cssi/SciSciGPT-SciSciNet huggingface dataset:
Applying Noether's Theorem to Matter in the Milky Way: Evidence for External Perturbations and Non-steady-state Effects from Gaia Data Release 2

We apply Noether's theorem to observations of main-sequence stars from the Gaia Data Release 2 archive to probe the matter distribution function of the Galaxy. That is, we examine the axial symmetry of stars at vertical heights $z$, $0.2 \le |z| \le 3$ kpc, to probe the quality of the angular momentum $L_z$ as an integral of motion. The failure of this symmetry test would speak to a Milky Way, in both its visible and dark matter, that is not isolated and/or not in steady state. The left-right symmetry-breaking pattern we have observed, north and south, reveals both effects, with a measured deviation from symmetry of typically 0.5%. We show that a prolate form of the gravitational distortion of the Milky Way by the Large Magellanic Cloud, determined from fits to the Orphan stream by Erkal et al., 2019, is compatible with the size and sign of the axial-symmetry-breaking effects we have discovered in our sample of up to 14.4 million main-sequence stars, speaking to a distortion of an emergent, rather than static, nature.
Convective heat transport in stratified atmospheres at low and high Mach number

Simulations of compressible convection in stratified atmospheres in both two and three dimensions display turbulent heat transport that is surprisingly similar to transport in incompressible, Rayleigh-B\'enard convection. Further, this heat transport is insensitive to the Mach number of the flows.
Kobayashi Non-hyperbolicity of Calabi–Yau Manifolds Via Mirror Symmetry

A compact complex manifold is Kobayashi non-hyperbolic if there exists an entire curve on it. Using mirror symmetry we establish that there are (possibly singular) elliptic or rational curves on any Calabi–Yau manifold X, whose mirror dual $${\check{X}}$$ exists and is not “Hodge degenerate”, therefore proving that X is Kobayashi non-hyperbolic. We are not aware of any higher dimensional simply connected Calabi–Yau manifolds that satisfy the “Hodge degenerate” condition.
$r$-tuple error functions and indefinite theta series of higher-depth

Theta functions for definite signature lattices constitute a rich source of modular forms. A natural question is then their generalization to indefinite signature lattices. One way to ensure a convergent theta series while keeping the holomorphicity property of definite signature theta series is to restrict the sum over lattice points to a proper subset. Although such series do not have the modular properties that a definite signature theta function has, as shown by Zwegers for signature $(1,n-1)$ lattices, they can be completed to a function that has these modular properties by compromising on the holomorphicity property in a certain way. This construction has recently been generalized to signature $(2,n-2)$ lattices by Alexandrov, Banerjee, Manschot, and Pioline. A crucial ingredient in this work is the notion of double error functions which naturally lends itself to generalizations to higher dimensions. In this work we study the properties of such higher dimensional error functions which we will call $r$-tuple error functions. We then construct an indefinite theta series for signature $(r,n-r)$ lattices and show they can be completed to modular forms by using these $r$-tuple error functions.
On the Likelihood of Supernova Enrichment of Protoplanetary Disks

We estimate the likelihood of direct injection of supernova ejecta into protoplanetary disks using a model in which the number of stars with disks decreases linearly with time, and clusters expand linearly with time such that their surface density is independent of stellar number. The similarity of disk dissipation and main-sequence lifetimes implies that the typical supernova progenitor is very massive, ~75-100 M☉. Such massive stars are found only in clusters with 104 members. Moreover, there is only a small region around a supernova within which disks can survive the blast yet be enriched to the level observed in the solar system. These two factors limit the overall likelihood of supernova enrichment of a protoplanetary disk to 1%. If the presence of short-lived radionucleides in meteorites is to be explained in this way, however, the solar system most likely formed in one of the largest clusters in the Galaxy, more than 2 orders of magnitude greater than Orion, where multiple supernovae impacted many disks in a short period of time.
Millimeter Wave Energy Harvesting

The millimeter wave (mmWave) band, a prime candidate for 5G cellular networks, seems attractive for wireless energy harvesting since it will feature large antenna arrays and extremely dense base station (BS) deployments. The viability of mmWave for energy harvesting though is unclear, due to the differences in propagation characteristics, such as extreme sensitivity to building blockages. This paper considers a scenario where low-power devices extract energy and/or information from the mmWave signals. Using stochastic geometry, analytical expressions are derived for the energy coverage probability, the average harvested power, and the overall (energy-and-information) coverage probability at a typical wireless-powered device in terms of the BS density, the antenna geometry parameters, and the channel parameters. Numerical results reveal several network and device level design insights. At the BSs, optimizing the antenna geometry parameters, such as beamwidth, can maximize the network-wide energy coverage for a given user population. At the device level, the performance can be substantially improved by optimally splitting the received signal for energy and information extraction, and by deploying multi-antenna arrays. For the latter, an efficient low-power multi-antenna mmWave receiver architecture is proposed for simultaneous energy and information transfer. Overall, simulation results suggest that mmWave energy harvesting generally outperforms lower frequency solutions.
A photonic crystal cavity-optical fiber tip nanoparticle sensor for biomedical applications

