cssi/SciSciGPT-SciSciNet huggingface dataset:
A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning

Real-world autonomous systems often employ probabilistic predictive models of human behavior during planning to reason about their future motion. Since accurately modeling human behavior a priori is challenging, such models are often parameterized, enabling the robot to adapt predictions based on observations by maintaining a distribution over the model parameters. Although this enables data and priors to improve the human model, observation models are difficult to specify and priors may be incorrect, leading to erroneous state predictions that can degrade the safety of the robot motion plan. In this work, we seek to design a predictor which is more robust to misspecified models and priors, but can still leverage human behavioral data online to reduce conservatism in a safe way. To do this, we cast human motion prediction as a Hamilton-Jacobi reachability problem in the joint state space of the human and the belief over the model parameters. We construct a new continuous-time dynamical system, where the inputs are the observations of human behavior, and the dynamics include how the belief over the model parameters change. The results of this reachability computation enable us to both analyze the effect of incorrect priors on future predictions in continuous state and time, as well as to make predictions of the human state in the future. We compare our approach to the worst-case forward reachable set and a stochastic predictor which uses Bayesian inference and produces full future state distributions. Our comparisons in simulation and in hardware demonstrate how our framework can enable robust planning while not being overly conservative, even when the human model is inaccurate. Videos of our experiments can be found at the project website1.
Adaptive Federated Learning With Gradient Compression in Uplink NOMA

Federated learning (FL) is an emerging machine learning technique that aggregates model attributes from a large number of distributed devices. Compared with the traditional centralized machine learning, FL uploads only model parameters rather than raw data during the learning process. Although distributed computing can lower down the information that needs to be uploaded, model updates in FL can still experience performance bottleneck, especially when training deep learning models in distributed networks. In this work, we investigate the performance of FL update at mobile edge devices that are connected to the parameter server (PS) with wireless links. Considering the spectrum limitation on the wireless fading channels, we further exploit non-orthogonal multiple access (NOMA) together with adaptive gradient quantization and sparsification to facilitate efficient uplink FL updates. Simulation results show that the proposed scheme can significantly reduce FL aggregation latency but still achieve a comparable accuracy with benchmark schemes.
Hardware implementation of Bayesian network building blocks with stochastic spintronic devices

Bayesian networks are powerful statistical models to understand causal relationships in real-world probabilistic problems such as diagnosis, forecasting, computer vision, etc. For systems that involve complex causal dependencies among many variables, the complexity of the associated Bayesian networks become computationally intractable. As a result, direct hardware implementation of these networks is one promising approach to reducing power consumption and execution time. However, the few hardware implementations of Bayesian networks presented in literature rely on deterministic CMOS devices that are not efficient in representing the stochastic variables in a Bayesian network that encode the probability of occurrence of the associated event. This work presents an experimental demonstration of a Bayesian network building block implemented with inherently stochastic spintronic devices based on the natural physics of nanomagnets. These devices are based on nanomagnets with perpendicular magnetic anisotropy, initialized to their hard axes by the spin orbit torque from a heavy metal under-layer utilizing the giant spin Hall effect, enabling stochastic behavior. We construct an electrically interconnected network of two stochastic devices and manipulate the correlations between their states by changing connection weights and biases. By mapping given conditional probability tables to the circuit hardware, we demonstrate that any two node Bayesian networks can be implemented by our stochastic network. We then present the stochastic simulation of an example case of a four node Bayesian network using our proposed device, with parameters taken from the experiment. We view this work as a first step towards the large scale hardware implementation of Bayesian networks.
mmRAPID: Machine Learning assisted Noncoherent Compressive Millimeter-Wave Beam Alignment

Millimeter-wave communication has the potential to deliver orders of magnitude increases in mobile data rates. A key design challenge is to enable rapid beam alignment with phased arrays. Traditional millimeter-wave systems require a high beam alignment overhead, typically an exhaustive beam sweep, to find the beam direction with the highest beamforming gain. Compressive sensing is a promising framework to accelerate beam alignment. However, model mismatch from practical array hardware impairments poses a challenge to its implementation. In this work, we introduce a neural network assisted compressive beam alignment method that uses noncoherent received signal strength measured by a small number of pseudorandom sounding beams to infer the optimal beam steering direction. We experimentally showcase our proposed approach with a 60GHz 36-element phased array in a suburban line-of-sight environment. The results show that our approach achieves post alignment beamforming gain within 1dB margin compared to an exhaustive search with 90.2% overhead reduction. Compared to purely model-based noncoherent compressive beam alignment, our method has 75% overhead reduction.
PopInf: An Approach for Reproducibly Visualizing and Assigning Population Affiliation in Genomic Samples of Uncertain Origin

Germline genetic variation contributes to cancer etiology, but self-reported race is not always consistent with genetic ancestry, and samples may not have identifying ancestry information. In this ...
Gender (Im)balance in Citation Practices in Cognitive Neuroscience

