nitrogen into the niobium cavities’ inner surface has been successfully implemented into the commercialization of SRF technology. The quest is still ongoing towards process development to achieve high accelerating gradient SRF structures with high-quality factors for future high energy accelerators. Here, we present the review of the research on process development to this date via nitrogen diffusion, material analysis, and present the summary of current theoretical understanding behind high Q0 SRF cavities.
Reply to: "QT prolongation with hydroxychloroquine and azithromycin for the treatment of COVID-19: The need for pharmacogenetic insights".

We thank Medina et al. for their interest in our recent work on QTc prolongation associated with treatment of COVID-19 patients with hydroxychloroquine and azithromycin. As they appropriately point out in their letter, genetic variation is likely a significant determinant of QT prolongation in the population at large and in COVID-19 patients specifically. While drugs causing acquired long QT syndrome and torsades de pointes are generally blockers of IKr, repolarization results from the aggregate of multiple inward and outward currents. Patients with sub-clinical defects in any of these ion channels can have normal or only slightly prolonged baseline QT intervals, but may possess decreased repolarization reserve leading to an exaggerated response to IKr blockade (1). In our study, a baseline QTc of > 460 ms was associated with excessive QTc prolongation, and this likely represents a group of patients with sub-clinical cardiac ion channel mutations (so called “first hit”) (2). We also agree that many patients with latent mutations demonstrate a normal baseline QT, which gets prolonged with the addition of a drug or a change in the clinical condition “second hit” (3). The patients in our study who exhibited QTc prolongation were generally acutely ill, and displayed “multiple hits” that led to QTc prolongation and it is certainly plausible that many may have had sub-clinical cardiac ion mutations. We therefore wholeheartedly agree that pharmacogenetics should be considered in studies of drug-induced QT prolongation, however this information is rarely available to include for acutely ill patients. And while it makes sense to obtain genetic profiles prior to administration of QT-prolonging medications, that can only be performed in the elective outpatient setting, while taking into consideration medical, ethical and social issues related to asymptomatic genetic screening (e.g. cost, reimbursement, informed consent, etc…). There is significant interest in building genomic databases, and when this becomes a reality for the population at large we believe that genetic information should certainly be included in studies of QT prolongation.Roden DM Long QT syndrome: reduced repolarization reserve and the genetic link. J Intern Med. 2006 Jan; 259(1):59-69.Napolitano C, Schwartz PJ, Brown AM, et al. Evidence for a cardiac ion channel mutation underlying drug-induced QT prolongation and life-threatening arrhythmias. J Cardiovasc Electrophysiol. 2000;11:691–6Sauer AJ and Newton-Cheh C. Clinical and genetic determinants of torsade de pointes risk. Circulation. 2012;125:1684-94.
Associations Between Maternal Stress, Early Language Behaviors, and Infant Electroencephalography During the First Year of Life

Associations have been observed between socioeconomic status (SES) and language outcomes from early childhood, but individual variability is high. Exposure to high levels of stress, often associated with low-SES status, might influence how parents and infants interact within the early language environment. Differences in these early language behaviors, and in early neurodevelopment, might underlie SES-based differences in language that emerge later on. Analysis of natural language samples from a predominantly low-/mid-income sample of mother-infant dyads, obtained using the Language Environment Analysis (LENA) system, found that maternal reports of exposure to stressful life events, and perceived stress, were negatively correlated with child vocalizations and conversational turns when infants were 6 and 12 months of age. Greater numbers of vocalizations and conversational turns were also associated with lower relative theta power and higher relative gamma power in 6- and 12-month baseline EEG - a pattern that might support subsequent language development.
A Method for Evaluating Soluble Redox Couple Stability Using Microelectrode Voltammetry

Soluble, redox-active, organic materials hold promise as charge-storage species for flow batteries; however, their stability during extended operation remains a key challenge. While a number of spectroscopic and electrochemical techniques are currently used to probe these complex and often ill-defined decay pathways, each technique has limitations, including accessibility and direct evaluation of practical electrolytes without preparatory steps. Here, we use microelectrode voltammetry to directly observe nonaqueous flow battery electrolytes, simultaneously identifying the rate of charged materials decay (reversible material loss) and total material decay (irreversible material loss). We validate this technique using ferrocene as a stable model redox couple, examine and address sources of error, and finally, demonstrate its capability by assessing the decay of a well-studied and moderately-stable substituted dialkoxybenzene [2,5-di-tert-butyl-1,4-bis(2-methoxyethoxy)benzene]. These results suggest that microelectrodes may have utility for rapid assessment of redox electrolyte state-of-charge and state-of-health, both in-operando and post-mortem.
How Reporters Can Evaluate Automated Driving Announcements

