cssi/SciSciGPT-SciSciNet huggingface dataset:
Exploring Neural Entity Representations for Semantic Information.

Neural methods for embedding entities are typically extrinsically evaluated on downstream tasks and, more recently, intrinsically using probing tasks. Downstream task-based comparisons are often difficult to interpret due to differences in task structure, while probing task evaluations often look at only a few attributes and models. We address both of these issues by evaluating a diverse set of eight neural entity embedding methods on a set of simple probing tasks, demonstrating which methods are able to remember words used to describe entities, learn type, relationship and factual information, and identify how frequently an entity is mentioned. We also compare these methods in a unified framework on two entity linking tasks and discuss how they generalize to different model architectures and datasets.
Adjoint Method and Inverse Design for Nonlinear Nanophotonic Devices

The development of inverse design, where computational optimization techniques are used to design devices based on certain specifications, has led to the discovery of many compact, nonintuitive structures with superior performance. Among various methods, large-scale, gradient-based optimization techniques have been one of the most important ways to design a structure containing a vast number of degrees of freedom. These techniques are made possible by the adjoint method, in which the gradient of an objective function with respect to all design degrees of freedom can be computed using only two full-field simulations. However, this approach has so far mostly been applied to linear photonic devices. Here, we present an extension of this method to modeling nonlinear devices in the frequency domain, with the nonlinear response directly included in the gradient computation. As illustrations, we use the method to devise compact photonic switches in a Kerr nonlinear material, in which low-power and high-power pul...
Signatures of Intergalactic Dust from the First Supernovae

We quantify the consequences of intergalactic dust produced by the first Type II supernovae in the universe. The fraction of gas converted into stars is calibrated based on the observed C/H ratio in the intergalactic medium at z = 3, assuming a Scalo mass function for the stars. The associated dust absorbs starlight energy and emits it at longer wavelengths. For a uniform mix of metals and dust with the intergalactic gas, we find that the dust distorts the microwave background spectrum by a y-parameter in the range (0.06-6) × 10-5 (MSN/0.3 M☉), where MSN is the average mass of dust produced per supernova. The opacity of intergalactic dust to infrared sources at redshifts of z 10 is significant, τdust = (0.1-1) × (MSN/0.3 M☉), and could be detected with the Next Generation Space Telescope. Although dust suppresses the Lyα emission from early sources, the redshifts of star clusters at z = 10-35 can be easily inferred from the Lyman limit break in their infrared spectrum between 1 and 3.5 μm.
A SIMPLICIAL POLYTOPE THAT MAXIMIZES THE ISOTROPIC CONSTANT MUST BE A SIMPLEX

The isotropic constant $L_K$ is an affine-invariant measure of the spread of a convex body $K$. For a $d$-dimensional convex body $K$, $L_K$ can be defined by $L_K^{2d} = \det(A(K))/(\mathrm{vol}(K))^2$, where $A(K)$ is the covariance matrix of the uniform distribution on $K$. It is an outstanding open problem to find a tight asymptotic upper bound of the isotropic constant as a function of the dimension. It has been conjectured that there is a universal constant upper bound. The conjecture is known to be true for several families of bodies, in particular, highly symmetric bodies such as bodies having an unconditional basis. It is also known that maximizers cannot be smooth. In this work we study the gap between smooth bodies and highly symmetric bodies by showing progress towards reducing to a highly symmetric case among non-smooth bodies. More precisely, we study the set of maximizers among simplicial polytopes and we show that if a simplicial polytope $K$ is a maximizer of the isotropic constant among $d$-dimensional convex bodies, then when $K$ is put in isotropic position it is symmetric around any hyperplane spanned by a $(d-2)$-dimensional face and the origin. By a result of Campi, Colesanti and Gronchi, this implies that a simplicial polytope that maximizes the isotropic constant must be a simplex.
State Observation and Sensor Selection for Nonlinear Networks

A large variety of dynamical systems, such as chemical and biomolecular systems, can be seen as networks of nonlinear entities. Prediction, control, and identification of such nonlinear networks require knowledge of the state of the system. However, network states are usually unknown, and only a fraction of the state variables are directly measurable. The observability problem concerns reconstructing the network state from this limited information. Here, we propose a general optimization-based approach for observing the states of nonlinear networks and for optimally selecting the observed variables. Our results reveal several fundamental limitations in network observability, such as the tradeoff between the fraction of observed variables and the observation length on one side, and the estimation error on the other side. We also show that, owing to the crucial role played by the dynamics, purely graph-theoretic observability approaches cannot provide conclusions about one's practical ability to estimate the states. We demonstrate the effectiveness of our methods by finding the key components in biological and combustion reaction networks from which we determine the full system state. Our results can lead to the design of novel sensing principles that can greatly advance prediction and control of the dynamics of such networks.
The effects of non-linear electron-phonon interactions on superconductivity and charge-density-wave correlations

