cssi/SciSciGPT-SciSciNet huggingface dataset:
Density Jumps Near the Virial Radius of Galaxy Clusters

Recent simulations have indicated that the dark matter halos of galaxy clusters should feature steep density jumps near the virial radius. Since the member galaxies are expected to follow similar collisionless dynamics as the dark matter, the galaxy density profile should show such a feature as well. We examine the potential of current datasets to test this prediction by selecting cluster members for a sample of 56 low-redshift (0.1<z<0.3) galaxy clusters, constructing their projected number density profiles, and fitting them with two profiles, one with a steep density jump and one without. Additionally, we investigate the presence of a jump using a non-parametric spline approach. We find that some of these clusters show strong evidence for a model with a density jump. We discuss avenues for further analysis of the density jump with future datasets.
BT worldsheet for supersymmetric gauge theories

Abstract We extend the Bardakci–Thorn (BT) worldsheet formalism to supersymmetric non-Abelian gauge theory. Our method covers the cases of N =1,2,4 extended supersymmetry. This task requires the introduction of spinor valued Grassmann variables on the worldsheet analogous to those of the supersymmetric formulation of superstring theory. As in the pure Yang–Mills case, the worldsheet formalism automatically generates the correct quartic vertices from the cubic vertices. We also discuss coupling renormalization to one loop order.
Verifiably Safe Off-Model Reinforcement Learning

The desire to use reinforcement learning in safety-critical settings has inspired a recent interest in formal methods for learning algorithms. Existing formal methods for learning and optimization primarily consider the problem of constrained learning or constrained optimization. Given a single correct model and associated safety constraint, these approaches guarantee efficient learning while provably avoiding behaviors outside the safety constraint. Acting well given an accurate environmental model is an important pre-requisite for safe learning, but is ultimately insufficient for systems that operate in complex heterogeneous environments. This paper introduces verification-preserving model updates, the first approach toward obtaining formal safety guarantees for reinforcement learning in settings where multiple possible environmental models must be taken into account. Through a combination of inductive data and deductive proving with design-time model updates and runtime model falsification, we provide a first approach toward obtaining formal safety proofs for autonomous systems acting in heterogeneous environments.
Marker Based Thermal-Inertial Localization for Aerial Robots in Obscurant Filled Environments

For robotic inspection tasks in known environments fiducial markers provide a reliable and low-cost solution for robot localization. However, detection of such markers relies on the quality of RGB camera data, which degrades significantly in the presence of visual obscurants such as fog and smoke. The ability to navigate known environments in the presence of obscurants can be critical for inspection tasks especially, in the aftermath of a disaster. Addressing such a scenario, this work proposes a method for the design of fiducial markers to be used with thermal cameras for the pose estimation of aerial robots. Our low cost markers are designed to work in the long wave infrared spectrum, which is not affected by the presence of obscurants, and can be affixed to any object that has measurable temperature difference with respect to its surroundings. Furthermore, the estimated pose from the fiducial markers is fused with inertial measurements in an extended Kalman filter to remove high frequency noise and error present in the fiducial pose estimates. The proposed markers and the pose estimation method are experimentally evaluated in an obscurant filled environment using an aerial robot carrying a thermal camera.
On an Elliptic Equation Arising from Composite Materials

In this paper, we derive an interior Schauder estimate for the divergence form elliptic equation $$D_i (a(x)D_iu) = D_i f_i$$ in \({\mathbb{R}^2}\),where \({a(x)}\) and \({f_i (x)}\) are piecewise Holder continuous in a domain containing two touching balls as subdomains. When \({f_i \equiv 0}\) and a is piecewise constant, we prove that u is piecewise smoothwith bounded derivatives.This completely answers a question raised by Li andVogelius (Arch Ration Mech Anal 153(2):91–151, 2000) in dimension 2.
Atomic data from the Iron Project XLV. Relativistic transition probabilities for carbon-like Ar XIII and Fe XXI using Breit-Pauli R-matrix method