This article identifies a series of specific questions that reporters (as well as policymakers, academics, and others) can ask about claims made by developers of automated motor vehicles (“AVs”). Its immediate intent is to facilitate more critical, credible, and ultimately constructive reporting on progress toward automated driving. In turn, reporting of this kind advances three additional goals. First, it encourages AV developers to qualify and support their public claims. Second, it appropriately manages public expectations about these vehicles. Third, it fosters more technical accuracy and technological circumspection in legal and policy scholarship.
Identification of the K-most Vulnerable Entities in a Smart Grid System

A smart grid system can be considered as a multi-layered network with power network in one layer and communication network in the other. The entities in both the layers exhibit complex intra-and-interdependencies between them. A reliable decision making by the smart grid operator is contingent upon correct analysis of such dependencies between its entities and also on accurate identification of the most critical entities in the system. The Modified Implicative Interdependency Model (MIIM) [1] successfully captures such dependencies using multi-valued Boolean Logic based equations called Interdependency Relations (IDRs) after most of the existing models made failed attempts in doing that. In this paper, for any given integer K, this model is used to identify the K-most vulnerable entities in a smart grid, failure of which can maximize the network damage. Owing to the problem being NP complete, an Integer Linear Programming (ILP) based solution is given here. Validation of the model [1] and the results of the ILP based solution is done by simulating a smart grid system of IEEE 14-Bus using MATPOWER and Java Network Simulator (JNS). Simulation results prove that not only the model MIIM [1] is correct but also it can predict the network damage for failure of K-most vulnerable entities more accurately than its predecessor Implicative Interdependency Model (IIM) [2].
Deterrence Effects of Antifraud and Abuse Enforcement in Health Care

Abstract Estimates of the benefits of antifraud enforcement in health care typically focus on direct monetary damages. Deterrence effects are acknowledged but unquantified. We evaluate the impact of a Department of Justice investigation of hospitals accused of billing Medicare for unnecessary implantable cardiac defibrillator (ICD) procedures on their use. Using 100 % inpatient and outpatient procedure data from Florida, we estimate that the investigation caused a 22 % decline in ICD implantations. The present value of savings nationally over a 10 year period is $2.7 billion, nearly 10 times larger than the $280 million in settlements the Department of Justice recovered from hospitals. The investigation had a large and long-lasting effect on physician behavior, indicating the utility of antifraud enforcement as a tool for reducing wasteful medical care.
Reducing parameter space for neural network training

ABSTRACT For neural networks (NNs) with rectified linear unit (ReLU) or binary activation functions, we show that their training can be accomplished in a reduced parameter space. Specifically, the weights in each neuron can be trained on the unit sphere, as opposed to the entire space, and the threshold can be trained in a bounded interval, as opposed to the real line. We show that the NNs in the reduced parameter space are mathematically equivalent to the standard NNs with parameters in the whole space. The reduced parameter space shall facilitate the optimization procedure for the network training, as the search space becomes (much) smaller. We demonstrate the improved training performance using numerical examples.
Understanding Human Intelligence through Human Limitations

Recent progress in artificial intelligence provides the opportunity to ask the question of what is unique about human intelligence, but with a new comparison class. I argue that we can understand human intelligence, and the ways in which it may differ from artificial intelligence, by considering the characteristics of the kind of computational problems that human minds have to solve. I claim that these problems acquire their structure from three fundamental limitations that apply to human beings: limited time, limited computation, and limited communication. From these limitations we can derive many of the properties we associate with human intelligence, such as rapid learning, the ability to break down problems into parts, and the capacity for cumulative cultural evolution.
Circumstellar disk evolution: Constraining theories of planet formation

Observations of circumstellar disks around stars as a function of stellar properties such as mass, metallicity, multiplicity, and age, provide constraints on theories concerning the formation and evolution of planetary systems. Utilizing ground- and space-based data from the far-UV to the millimeter, astronomers can assess the amount, composition, and location of circumstellar gas and dust as a function of time. We review primarily results from the Spitzer Space Telescope, with reference to other ground- and space-based observations. Comparing these results with those from exoplanet search techniques, theoretical models, as well as the inferred history of our solar system, helps us to assess whether planetary systems like our own, and the potential for life that they represent, are common or rare in the Milky Way galaxy.
Topological properties of SnSe/EuS and SnTe/CaTe interfaces