Determinant quantum Monte Carlo (DQMC) simulations are used to study non-linear electron-phonon interactions in a two-dimensional Holstein-like model on a square lattice. We examine the impact of non-linear electron-lattice interactions on superconductivity and on Peierls charge-density-wave (CDW) correlations at finite temperatures and carrier concentrations. We find that the CDW correlations are dramatically suppressed with the inclusion of even a small non-linear interaction. Conversely, the effect of the non-linearity on superconductivity is found to be less dramatic at high temperatures; however, we find evidence that the non-linearity is ultimately detrimental to superconductivity. These effects are attributed to the combined hardening of the phonon frequency and a renormalization of the effective linear electron-phonon coupling towards weaker values. These results demonstrate the importance of non-linear interactions at finite carrier concentrations when one is addressing CDW and superconducting order and have implications for experiments that drive the lattice far from equilibrium.
An Improved Algorithm for Generating Database Transactions from Relational Algebra Specifications

Alloy is a lightweight modeling formalism based on relational algebra. In prior work with Fisler, Giannakopoulos, Krishnamurthi, and Yoo, we have presented a tool, Alchemy, that compiles Alloy specifications into implementations that execute against persistent databases. The foundation of Alchemy is an algorithm for rewriting relational algebra formulas into code for database transactions. In this paper we report on recent progress in improving the robustness and efficiency of this transformation.
Shining Light on Quantum Gravity with Pulsar–Black hole Binaries

Pulsars are some of the most accurate clocks found in nature, while black holes offer a unique arena for the study of quantum gravity. As such, pulsar–black hole (PSR–BH) binaries provide ideal astrophysical systems for detecting the effects of quantum gravity. With the success of aLIGO and the advent of instruments like SKA and eLISA, the prospects for the discovery of such PSR–BH binaries are very promising. We argue that PSR–BH binaries can serve as ready-made testing grounds for proposed resolutions to the black hole information paradox. We propose using timing signals from a pulsar beam passing through the region near a black hole event horizon as a probe of quantum gravitational effects. In particular, we demonstrate that fluctuations of the geometry outside a black hole lead to an increase in the measured root mean square deviation of the arrival times of pulsar pulses traveling near the horizon. This allows for a clear observational test of the nonviolent nonlocality proposal for black hole information escape. For a series of pulses traversing the near-horizon region, this model predicts an rms in pulse arrival times of for a black hole, for a black hole, and for Sgr A*. The current precision of pulse time-of-arrival measurements is sufficient to discern these rms fluctuations. This work is intended to motivate observational searches for PSR–BH systems as a means of testing models of quantum gravity.
A Free Boundary Problem with Facets

We study a free boundary problem on the lattice whose scaling limit is a harmonic free boundary problem with a discontinuous Hamiltonian. We find an explicit formula for the Hamiltonian, prove that the solutions are unique, and prove that the limiting free boundary has a facets in every rational direction. Our choice of problem presents difficulties that require the development of a new uniqueness proof for certain free boundary problems. The problem is motivated by physical experiments involving liquid drops on patterned solid surfaces.
Lattice thermal conductivity of organic-inorganic hybrid perovskite CH3NH3PbI3

Great success has been achieved in improving the photovoltaic energy conversion efficiency of the organic-inorganic hybrid perovskite-based solar cells, but with very limited knowledge on the thermal transport in hybrid perovskites, which could affect the device lifetime and stability. Based on the potential field derived from the density functional theory calculations, we studied the lattice thermal conductivity of the hybrid halide perovskite CH3NH3PbI3 using equilibrium molecular dynamics simulations. Temperature-dependent thermal conductivity is reported from 160 K to 400 K, which covers the tetragonal phase (160–330 K) and the pseudocubic phase (>330 K). A very low thermal conductivity (0.59 W/m K) is found in the tetragonal phase at room temperature, whereas a much higher thermal conductivity is found in the pseudocubic phase (1.80 W/m K at 330 K). The low group velocity of acoustic phonons and the strong anharmonicity are found responsible for the relatively low thermal conductivity of the tetragon...
Tidal alignment of galaxies

We develop an analytic model for galaxy intrinsic alignments (IA) based on the theory of tidal alignment. We calculate all relevant nonlinear corrections at one-loop order, including effects from nonlinear density evolution, galaxy biasing, and source density weighting. Contributions from density weighting are found to be particularly important and lead to bias dependence of the IA amplitude, even on large scales. This effect may be responsible for much of the luminosity dependence in IA observations. The increase in IA amplitude for more highly biased galaxies reflects their locations in regions with large tidal fields. We also consider the impact of smoothing the tidal field on halo scales. We compare the performance of this consistent nonlinear model in describing the observed alignment of luminous red galaxies with the linear model as well as the frequently used nonlinear alignment model, finding a significant improvement on small and intermediate scales. We also show that the cross-correlation between density and IA (the GI term) can be effectively separated into source alignment and source clustering, and we accurately model the observed alignment down to the one-halo regime using the tidal field from the fully nonlinear halo-matter cross correlation. Inside the one-halo regime, the average alignment of galaxies with density tracers no longer follows the tidal alignment prediction, likely reflecting nonlinear processes that must be considered when modeling IA on these scales. Finally, we discuss tidal alignment in the context of cosmic shear measurements.
On the one-loop Fayet-Iliopoulos term in chiral four-dimensional type I orbifolds