In the field of neuroscience, despite the fact that the proportion of peer-reviewed publications authored by women has increased in recent decades, the proportion of citations of women-led publications has not seen a commensurate increase: In five broad-scope journals, citations of papers first- and/or last-authored by women have been shown to be fewer than would be expected if gender was not a factor in citation decisions [Dworkin, J. D., Linn, K. A., Teich, E. G., Zurn, P., Shinohara, R. T., & Bassett, D. S. The extent and drivers of gender imbalance in neuroscience reference lists. Nature Neuroscience, 23, 918-926, 2020]. Given the important implications that such underrepresentation may have on the careers of women researchers, it is important to determine whether this same trend is true in subdisciplines of the field, where interventions might be more targeted. Here, we report the results of an extension of the analyses carried out by Dworkin et al. (2020) to citation patterns in the Journal of Cognitive Neuroscience. The results indicate that the underrepresentation of women-led publications in reference sections is also characteristic of papers published in Journal of Cognitive Neuroscience over the past decade. Furthermore, this pattern of citation imbalances is present regardless of author gender, implicating systemic factors. These results contribute to the growing body of evidence that intentional action is needed to address inequities in the way that we carry out and communicate our science.
A generalized Boltzmann kinetic theory for strongly magnetized plasmas with application to friction

Coulomb collisions in plasmas are typically modeled using the Boltzmann collision operator, or its variants, which apply to weakly magnetized plasmas in which the typical gyroradius of particles significantly exceeds the Debye length. Conversely, O'Neil has developed a kinetic theory to treat plasmas that are so strongly magnetized that the typical gyroradius of particles is much smaller than the distance of the closest approach in a binary collision. Here, we develop a generalized collision operator that applies across the full range of magnetization strength. Since there is no closed-form solution for the scattering cross section when plasma is strongly magnetized, the input to the collision operator is obtained by numerically calculating particle trajectories. To demonstrate novel physics associated with strong magnetization, it is used to compute the friction force on a massive test charge. In addition to the traditional stopping power component, this is found to exhibit a transverse component that is perpendicular to both the velocity and Lorentz force vectors in the strongly magnetized regime, as was predicted recently using linear response theory. Good agreement is found between the collision theory and linear response theory in the regime in which both apply, but the new collision theory also applies to stronger magnetization strength regimes than the linear response theory is expected to apply in.
On spin chains and field theories

We point out that the existence of global symmetries in a fleld theory is not an essential ingredient in its relation with an integrable model. We describe an obvious construction which, given an integrable spin chain, yields a fleld theory whose 1-loop scale transformations are generated by the spin chain hamiltonian. We also identify a necessary condition for a given fleld theory to be related to an integrable spin chain. As an example, we describe an anisotropic and parity-breaking generalization of the XXZ Heisenberg spin chain and its associated fleld theory. The system has no nonabelian global symmetries and generally does not admit a supersymmetric extension without the intro- duction of more propagating bosonic flelds. For the case of a 2-state chain we flnd the spectrum and the eigenstates. For certain values of its coupling constants the fleld theory associated to this general type of chain is the bosonic sector of the q-deformation ofN = 4 SYM theory.
INFERRING GRAVITATIONAL POTENTIALS FROM MASS DENSITIES IN CLUSTER-SIZED HALOS

We use N-body simulations to quantify how the escape velocity in cluster-sized halos maps to the gravitational potential in a ΛCDM universe. Using spherical density-potential pairs and the Poisson equation, we find that the matter density inferred gravitational potential profile predicts the escape velocity profile to within a few percent accuracy for group and cluster-sized halos (10 M , with respect to the critical density). The accuracy holds from just outside the core to beyond the virial radius. We show the importance of explicitly incorporating a cosmological constant when inferring the potential from the Poisson equation. We consider three density models and find that the Einasto and Gamma profiles provide a better joint estimate of the density and potential profiles than the Navarro, Frenk, and White profile, which fails to accurately represent the escape velocity. For individual halos, the 1σ scatter between the measured escape velocity and the density-inferred potential profile is small (<5%). Finally, while the sub-halos show 15% biases in their representation of the particle velocity dispersion profile, the sub-halo escape velocity profile matches the dark matter escape velocity profile to high accuracy with no evidence of velocity bias outside 0.4r 200.
High-temperature superconductivity in alkaline and rare earth polyhydrides at high pressure: A theoretical perspective.