We present a sensor capable of detecting solution-based nanoparticles using an optical fiber tip functionalized with a photonic crystal cavity. When sensor tips are retracted from a nanoparticle solution after being submerged, we find that a combination of convective fluid forces and optically induced trapping cause an aggregation of nanoparticles to form directly on cavity surfaces. A simple readout of quantum dot photoluminescence coupled to the optical fiber shows that nanoparticle presence and concentration can be detected through modified cavity properties. Our sensor can detect both gold and iron oxide nanoparticles and can be utilized for molecular sensing applications in biomedicine.
Instability of super-entropic black holes in extended thermodynamics

The charged black hole of Banados, Teitelbiom and Zanelli is studied in extended gravitational thermodynamics where there is a dynamical pressure and volume. It is a simple example of a super-entro...
HEREDITARILY ANTISYMMETRIC OPERATOR ALGEBRAS

We introduce a notion of ‘hereditarily antisymmetric’ operator algebras and prove a structure theorem for them in finite dimensions. We also characterize those operator algebras in finite dimensions which can be made upper triangular and prove matrix analogs of the theorems of Dilworth and Mirsky for finite posets. Some partial results are obtained in the infinite dimensional case.
Pseudo-maximization and self-normalized processes

Self-normalized processes are basic to many probabilistic and statistical studies. They arise naturally in the the study of stochastic inte- grals, martingale inequalities and limit theorems, likelihood-based methods in hypothesistesting and parameterestimation, and Studentizedpivots and bootstrap-t methods for confidence intervals. In contrast to standard nor- malization, large values of the observationsplay a lesser role as they appear both in the numerator and its self-normalized denominator, thereby mak- ing the process scale invariantand contributing to its robustness. Herein we survey a number of results for self-normalized processes in the case of de- pendentvariablesand describe a key method called "pseudo-maximization" that has been used to derive these results. In the multivariate case, self- normalization consists of multiplying by the inverse of a positive definite matrix (instead of dividing by a positive random variable as in the scalar case) and is ubiquitous in statistical applications, examples of which are given. AMS 2000 subject classifications: Primary 60K35, 60K35; secondary 60K35.
The vortex-entrainment sheet in an inviscid fluid: theory and separation at a sharp edge

In this paper a model for viscous boundary and shear layers in three dimensions is introduced and termed a vortex-entrainment sheet. The vorticity in the layer is accounted for by a conventional vortex sheet. The mass and momentum in the layer are represented by a two-dimensional surface having its own internal tangential flow. Namely, the sheet has a mass density per-unit-area making it dynamically distinct from the surrounding outer fluid and allowing the sheet to support a pressure jump. The mechanism of entrainment is represented by a discontinuity in the normal component of the velocity across the sheet. The velocity field induced by the vortex-entrainment sheet is given by a generalized Birkhoff–Rott equation with a complex sheet strength. The model was applied to the case of separation at a sharp edge. No supplementary Kutta condition in the form of a singularity removal is required as the flow remains bounded through an appropriate balance of normal momentum with the pressure jump across the sheet. A pressure jump at the edge results in the generation of new vorticity. The shedding angle is dictated by the normal impulse of the intrinsic flow inside the bound sheets as they merge to form the free sheet. When there is zero entrainment everywhere the model reduces to the conventional vortex sheet with no mass. Consequently, the pressure jump must be zero and the shedding angle must be tangential so that the sheet simply convects off the wedge face. Lastly, the vortex-entrainment sheet model is demonstrated on several example problems.
A class of three-dimensional gyroviscous magnetohydrodynamic models

A Hamiltonian and action principle formalism for deriving three-dimensional gyroviscous magnetohydrodynamic models is presented. The uniqueness of the approach in constructing the gyroviscous tensor from first principles and its ability to explain the origin of the gyromap and the gyroviscous terms are highlighted. The procedure allows for the specification of free functions, which can be used to generate a wide range of gyroviscous models. Through the process of reduction, the noncanonical Hamiltonian bracket is obtained and briefly analysed.
Smooth Potential Chaos and N-Body Simulations

Integrations in fixed N-body realizations of smooth density distributions corresponding to a chaotic galactic potential can be used to derive reliable estimates of the largest (finite-time) Lyapunov exponent χS associated with an orbit in the smooth potential generated from the same initial condition, even though the N-body orbit is typically characterized by an N-body exponent χN χS. This can be accomplished by either comparing initially nearby orbits in a single N-body system or tracking orbits with the same initial condition evolved in two different N-body realizations of the same smooth density.
Quantum Liouville Theory from a Diffeomorphism Chern-Simons Action