We consider the generation of Fayet-Iliopoulos terms at one string loop in some recently found N = 1 open string orbifolds with anomalous U(1) factors with non-vanishing trace of the charge. Low-energy field theory arguments lead one to expect a one-loop quadratically divergent Fayet-Iliopoulos term. We show that a one-loop Fayet-Iliopoulos term is not generated, due to a cancellation between contributions of world-sheets of different topology. The vanishing of the one-loop Fayet-Iliopoulos term in open string compactifications is related to the cancellation of twisted Ramond-Ramond tadpoles.
Effective Field Theory for Fermi Systems in a Large N Expansion

Abstract A system of fermions with short-range interactions at finite density is studied using the framework of effective field theory. The effective action formalism for fermions with auxiliary fields leads to a loop expansion in which particle–hole bubbles are resummed to all orders. For spin-independent interactions, the loop expansion is equivalent to a systematic expansion in 1/N, where N is the spin–isospin degeneracy g. Numerical results at next-to-leading order are presented and the connection to the Bose limit of this system is elucidated.
Small inner companions of warm jupiters: Lifetimes and legacies

Although warm Jupiters are generally too far from their stars for tides to be important, the presence of an inner planetary companion to a warm Jupiter can result in tidal evolution of the system. Insight into the process and its effects comes form classical secular theory of planetary perturbations. The lifetime of the inner planet may be shorter than the age of the system, because the warm Jupiter maintains its eccentricity and hence promotes tidal migration into the star. Thus a warm Jupiter observed to be alone in its system might have previously cleared away any interior planets. Before its demise, even if an inner planet is of terrestrial scale, it may promote damping of the warm Jupiter's eccentricity. Thus any inferences of the initial orbit of an observed warm Jupiter must include the possibility of a greater initial eccentricity than would be estimated by assuming it had always been alone. Tidal evolution involving multiple planets also enhances the internal heating of the planets, which readily exceeds that of stellar radiation for the inner planet, and may be great enough to affect the internal structure of warm Jupiters. Secular theory gives insight into the tidal processes, providing, among other things, a way to constrain eccentricities of transiting planets based on estimates of the tidal parameter Q.
Planar open books, monodromy factorizations and symplectic fillings

We study fillings of contact structures supported by planar open books by analyzing positive factorizations of their monodromy. Our method is based on Wendl’s theorem on symplectic fillings of planar open books. We prove that every virtually overtwisted contact structure on L(p,1) has a unique filling, and describe fillable and nonfillable tight contact structures on certain Seifert fibered spaces.
Ordinal Approaches to Decomposing Between-Group Test Score Disparities:

The estimation of test score “gaps” and gap trends plays an important role in monitoring educational inequality. Researchers decompose gaps and gap changes into within- and between-school portions ...
EXACT PARTITION FUNCTION AND BOUNDARY STATE OF CRITICAL ISING MODEL WITH BOUNDARY MAGNETIC FIELD

We compute the exact partition function of the 2-D Ising Model at critical temperature but with nonzero magnetic field at the boundary. The model describes a renormalization group flow between the free and fixed conformal boundary conditions in the space of boundary interactions. For this flow the universal ground state degeneracy g and the full boundary state is computed exactly.
THE DIFFUSE SOURCE AT THE CENTER OF LMC SNR 0509–67.5 IS A BACKGROUND GALAXY AT z = 0.031

Type Ia supernovae (SNe Ia) are well-known for their use in the measurement of cosmological distances, but our continuing lack of concrete knowledge about their progenitor stars is both a matter of debate and a source of systematic error. In our attempts to answer this question, we presented unambiguous evidence that LMC SNR 0509−67.5, the remnant of an SN Ia that exploded in the Large Magellanic Cloud 400 ± 50 yr ago, did not have any point sources (stars) near the site of the original supernova explosion, from which we concluded that this particular supernova must have had a progenitor system consisting of two white dwarfs. There is, however, evidence of nebulosity near the center of the remnant, which could have been left over detritus from the less massive WD, or could have been a background galaxy unrelated to the supernova explosion. We obtained long-slit spectra of the central nebulous region using GMOS on Gemini South to determine which of these two possibilities is correct. The spectra show Hα emission at a redshift of z = 0.031, which implies that the nebulosity in the center of LMC SNR 0509−67.5 is a background galaxy, unrelated to the supernova.
High-mobility indirect excitons in wide single quantum well