The theoretical exploration of the phase diagrams of binary hydrides under pressure using ab initio crystal structure prediction techniques coupled with first principles calculations has led to the in silico discovery of numerous novel superconducting materials. This Perspective focuses on the alkaline earth and rare earth polyhydrides whose superconducting critical temperature, Tc, was predicted to be above the boiling point of liquid nitrogen. After providing a brief overview of the computational protocol used to predict the structures of stable and metastable hydrides under pressure, we outline the equations that can be employed to estimate Tc. The systems with a high Tc can be classified according to the motifs found in their hydrogenic lattices. The highest Tcs are found for cages that are reminiscent of clathrates and the lowest for systems that contain atomic and molecular hydrogen. A wide variety of hydrogenic motifs including 1- and 2-dimensional lattices, as well as H10δ− molecular units comprising fused H5δ− pentagons, are present in phases with intermediate Tcs. Some of these phases are predicted to be superconducting at room temperature. Some may have recently been synthesized in diamond anvil cells.
A convergence criterion for the solutions of nonlinear difference equations and dynamical systems

AbstractWe show that the solutions of nonlinear higher order difference equations may have convergent subsequences, even when the solution as a whole does not converge, if the defining function sequence is suitably bounded near the origin. The delay size and pattern in the higher order equation play an essential role in determining which subsequences of its solutions converge. We then show that this method can be extended to planar systems and discuss applications to discrete dynamical systems that have been used in biological population models.
Geometric Langlands in Prime Characteristic

Let G be a semi-simple algebraic group over an algebraically closed field k, whose characteristic is positive and does not divide the order of the Weyl group of G, and let Ğ be its Langlands dual group over k. Let C be a smooth projective curve over k of genus at least two. Denote by Bun_G the moduli stack of G-bundles on C and LocSys_Ğ the moduli stack of Ğ-local systems on C. Let D_(Bun_G) be the sheaf of crystalline differential operators on Bun_G. In this paper we construct an equivalence between the bounded derived category D^b (QCoh(LocSys^0_Ğ)) of quasi-coherent sheaves on some open subset LocSys^0_Ğ ⊂ LocSys_Ğ and bounded derived category D^b (D^0_(Bun_G) -mod) of modules over some localization D^0_(Bun_G) of D_(Bun_G). This generalizes the work of Bezrukavnikov and Braverman in the GL_n case.
Statistical Thermodynamics of Crystal Plasticity

This article is written in memory of Pierre Hohenberg with appreciation for his deep commitment to the basic principles of theoretical physics. I summarize recent developments in the theory of dislocation-enabled deformation of crystalline solids. This topic is especially appropriate for the Journal of Statistical Physics because materials scientists, for decades, have asserted that statistical thermodynamics is not applicable to dislocations. By use of simple, first-principles analyses and comparisons with experimental data, I argue that these people have been wrong, and that this field should now be revitalized because of its wide-ranging intellectual and technological importance.
Time evolution of cascade decay

We study non-perturbatively the time evolution of cascade decay for generic fields and obtain the time dependence of amplitudes and populations for the resonant and final states. We analyze in detail the different time scales and the manifestation of unitary time evolution in the dynamics of production and decay of resonant intermediate and final states. The probability of occupation (population) ‘flows’ as a function of time from the initial to the final states. When the decay width of the parent particle is much larger than that of the intermediate resonant state there is a ‘bottleneck’ in the flow, the population of resonant states builds up to a maximum at nearly saturating unitarity and decays to the final state on the longer time scale . As a consequence of the wide separation of time scales in this case the cascade decay can be interpreted as evolving sequentially . In the opposite limit the population of resonances () does not build up substantially and the cascade decay proceeds almost directly from the initial parent to the final state without resulting in a large amplitude of the resonant state. An alternative but equivalent non-perturbative method useful in cosmology is presented. Possible phenomenological implications for heavy sterile neutrinos as resonant states and consequences of quantum entanglement and correlations in the final state are discussed.
What is the scale of supersymmetry breaking

For a long time, it has been widely assumed that if the underlying laws of nature are supersymmetric, super-symmetry is broken at a scale intermediate between the weak scale and the Planck mass. The construction of realistic models of dynamical supersymmetry breaking in which supersymmetry is broken at a much lower scale, as well as a growing appreciation of the supersymmetric flavor problem has reopened this question. After reviewing some ideas for understanding the microscopic origin of the soft breaking parameters in the context of string theory, I turn to low energy breaking. Independent of the details of the underlying theory, events with photons and missing energy, like the CDF e+e−γγ/ET event, are likely signals of low energy breaking. I briefly review the predictions of the simplest model of low energy supersymmetry breaking for the soft breaking parameters (MGM), and then ask what sorts of generalizations are possible. It turns out that if all couplings are weak, there are only a limited number of ways to modify the model.
GHOST-FREE HIGHER DERIVATIVE QUANTUM GRAVITY, THE HIERARCHY AND THE COSMOLOGICAL CONSTANT PROBLEMS

We propose a new solution to problems of the hierarchy and smallness of the cosmological constant using the TeV scale of the Standard Model in a new framework of the higher-order gravity.
Contrast of LiFeAs with isostructural, isoelectronic, and non-superconducting MgFeGe