A Chern-Simons action written with Christoffel symbols has a natural gauge symmetry of diffeomorphisms. This Chern-Simons action will induce a Wess-Zumino-Witten model on the boundary of the manifold. If we restrict the diffeomorphisms to chiral diffeomorphism, the Wess-Zumino-Witten model is equivalent to a quantum Liouville action.
A Hybrid Model for the Population Dynamics of Periodical Cicadas

In addition to their unusually long life cycle, periodical cicadas, Magicicada spp., provide an exceptional example of spatially synchronized life stage phenology in nature. Within regions ("broods") spanning 50,000-500,000 km[Formula: see text], adults emerge synchronously every 13 or 17 years. While satiation of avian predators is believed to be a key component of the ability of these populations to reach high densities, it is not clear why populations at a single location remain entirely synchronized. We develop nonlinear Leslie matrix-type models of periodical cicadas that include predation-driven Allee effects and competition in addition to reproduction and survival. Using both analytical and numerical techniques, we demonstrate the observed presence of a single brood critically depends on the relationship between fecundity, competition and predation. We analyze the single-brood, two-brood and all-brood equilibria in the large life span limit using a tractable hybrid approximation to the Leslie matrix model with continuous time competition in between discrete reproduction events. Within the hybrid model, we prove that the single-brood equilibrium is the only stable equilibrium. This hybrid model allows us to quantitatively predict population sizes and the range of parameters for which the stable single-brood and unstable two-brood and all-brood equilibria exist. The hybrid model yields a good approximation to the numerical results for the Leslie matrix model for the biologically relevant case of a 17-year life span.
Geometric Adaptive Control for a Quadrotor UAV with Wind Disturbance Rejection

This paper presents a geometric adaptive control scheme for a quadrotor unmanned aerial vehicle, where the effects of unknown, unstructured disturbances are mitigated by a multilayer neural network that is adjusted online. The stability of the proposed controller is analyzed with Lyapunov stability theory on the special Euclidean group, and it is shown that the tracking errors are uniformly ultimately bounded with an ultimate bound that can be abridged arbitrarily. A mathematical model of wind disturbance on the quadrotor dynamics is presented, and it is shown that the proposed adaptive controller is capable of rejecting the effects of wind disturbances successfully. These are illustrated by numerical examples.
Integrative biological simulation praxis: Considerations from physics, philosophy, and data/model curation practices

Integrative biological simulations have a varied and controversial history in the biological sciences. From computational models of organelles, cells, and simple organisms, to physiological models of tissues, organ systems, and ecosystems, a diverse array of biological systems have been the target of large-scale computational modeling efforts. Nonetheless, these research agendas have yet to prove decisively their value among the broader community of theoretical and experimental biologists. In this commentary, we examine a range of philosophical and practical issues relevant to understanding the potential of integrative simulations. We discuss the role of theory and modeling in different areas of physics and suggest that certain sub-disciplines of physics provide useful cultural analogies for imagining the future role of simulations in biological research. We examine philosophical issues related to modeling which consistently arise in discussions about integrative simulations and suggest a pragmatic viewpoint that balances a belief in philosophy with the recognition of the relative infancy of our state of philosophical understanding. Finally, we discuss community workflow and publication practices to allow research to be readily discoverable and amenable to incorporation into simulations. We argue that there are aligned incentives in widespread adoption of practices which will both advance the needs of integrative simulation efforts as well as other contemporary trends in the biological sciences, ranging from open science and data sharing to improving reproducibility.
Liberating Efimov Physics from Three Dimensions

When two particles attract via a resonant short-range interaction, three particles always form an infinite tower of bound states characterized by a discrete scaling symmetry. It has been considered that this Efimov effect exists only in three dimensions. Here we review how the Efimov physics can be liberated from three dimensions by considering two-body and three-body interactions in mixed dimensions and four-body interaction in one dimension. In such new systems, intriguing phenomena appear, such as confinement-induced Efimov effect, Bose–Fermi crossover in Efimov spectrum, and formation of interlayer Efimov trimers. Some of them are observable in ultracold atom experiments and we believe that this study significantly broadens our horizons of universal Efimov physics.
A light complex scalar for the electron and muon anomalous magnetic moments

The anomalous magnetic moments of the electron and the muon are interesting observables, since they can be measured with great precision and their values can be computed with excellent accuracy within the Standard Model (SM). The current experimental measurement of this quantities show a deviation of a few standard deviations with respect to the SM prediction, which may be a hint of new physics. The fact that the electron and the muon masses differ by two orders of magnitude and the deviations have opposite signs makes it difficult to find a common origin of these anomalies. In this work we introduce a complex singlet scalar charged under a Peccei-Quinn-like (PQ) global symmetry together with the electron transforming chirally under the same symmetry. In this realization, the CP-odd scalar couples to electron only, while the CP-even part can couple to muons and electrons simultaneously. In addition, the CP-odd scalar can naturally be much lighter than the CP-even scalar, as a pseudo-Goldstone boson of the PQ-like symmetry, leading to an explanation of the suppression of the electron anomalous magnetic moment with respect to the SM prediction due to the CP-odd Higgs effect dominance, as well as an enhancement of the muon one induced by the CP-even component.
On the Taylor tower of relative K–theory