We use density functional theory calculations to study the electronic structure of epitaxial (111) interfaces of the topological crystalline insulators SnSe and SnTe with the magnetic insulator EuS and the nonmagnetic insulator CaTe, respectively. We consider both interface slab models with a vacuum region and periodic heterostructures without vacuum. We find that gaps of 21 meV at the $\mathrm{\ensuremath{\Gamma}}$ point and 9 meV at the $M$ point arise in the topological state at the SnSe/EuS interface, due to the magnetic proximity effect, which breaks the time reversal symmetry. The surface state at $\mathrm{\ensuremath{\Gamma}}$ is shifted below the Fermi level by 88 meV and the surface state at $M$ is shifted above the Fermi level by 47 meV, due to band bending at the interface. By comparison, the topological state at the interface of SnTe/CaTe is unperturbed by the presence of nonmagnetic CaTe.
How Changes in Entry Requirements Alter the Teacher Workforce and Affect Student Achievement

Abstract We are in the midst of what amounts to a national experiment in how best to attract, prepare, and retain teachers, particularly for high-poverty urban schools. Using data on students and teachers in grades 3–8, this study assesses the effects of pathways into teaching in New York City on the teacher workforce and on student achievement. We ask whether teachers who enter through new routes, with reduced coursework prior to teaching, are more or less effective at improving student achievement. When compared to teachers who completed a university-based teacher education program, teachers with reduced coursework prior to entry often provide smaller initial gains in both mathematics and English language arts. Most differences disappear as the cohort matures, and many of the differences are not large in magnitude, typically 2 to 5 percent of a standard deviation. The variation in effectiveness within pathways is far greater than the average differences between pathways.
THE CHEMICAL IMPRINT OF SILICATE DUST ON THE MOST METAL-POOR STARS

We investigate the impact of dust-induced gas fragmentation on the formation of the first low-mass, metal-poor stars (<1 M ☉) in the early universe. Previous work has shown the existence of a critical dust-to-gas ratio, below which dust thermal cooling cannot cause gas fragmentation. Assuming that the first dust is silicon-based, we compute critical dust-to-gas ratios and associated critical silicon abundances ([Si/H]crit). At the density and temperature associated with protostellar disks, we find that a standard Milky Way grain size distribution gives [Si/H]crit = –4.5 ± 0.1, while smaller grain sizes created in a supernova reverse shock give [Si/H]crit = –5.3 ± 0.1. Other environments are not dense enough to be influenced by dust cooling. We test the silicate dust cooling theory by comparing to silicon abundances observed in the most iron-poor stars ([Fe/H] < -4.0). Several stars have silicon abundances low enough to rule out dust-induced gas fragmentation with a standard grain size distribution. Moreover, two of these stars have such low silicon abundances that even dust with a shocked grain size distribution cannot explain their formation. Adding small amounts of carbon dust does not significantly change these conclusions. Additionally, we find that these stars exhibit either high carbon with low silicon abundances or the reverse. A silicate dust scenario thus suggests that the earliest low-mass star formation in the most metal-poor regime may have proceeded through two distinct cooling pathways: fine-structure line cooling and dust cooling. This naturally explains both the carbon-rich and carbon-normal stars at extremely low [Fe/H].
Impact of carrier localization on recombination in InGaN quantum wells and the efficiency of nitride light-emitting diodes: Insights from theory and numerical simulations

We examine the effect of carrier localization due to random alloy fluctuations on the radiative and Auger recombination rates in InGaN quantum wells as a function of alloy composition, crystal orientation, carrier density, and temperature. Our results show that alloy fluctuations reduce individual transition matrix elements by the separate localization of electrons and holes, but this effect is overcompensated by the additional transitions enabled by translational symmetry breaking and the resulting lack of momentum conservation. Hence, we find that localization increases both radiative and Auger recombination rates, but that Auger recombination rates increase by one order of magnitude more than radiative rates. Furthermore, we demonstrate that localization has an overall detrimental effect on the efficiency-droop and green-gap problems of InGaN light-emitting diodes.
Near Hagedorn dynamics of NS fivebranes or a new universality class of coiled strings

We analyze the thermodynamics of NS fivebranes as the temperature approaches the NS fivebranes' Hagedorn temperature, and conclude that the dynamics of ``Little String Theory'' is a new universality class of interacting strings. First we point out how to vary the temperature of the near extremal solution by taking into account gs corrections. The Hagedorn temperature is shown to be a limiting temperature for the theory. We then compare the thermodynamics to that of a toy model made of free strings and find basic discrepancies. This suggests a need for a new class of string interactions. We suggest that this new universality class is characterized by a strong attractive self-intersection interaction, which causes strings to be coiled. This model might also explain why ``Little String Theories'' exist in at most 5+1 dimensions.
Self-updating models with error remediation