Stoichiometric LiFeAs at ambient pressure is an 18 K superconductor while isostructural, isoelectronic MgFeGe does not superconduct, despite their extremely similar electronic structures. To investigate possible sources of this distinctively different superconducting behavior, we quantify the differences using first principles density functional theory. Total Fe \(3d\) occupations are identical, with individual \(3d\) orbital occupations differing by no more than 0.015. However, a redistribution of bands just above the Fermi level \(\varepsilon_{\text{F}}\) provides an important distinction, with more Fe-derived states within 0.5 eV of the Fermi level and a higher \(N(\varepsilon_{\text{F}})\) in MgFeGe. For many mechanisms these features would enhance the tendency toward superconductivity by providing more Cooper pairs (in MgFeGe), but the tendency toward magnetic instability might be more important. Two of the five Fermi surfaces differ between LiFeAs and MgFeGe, but still lead to similar \(q\)-dependen...
SSCR: Iterative Language-Based Image Editing via Self-Supervised Counterfactual Reasoning

Iterative Language-Based Image Editing (ILBIE) tasks follow iterative instructions to edit images step by step. Data scarcity is a significant issue for ILBIE as it is challenging to collect large-scale examples of images before and after instruction-based changes. Yet, humans still accomplish these editing tasks even when presented with an unfamiliar image-instruction pair. Such ability results from counterfactual thinking, the ability to think about possible alternatives to events that have happened already. In this paper, we introduce a Self-Supervised Counterfactual Reasoning (SSCR) framework that incorporates counterfactual thinking to overcome data scarcity. SSCR allows the model to consider out-of-distribution instructions paired with previous images. With the help of cross-task consistency (CTC), we train these counterfactual instructions in a self-supervised scenario. Extensive results show that SSCR improves the correctness of ILBIE in terms of both object identity and position, establishing a new state of the art (SOTA) on two IBLIE datasets (i-CLEVR and CoDraw). Even with only 50\% of the training data, SSCR achieves a comparable result to using complete data.
Mapping the conformations of biological assemblies

Mapping conformational heterogeneity of macromolecules presents a formidable challenge to x-ray crystallography and cryo-electron microscopy, which often presume its absence. This has severely limited our knowledge of the conformations assumed by biological systems and their role in biological function, even though they are known to be important. We propose a new approach to determining to high resolution the three-dimensional conformations of biological entities such as molecules, macromolecular assemblies and ultimately cells with existing and emerging experimental techniques. This approach may also enable one to circumvent current limits due to radiation damage and solution purification.
Optimal Control of Vehicular Formations With Nearest Neighbor Interactions

We consider the design of optimal localized feedback gains for one-dimensional formations in which vehicles only use information from their immediate neighbors. The control objective is to enhance coherence of the formation by making it behave like a rigid lattice. For the single-integrator model with symmetric gains, we establish convexity, implying that the globally optimal controller can be computed efficiently. We also identify a class of convex problems for double-integrators by restricting the controller to symmetric position and uniform diagonal velocity gains. To obtain the optimal non-symmetric gains for both the single- and the double-integrator models, we solve a parameterized family of optimal control problems ranging from an easily solvable problem to the problem of interest as the underlying parameter increases. When this parameter is kept small, we employ perturbation analysis to decouple the matrix equations that result from the optimality conditions, thereby rendering the unique optimal feedback gain. This solution is used to initialize a homotopy-based Newton's method to find the optimal localized gain. To investigate the performance of localized controllers, we examine how the coherence of large-scale stochastically forced formations scales with the number of vehicles. We establish several explicit scaling relationships and show that the best performance is achieved by a localized controller that is both non-symmetric and spatially-varying.
Sequences of open Riemannian manifolds with boundary

We consider sequences of open Riemannian manifolds with boundary that have no regularity conditions on the boundary. To define a reasonable notion of a limit of such a sequence, we examine -inner regions, that avoid the boundary by a distance . We prove Gromov‐Hausdorff compactness theorems for sequences of these -inner regions. We then build “glued limit spaces” out of the Gromov‐Hausdorff limits of -inner regions and study the properties of these glued limit spaces. Our main applications assume the sequence is noncollapsing and has nonnegative Ricci curvature. We include open questions.
THE ROLE OF DIAGONALIZATION WITHIN A DIAGONALIZATION/MONTE CARLO SCHEME

We discuss a method called quasi-sparse eigenvector diagonalization which finds the most important basis vectors of the low energy eigenstates of a quantum Hamiltonian. It can operate using any basis, either orthogonal or non-orthogonal, and any sparse Hamiltonian, either Hermitian, non-Hermitian, finite-dimensional, or infinite-dimensional. The method is part of a new computational approach which combines both diagonalization and Monte Carlo techniques.
Constraints on vacuum energy from structure formation and Nucleosynthesis