The Breit-Pauli R-matrix method developed under the Iron Project has been used to obtain exten- sive sets of oscillator strengths and transition probabil- ities for dipole allowed and intercombination ne struc- ture transitions in carbon like ions, Ar XIII and Fe XXI. The complete set consists of 1274 ne structure bound energy levels and 198 259 oscillator strengths for Ar XIII, and 1611 bound levels and 300 079 oscillator strengths for Fe XXI. These correspond to levels of total angular mo- menta of 0 J 7 of even and odd parities formed from total spin of 2S + 1 = 5, 3, 1, and orbital angular mo- menta 0 L 9 with n 10, 0 l 9f or each ion. The relativistic eects are included in the Breit-Pauli ap- proximation. The close coupling wavefunction expansion for each ion is represented by the lowest 15 ne struc- ture levels of target congurations, 2s 2 2p, 2s2p 2 and 2p 3 . The energy levels are identied spectroscopically using a newly developed identication procedure. The procedure also makes a correspondence between the ne structure energy levels and LS terms. This provides the check for completeness of the calculated levels. Comparison is made of the present energies and the f-values with the avail- able observed and theoretical values. Present transition probabilities agree very well with the relativistic atomic structure calculations of Mendoza et al. for the intercom- bination transitions, 2s2p 3 ( 5 S o) 2s 2 2p 2 ( 3 P1;2; 1 D2). This further indicates that the importance of the neglected Breit interaction decreases with ion charge and constrains the uncertainty in the present calculations to within 15% even for the weak transitions.
An “A star” on an M star during a flare within a flare

M dwarfs produce explosive flare emission in the near-UV and optical continuum, and the mechanism responsible for this phenomenon is not well-understood. We present a near-UV/optical flare spectrum from the rise phase of a secondary flare, which occurred during the decay of a much larger flare. The newly formed flare emission resembles the spectrum of an early-type star, with the Balmer lines and continuum in absorption. We model this observation phenomonologically as a temperature bump (hot spot) near the photosphere of the M dwarf. The amount of heating implied by our model (\Delta T_phot ~ 16,000K) is far more than predicted by chromospheric backwarming in current 1D RHD flare models (\Delta T_phot ~ 1200K).
SYMMETRY OF BOUND AND ANTIBOUND STATES IN THE SEMICLASSICAL LIMIT FOR A GENERAL CLASS OF POTENTIALS

We consider the Schrodinger operator −h 2 @ 2 + V (x) on a half-line, where V is a compactly supported potential which is positive near the endpoint of its support. We prove that the eigenvalues and the purely imaginary resonances are symmetric up to an error Ce �/h . In this paper, we study spectral properties of the Schrodinger oper- ator P(h) = −h 2 @ 2 x +V (x) defined for x in the half-line (−1 ,B). Here h > 0 is the semiclassical parameter and V (x) is a piecewise continuous real-valued potential supported in (0,B). The operator P(h) with the Neumann boundary condition at B is self-adjoint on L 2 (−1 ,B); therefore, its resolvent
Supervised Learning of the Global Risk Network Activation from Media Event Reports

The World Economic Forum (WEF) publishes annual reports of global risks which have the high impact on the world’s economy. Currently, many researchers analyze the modeling and evolution of risks. However, few studies focus on validation of the global risk networks published by the WEF. In this paper, we first create a risk knowledge graph from the annotated risk events crawled from the Wikipedia. Then, we compare the relational dependencies of risks in the WEF and Wikipedia networks and find that they share over 50% of their edges. Moreover, the edges unique to each network signify the different perspectives of the experts and the public on global risks. To reduce the cost of manual annotation of events triggering risk activation, we build an auto-detection tool which filters out over 80% media reported events unrelated to the global risks. In the process of filtering, our tool also continuously learns keywords relevant to global risks from the event sentences. Using locations of events extracted from the risk knowledge graph, we find characteristics of geographical distributions of the categories of global risks.
Thermal tunability in terahertz metamaterials fabricated on strontium titanate single-crystal substrates

We report an experimental demonstration of thermal tuning of resonance frequency in a planar terahertz metamaterial consisting of a gold split-ring resonator array fabricated on a bulk single-crystal strontium titanate (SrTiO₃) substrate. Cooling the metamaterial starting from 409 K down to 150 K causes about a 43% shift in resonance frequency, and there is very little variation in resonance strength. The resonance shift is due to the temperature-dependent dielectric constant of the strontium titanate. The experiment opens up avenues for designing tunable terahertz devices by exploiting the temperature-sensitive characteristic of high dielectric constant substrates and complex metal oxide materials.
Triaxial Black Hole Nuclei