Indirect excitons (IXs) are bound pairs of electrons and holes confined in spatially separated layers. We present wide single quantum well (WSQW) heterostructures with high IX mobility, spectrally narrow IX emission, voltage-controllable IX energy, and long and voltage-controllable IX lifetime. This set of properties shows that WSQW heterostructures provide an advanced platform both for studying basic properties of IXs in low-disorder environments and for the development of high-mobility excitonic devices.
Holomorphic mappings between pseudoellipsoids in different dimensions

We give a necessary and sufficient condition for the existence of nondegenerate holomorphic mappings between pseudoellipsoidal real hypersurfaces, and provide an explicit parametrization for the collection of all such mappings (in the situations where they exist).
Improving performance of iterative methods by lossy checkponting

Iterative methods are commonly used approaches to solve large, sparse linear systems, which are fundamental operations for many modern scientific simulations. When the large-scale iterative methods are running with a large number of ranks in parallel, they have to checkpoint the dynamic variables periodically in case of unavoidable fail-stop errors, requiring fast I/O systems and large storage space. To this end, significantly reducing the checkpointing overhead is critical to improving the overall performance of iterative methods. Our contribution is fourfold. (1) We propose a novel lossy checkpointing scheme that can significantly improve the checkpointing performance of iterative methods by leveraging lossy compressors. (2) We formulate a lossy checkpointing performance model and derive theoretically an upper bound for the extra number of iterations caused by the distortion of data in lossy checkpoints, in order to guarantee the performance improvement under the lossy checkpointing scheme. (3) We analyze the impact of lossy checkpointing (i.e., extra number of iterations caused by lossy checkpointing files) for multiple types of iterative methods. (4) We evaluate the lossy checkpointing scheme with optimal checkpointing intervals on a high-performance computing environment with 2,048 cores, using a well-known scientific computation package PETSc and a state-of-the-art checkpoint/restart toolkit. Experiments show that our optimized lossy checkpointing scheme can significantly reduce the fault tolerance overhead for iterative methods by 23%∼70% compared with traditional checkpointing and 20%∼58% compared with lossless-compressed checkpointing, in the presence of system failures.
Geometric Quantization¶and the Generalized Segal--Bargmann Transform¶for Lie Groups of Compact Type

Let K be a connected Lie group of compact type and let T *(K) be its cotangent bundle. This paper considers geometric quantization of T *(K), first using the vertical polarization and then using a natural Kahler polarization obtained by identifying T *(K) with the complexified group K ℂ. The first main result is that the Hilbert space obtained by using the Kahler polarization is naturally identifiable with the generalized Segal–Bargmann space introduced by the author from a different point of view, namely that of heat kernels. The second main result is that the pairing map of geometric quantization coincides with the generalized Segal–Bargmann transform introduced by the author. This means that the pairing map, in this case, is a constant multiple of a unitary map. For both results it is essential that the half-form correction be included when using the Kahler polarization. These results should be understood in the context of results of K. Wren and of the author with B. Driver concerning the quantization of (1+1)-dimensional Yang–Mills theory. Together with those results the present paper may be seen as an instance of “quantization commuting with reduction”.
The direct enstrophy cascade of two-dimensional soap film flows

We investigate the direct enstrophy cascade of two-dimensional decaying turbulence in a flowing soap film channel. We use a coarse-graining approach that allows us to resolve the nonlinear dynamics and scale-coupling simultaneously in space and in scale. From our data, we verify an exact relation due to Eyink [“Local energy flux and the refined similarity hypothesis,” J. Stat. Phys. 78, 335–351 (1995); Eyink “Exact results on scaling exponents in the 2D enstrophy cascade,” Phys. Rev. Lett. 74, 3800–3803 (1995)] between traditional 3rd-order structure function and the enstrophy flux obtained by coarse-graining. We also present experimental evidence that enstrophy cascades to smaller (larger) scales with a 60% (40%) probability, in support of theoretical predictions by Merilees and Warn [“On energy and enstrophy exchanges in two-dimensional non-divergent flow,” J. Fluid Mech. 69, 625–630 (1975)] which appear to be valid in our flow owing to the ergodic nature of turbulence. We conjecture that their kinemati...
Twisted Logarithmic Modules of Vertex Algebras

Motivated by logarithmic conformal field theory and Gromov–Witten theory, we introduce a notion of a twisted module of a vertex algebra under an arbitrary (not necessarily semisimple) automorphism. Its main feature is that the twisted fields involve the logarithm of the formal variable. We develop the theory of such twisted modules and, in particular, derive a Borcherds identity and commutator formula for them. We investigate in detail the examples of affine and Heisenberg vertex algebras.
Collimation of a Central Wind by a Disk-Associated Magnetic Field

We present the results of time-dependent, numerical magnetohydrodynamic simulations of a realistic young stellar object outflow model with the addition of a disk-associated magnetic field. The outflow produced by the magnetic star-disk interaction consists of an episodic jet plus a wide-angle wind with an outflow speed comparable to that of the jet (100–200 km s-1). An initially vertical field of ≪ 0.1 Gauss, embedded in the disk, has little effect on the wind launching mechanism, but we show that it collimates the entire flow (jet + wide wind) at large (several AU) distances. The collimation does not depend on the polarity of the vertical field. We also discuss the possible origin of the disk-associated field.
Bottom quark production cross-section at HERA-B