Many environments currently employ machine learning models for data processing and analytics that were built using a limited number of training data points. Once deployed, the models are exposed to significant amounts of previously-unseen data, not all of which is representative of the original, limited training data. However, updating these deployed models can be difficult due to logistical, bandwidth, time, hardware, and/or data sensitivity constraints. We propose a framework, Self-Updating Models with Error Remediation (SUMER), in which a deployed model updates itself as new data becomes available. SUMER uses techniques from semi-supervised learning and noise remediation to iteratively retrain a deployed model using intelligently-chosen predictions from the model as the labels for new training iterations. A key component of SUMER is the notion of error remediation as self-labeled data can be susceptible to the propagation of errors. We investigate the use of SUMER across various data sets and iterations. We find that self-updating models (SUMs) generally perform better than models that do not attempt to self-update when presented with additional previously-unseen data. This performance gap is accentuated in cases where there is only limited amounts of initial training data. We also find that the performance of SUMER is generally better than the performance of SUMs, demonstrating a benefit in applying error remediation. Consequently, SUMER can autonomously enhance the operational capabilities of existing data processing systems by intelligently updating models in dynamic environments.
Observational Constraints on the Internal Structure and Dynamics of the VELA Pulsar

We show that the short spin-up time observed for the Vela pulsar during the 1988 "Christmas" glitch implies that the coupling time of the pulsar core to its crust is less than ~10 s. Ekman pumping cannot explain the fast core-crust coupling and a more effective coupling is necessary. The internal magnetic field of the Vela pulsar can provide the necessary coupling if the field threads the core with a magnitude that exceeds 1013 G for a normal interior and 1011 G for a superconducting interior. These lower bounds favor the hypothesis that the interior of neutron stars contains superfluid neutrons and protons and challenge the notion that pulsar magnetic fields decay over million year timescales or that magnetic flux is expelled from the core as the star slows.
Modeling UX Ursae Majoris: An Abundance of Challenges*

We present a system model for optical and far-UV spectra of the nova-like variable UX UMa involving a white dwarf, secondary star, gas stream, hot spot, and accretion disk using our code BINSYN and based on an initially adopted system distance. Calculated SED intensity data successfully fit successive tomographically extracted annuli longward of the Balmer limit but require a postulated "iron curtain" shortward of the Balmer limit that is applied to the annulus section closest to the secondary star, while postulated recombination emission fills in the model SED shortward of the Balmer limit and is applied to the annulus section more remote from the secondary star. The same model fits UBV 1954 light curves by Walker and Herbig. Fits to HST FOS spectra are approximate but require assumed time-variable changes in the SED. Comparable effects, possibly involving variable absorption, afflict FUSE spectra. Fits to IUE spectra by the model show time-dependent residuals that indicate changes in the accretion disk temperature profile, possibly indicative of a slightly variable from the secondary star. Using model-based component light contributions and the improvement on the Bailey relation by Knigge we determine the system distance and mass transfer rate.
Point process models for sequence detection in high-dimensional neural spike trains

Sparse sequences of neural spikes are posited to underlie aspects of working memory, motor production, and learning. Discovering these sequences in an unsupervised manner is a longstanding problem in statistical neuroscience. Promising recent work utilized a convolutive nonnegative matrix factorization model to tackle this challenge. However, this model requires spike times to be discretized, utilizes a sub-optimal least-squares criterion, and does not provide uncertainty estimates for model predictions or estimated parameters. We address each of these shortcomings by developing a point process model that characterizes fine-scale sequences at the level of individual spikes and represents sequence occurrences as a small number of marked events in continuous time. This ultra-sparse representation of sequence events opens new possibilities for spike train modeling. For example, we introduce learnable time warping parameters to model sequences of varying duration, which have been experimentally observed in neural circuits. We demonstrate these advantages on experimental recordings from songbird higher vocal center and rodent hippocampus.
General relativity as a hybrid theory: The genesis of Einstein's work on the problem of motion