We demonstrate that the nuclei of galaxies containing supermassive black holes can be triaxial in shape. Schwarzschild's method was first used to construct self-consistent orbital superpositions representing nuclei with axis ratios of 1 : 0.79 : 0.5 and containing a central point mass representing a black hole. Two different density laws were considered: ρ ∝ r-γ and γ = {1, 2}. We constructed two solutions for each γ: one containing only regular orbits and the other containing both regular and chaotic orbits. Monte Carlo realizations of the models were then advanced in time using an N-body code to verify their stability. All four models were found to retain their triaxial shapes for many crossing times. The possibility that galactic nuclei may be triaxial complicates the interpretation of stellar kinematical data from the centers of galaxies and may alter the inferred interaction rates between stars and supermassive black holes.
Fabrication of GaNxAs1−x Quantum Structures by Focused Ion Beam Patterning

A novel approach to the fabrication of GaNxAs1−x quantum dots and wires via ion beam patterning is presented. Photomodulated reflectance spectra confirm that N can be released from the As sublattice of an MBE‐grown GaNxAs1−x film by amorphization through ion implantation followed by regrowth upon rapid thermal annealing (RTA). Amorphization may be achieved with a focused ion beam (FIB), which is used to implant Ga ions in patterned lines such that annealing produces GaAs regions within a GaNxAs1−x film. The profiles of these amorphized lines are dependent upon the dose implanted, and the film reaches a damage threshold during RTA due to excess Ga. By altering the FIB implantation pattern, quantum dots or wires may be fabricated.
Long-time behavior of 3–dimensional Ricci flow : introduction

In the following series of papers we analyze the long-time behavior of 3–dimensional Ricci flows with surgery. Our main result will be that if the surgeries are performed correctly, then only finitely many surgeries occur and after some time the curvature is bounded by Ct−1. This result confirms a conjecture of Perelman. In the course of the proof, we also obtain a qualitative description of the geometry as t→∞.
Correcting 100 Years of Misunderstanding: Electric Fields in Superconductors, Hole Superconductivity, and the Meissner Effect

From the outset of superconductivity research it was assumed that no electrostatic fields could exist inside superconductors, and this assumption was incorporated into conventional London electrodynamics. Yet the London brothers themselves initially (in 1935) had proposed an electrodynamic theory of superconductors that allowed for static electric fields in their interior, which they unfortunately discarded a year later. I argue that the Meissner effect in superconductors necessitates the existence of an electrostatic field in their interior, originating in the expulsion of negative charge from the interior to the surface when a metal becomes superconducting. The theory of hole superconductivity predicts this physics, and associated with it a macroscopic spin current in the ground state of superconductors (“Spin Meissner effect”), qualitatively different from what is predicted by conventional BCS–London theory. A new London-like electrodynamic description of superconductors is proposed to describe this physics. Within this theory superconductivity is driven by lowering of quantum kinetic energy, the fact that the Coulomb repulsion strongly depends on the character of the charge carriers, namely whether electron- or hole-like, and the spin–orbit interaction. The electron–phonon interaction does not play a significant role, yet the existence of an isotope effect in many superconductors is easily understood. In the strong coupling regime, the theory appears to favor local charge inhomogeneity. The theory is proposed to apply to all superconducting materials, from the elements to the high T c cuprates and pnictides, is highly falsifiable, and explains a wide variety of experimental observations.
STELLAR POPULATIONS AND THE STAR FORMATION HISTORIES OF LSB GALAXIES. V. WFC3 COLOR–MAGNITUDE DIAGRAMS

We present WFC3 observations of three low surface brightness (LSB) galaxies from the Schombert et al. LSB catalog that are within 11 Mpc of the Milky Way. Deep imaging at F336W, F555W, and F814W allow the construction of the V ? I color?magnitude diagrams (CMD) to MI = ?2. Overall 1869, 465, and 501 stellar sources are identified in the three LSB galaxies F415-3, F608-1, and F750-V1, respectively. The spatial distribution of young blue stars matches the H? maps from ground-based imaging, indicating that star formation in LSB galaxies follows the same style as in other irregular galaxies. Several star complexes are identified, matching regions of higher surface brightness as seen from ground-based imaging. The CMD for each LSB galaxy has a similar morphology to Local Volume (LV) dwarf galaxies (i.e., a blue main sequence, blue and red He burning branches, and asymptotic giant branch (AGB) stars). The LSB CMD?s distinguish themselves from nearby dwarf CMD?s by having a higher proportion of blue main sequence stars and fewer AGB stars than expected from their mean metallicities. Current [Fe/H] values below ?0.6 are deduced from the position of the red helium-burning branch (rHeB) stars in the V ? I diagram. The distribution of stars on the blue helium-burning branch (bHeB) and rHeB from the U ? V and V ? I CMD indicate a history of constant star formation for the last 100 Myr.
Transformation inverse design.