The cross-section for bottom quark production is calculated for the HERA-B experiment. We consider both the order cross-section and the resummation of soft gluon corrections in all orders of QCD perturbation theory.
On the effectiveness of small, discriminatively pre-trained language representation models for biomedical text mining

Neural language representation models such as BERT have recently shown state of the art performance in downstream NLP tasks and bio-medical domain adaptation of BERT (Bio-BERT) has shown same behavior on biomedical text mining tasks. However, due to their large model size and resulting increased computational need, practical application of models such as BERT is challenging making smaller models with comparable performance desirable for real word applications. Recently, a new language transformers based language representation model named ELECTRA is introduced, that makes efficient usage of training data in a generative-discriminative neural model setting that shows performance gains over BERT. These gains are especially impressive for smaller models. Here, we introduce two small ELECTRA based model named Bio-ELECTRA and Bio-ELECTRA++ that are eight times smaller than BERT Base and Bio-BERT and achieves comparable or better performance on biomedical question answering, yes/no question answer classification, question answer candidate ranking and relation extraction tasks. Bio-ELECTRA is pre-trained from scratch on PubMed abstracts using a consumer grade GPU with only 8GB memory. Bio-ELECTRA++ is the further pre-trained version of Bio-ELECTRA trained on a corpus of open access full papers from PubMed Central. While, for biomedical named entity recognition, large BERT Base model outperforms Bio-ELECTRA++, Bio-ELECTRA and ELECTRA-Small++, with hyperparameter tuning Bio-ELECTRA++ achieves results comparable to BERT.
Electrohydrodynamics of deflated vesicles: budding, rheology and pairwise interactions

We develop a new boundary integral method for solving the coupled electro- and hydrodynamics of vesicle suspensions in Stokes flow. This relies on a well-conditioned boundary integral equation formulation for the leaky-dielectric model describing the electric response of the vesicles and an efficient numerical solver capable of handling highly deflated vesicles. Our method is applied to explore vesicle electrohydrodynamics in three cases. First, we study the classical prolate–oblate–prolate transition dynamics observed upon application of a uniform DC electric field. We discover that, in contrast to the squaring previously found with nearly spherical vesicles, highly deflated vesicles tend to form buds. Second, we illustrate the capabilities of the method by quantifying the electrorheology of a dilute vesicle suspension. Finally, we investigate the pairwise interactions of vesicles and find three different responses when the key parameters are varied: (i) chain formation, where they self-assemble to form a chain that is aligned along the field direction; (ii) circulatory motion, where they rotate about each other; (iii) oscillatory motion, where they form a chain but oscillate about each other. The last two are unique to vesicles and are not observed in the case of other soft particle suspensions such as drops.
Laminar Flow Control on a Swept Wing with Distributed Roughness

The work cumulated in a series of laminar-turbulent transition flight-test experiments on a swept wing with the goal of validating the spanwise-periodic distributed roughness elements (DRE) technology in a Reynolds number range applicable to SensorCraft technology. Phase I of the program measured freestream turbulence levels that were nominally 0.05% to 0.06% of the freestream speed and thus established the suitability of the flight environment for the laminarization flights. Phase II of the program did the baseline transition measurements on the airfoil i.e. with and without DRE technology. The region of laminar flow was extended from 30% to 60% chord at a chord Reynolds number of Rec = 8 x10 6 and sweep angle, Λ = 30°. Establishing the origins of turbulent flow and transition from laminar to turbulent flow remains an important challenge of fluid mechanics. The common thread connecting aerodynamic applications is the fact that they deal with bounded shear flows (boundary layers) in open systems (with different upstream or initial amplitude conditions). It is well known that the stability, transition, and turbulent characteristics of bounded shear layers are fundamentally different from those of free shear layers. Likewise, open systems are fundamentally different from those of closed systems. The distinctions are trenchant and thus form separate areas of study. For the classic open system, no mathematical model exists that can predict the transition Reynolds number on a simple flat plate because the influences of freestream turbulence, sound, and surface roughness are incompletely understood. With the maturation of linear stability methods and the conclusions that breakdown mechanisms are initial-condition dependent, more emphasis is now placed on the understanding of the source of initial disturbances than on the details of the later stages of transition.
Coded Computing for Low-Latency Federated Learning Over Wireless Edge Networks