First published in Geometry & Topology in 16(2), published by Mathematical Sciences Publishers.
RESPONSE OF THE PHOTOSPHERIC MAGNETIC FIELD TO THE X2.2 FLARE ON 2011 FEBRUARY 15

It is well known that the long-term evolution of the photospheric magnetic field plays an important role in building up free energy to power solar eruptions. Observations, despite being controversial, have also revealed a rapid and permanent variation of the photospheric magnetic field in response to the coronal magnetic field restructuring during the eruption. The Helioseismic and Magnetic Imager instrument (HMI) on board the newly launched Solar Dynamics Observatory produces seeing-free full-disk vector magnetograms at consistently high resolution and high cadence, which finally makes possible an unambiguous and comprehensive study of this important back-reaction process. In this study, we present a near disk-center, GOES-class X2.2 flare, which occurred in NOAA AR 11158 on 2011 February 15. Using the magnetic field measurements made by HMI, we obtained the first solid evidence of a rapid (in about 30 minutes) and irreversible enhancement in the horizontal magnetic field at the flaring magnetic polarity inversion line (PIL) by a magnitude of {approx}30%. It is also shown that the photospheric field becomes more sheared and more inclined. This field evolution is unequivocally associated with the flare occurrence in this sigmoidal active region, with the enhancement area located in between the two chromospheric flare ribbons andmore » the initial conjugate hard X-ray footpoints. These results strongly corroborate our previous conjecture that the photospheric magnetic field near the PIL must become more horizontal after eruptions, which could be related to the newly formed low-lying fields resulting from the tether-cutting reconnection.« less
Evolution and analysis of embodied spiking neural networks reveals task-specific clusters of effective networks

Elucidating principles that underlie computation in neural networks is currently a major research topic of interest in neuroscience. Transfer Entropy (TE) is increasingly used as a tool to bridge the gap between network structure, function, and behavior in fMRI studies. Computational models allow us to bridge the gap even further by directly associating individual neuron activity with behavior. However, most computational models that have analyzed embodied behaviors have employed non-spiking neurons. On the other hand, computational models that employ spiking neural networks tend to be restricted to disembodied tasks. We show for the first time the artificial evolution and TE-analysis of embodied spiking neural networks to perform a cognitively-interesting behavior. Specifically, we evolved an agent controlled by an Izhikevich neural network to perform a visual categorization task. The smallest networks capable of performing the task were found by repeating evolutionary runs with different network sizes. Informational analysis of the best solution revealed task-specific TE-network clusters, suggesting that within-task homogeneity and across-task heterogeneity were key to behavioral success. Moreover, analysis of the ensemble of solutions revealed that task-specificity of TE-network clusters correlated with fitness. This provides an empirically testable hypothesis that links network structure to behavior.
ATLAS: Adaptive Topology- and Load-Aware Scheduling

The largest strength of contention-based MAC protocols is simultaneously the largest weakness of their scheduled counterparts: the ability to adapt to changes in network conditions. For scheduling to be competitive in mobile wireless networks, continuous adaptation must be addressed. We propose ATLAS, an Adaptive Topology- and Load-Aware Scheduling protocol to address this problem. In ATLAS, each node employs a random schedule achieving its persistence, the fraction of time a node is permitted to transmit, that is computed in a topology and load dependent manner. A distributed auction (REACT) piggybacks offers and claims onto existing network traffic to compute a lexicographic max-min channel allocation. A node's persistence p is related to its allocation. Its schedule achieving p is updated where and when needed, without waiting for a frame boundary.We study how ATLAS adapts to controlled changes in topology and load. Our results show that ATLAS adapts to most network changes in less than 0.1s, with about 20% relative error, scaling with network size. We further study ATLAS in more dynamic networks showing that it keeps up with changes in topology and load sufficient for TCP to sustain multi-hop flows, a struggle in IEEE 802.11 networks. The stable performance of ATLAS supports the design of higher-layer services that inform, and are informed by, the underlying communication network.
Stability Properties of the Time Domain Electric Field Integral Equation Using a Separable Approximation for the Convolution With the Retarded Potential

The state of art of time domain integral equation (TDIE) solvers has grown by leaps and bounds over the past decade. During this time, advances have been made in (i) the development of accelerators that can be retrofitted with these solvers and (ii) understanding the stability properties of the electric field integral equation. As is well known, time domain electric field integral equation solvers have been notoriously difficult to stabilize. Research into methods for understanding and prescribing remedies have been on the uptick. The most recent of these efforts are (i) Lubich quadrature and (ii) exact integration. In this paper, we re-examine the solution to this equation using (i) the undifferentiated form of the time domain electric field integral equation (TDEFIE) and (ii) a separable approximation to the spatio-temporal convolution. The proposed scheme can be constructed such that the spatial integrand over the source and observer domains is smooth and integrable. As several numerical results will demonstrate, the proposed scheme yields stable results for long simulation times and a variety of targets, both of which have proven extremely challenging in the past.
TWO-FLUID MAGNETOHYDRODYNAMIC SIMULATIONS OF RELATIVISTIC MAGNETIC RECONNECTION