We present a new technique for the design of transformation-optics devices based on large-scale optimization to achieve the optimal effective isotropic dielectric materials within prescribed index bounds, which is computationally cheap because transformation optics circumvents the need to solve Maxwell’s equations at each step. We apply this technique to the design of multimode waveguide bends (realized experimentally in a previous paper) and mode squeezers, in which all modes are transported equally without scattering. In addition to the optimization, a key point is the identification of the correct boundary conditions to ensure reflectionless coupling to untransformed regions while allowing maximum flexibility in the optimization. Many previous authors in transformation optics used a certain kind of quasiconformal map which overconstrained the problem by requiring that the entire boundary shape be specified a priori while at the same time underconstraining the problem by employing “slipping” boundary conditions that permit unwanted interface reflections.
The Solar Wind Environment in Time

We use magnetograms of 8 solar analogues of ages 30~Myr to 3.6~Gyr obtained from Zeeman Doppler Imaging (ZDI) and taken from the literature, together with two solar magnetograms, to drive magnetohydrodynamical (MHD) wind simulations and construct an evolutionary scenario of the solar wind environment and its angular momentum loss rate. With observed magnetograms of the radial field strength as the only variant in the wind model, we find that power law model fitted to the derived angular momentum loss rate against time, $t$, results in a spin down relation $\Omega\propto t^{-0.51}$, for angular speed $\Omega$, which is remarkably consistent with the well-established Skumanich law $\Omega\propto t^{-0.5}$. We use the model wind conditions to estimate the magnetospheric standoff distances for an Earth-like test planet situated at 1~AU for each of the stellar cases, and to obtain trends of minimum and maximum wind ram pressure and average ram pressure in the solar system through time. The wind ram pressure declines with time as $\overline{P_{ram}}\propto t^{2/3}$, amounting to a factor of 50 or so over the present lifetime of the solar system.
Measures of Complexity for Large Scale Image Datasets

Large scale image datasets are a growing trend in the field of machine learning. However, it is hard to quantitatively understand or specify how various datasets compare to each other - i.e., if one dataset is more complex or harder to “learn” with respect to a deep-learning based network. In this work, we build a series of relatively computationally simple methods to measure the complexity of a dataset. Furthermore, we present an approach to demonstrate visualizations of high dimensional data, in order to assist with visual comparison of datasets. We present our analysis using four datasets from the autonomous driving research community - Cityscapes, IDD, BDD and Vistas. Using entropy based metrics, we present a rank-order complexity of these datasets, which we compare with an established rank-order with respect to deep learning.
Ridge regression and asymptotic minimax estimation over spheres of growing dimension

We study asymptotic minimax problems for estimating a $d$-dimensional regression parameter over spheres of growing dimension ($d\to\infty$). Assuming that the data follows a linear model with Gaussian predictors and errors, we show that ridge regression is asymptotically minimax and derive new closed form expressions for its asymptotic risk under squared-error loss. The asymptotic risk of ridge regression is closely related to the Stieltjes transform of the Marcenko–Pastur distribution and the spectral distribution of the predictors from the linear model. Adaptive ridge estimators are also proposed (which adapt to the unknown radius of the sphere) and connections with equivariant estimation are highlighted. Our results are mostly relevant for asymptotic settings where the number of observations, $n$, is proportional to the number of predictors, that is, $d/n\to\rho\in(0,\infty)$.
On the kurtosis of deep-water gravity waves