In this paper I describe the genesis of Einstein's early work on the problem of motion in general relativity (GR): the question of whether the motion of matter subject to gravity can be derived directly from the Einstein field equations. In addressing this question, Einstein himself always preferred the vacuum approach to the problem: the attempt to derive geodesic motion of matter from the vacuum Einstein equations. The paper first investigates why Einstein was so skeptical of the energy-momentum tensor and its role in GR. Drawing on hitherto unknown correspondence between Einstein and George Yuri Rainich, I then show step by step how his work on the vacuum approach came about, and how his quest for a unified field theory informed his interpretation of GR. I show that Einstein saw GR as a hybrid theory from very early on: fundamental and correct as far as gravity was concerned but phenomenological and effective in how it accounted for matter. As a result, Einstein saw energy-momentum tensors and singularities in GR as placeholders for a theory of matter not yet delivered. The reason he preferred singularities was that he hoped that their mathematical treatment would give a hint as to the sought after theory of matter, a theory that would do justice to quantum features of matter.
Solitons and ADS String Solutions

In this contribution we describe some soliton based techniques for generating classical AdS string solutions. The methods introduced are useful for further understanding of rotating AdS configurations with spikes which correspond to higher twist operators in SYM theory. The main identification (accomplished in arXiv:0712.1193) between solitons and string spikes is reviewed and extended. We desribe how inverse scattering technique can be applied for reconstructing AdS string configurations from soliton solutions of sinh-Gordon theory (in the example of AdS3).
The universal Glivenko-Cantelli property

Let $${\mathcal{F}}$$ be a separable uniformly bounded family of measurable functions on a standard measurable space $${(X, \mathcal{X})}$$ , and let $${N_{[]}(\mathcal{F}, \varepsilon, \mu)}$$ be the smallest number of $${\varepsilon}$$ -brackets in L 1(μ) needed to cover $${\mathcal{F}}$$ . The following are equivalent: It follows that universal Glivenko–Cantelli classes are uniformity classes for general sequences of almost surely convergent random measures.
Interval parking functions

Abstract Interval parking functions (IPFs) are a generalization of ordinary parking functions in which each car is willing to park only in a fixed interval of spaces. Each interval parking function can be expressed as a pair ( a , b ) , where a is a parking function and b is a dual parking function. We say that a pair of permutations ( x , y ) is reachable if there is an IPF ( a , b ) such that x , y are the outcomes of a , b , respectively, as parking functions. Reachability is reflexive and antisymmetric, but not in general transitive. We prove that its transitive closure, the pseudoreachability order, is precisely the bubble-sorting order on the symmetric group S n , which can be expressed in terms of the normal form of a permutation in the sense of du Cloux; in particular, it is isomorphic to the product of chains of lengths 2 , … , n . It is thus seen to be a special case of Armstrong's sorting order, which lies between the Bruhat and (left) weak orders.
Finite range and upper branch effects on itinerant ferromagnetism in repulsive Fermi gases: Bethe-Goldstone ladder resummation approach

Abstract We investigate the ferromagnetic transition in repulsive Fermi gases at zero temperature with upper branch and effective range effects. Based on a general effective Lagrangian that reproduces precisely the two-body s -wave scattering phase shift, we obtain a nonperturbative expression of the energy density as a function of the polarization by using the Bethe–Goldstone ladder resummation. For hard sphere potential, the predicted critical gas parameter k F a = 0.816 and the spin susceptibility agree well with the results from fixed-node diffusion Monte Carlo calculations. In general, positive and negative effective ranges have opposite effects on the critical gas parameter k F a : While a positive effective range reduces the critical gas parameter, a negative effective range increases it. For attractive potential or Feshbach resonance model, the many-body upper branch exhibits an energy maximum at k F a = α with α = 1.34 from the Bethe–Goldstone ladder resummation, which is qualitatively consistent with experimental results. The many-body T-matrix has a positive-energy pole for k F a > α and it becomes impossible to distinguish the bound state and the scattering state. These positive-energy bound states become occupied and therefore the upper branch reaches an energy maximum at k F a = α . In the zero range limit, there exists a narrow window ( 0.86 k F a 1.56 ) for the ferromagnetic phase. At sufficiently large negative effective range, the ferromagnetic phase disappears. On the other hand, the appearance of positive-energy bound state resonantly enhances the two-body decay rate around k F a = α and may prevent the study of equilibrium phases and ferromagnetism of the upper branch Fermi gas.
OPTICAL MASS FLOW DIAGNOSTICS IN HERBIG AE/BE STARS