We investigate the large-scale evolution of a relativistic magnetic reconnection in an electron-positron pair plasma by a relativistic two-fluid magnetohydrodynamic (MHD) code. We introduce an interspecies friction force as an effective resistivity to dissipate magnetic fields. We demonstrate that magnetic reconnection successfully occurs in our two-fluid system, and that it involves Petschek-type bifurcated current layers in a later stage. We further observe a quasi-steady evolution thanks to an open boundary condition, and find that the Petschek-type structure is stable over the long time period. Simulation results and theoretical analyses exhibit that the Petschek outflow channel becomes narrower when the reconnection inflow contains more magnetic energy, as previously claimed. Meanwhile, we find that the reconnection rate goes up to ~1 in extreme cases, which is faster than previously thought. The role of the resistivity, implications for reconnection models in the magnetically dominated limit, and relevance to kinetic reconnection works are discussed.
Fast CapsNet for Lung Cancer Screening

Lung cancer is the leading cause of cancer-related deaths in the past several years. A major challenge in lung cancer screening is the detection of lung nodules from computed tomography (CT) scans. State-of-the-art approaches in automated lung nodule classification use deep convolutional neural networks (CNNs). However, these networks require a large number of training samples to generalize well. This paper investigates the use of capsule networks (CapsNets) as an alternative to CNNs. We show that CapsNets significantly outperforms CNNs when the number of training samples is small. To increase the computational efficiency, our paper proposes a consistent dynamic routing mechanism that results in \(3\times \) speedup of CapsNet. Finally, we show that the original image reconstruction method of CapNets performs poorly on lung nodule data. We propose an efficient alternative, called convolutional decoder, that yields lower reconstruction error and higher classification accuracy.
Subtraction method for NLO corrections in Monte Carlo event generators for leptoproduction

In the case of the gluon-fusion process in deep-inelastic leptoproduction, I explicitly show how to incorporate NLO corrections in a Monte-Carlo event generator by a subtraction method. I calculate the parton densities to be used by the event generator in terms of MSbar densities. The method is generalizable. A particular motivation for treating the gluon-fusion process is to treat diffractive deep-inelastic scattering properly, since in diffractive scattering the gluon density dominates the quark densities. I also propose a modified algorithm for treating parton kinematics in event generators; the new algorithm results in much simpler formulae for the NLO corrections. A disadvantage of the new method is that some of the generated events may have negative weights. However, an adjustable cut-off function is present in the formalism, and this permits a renormalization-group-like transformation that can be used to at least reduce the proportion of events with negative weights.
WKB approximation to the power wall

We present a semiclassical analysis of the quantum propagator of a particle confined on one side by a steeply monotonically rising potential. The models studied in detail have potentials proportional to xα for x > 0; the limit α → ∞ would reproduce a perfectly reflecting boundary, but at present we concentrate on the cases α = 1 and 2, for which exact solutions in terms of well known functions are available for comparison. We classify the classical paths in this system by their qualitative nature and calculate the contributions of the various classes to the leading-order semiclassical approximation: for each classical path we find the action S, the amplitude function A and the Laplacian of A. (The Laplacian is of interest because it gives an estimate of the error in the approximation and is needed for computing higher-order approximations.) The resulting semiclassical propagator can be used to rewrite the exact problem as a Volterra integral equation, whose formal solution by iteration (Neumann series) is a semiclassical, not perturbative, expansion. We thereby test, in the context of a concrete problem, the validity of the two technical hypotheses in a previous proof of the convergence of such a Neumann series in the more abstract setting of an arbitrary smooth potential. Not surprisingly, we find that the hypotheses are violated when caustics develop in the classical dynamics; this opens up the interesting future project of extending the methods to momentum space.
Insights into DNA-mediated interparticle interactions from a coarse-grained model

DNA-functionalized particles have great potential for the design of complex self-assembled materials. The major hurdle in realizing crystal structures from DNA-functionalized particles is expected to be kinetic barriers that trap the system in metastable amorphous states. Therefore, it is vital to explore the molecular details of particle assembly processes in order to understand the underlying mechanisms. Molecular simulations based on coarse-grained models can provide a convenient route to explore these details. Most of the currently available coarse-grained models of DNA-functionalized particles ignore key chemical and structural details of DNA behavior. These models therefore are limited in scope for studying experimental phenomena. In this paper, we present a new coarse-grained model of DNA-functionalized particles which incorporates some of the desired features of DNA behavior. The coarse-grained DNA model used here provides explicit DNA representation (at the nucleotide level) and complementary interactions between Watson-Crick base pairs, which lead to the formation of single-stranded hairpin and double-stranded DNA. Aggregation between multiple complementary strands is also prevented in our model. We study interactions between two DNA-functionalized particles as a function of DNA grafting density, lengths of the hybridizing and non-hybridizing parts of DNA, and temperature. The calculated free energies as a function of pair distance between particles qualitatively resemble experimental measurements of DNA-mediated pair interactions.
The Motion of Small Bodies in Space-time