In this paper, we revisit Janssen’s (J. Phys. Oceanogr., vol. 33 (4), 2003, pp. 863–884) formulation for the dynamic excess kurtosis of weakly nonlinear gravity waves in deep water. For narrowband directional spectra, the formulation is given by a sixfold integral that depends upon the Benjamin–Feir index and the parameter , a measure of short-crestedness for the dominant waves, with and denoting spectral bandwidth and angular spreading. Our refinement leads to a new analytical solution for the dynamic kurtosis of narrowband directional waves described with a Gaussian-type spectrum. For multidirectional or short-crested seas initially homogeneous and Gaussian, in a focusing (defocusing) regime dynamic kurtosis grows initially, attaining a positive maximum (negative minimum) at the intrinsic time scale , or , where denotes the dominant angular frequency. Eventually the dynamic excess kurtosis tends monotonically to zero as the wave field reaches a quasi-equilibrium state characterized by nonlinearities mainly due to bound harmonics. Quasi-resonant interactions are dominant only in unidirectional or long-crested seas where the longer-time dynamic kurtosis can be larger than that induced by bound harmonics, especially as the Benjamin–Feir index increases. Finally, we discuss the implication of these results for the prediction of rogue waves.
String melting in a photon bath

We compute the decay rate of a metastable cosmic string in contact with a thermal bath by finding the instanton solution. The new feature is that this decay rate is found in the context of non thermal scalar fields in contact with a thermal bath of photons. In general, to make topologically unstable strings stable, one can couple them to such a bath. The resulting plasma effect creates metastable configurations which can decay from the false vacuum to the true vacuum. In our specific set-up, the instanton computation is realized for the case of two out-of-equilibrium complex scalar fields: one is charged and coupled to the photon field, and the other is neutral. New effects coming from the thermal bath of photons make the radius of the nucleated bubble and most of the relevant physical quantities temperature-dependent. However, the temperature appears in a different way than in the purely thermal case, where all scalar fields are in thermal equilibrium. As a result of the tunneling, the core of the initial string melts while bubbles of true vacuum expand at the speed of light.
Synthesis of mixed hypermetallic oxide BaOCa+ from laser-cooled reagents in an atom-ion hybrid trap

Hypermetallic alkaline earth (M) oxides of formula MOM have been studied under plasma conditions that preclude insight into their formation mechanism. We present here the application of emerging techniques in ultracold physics to the synthesis of a mixed hypermetallic oxide, BaOCa+. These methods, augmented by high-level electronic structure calculations, permit detailed investigation of the bonding and structure as well as the mechanism of its formation via the barrierless reaction of Ca (3PJ) with BaOCH3+. Further investigations of the reaction kinetics as a function of collision energy over the range 0.005 kelvin (K) to 30 K and of individual Ca fine-structure levels compare favorably with calculations based on long-range capture theory.
Exact solution of the Landau–Lifshitz equations for a radiating charged particle in the Coulomb potential

Abstract We solve exactly the classical non-relativistic Landau–Lifshitz equations of motion for a charged particle moving in a Coulomb potential, including radiation damping. The general solution involves the Painleve transcendent of type II. It confirms our physical intuition that a negatively charged classical particle will spiral into the nucleus, supporting the validity of the Landau–Lifshitz equation.
Hypermodular self-assembling space solar power — Design option for mid-term GEO utility-scale power plants

This paper presents a design for scaleable space solar power systems based on free-flying reflectors and module self-assembly. Lower system cost of utility-scale space solar power is achieved by design independence of yet-to-be-built in-space assembly or transportation infrastructure. Using current and expected near-term technology, this study describe a design for mid-term utility-scale power plants in geosynchronous orbits. High-level economic considerations in the context of current and expected future launch costs are given as well.
Benefit or burden? A comparison of CFO and CEO outside directorships

We study the association between chief financial officer (CFO), compared to chief executive officer (CEO), outside board directorships and their home firm strategic investments, capital management, and overall performance. Using a sample of firms from 2003-2014, we find only about nine percent of CFOs sit on outside boards, while about 24 percent of CEOs sit on outside boards. We find robust evidence that CFO outside directorships are associated with fewer underinvestment problems, lower sensitivity between cash holdings and cash flows, and higher long-term performance at their home firm, consistent with positive knowledge transfer by the CFO. On the other hand, we find little evidence of knowledge transfer for CEO outside board directorships, consistent with concerns that executives are too busy to hold outside directorships. Our findings support a need to recognize that outside directorships could provide benefits for some, but not all, executives. For CFOs our findings support the argument that outside directorships provide CFOs an opportunity to network with and learn from other executives and directors, enabling these CFOs to improve practices in their home firm.
Captioning Images Taken by People Who Are Blind.