Federated learning enables training a global model from data located at the client nodes, without data sharing and moving client data to a centralized server. Performance of federated learning in a multi-access edge computing (MEC) network suffers from slow convergence due to heterogeneity and stochastic fluctuations in compute power and communication link qualities across clients. We propose a novel coded computing framework, CodedFedL, that injects structured coding redundancy into federated learning for mitigating stragglers and speeding up the training procedure. CodedFedL enables coded computing for non-linear federated learning by efficiently exploiting distributed kernel embedding via random Fourier features that transforms the training task into computationally favourable distributed linear regression. Furthermore, clients generate local parity datasets by coding over their local datasets, while the server combines them to obtain the global parity dataset. Gradient from the global parity dataset compensates for straggling gradients during training, and thereby speeds up convergence. For minimizing the epoch deadline time at the MEC server, we provide a tractable approach for finding the amount of coding redundancy and the number of local data points that a client processes during training, by exploiting the statistical properties of compute as well as communication delays. We also characterize the leakage in data privacy when clients share their local parity datasets with the server. Additionally, we analyze the convergence rate and iteration complexity of CodedFedL under simplifying assumptions, by treating CodedFedL as a stochastic gradient descent algorithm. Finally, for demonstrating gains that CodedFedL can achieve in practice, we conduct numerical experiments using practical network parameters and benchmark datasets, in which CodedFedL speeds up the overall training time by up to $15\times $ in comparison to the benchmark schemes.
Anomalous diffusion in comb-shaped domains and graphs

In this paper we study the asymptotic behavior of Brownian motion in both comb-shaped planar domains, and comb-shaped graphs. We show convergence to a limiting process when both the spacing between the teeth \emph{and} the width of the teeth vanish at the same rate. The limiting process exhibits an anomalous diffusive behavior and can be described as a Brownian motion time-changed by the local time of an independent sticky Brownian motion. In the two dimensional setting the main technical step is an oscillation estimate for a Neumann problem, which we prove here using a probabilistic argument. In the one dimensional setting we provide both a direct SDE proof, and a proof using the trapped Brownian motion framework in Ben Arous \etal (Ann.\ Probab.\ '15).
Some Remarks on the Entanglement Number

Gudder, in a recent paper, defined a candidate entanglement measure which is called the entanglement number. The entanglement number is first defined on pure states and then it extends to mixed states by the convex roof construction. In Gudder's article it was left as an open problem to show that Optimal Pure State Ensembles (OPSE) exist for the convex roof extension of the entanglement number from pure to mixed states. We answer Gudder's question in the affirmative, and therefore we obtain that the entanglement number vanishes only on the separable states. More generally we show that OPSE exist for the convex roof extension of any function that is norm continuous on the pure states of a finite dimensional Hilbert space. Further we prove that the entanglement number is an LOCC monotone, (and thus an entanglement measure), by using a criterion that was developed by Vidal in 2000. We present a simplified proof of Vidal's result where moreover we use an interesting point of view of tree representations for LOCC communications. Lastly, we generalize Gudder's entanglement number by producing a monotonic family of entanglement measures which converge in a natural way to the entropy of entanglement. Quanta 2020; 9: 22–36.
On-chip optical non-reciprocity through a synthetic Hall effect for photons

We demonstrate a synthetic Hall effect for light, using an acousto-optically modulated nanophotonic resonator chain. To produce this effect, we simultaneously generate the required synthetic electric field using temporal modulation and the required synthetic magnetic field using spatial modulation of the resonator chain. We show how the combination of these synthetic fields transverse to the direction of light propagation can be used to produce non-reciprocal optical transmission, as a basis for new photonic and topological devices.
A set of distinct facial traits learned by machines is not predictive of appearance bias in the wild

Research in social psychology has shown that people’s biased, subjective judgments about another’s personality based solely on their appearance are not predictive of their actual personality traits. But researchers and companies often utilize computer vision models to predict similarly subjective personality attributes such as “employability”. We seek to determine whether state-of-the-art, black box face processing technology can learn human-like appearance biases. With features extracted with FaceNet, a widely used face recognition framework, we train a transfer learning model on human subjects’ first impressions of personality traits in other faces as measured by social psychologists. We find that features extracted with FaceNet can be used to predict human appearance bias scores for deliberately manipulated faces but not for randomly generated faces scored by humans. Additionally, in contrast to work with human biases in social psychology, the model does not find a significant signal correlating politicians’ vote shares with perceived competence bias. With Local Interpretable Model-Agnostic Explanations (LIME), we provide several explanations for this discrepancy. Our results suggest that some signals of appearance bias documented in social psychology are not embedded by the machine learning techniques we investigate. We shed light on the ways in which appearance bias could be embedded in face processing technology and cast further doubt on the practice of predicting subjective traits based on appearances.
Large and Local Magnetoresistance in a State-of-the-Art Perpendicular Magnetic Medium