We consider the motion of small bodies in general relativity. The key result captures a sense in which such bodies follow timelike geodesics (or, in the case of charged bodies, Lorentz-force curves). This result clarifies the relationship between approaches that model such bodies as distributions supported on a curve, and those that employ smooth fields supported in small neighborhoods of a curve. This result also applies to “bodies” constructed from wave packets of Maxwell or Klein–Gordon fields. There follows a simple and precise formulation of the optical limit for Maxwell fields.
The Parisi Formula has a Unique Minimizer

In 1979, Parisi (Phys Rev Lett 43:1754–1756, 1979) predicted a variational formula for the thermodynamic limit of the free energy in the Sherrington–Kirkpatrick model, and described the role played by its minimizer. This formula was verified in the seminal work of Talagrand (Ann Math 163(1):221–263, 2006) and later generalized to the mixed p-spin models by Panchenko (Ann Probab 42(3):946–958, 2014). In this paper, we prove that the minimizer in Parisi’s formula is unique at any temperature and external field by establishing the strict convexity of the Parisi functional.
SEMI-CONTAINED NEUTRINO EVENTS IN MACRO

Updated results are presented of low-energy neutrino interactions observed by the MACRO detector. Two analyses (of different topologies) are presented; individually, and especially in their ratio, they are inconsistent with no oscillations and consistent with maximal mixing at Δm2 of a few times 10-3.
Stokes' cradle: normal three-body collisions between wetted particles

In this work, a combination of experiments and theory is used to investigate three-body normal collisions between solid particles with a liquid coating (i.e. ‘wetted’ particles). Experiments are carried out using a Stokes' cradle, an apparatus inspired by the Newton's cradle desktop toy except with wetted particles. Unlike previous work on two-body systems, which may either agglomerate or rebound upon collision, four outcomes are possible in three-body systems: fully agglomerated, Newton's cradle (striker and target particle it strikes agglomerate), reverse Newton's cradle (targets agglomerate while striker separates) and fully separated. Post-collisional velocities are measured over a range of parameters. For all experiments, as the impact velocity increases, the progression of outcomes observed is fully agglomerated, reverse Newton's cradle and fully separated. Notably, as the viscosity of the oil increases, experiments reveal a decrease in the critical Stokes number (the Stokes number that demarcates a transition from agglomeration to separation) for both sets of adjacent particles. A scaling theory is developed based on lubrication forces and particle deformation and elasticity. Unlike previous work for two-particle systems, two pieces of physics are found to be critical in the prediction of a regime map that is consistent with experiments: (i) an additional resistance upon rebound of the target particles due to the pre-existing liquid bridge between them (which has no counterpart in two-particle collisions), and (ii) the addition of a rebound criterion due to glass transition of the liquid layer at high pressure between colliding particles.
A multi-smartwatch system for assessing speech characteristics of people with dysarthria in group settings

Speech-language pathologists (SLPs) frequently use vocal exercises in the treatment of patients with speech disorders. Patients receive treatment in a clinical setting and need to practice outside of the clinical setting to generalize speech goals to functional communication. In this paper, we describe the development of technology that captures mixed speech signals in a group setting and allows the SLP to analyze the speech signals relative to treatment goals. The mixed speech signals are blindly separated into individual signals that are preprocessed before computation of loudness, pitch, shimmer, jitter, semitone standard deviation and sharpness. The proposed method has been previously validated on data obtained from clinical trials of people with Parkinson disease and healthy controls.
Kadison's Pythagorean Theorem and essential codimension

Kadison’s Pythagorean theorem (Proc Natl Acad Sci USA, 99(7):4178–4184, 2002; Proc Natl Acad Sci USA 99(8):5217–5222, 2002) provides a characterization of the diagonals of projections with a subtle integrality condition. Arveson (Proc Natl Acad Sci USA 104(4):1152–1158, 2007), Kaftal, Ng, Zhang (J Funct Anal 257(8):2497–2529, 2009), and Argerami (Integral Equ Oper Theory 82(1):33–49, 2015) all provide different proofs of that integrality condition. In this paper we interpret the integrality condition in terms of the essential codimension of a pair of projections introduced by Brown et al. (Proceedings of a conference on operator theory, Lecture notes in mathematics, Springer, Berlin, 1973), or, equivalently of the index of a Fredholm pair of projections introduced by Avron, Seiler and Simon (J Funct Anal 120(1):220–237, 1994). The same techniques explain the integer occurring in the characterization of diagonals of selfadjoint operators with finite spectrum by Bownik and Jasper (Trans Am Math Soc 367(7):5099–5140, 2015).
How Quantum Theory Helps Us Explain