This paper derives an upper limit on the density $\rho_{\scriptstyle\Lambda}$ of dark energy based on the requirement that cosmological structure forms before being frozen out by the eventual acceleration of the universe. By allowing for variations in both the cosmological parameters and the strength of gravity, the resulting constraint is a generalization of previous limits. The specific parameters under consideration include the amplitude $Q$ of the primordial density fluctuations, the Planck mass $M_{\rm pl}$, the baryon-to-photon ratio $\eta$, and the density ratio $\Omega_M/\Omega_b$. In addition to structure formation, we use considerations from stellar structure and Big Bang Nucleosynthesis (BBN) to constrain these quantities. The resulting upper limit on the dimensionless density of dark energy becomes $\rho_{\scriptstyle\Lambda}/M_{\rm pl}^4<10^{-90}$, which is $\sim30$ orders of magnitude larger than the value in our universe $\rho_{\scriptstyle\Lambda}/M_{\rm pl}^4\sim10^{-120}$. This new limit is much less restrictive than previous constraints because additional parameters are allowed to vary. With these generalizations, a much wider range of universes can develop cosmic structure and support observers. To constrain the constituent parameters, new BBN calculations are carried out in the regime where $\eta$ and $G=M_{\rm pl}^{-2}$ are much larger than in our universe. If the BBN epoch were to process all of the protons into heavier elements, no hydrogen would be left behind to make water, and the universe would not be viable. However, our results show that some hydrogen is always left over, even under conditions of extremely large $\eta$ and $G$, so that a wide range of alternate universes are potentially habitable.
G-Mode Excitation During the Pre-explosive Simmering of Type Ia Supernovae

Prior to the explosive burning of a white dwarf (WD) that makes a Type Ia supernova (SN Ia), the star "simmers" for ~10^3 yr in a convecting, carbon-burning region. I estimate the excitation of g-modes by convection during this phase and explore their possible effect on the WD. As these modes propagate from the core of the WD toward its surface, their amplitudes grow with decreasing density. Once the modes reach nonlinear amplitudes, they break and deposit their energy into a shell of mass ~10^(–4) M_⊙. This raises the surface temperature by ≈4 × 10^8 K, which is sufficient to ignite a layer of helium, as is expected to exist for some SN Ia scenarios. This predominantly synthesizes ^(40)Ca, but some amount of ^(28)Si, ^(32)S, and ^(44)Ti may also be present. These ashes are expanded out with the subsequent explosion up to velocities of ~20, 000 km s^(–1), which may explain the high velocity features (HVFs) seen in many SNe Ia. The appearance of HVFs would therefore be a useful discriminant for determining between progenitors, since a flammable helium-rich layer will not be present for accretion from a C/O WD as in a merger scenario. I also discuss the implications of ^(44)Ti production.
The gravitational wave signal from core-collapse supernovae

We study gravitational waves (GWs) from a set of two-dimensional multi-group neutrino radiation hydrodynamic simulations of core-collapse supernovae (CCSNe). Our goal is to systematize the current knowledge about the post-bounce CCSN GW signal and recognize the templatable features that could be used by the ground-based laser interferometers. We demonstrate that starting from ~400ms after core bounce the dominant GW signal represents the fundamental quadrupole (l=2) oscillation mode (f-mode) of the proto-neutron star (PNS), which can be accurately reproduced by a linear perturbation analysis of the angle-averaged PNS profile. Before that, in the time interval between ~200 and ~400ms after bounce, the dominant mode has two radial nodes and represents a g-mode. We associate the high-frequency noise in the GW spectrograms above the main signal with p-modes, while below the dominant frequency there is a region with very little power. The collection of models presented here summarizes the dependence of the CCSN GW signal on the progenitor mass, equation of state, many-body corrections to the neutrino opacity, and rotation. Weak dependence of the dominant GW frequency on the progenitor mass motivates us to provide a simple fit for it as a function of time, which can be used as a prior when looking for CCSN candidates in the LIGO data.
Physics of Coevolution of Galaxies and Supermassive Black Holes

A new physically based model for coevolution of galaxies and supermassive black holes (SMBHs) is presented. The evolutionary track starts with an event that triggers a significant starburst in the central region of a galaxy. In this model, the main SMBH growth takes place in the post-starburst phase, fueled by recycled gas from inner bulge stars in a self-regulated fashion on a timescale that is substantially longer than 100 Myr and at a diminishing Eddington ratio with time. We argue that the SMBH cannot gorge itself during the starburst phase, despite the abundant supply of cold gas, because star formation (SF) is a preferred mode of gas consumption over accretion to the central SMBH in such an environment. We also show that feedback from SF is at least as strong as that from an active galactic nucleus (AGN); thus, if SF is in need of being quenched, AGN feedback generally does not play the primary role. The predicted relation between SMBH mass and bulge mass/velocity dispersion is consistent with observations. A clear prediction is that early-type galaxy hosts of high-Eddington-rate AGNs are expected to be light blue to green in optical color, gradually evolving to the red sequences with decreasing AGN luminosity. A suite of falsifiable predictions and implications with respect to relationships between various types of galaxies, AGNs, and others are made. For those where comparisons to extant observations are possible, the model appears to be in good standing.
Viscosity Prescription for Gravitationally Unstable Accretion Disks