Purpose Magnetotransport properties of granular oxide-segregated CoPtCr films were studied on both macroscopic and microscopic length scales by performing bulk and point-contact magnetoresistance measurements, respectively. Such a perpendicular magnetic medium is used in state-of-the-art hard disc drives and, when combined with magnetotransport phenomena for read/write operations, may lead to a novel concept for magnetic recording with high areal density. Materials and Methods The CoPtCr films were deposited by an epitaxy-like sputtering and contained several perpendicularly magnetized granular-media layers with different coercivities; they are very much like the state-of-the-art perpendicular magnetic medium, which can be found in today's hard disc drives. Magnetoresistive properties of bulk films were assessed by measuring the film resistance in the standard Van der Pauw geometry, while the local transport was probed by the point-contact technique. Results The bulk measurements showed only a negligible magnetoresistance of less than 0.02%. In contrast, the local point-contact measurements revealed giant-magnetoresistance-like changes ΔR in local resistance of the contact R with more than 10,000% ratio ΔR/R. Conclusion The observed large and local magnetoresistive effect could be tentatively attributed to a tunnel magnetoresistance between oxide-segregated CoPtCr grains with different coercivities. The tunneling picture of electronic transport in our granular medium was confirmed by the observation of tunneling-like current-voltage characteristics of the contacts and bias dependence of the contact magnetoresistance - both the local point-contact resistance and magnetoresistance were found to decrease with the applied dc bias.
SNARE complex alters the interactions of the Ca2+ sensor synaptotagmin 1 with lipid bilayers.

Abstract Release of neuronal transmitters from nerve terminals is triggered by the molecular Ca2+ sensor synaptotagmin 1 (Syt1). Syt1 is a transmembrane protein attached to the synaptic vesicle (SV), and its cytosolic region comprises two domains, C2A and C2B, which are thought to penetrate into lipid bilayers upon Ca2+ binding. Before fusion, SVs become attached to the presynaptic membrane (PM) by the four-helical SNARE complex, which is thought to bind the C2B domain in vivo. To understand how the interactions of Syt1 with lipid bilayers and the SNARE complex trigger fusion, we performed molecular dynamics (MD) simulations at a microsecond scale. We investigated how the isolated C2 modules and the C2AB tandem of Syt1 interact with membranes mimicking either SV or PM. The simulations showed that the C2AB tandem can either bridge SV and PM or insert into PM with its Ca2+-bound tips and that the latter configuration is more favorable. Surprisingly, C2 domains did not cooperate in penetrating into PM but instead mutually hindered their insertion into the bilayer. To test whether the interaction of Syt1 with lipid bilayers could be affected by the C2B-SNARE attachment, we performed systematic conformational analysis of the C2AB-SNARE complex. Notably, we found that the C2B-SNARE interface precludes the coupling of C2 domains and promotes their insertion into PM. We performed the MD simulations of the prefusion protein complex positioned between the lipid bilayers mimicking PM and SV, and our results demonstrated in silico that the presence of the Ca2+ bound C2AB tandem promotes lipid merging. Altogether, our MD simulations elucidated the role of the Syt1-SNARE interactions in the fusion process and produced the dynamic all-atom model of the prefusion protein-lipid complex.
Learning Highway Ramp Merging Via Reinforcement Learning with Temporally-Extended Actions

Several key scenarios, such as intersection navigation, lane changing, and ramp merging, are active areas of research in autonomous driving. In order to properly navigate these scenarios, autonomous vehicles must implicitly negotiate with human drivers. Prior work in driving behaviors presents reinforcement learning as a promising technique, as it can leverage data as well as the underlying decision-making structure of driving with interaction. We apply a hierarchical approach to decision-making, where we train a high-level policy using reinforcement learning, and execute the policy's output on a low-level controller. This hierarchical structure helps increase the policy's overall safety, and allows the learning component to be agnostic to the low-level control scheme. We validate our approach on a simulation using real-world highway data and find improved results compared to prior work in ramp merging.
Paying People to Lie: the Truth about the Budgeting Process

This paper analyzes the counterproductive effects associated with using budgets or targets in an organisation's performance measurement and compensation systems. Paying people on the basis of how their performance relates to a budget or target causes people to game the system and in doing so to destroy value in two main ways: (a) both superiors and subordinates lie in the formulation of budgets and, therefore, gut the budgeting process of the critical unbiased information that is required to coordinate the activities of disparate parts of an organisation, and (b) they game the realisation of the budgets or targets and in doing so destroy value for their organisations. Although most managers and analysts understand that budget gaming is widespread, few understand the huge costs it imposes on organisations and how to lower them. My purpose in this paper is to explain exactly how this happens and how managers and firms can stop this counter-productive cycle. The key lies not in destroying the budgeting systems, but in changing the way organisations pay people. In particular to stop this highly counter-productive behaviour we must stop using budgets or targets in the compensation formulas and promotion systems for employees and managers. This means taking all kinks, discontinuities and non-linearities out of the pay-for-performance profile of each employee and manager. Such purely linear compensation formulas provide no incentives to lie, or to withhold and distort information, or to game the system. While the evidence on the costs of these systems is not extensive, I believe that solving the problems could easily result in large productivity and value increases – sometimes as much as 50–100% improvements in productivity. I believe the less intensive reliance on such budget/target systems is an important cause of the increased productivity of entrepreneurial and LBO firms. Moreover, eliminating budget/target-induced gaming from the management system will eliminate one of the major forces leading to the general loss of integrity in organisations. People are taught to lie in these pervasive budgeting systems because if they tell the truth they often get punished and if they lie they get rewarded. Once taught to lie in this system people generally cannot help but extend that behaviour to all sorts of other relationships in the organisation.
On the efficiency of long intermediation chains