I offer an account of how the quantum theory we have helps us explain the enormous variety of phenomena it is generally taken to explain. The account depends on what I have elsewhere called a pragmatist interpretation of the theory. This rejects views according to which a quantum state describes or represents a physical system, holding instead that it functions as a source of sound advice to physically situated agents like us on the content and appropriate degree of belief about matters concerning which they are currently inevitably ignorant. So while the account given here is incompatible with some views of structural explanation in quantum theory it is nevertheless able to incorporate what I take to be their valuable insights.
Langmuir wave filamentation in the kinetic regime. II. Weak and strong pumping of nonlinear electron plasma waves as the route to filamentation

We consider two kinds of pumped Langmuir waves (LWs) in the kinetic regime, k λ D ≳ 0.2 , where k is the LW wavenumber and λD is the Debye length, driven to finite amplitude by a coherent external potential whose amplitude is either weak or strong. These dynamically prepared nonlinear LWs develop a transverse (filamentation) instability whose nonlinear evolution destroys the LW's transverse coherence. Instability growth rates in the weakly pumped regime are the same as those of Bernstein-Greene-Kruskal modes considered in Part I (D. A. Silantyev et al., Phys. Plasmas 24, 042104 (2017)), while strongly pumped LWs have higher filamentation grow rates.
Analysis of problem tokens to rank factors impacting quality in VoIP applications

User-perceived quality-of-experience (QoE) in internet telephony systems is commonly evaluated using subjective ratings computed as a Mean Opinion Score (MOS). In such systems, while user MOS can be tracked on an ongoing basis, it does not give insight into which factors of a call induced any perceived degradation in QoE — it does not tell us what caused a user to have a sub-optimal experience. For effective planning of product improvements, we are interested in understanding the impact of each of these degrading factors, allowing the estimation of the return (i.e., the improvement in user QoE) for a given investment. To obtain such insights, we advocate the use of an end-of-call “problem token questionnaire” (PTQ) which probes the user about common call quality issues (e.g., distorted audio or frozen video) which they may have experienced. In this paper, we show the efficacy of this questionnaire using data gathered from over 700,000 end-of-call surveys gathered from Skype (a large commercial VoIP application). We present a method to rank call quality and reliability issues and address the challenge of isolating independent factors impacting the QoE. Finally, we present representative examples of how these problem tokens have proven to be useful in practice.
Making Sense of Computational Psychiatry

In psychiatry we often speak of constructing "models." Here we try to make sense of what such a claim might mean, starting with the most fundamental question: "What is (and isn't) a model?" We then discuss, in a concrete measurable sense, what it means for a model to be useful. In so doing, we first identify the added value that a computational model can provide in the context of accuracy and power. We then present limitations of standard statistical methods and provide suggestions for how we can expand the explanatory power of our analyses by reconceptualizing statistical models as dynamical systems. Finally, we address the problem of model building-suggesting ways in which computational psychiatry can escape the potential for cognitive biases imposed by classical hypothesis-driven research, exploiting deep systems-level information contained within neuroimaging data to advance our understanding of psychiatric neuroscience.
On the strengths of connectivity and robustness in general random intersection graphs

Random intersection graphs have received much attention for nearly two decades, and currently have a wide range of applications ranging from key predistribution in wireless sensor networks to modeling social networks. In this paper, we investigate the strengths of connectivity and robustness in a general random intersection graph model. Specifically, we establish sharp asymptotic zero-one laws for k-connectivity and k-robustness, as well as the asymptotically exact probability of k-connectivity, for any positive integer k. The k-connectivity property quantifies how resilient is the connectivity of a graph against node or edge failures. On the other hand, k-robustness measures the effectiveness of local diffusion strategies (that do not use global graph topology information) in spreading information over the graph in the presence of misbehaving nodes. In addition to presenting the results under the general random intersection graph model, we consider two special cases of the general model, a binomial random intersection graph and a uniform random intersection graph, which both have numerous applications as well. For these two specialized graphs, our results on asymptotically exact probabilities of k-connectivity and asymptotic zero-one laws for k-robustness are also novel in the literature.
Series acceleration formulas for Dirichlet series with periodic coefficients

Series acceleration formulas are obtained for Dirichlet series with periodic coefficients. Special cases include Ramanujan's formula for the values of the Riemann zeta function at the odd positive integers exceeding two, and related formulas for values of Dirichlet L-series and the Lerch zeta function.
A categorification of Morelli’s theorem