Gravitationally unstable accretion disks emerge in a variety of astrophysical contexts—giant planet formation, FU Orioni outbursts, feeding of active galactic nuclei, and the origin of Pop III stars. When a gravitationally unstable disk is unable to cool rapidly, it settles into a quasi-stationary, fluctuating gravitoturbulent state, in which its Toomre Q remains close to a constant value . Here we develop an analytical formalism describing the evolution of such a disk, which is based on the assumptions of and local thermal equilibrium. Our approach works in the presence of additional sources of angular momentum transport (e.g., MRI), as well as external irradiation. Thermal balance dictates a unique value of the gravitoturbulent stress driving disk evolution, which is a function of the local surface density and angular frequency. We compare this approach with other commonly used gravitoturbulent viscosity prescriptions, which specify the explicit dependence of stress on Toomre Q in an ad hoc fashion, and identify the ones that provide consistent results. We nevertheless argue that our approach is more flexible, robust, and straightforward and should be given preference in applications. We illustrate this with a couple of analytical calculations—locations of the snow line and of the outer edge of the dead zone in a gravitoturbulent protoplanetary disk—which clearly show the simplicity and versatility of the approach.
Visualizing the Flow of Discourse with a Concept Ontology

Understanding and visualizing human discourse has long being a challenging task. Although recent work on argument mining have shown success in classifying the role of various sentences, the task of recognizing concepts and understanding the ways in which they are discussed remains challenging. Given an email thread or a transcript of a group discussion, our task is to extract the relevant concepts and understand how they are referenced and re-referenced throughout the discussion. In the present work, we present a preliminary approach for extracting and visualizing group discourse by adapting Wikipedia's category hierarchy to be an external concept ontology. From a user study, we found that our method achieved better results than 4 strong alternative approaches, and we illustrate our visualization method based on the extracted discourse flows.
Single charge sensing and transport in double quantum dots fabricated from commercially grown Si/SiGe heterostructures

We perform quantum Hall measurements on three types of commercially available modulation-doped Si/SiGe heterostructures to determine their suitability for depletion gate defined quantum dot devices. By adjusting the growth parameters, we are able to achieve electron gases with charge densities 1–3 × 1011/cm2 and mobilities in excess of 100 000 cm2/Vs. Double quantum dot devices fabricated on these heterostructures show clear evidence of single charge transitions as measured in dc transport and charge sensing and exhibit electron temperatures of 100 mK in the single quantum dot regime.
Optimal Vehicle Dynamics and Powertrain Control for Connected and Automated Vehicles

The implementation of connected and automated vehicle technologies enables opportunities for a novel computational framework for real-time control actions aimed at optimizing energy consumption and associated benefits. In this paper, we present a two-level control architecture for a connected and automated plug-in hybrid electric vehicle to optimize simultaneously its speed profile and powertrain efficiency. We evaluate the proposed architecture through simulation in a network of vehicles.
Single-Photon Pulse Induced Transient Entanglement Force

We show that a single photon pulse (SPP) incident on two interacting two-level atoms induces a transient entanglement force between them. After absorption of a multi-mode Fock state pulse, the time-dependent atomic interaction mediated by the vacuum fluctuations changes from the van der Waals interaction to the resonant dipole-dipole interaction (RDDI). We explicitly show that the RDDI force induced by the SPP fundamentally arises from the two-body transient entanglement between the atoms. This SPP induced entanglement force can be continuously tuned from being repulsive to attractive by varying the polarization of the pulse. We further demonstrate that the entanglement force can be enhanced by more than three orders of magnitude if the atomic interactions are mediated by graphene plasmons. These results demonstrate the potential of shaped SPPs as a powerful tool to manipulate this entanglement force and also provides a new approach to witness transient atom-atom entanglement.
MAGNESIUM-RICH EJECTA IN THE SNR G284.3–1.8 AROUND THE HIGH-MASS GAMMA-RAY BINARY 1FGL J1018.6–5856

We present results from two Chandra observations of the 16.6 day X-ray/γ-ray high-mass binary 1FGL J1018.6–5856 located at the center of the supernova remnant (SNR) G284.3–1.8. The binary spectra, separated by 0.25 in binary phase, are fit with an absorbed power-law model with for both observations (the flux during the second observation is a factor of 1.7 smaller). In the high-resolution ACIS-I image we found a hint of extended emission –3″ southeast of the binary, significant at the level. Binary evolution codes reproduce the system’s observed properties with two massive stars with an initial 18 day period, undergoing mass transfer and leaving behind a heavy neutron star. The initial mass of the progenitor star in this scenario is 27 ± 4 . Chandra and XMM-Newton images of the remnant show it has a relatively low X-ray surface brightness. The two brightest regions of extended X-ray emission, with luminosities erg s−1 for d = 5 kpc, lie in the northern and western portions and show significantly different spectra. The northern patch is consistent with shocked ISM, with a low temperature and long ionization timescale. However, the western patch is dominated by ejecta, and shows significantly enhanced Mg content relative to other ejecta products. The abundance ratios inferred resemble those from the Large Magellanic Cloud remnant N49B. To our knowledge, this is only the second case of such Mg-rich ejecta found in an SNR. Nucleosynthesis models for core-collapse supernovae predict Mg-rich ejecta from very massive progenitors of .
COVARIANT BALANCE LAWS IN CONTINUA WITH MICROSTRUCTURE