We examine a broad range of mass flow diagnostics in a large sample of Herbig Ae/Be stars (HAEBES) using high resolution optical spectra. The Hβ and He i 5876 Å lines show the highest incidence of P Cygni (30%) and inverse P Cygni (14%) morphologies, respectively. The Fe ii 4924 Å line also shows a large incidence of P Cygni profiles (11%). We find support for many of the conclusions reached in a study based on the analysis of the He i λ10830 line in a large sample of HAEBES. Namely, HAEBES exhibit smaller fractions of both blueshifted absorption (i.e., mass outflow) and redshifted absorption (i.e., mass infall or accretion) than their lower mass cousins, the classical T Tauri stars (CTTSs). In particular, the optical data supports the conclusion that HAEBES displaying redshifted absorption, in general, show maximum redshifted absorption velocities that are smaller fractions of their stellar escape velocities than is found for CTTSs. This suggests that HAEBE accretion flows are originating deeper in the gravitational potentials of their stars than in CTTS systems. In addition, we find a lack of inner disk wind signatures in the blueshifted absorption objects; only stellar wind signatures are clearly observed. These findings, along with the lack of detected magnetic fields around HAEBES, support the idea that large magnetospheres are not prevalent around HAEBES and that accretion flows are instead mediated by significantly smaller magnetospheres with relatively smaller truncation radii (e.g., 1–2 R*). Redshifted absorption is much more common around Herbig Ae stars than Be stars, suggesting that Herbig Be stars may accrete via a boundary layer rather than along magnetic field lines.
The Brauer Group of an Affine Double Plane Associated to a Hyperelliptic Curve

ABSTRACTWe study the Brauer group of an affine double plane π:X→&#x1d538;2 defined by an equation of the form z2 = f in two separate cases. In the first case, f is a product of n linear forms in k[x,y] and...
Bootstrap bounds on closed Einstein manifolds

A compact Riemannian manifold is associated with geometric data given by the eigenvalues of various Laplacian operators on the manifold and the triple overlap integrals of the corresponding eigenmodes. This geometric data must satisfy certain consistency conditions that follow from associativity and the completeness of eigenmodes. We show that it is possible to obtain nontrivial bounds on the geometric data of closed Einstein manifolds by using semidefinite programming to study these consistency conditions, in analogy to the conformal bootstrap bounds on conformal field theories. These bootstrap bounds translate to constraints on the tree-level masses and cubic couplings of Kaluza-Klein modes in theories with compact extra dimensions. We show that in some cases the bounds are saturated by known manifolds.
Performance and Design of Consensus on Matrix-Weighted and Time-Scaled Graphs

In this article, we consider the ${\mathcal {H}_2}$ -norm of networked systems with multi-time-scale consensus dynamics and vector-valued agent states. This allows us to explore how measurement and process noise affect consensus on matrix-weighted graphs by examining edge-state consensus. In particular, we highlight an interesting case where the influences of the weighting and scaling on the ${\mathcal {H}_2}$ -norm can be separated in the design problem. We then consider optimization algorithms for updating the time-scale parameters and matrix weights in order to minimize network response to injected noise. Finally, we present an application to formation control for multivehicle systems.
How to hide a cosmological constant

Naive calculations in quantum field theory suggest that vacuum fluctuations should induce an enormous cosmological constant. What if these estimates are right? I argue that even a huge cosmological...
Defining Contact at the Atomic Scale

Contact area plays a central role in continuum theories of friction and adhesion, and there is growing interest in calculating it with atomic resolution. Molecular dynamics simulations are used to study definitions of contact area based on instantaneous and time-averaged forces or separations between atoms. Flat and spherical surfaces with different atomic geometries, adhesion, and temperatures are examined. In continuum theory, the fraction of two flat surfaces that is in contact rises sharply from zero to unity when a load is applied. This simple behavior is surprisingly difficult to reproduce with atomic scale definitions of contact. At typical temperatures, nonadhesive surfaces are held apart by a small fraction of atoms with large thermal fluctuations until the normal pressure is comparable to the ideal hardness. The contact area associated with atoms interacting at any instant rises linearly with load. Time averaging produces a monotonic increase in area with time interval that only converges to the sharp rise in continuum models for the special case of identical crystal surfaces. Except in this special case, the time-averaged contact area between adhesive surfaces also rises to full contact over a range of pressures comparable to the ideal hardness. Similar complications are encountered in defining contact areas for spherical tips. The fraction of atoms in contact rises linearly with local pressure, and the contact area based on time-averaged forces does not fit continuum theory. A simple harmonic mean-field theory provides a quantitative description of the simulation results and explains why the instantaneous forces on atoms are observed to have a universal exponential form. The results imply that continuum models of contact only apply to forces averaged over areas containing many atoms.
Measuring the Number of M Dwarfs per M Dwarf Using Kepler Eclipsing Binaries