While an important problem in the vision community is to design algorithms that can automatically caption images, few publicly-available datasets for algorithm development directly address the interests of real users. Observing that people who are blind have relied on (human-based) image captioning services to learn about images they take for nearly a decade, we introduce the first image captioning dataset to represent this real use case. This new dataset, which we call VizWiz-Captions, consists of over 39,000 images originating from people who are blind that are each paired with five captions. We analyze this dataset to (1) characterize the typical captions, (2) characterize the diversity of content found in the images, and (3) compare its content to that found in eight popular vision datasets. We also analyze modern image captioning algorithms to identify what makes this new dataset challenging for the vision community. We publicly-share the dataset with captioning challenge instructions at https://vizwiz.org.
Distributed quantum sensing

A plethora of applications hinge on a network or an array of sensors to undertake measurement tasks. A rule of thumb for sensing is that a collective measurement taken by $M$ independent sensors can improve the sensitivity by $1/\sqrt{M}$, known as the standard quantum limit (SQL). Quantum resources such as entanglement and squeezed light can be harnessed to surpass the SQL. Distributed quantum sensing is an emerging subject dedicated to investigating the performance gain enabled by entangled states shared by multiple sensors in tackling different measurement problems. This Review formulates distributed quantum sensing from a quantum-information perspective and describes distributed quantum sensing protocols and their experimental demonstrations. The applications enabled by distributed quantum sensing and an outlook for future opportunities will also be discussed.
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information

Graph neural networks (GNNs) have shown great power in modeling graph structured data. However, similar to other machine learning models, GNNs may make predictions biased on protected sensitive attributes, e.g., skin color and gender. Because machine learning algorithms including GNNs are trained to reflect the distribution of the training data which often contains historical bias towards sensitive attributes. In addition, the discrimination in GNNs can be magnified by graph structures and the message-passing mechanism. As a result, the applications of GNNs in sensitive domains such as crime rate prediction would be largely limited. Though extensive studies of fair classification have been conducted on i.i.d data, methods to address the problem of discrimination on non-i.i.d data are rather limited. Furthermore, the practical scenario of sparse annotations in sensitive attributes is rarely considered in existing works. Therefore, we study the novel and important problem of learning fair GNNs with limited sensitive attribute information. FairGNN is proposed to eliminate the bias of GNNs whilst maintaining high node classification accuracy by leveraging graph structures and limited sensitive information. Our theoretical analysis shows that FairGNN can ensure the fairness of GNNs under mild conditions given limited nodes with known sensitive attributes. Extensive experiments on real-world datasets also demonstrate the effectiveness of FairGNN in debiasing and keeping high accuracy.
How Effective is Model Predictive Control in Real‐Time Water Quality Regulation? State‐Space Modeling and Scalable Control

Real-time water quality control (WQC) in water distribution networks (WDN), the problem of regulating disinfectant levels, is challenging due to lack of (i) a proper control-oriented modeling considering complicated components (junctions, reservoirs, tanks, pipes, pumps, and valves) for water quality modeling in WDN and (ii) a corresponding scalable control algorithm that performs real-time water quality regulation. In this paper, we solve the WQC problem by (a) proposing a novel state-space representation of the WQC problem that provides an explicit relationship between inputs (chlorine dosage at booster stations) and states/outputs (chlorine concentrations in the entire network) and (b) designing a highly scalable model predictive control (MPC) algorithm that showcases fast response time and resilience against some sources of uncertainty.
Learning-to-Fly: Learning-based Collision Avoidance for Scalable Urban Air Mobility