The purpose of this paper is to extend the Green-Naghdi-Rivlin balance of energy method to continua with microstructure. The key idea is to replace the group of Galilean transformations with the group of diffeomorphisms of the ambient space. A key advantage is that one obtains in a natural way all the needed balance laws on both the macro and micro levels along with two Doyle-Erickson formulas. We model a structured continuum as a triplet of Riemannian manifolds: a material manifold, the ambient space manifold of material particles and a director field manifold. The Green-Naghdi-Rivlin theorem and its extensions for structured continua are critically reviewed. We show that when the ambient space is Euclidean and when the microstructure manifold is the tangent space of the ambient space manifold, postulating a single balance of energy law and its invariance under time-dependent isometries of the ambient space, one obtains conservation of mass, balances of linear and angular momenta but not a separate balance of linear momentum. We develop a covariant elasticity theory for structured continua by postulating that energy balance is invariant under time-dependent spatial diffeomorphisms of the ambient space, which in this case is the product of two Riemannian manifolds. We then introduce two types of constrained continua in which microstructure manifold is linked to the reference and ambient space manifolds. In the case when at every material point, the microstructure manifold is the tangent space of the ambient space manifold at the image of the material point, we show that the assumption of covariance leads to balances of linear and angular momenta with contributions from both forces and micro-forces along with two Doyle-Ericksen formulas. We show that generalized covariance leads to two balances of linear momentum and a single coupled balance of angular momentum. Using this theory, we covariantly obtain the balance laws for two specific examples, namely elastic solids with distributed voids and mixtures. Finally, the Lagrangian field theory of structured elasticity is revisited and a connection is made between covariance and Noether's theorem.
Orientation-Dependent Handedness and Chiral Design

The handedness of an object has always been a binary concept: either left handed or right handed. Scientists now show that quantifying handedness as direction-dependent properties actually makes fundamental physical sense and can guide both our understanding of known handedness phenomena and design of materials with novel handed-response properties.
Topological Criteria for Schlichtness

We give two sufficient criteria for schlichtness of envelopes of holomorphy in terms of topology. These are weakened converses of results of Kerner and Royden. Our first criterion generalizes a result of Hammond in dimension 2. Along the way, we also prove a generalization of Royden’s theorem.
The Bohr superconductor

Superconductors have often been described as "giant atoms". The simplest description of atoms that heralded their quantum understanding was proposed by Bohr in 1913. The Bohr atom starts from some simple assumptions and deduces that the angular momentum of the electron in Bohr orbits is quantized in integer units of . This remarkable result, which does not appear to be implicit in the assumptions of the model, can be interpreted as a "theoretical proof" of the model's validity to describe physical reality at some level. Similarly we point out here that from some simple assumptions it can be deduced that electrons in superconductors reside in mesoscopic orbits with orbital angular momentum . This implies that both in superconductors and in ferromagnets the long-range order results from elementary units of identical angular momentum. Similarly to the case of the Bohr atom we propose that this remarkable result is compelling evidence that this physics, which is not part of conventional BCS theory, describes physical reality at some level and heralds a qualitatively new understanding of superconductors.
Stellar Spin–Orbit Alignment for Kepler-9, a Multi-transiting Planetary System with Two Outer Planets Near 2:1 Resonance

We present spectroscopic measurements of the Rossiter–McLaughlin effect for the planet b of the Kepler-9 multi-transiting planetary system. The resulting sky-projected spin–orbit angle is λ = −13° ± 16°, which favors an aligned system and strongly disfavors highly misaligned, polar, and retrograde orbits. Including Kepler-9, there are now a total of four Rossiter–McLaughlin effect measurements for multiplanet systems, all of which are consistent with spin–orbit alignment.
Emergence of the Born rule in quantum optics

The Born rule provides a fundamental connection between theory and observation in quantum mechanics, yet its origin remains a mystery. We consider this problem within the context of quantum optics using only classical physics and the assumption of a quantum electrodynamic vacuum that is real rather than virtual. The connection to observation is made via classical intensity threshold detectors that are used as a simple, deterministic model of photon detection. By following standard experimental conventions of data analysis on discrete detection events, we show that this model is capable of reproducing several observed phenomena thought to be uniquely quantum in nature, thus providing greater elucidation of the quantum-classical boundary.
Query Complexity of Sampling and Small Geometric Partitions

In this paper we study the following problem: Discrete partitioning problem (DPP): Let $\mathbb{F}_q P^n$ denote the $n$-dimensional finite projective space over $\mathbb{F}_q$. For positive integer $k \leq n$, let $\{ A^i\}_{i=1}^N$ be a partition of $(\mathbb{F}_q P^n)^k$ such that (1) for all $i \leq N$, $A^i = \prod_{j=1}^k A^i_j$ (partition into product sets), (2) for all $i \leq N$, there is a $(k-1)$-dimensional subspace $L^i \subseteq \mathbb{F}_q P^n$ such that $A^i \subseteq (L^i)^k$. What is the minimum value of $N$ as a function of $q,n,k$? We will be mainly interested in the case $k=n$.
Measurement of the Lorentz-FitzGerald body contraction