We measure the binarity of detached M-dwarfs in the Kepler field with orbital periods in the range of 1-90 days. Kepler's photometric precision and nearly continuous monitoring of stellar targets over time baselines ranging from 3 months to 4 years make its detection efficiency for eclipsing binaries nearly complete over this period range and for all radius ratios. Our investigation employs a statistical framework akin to that used for inferring planetary occurrence rates from planetary transits. The obvious simplification is that eclipsing binaries have a vastly improved detection efficiency that is limited chiefly by their geometric probabilities to eclipse. For the M-dwarf sample observed by the Kepler Mission, the fractional incidence of eclipsing binaries implies that there are $0.11 ^{+0.02} _{-0.04}$ close stellar companions per apparently single M-dwarf. Our measured binarity is higher than previous inferences of the occurrence rate of close binaries via radial velocity techniques, at roughly the 2$\sigma$ level. This study represents the first use of eclipsing binary detections from a high quality transiting planet mission to infer binary statistics. Application of this statistical framework to the eclipsing binaries discovered by future transit surveys will establish better constraints on short-period M$+$M binary rate, as well as binarity measurements for stars of other spectral types.
Ergodicity of skew products over linearly recurrent IETs

We prove that the skew product over a linearly recurrent interval exchange transformation defined by almost any real-valued, mean-zero linear combination of characteristic functions of intervals is ergodic with respect to Lebesgue measure.
Single-shot three-dimensional imaging of dilute atomic clouds

Light field microscopy methods together with three-dimensional (3D) deconvolution can be used to obtain single-shot 3D images of atomic clouds. We demonstrate the method using a test setup that extracts 3D images from a fluorescent Rb87 atomic vapor.
Kinetic Simulations of the Lowest-order Unstable Mode of Relativistic Magnetostatic Equilibria

We present the results of particle-in-cell numerical pair plasma simulations of relativistic 2D magnetostatic equilibria known as the 'ABC' fields. In particular, we focus on the lowest-order unstable configuration consisting of two minima and two maxima of the magnetic vector potential. Breaking of the initial symmetry leads to exponential growth of the electric energy and to the formation of two current layers, which is consistent with the picture of 'X-point collapse' first described by Syrovatskii. Magnetic reconnection within the layers heats a fraction of particles to very high energies. After the saturation of the linear instability, the current layers are disrupted and the system evolves chaotically, diffusing the particle energies in a stochastic second-order Fermi process leading to the formation of power-law energy distributions. The power-law slopes harden with the increasing mean magnetization, but they are significantly softer than those produced in simulations initiated from Harris-type layers. The maximum particle energy is proportional to the mean magnetization, which is attributed partly to the increase of the effective electric field and partly to the increase of the acceleration time scale. We describe in detail the evolving structure of the dynamical current layers, and report on the conservation of magnetic helicity. These results can be applied to highly magnetized astrophysical environments, where ideal plasma instabilities trigger rapid magnetic dissipation with efficient particle acceleration and flares of high-energy radiation.
Ukaliq: Seeing Long-Term with Small, Precise Arctic Telescopes

Time-domain astrophysics benefits from extreme-latitude sites, which can combine intrinsically extended nighttime with good sky conditions. One such location is the Polar Environment Atmospheric Research Laboratory (PEARL), at 80° North latitude, on the northwestern edge of Ellesmere Island, Canada. Experience gained deploying seeing monitors there has been incorporated into an automated system called "Ukaliq" after the common arctic hare, which is also very well suited to its local environment. Even with modest aperture, high photometric reliability may be achieved using simple adaptive optics together with observing strategies that best fit the unique set of advantages available at PEARL: excellent image quality maintained during many clear, calm, dark periods of 100 hours or more. A potential multi-year search for gravitational microlensing of quasars with Ukaliq helps illustrate this niche in the era of large wide-field survey facilities.
Student Understanding of Rotational and Rolling Motion Concepts.