We prove a theorem relating torus-equivariant coherent sheaves on toric varieties to polyhedrally-constructible sheaves on a vector space. At the level of K-theory, the theorem recovers Morelli’s description of the K-theory of a smooth projective toric variety (Morelli in Adv. Math. 100(2):154–182, 1993). Specifically, let X be a proper toric variety of dimension n and let $M_{\mathbb{R}} = \mathrm{Lie}(T_{\mathbb{R}}^{\vee})\cong\mathbb {R}^{n}$ be the Lie algebra of the compact dual (real) torus $T_{\mathbb{R}}^{\vee}\cong U(1)^{n}$ . Then there is a corresponding conical Lagrangian Λ⊂T ∗ M ℝ and an equivalence of triangulated dg categories $\mathcal{P}\mathrm{erf}_{T}(X) \cong\mathit{Sh}_{cc}(M_{\mathbb{R}};\Lambda)$ , where $\mathcal{P}\mathrm{erf}_{T}(X)$ is the triangulated dg category of perfect complexes of torus-equivariant coherent sheaves on X and Sh cc (M ℝ;Λ) is the triangulated dg category of complex of sheaves on M ℝ with compactly supported, constructible cohomology whose singular support lies in Λ. This equivalence is monoidal—it intertwines the tensor product of coherent sheaves on X with the convolution product of constructible sheaves on M ℝ.
Learning from Multi-View Multi-Way Data via Structural Factorization Machines

Real-world relations among entities can often be observed and determined by different perspectives/views. For example, the decision made by a user on whether to adopt an item relies on multiple aspects such as the contextual information of the decision, the item»s attributes, the user»s profile and the reviews given by other users. Different views may exhibit multi-way interactions among entities and provide complementary information. In this paper, we introduce a multi-tensor-based approach that can preserve the underlying structure of multi-view data in a generic predictive model. Specifically, we propose structural factorization machines (SFMs) that learn the common latent spaces shared by multi-view tensors and automatically adjust the importance of each view in the predictive model. Furthermore, the complexity of SFMs is linear in the number of parameters, which make SFMs suitable to large-scale problems. Extensive experiments on real-world datasets demonstrate that the proposed SFMs outperform several state-of-the-art methods in terms of prediction accuracy and computational cost.
A data-driven MHD model of the global solar corona within Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS)

We have developed a data-driven magnetohydrodynamic (MHD) model of the global solar corona which uses characteristically-consistent boundary conditions (BCs) at the inner boundary. Our global solar corona model can be driven by different observational data including Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI) synoptic vector magnetograms together with the horizontal velocity data in the photosphere obtained by the time-distance helioseismology method, and the line-of-sight (LOS) magnetogram data obtained by HMI, Solar and Heliospheric Observatory/Michelson Doppler Imager (SOHO/MDI), National Solar Observatory/Global Oscillation Network Group (NSO/GONG) and Wilcox Solar Observatory (WSO). We implemented our model in the Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS) – a suite of adaptive mesh refinement (AMR) codes built upon the Chombo AMR framework developed at the Lawrence Berkeley National Laboratory. We present an overview of our model, characteristic BCs, and two results we obtained using our model: A benchmark test of relaxation of a dipole field using characteristic BCs, and relaxation of an initial PFSS field driven by HMI LOS magnetogram data, and horizontal velocity data obtained by the time-distance helioseismology method using a set of non-characteristic BCs.
Characterizing Ranked Chinese Syllable-to-Character Mapping Spectrum: A Bridge between the Spoken and Written Chinese Language

Abstract One important aspect of the relationship between spoken and written Chinese is the ranked syllable-to-character mapping spectrum, which is the ranked list of syllables by the number of characters that map to the syllable. Previously, this spectrum was analysed for more than 400 syllables without distinguishing the four intonations. In the current study, the spectrum with 1280 toned syllables is analysed by logarithmic function, Beta rank function, and piecewise logarithmic function. Out of the three fitting functions, the two-piece logarithmic function fits the data the best, both by the smallest sum of squared errors (SSE) and by the lowest Akaike information criterion (AIC) value. The Beta rank function is the close second. By sampling from a Poisson distribution whose parameter value is chosen from the observed data, we empirically estimate the chance probability that Beta function could outperform two-piece logarithmic function, to be 0.12-0.14. For practical purposes, the piecewise logarithm...
The model of a level crossing with a Coulomb band: exact probabilities of nonadiabatic transitions

We derive an exact solution of an explicitly time-dependent multichannel model of quantum mechanical nonadiabatic transitions. Our model corresponds to the case of a single linear diabatic energy level interacting with a band of an arbitrary N states, for which the diabatic energies decay with time according to the Coulomb law. We show that the time-dependent Schrodinger equation for this system can be solved in terms of Meijer functions whose asymptotics at a large time can be compactly written in terms of elementary functions that depend on the roots of an Nth order characteristic polynomial. Our model can be considered a generalization of the Demkov–Osherov model. In comparison to the latter, our model allows one to explore the role of curvature of the band levels and diabatic avoided crossings.
Gorenstein rings through face rings of manifolds

The face ring of a homology manifold (without boundary) modulo a generic system of parameters is studied. Its socle is computed and it is verified that a particular quotient of this ring is Gorenstein. This fact is used to prove that the algebraic g-conjecture for spheres implies all enumerative consequences of its far-reaching generalization (due to Kalai) to manifolds. A special case of Kalai’s conjecture is established for homology manifolds that have a codimension-two face whose link contains many vertices.