A complete foundational discussion of acceleration in the context of Special Relativity (SR) is presented. Acceleration allows the measurement of a Lorentz-FitzGerald body contraction created. It is argued that in the back scattering of a probing laser beam from a relativistic flying electron cloud mirror generated by an ultra-intense laser pulse, a first measurement of a Lorentz-FitzGerald body contraction is feasible.
The generalized Chaplygin-Jacobi gas

The present paper is devoted to find a new generalization of the generalized Chaplygin gas. Therefore, starting from the Hubble parameter associated to the Chaplygin scalar field and using some elliptic identities, the elliptic generalization is straightforward. Thus, all relevant quantities that drive inflation are calculated exactly. Finally, using the measurement on inflation from the Planck 2015 results, observational constraints on the parameters are given.
Propagator of a Charged Particle with a Spin in Uniform Magnetic and Perpendicular Electric Fields

We construct an explicit solution of the Cauchy initial value problem for the time-dependent Schrodinger equation for a charged particle with a spin moving in a uniform magnetic field and a perpendicular electric field varying with time. The corresponding Green function (propagator) is given in terms of elementary functions and certain integrals of the fields with a characteristic function, which should be found as an analytic or numerical solution of the equation of motion for the classical oscillator with a time-dependent frequency. We discuss a particular solution of a related nonlinear Schrodinger equation and some special and limiting cases are outlined.
ENHANCED SECURE KEY EXCHANGE SYSTEMS BASED ON THE JOHNSON- NOISE SCHEME

We introduce seven new versions of the Kirchhoff -Law-Johnson-(like)-Noise (KLJN) classical physical secure key exchange scheme and a new transient protocol for practically -perfect security. While these practical improvements offer progressively enhanced security and/or speed for non-ideal conditions, the fundamental physical laws providing the security remain the same. In the "intelligent" KLJN (iKLJN) scheme, Alice and Bob utilize the fact that they exactly know not only their own resistor value but also the stochastic time function of their own noise, which they generate before feeding it into the loop. By using this extra information, they can reduce the duration of exchanging a single bit and in this way they achieve not only higher speed but also an enhanced security because Eve's information will significantly be reduced due to smaller statistics. In the "multiple" KLJN (MKLJN) system, Alice and Bob have publicly known identical sets of different resistors with a proper, publicly known truth table about the bit-interpretation of their combination. In this new situation, for Eve to succeed, it is not enough to find out which end has the higher resistor. Eve must exactly identify the actual resistor values at both sides. In the "keyed" KLJN (KKLJN) system, by using secure communication with a formerly shared key, Alice and Bob share a proper time -dependent truth table for the bit-interpretation of the resistor situation for each secure bit exchange step during generating the next key. In this new situation, for Eve to succeed, it is not enough to find out the resistor values at the two ends. Eve must also know the former key. The remaining four KLJN schemes are the combinations of the above protocols to synergically enhance the security properties. The se are: the "intelligent-multiple" (iMKLJN), the "intelligent-keyed" (iKKLJN), the "keyed -multiple" (KMKLJN) and the "intelligent-keyed-multiple" (iKMKLJN) KLJN key exchange systems. Finally, we introduce a new transient -protocol offering practically-perfe ct security without privacy amplification, which is not needed in practical applications but it is shown for the sake of ongoing discussions.
Fast learning-based registration of sparse 3D clinical images

We introduce SparseVM, a method that registers clinical-quality 3D MR scans both faster and more accurately than previously possible. Deformable alignment, or registration, of clinical scans is a fundamental task for many clinical neuroscience studies. However, most registration algorithms are designed for high-resolution research-quality scans. In contrast to research-quality scans, clinical scans are often sparse, missing up to 86% of the slices available in research-quality scans. Existing methods for registering these sparse images are either inaccurate or extremely slow. We present a learning-based registration method, SparseVM, that is more accurate and orders of magnitude faster than the most accurate clinical registration methods. To our knowledge, it is the first method to use deep learning specifically tailored to registering clinical images. We demonstrate our method on a clinically-acquired MRI dataset of stroke patients and on a simulated sparse MRI dataset. Our code is available as part of the VoxelMorph package at http://voxelmorph.mit.edu.
TWISTED FORMS OF TORIC VARIETIES

We consider the set of forms of a toric variety over an arbitrary field: those varieties which become isomorphic to a toric variety after base field extension. In contrast to most previous work, we also consider arbitrary isomorphisms rather than just those that respect a torus action. We define an injective map from the set of forms of a toric variety to a non-abelian second cohomology set, which generalizes the usual Brauer class of a Severi-Brauer variety. Additionally, we define a map from the set of forms of a toric variety to the set of forms of a separable algebra along similar lines to a construction of A. Merkurjev and I. Panin. This generalizes both a result of M. Blunk for del Pezzo surfaces of degree 6, and the standard bijection between Severi-Brauer varieties and central simple algebras.