We investigated the common difficulties that students have with concepts related to rotational and rolling motion covered in the introductory physics courses. We compared the performance of calculus- and algebra-based introductory physics students with physics juniors who had learned rotational and rolling motion concepts in an intermediate level mechanics course. Interviews were conducted with six physics juniors and ten introductory students using demonstration-based tasks. We also administered free-response and multiple-choice questions to a large number of students enrolled in introductory physics courses, and interviewed six additional introductory students on the test questions (during the test design phase). All students showed similar difficulties regardless of their background, and higher mathematical sophistication did not seem to help acquire a deeper understanding. We found that some difficulties were due to related difficulties with linear motion, while others were tied specifically to the more intricate nature of rotational and rolling motion.
Non-relativistic holography from Horava gravity

Many non-relativistic Quantum Field Theories with conserved particle number share a common set of symmetries: time dependent spatial diffeomorphisms acting on the background metric and U(1) invariance acting on the background fields which couple to particle number. Here we use these symmetries to deduce a gravity dual for any such theory in terms of a non-relativistic theory of gravity, a variant of Hořava gravity. This duality allows the extension of holography to generic non-relativistic field theories. As Hořava gravity is presumed to be a consistent quantum theory, this duality also allows holography to move beyond the limit of a large number of colors, in principle. In the case when the field theory is conformally invariant, we prove that our proposal reproduces the form of the two point function demanded by this symmetry.
Engineering a Simplified 0-Bit Consistent Weighted Sampling

The Min-Hashing approach to sketching has become an important tool in data analysis, information retrial, and classification. To apply it to real-valued datasets, the ICWS algorithm has become a seminal approach that is widely used, and provides state-of-the-art performance for this problem space. However, ICWS suffers a computational burden as the sketch size K increases. We develop a new Simplified approach to the ICWS algorithm, that enables us to obtain over 20x speedups compared to the standard algorithm. The veracity of our approach is demonstrated empirically on multiple datasets and scenarios, showing that our new Simplified CWS obtains the same quality of results while being an order of magnitude faster.
Influence of broken-pair excitations on the exact pair wavefunction

ABSTRACTDoubly occupied configuration interaction (DOCI), the exact diagonalisation of the Hamiltonian in the paired (seniority zero) sector of the Hilbert space, is a combinatorial cost wave function that can be very efficiently approximated by pair coupled cluster doubles (pCCD) at mean-field computational cost. As such, it is a very interesting candidate as a starting point for building the full configuration interaction (FCI) ground state eigenfunction belonging to all (not just paired) seniority sectors. The true seniority zero sector of FCI (referred to here as FCI0) includes the effect of coupling between all seniority sectors rather than just seniority zero, and is, in principle, different from DOCI. We here study the accuracy with which DOCI approximates FCI0. Using a set of small Hubbard lattices, where FCI is possible, we show that DOCI ∼ FCI0 under weak correlation. However, in the strong correlation regime, the nature of the FCI0 wavefunction can change significantly, rendering DOCI and pCCD ...
A Boltzmann Machine Implementation for the D-Wave

The D-Wave is an adiabatic quantum computer. It is an understatement to say that it is not a traditional computer. It can be viewed as a computational accelerator or more precisely a computational oracle, where one asks it a relevant question and it returns a useful answer. The question is how do you ask a relevant question and how do you use the answer it returns. This paper addresses these issues in a way that is pertinent to machine learning. A Boltzmann machine is implemented with the D-Wave since the D-Wave is merely a hardware instantiation of a partially connected Boltzmann machine. This paper presents a prototype implementation of a 3-layered neural network where the D-Wave is used as the middle (hidden) layer of the neural network. This paper also explains how the D-Wave can be utilized in a multi-layer neural network (more than 3 layers) and one in which each layer may be multiple times the size of the D-Wave being used.
An Exploration of Heating Mechanisms in a Supra-arcade Plasma Sheet Formed after a Coronal Mass Ejection

We perform a detailed analysis of the thermal structure of the region above the post-eruption arcade for a flare that occurred on 2011 October 22. During this event, a sheet of hot plasma is visible above the flare loops in the 131 A bandpass of the Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory. Supra-arcade downflows (SADs) are observed traveling sunward through the post-eruption plasma sheet. We calculate differential emission measures using the AIA data and derive an emission measure weighted average temperature in the supra-arcade region. In areas where many SADs occur, the temperature of the supra-arcade plasma tends to increase, while in areas where no SADs are observed, the temperature tends to decrease. We calculate the plane-of-sky velocities in the supra-arcade plasma and use them to determine the potential heating due to adiabatic compression and viscous heating. Of the 13 SADs studied, 10 have noticeable signatures in both the adiabatic and the viscous terms. The adiabatic heating due to compression of plasma in front of the SADs is on the order of 0.1–0.2 MK/s, which is similar in magnitude to the estimated conductive cooling rate. This result supports the notion that SADs contribute locally to the heating of plasma in the supra-arcade region. We also find that in the region without SADs, the plasma cools at a rate that is slower than the estimated conductive cooling, indicating that additional heating mechanisms may act globally to keep the plasma temperature high.