Abstract Intermediation chains represent a common pattern of trade in over-the-counter markets. We study a classic problem impeding trade in these markets: an agent uses his market power to inefficiently screen a privately informed counterparty. We show that, generically, if efficient trade is implementable via any incentive-compatible mechanism, it is also implementable via a trading network that takes the form of a sufficiently long intermediation chain. We characterize information sets of intermediaries that ensure this striking result. Sparse trading networks featuring long intermediation chains might thus constitute an efficient market response to frictions, in which case no regulatory action is warranted.
Substantive Rationality and Backward Induction

Aumann has proved that common knowledge of substantive rationality implies the backwards induction solution in games of perfect information. Stalnaker has proved that it does not. Roughly speaking, a player is substantively rational if, for all vertices v, if the player were to reach vertex v, then the player would be rational at vertex v. It is shown here that the key difference between Aumann and Stalnaker lies in how they interpret this counterfactual. A formal model is presented that lets us capture this difference, in which both Aumann’s result and Stalnaker’s result are true (under appropriate assumptions).
The Rhetoric of Legal Backfire

This Article focuses on legal backfire claims. A claim of legal backfire constitutes the position that a law produces or will produce results directly contrary to one or more of those intended. Legal backfire claims are pervasive, yet potentially misleading and harmful argumentation used primarily to undermine existing law (or policy) or to forestall the enactment of new law. This Article analyzes many examples of legal backfire to suggest that the concept is often a rhetorical strategy for opposing the promulgation of new law or policy or for attempting to have existing law rolled back, and that actual legal backfires are much more rare (or at least unproven) than use of the rhetoric would suggest. This Article also addresses a much more basic problem: the challenges to effective lawmaking and the limitations of techniques to evaluate the effects of law make an accurate assessment of law problematic. Ultimately, this Article suggests that lawmakers should proceed with caution when dealing with legal backfire claims because critics of laws almost invariably author these claims, the claims are rhetorically charged, and the claims themselves are extraordinary.
American Corporate Reform Abroad: Sarbanes-Oxley and the Foreign Private Issuer

After Enron, WorldCom, and other US business scandals, politicians in Washington faced enormous pressure to take swift action to address seemingly widespread malfeasance at US corporations. So only twenty-nine days from the disclosure of the accounting irregularities at WorldCom, Congress passed with near unanimity the Sarbanes-Oxley Act of 2002. When President Bush signed the law, he claimed it was one of ‘the most far-reaching reforms of American business practices since the time of Franklin Delano Roosevelt.’ The President significantly understated the case, however, because the Act does much more than reform the laws applicable to US-based issuers – a substantial number of the Act's provisions reach overseas to affect foreign private issuers whose securities trade in the United States.
Channel Selection and Coordination in Dual-Channel Supply Chains

Abstract This paper investigates the influence of channel structures and channel coordination on the supplier, the retailer, and the entire supply chain in the context of two single-channel and two dual-channel supply chains. We extensively study two Pareto zone concepts: channel-adding Pareto zone and contract-implementing Pareto zone. In the channel-adding Pareto zone, both the supplier and the retailer benefit from adding a new channel to the traditional single-channel supply chain. In the contract-implementing Pareto zone, it is mutually beneficial for the supplier and the retailer to utilize the proposed contract coordination policy. The analysis suggests the preference lists of the supplier and the retailer over channel structures with and without coordination are different, and depend on parameters like channel base demand, channel operational costs, and channel substitutability.
Task-Agnostic Morphology Evolution

Deep reinforcement learning primarily focuses on learning behavior, usually overlooking the fact that an agent's function is largely determined by form. So, how should one go about finding a morphology fit for solving tasks in a given environment? Current approaches that co-adapt morphology and behavior use a specific task's reward as a signal for morphology optimization. However, this often requires expensive policy optimization and results in task-dependent morphologies that are not built to generalize. In this work, we propose a new approach, Task-Agnostic Morphology Evolution (TAME), to alleviate both of these issues. Without any task or reward specification, TAME evolves morphologies by only applying randomly sampled action primitives on a population of agents. This is accomplished using an information-theoretic objective that efficiently ranks agents by their ability to reach diverse states in the environment and the causality of their actions. Finally, we empirically demonstrate that across 2D, 3D, and manipulation environments TAME can evolve morphologies that match the multi-task performance of those learned with task supervised algorithms. Our code and videos can be found at https://sites.google.com/view/task-agnostic-evolution .
Integrating personality psychology into economics

This paper reviews the problems and potential benefits of integrating personality psychology into economics. Economists have much to learn from and contribute to personality psychology.