With increasing urban population, there is global interest in Urban Air Mobility (UAM), where hundreds of autonomous Unmanned Aircraft Systems (UAS) execute missions in the airspace above cities. Unlike traditional human-in-the-loop air traffic management, UAM requires decentralized autonomous approaches that scale for an order of magnitude higher aircraft densities and are applicable to urban settings. We present Learning-to-Fly (L2F), a decentralized on-demand airborne collision avoidance framework for multiple UAS that allows them to independently plan and safely execute missions with spatial, temporal and reactive objectives expressed using Signal Temporal Logic. We formulate the problem of predictively avoiding collisions between two UAS without violating mission objectives as a Mixed Integer Linear Program (MILP). This however is intractable to solve online. Instead, we develop L2F, a two-stage collision avoidance method that consists of: 1) a learning-based decision-making scheme and 2) a distributed, linear programming-based UAS control algorithm. Through extensive simulations, we show the real-time applicability of our method which is $\approx 6000\times$ faster than the MILP approach and can resolve 100% of collisions when there is ample room to maneuver, and shows graceful degradation in performance otherwise. We also compare L2F to two other methods and demonstrate an implementation on quad-rotor robots.
A construction of infinitely many solutions to the Strominger system

In this paper we construct explicit smooth solutions to the Strominger system on generalized Calabi-Gray manifolds, which are compact non-Kahler Calabi-Yau 3-folds with infinitely many distinct topological types and sets of Hodge numbers.
Zeroth-order Feedback Optimization for Cooperative Multi-Agent Systems

We consider a class of multi-agent optimization problems, where each agent is associated with an action vector and a local cost that depends on the joint actions of all agents, and the goal is to minimize the average of the local costs. Such problems arise in many control applications such as wind farm operation and mobile sensor coverage. In many of these applications, while we have access to (zeroth-order) information about function values, it can be difficult to obtain (first-order) gradient information. In this paper, we propose a zeroth-order feedback optimization (ZFO) algorithm based on two-point gradient estimators for the considered class of problems, and provide the convergence rate to a first-order stationary point for nonconvex problems. We complement our theoretical analysis with numerical simulations on a wind farm power maximization problem.
Privacy-Preserving Resilience of Cyber-Physical Systems to Adversaries

A cyber-physical system (CPS) is expected to be resilient to more than one type of adversary. In this paper, we consider a CPS that has to satisfy a linear temporal logic (LTL) objective in the presence of two kinds of adversaries. The first adversary has the ability to tamper with inputs to the CPS to influence satisfaction of the LTL objective. The interaction of the CPS with this adversary is modeled as a stochastic game. We synthesize a controller for the CPS to maximize the probability of satisfying the LTL objective under any policy of this adversary. The second adversary is an eavesdropper who can observe labeled trajectories of the CPS generated from the previous step. It could then use this information to launch other kinds of attacks. A labeled trajectory is a sequence of labels, where a label is associated to a state and is linked to the satisfaction of the LTL objective at that state. We use differential privacy to quantify the indistinguishability between states that are related to each other when the eavesdropper sees a labeled trajectory. Two trajectories of equal length will be differentially private if they are differentially private at each state along the respective trajectories. We use a skewed Kantorovich metric to compute distances between probability distributions over states resulting from actions chosen according to policies from related states in order to quantify differential privacy. Moreover, we do this in a manner that does not affect the satisfaction probability of the LTL objective. We validate our approach on a simulation of a UAV that has to satisfy an LTL objective in an adversarial environment.
Fiscal increasing returns, hysteresis, real wages and unemployment

European unemployment is widely regarded as a problem of excessive real wages. This view as it is usually expressed carries the disturbing implication that there is a sharp conflict between the interests of those currently employed and the unemployed because it suggests that increases in employment will require reductions in the real wages of those currently employed. The first part of this paper shows that increases in employment in Europe are likely to be associated with rising real take-home pay for workers because of fiscal increasing returns. Increases in employment and output will make possible reductions in taxes sufficiently large to offset any effects of diminishing returns to labor. The second part of the paper considers alternative explanations for the failure of nominal wages to adjust so as to restore full employment and their implications for the efficacy of fiscal policies. It concludes that under a variety of plausible conditions tax cuts would succeed in stimulating employment.
Ego depletion and auditors’ JDM quality

Abstract I report two experiments with senior-associate auditors that investigate whether selfcontrol requirements in auditing tasks cause ego depletion, and whether depleting tasks impact auditors' judgment and decision-making (JDM). In Experiment 1, I find that using self-control to maintain vigilance/focus leads to greater levels of depletion than does using self-control to engage in cognitive processing in an audit planning task or inhibit impulses in a task from the psychology literature. However, I do not find that task-specific experience significantly reduces self-control resources required for task performance. In Experiment 2, I find evidence that depleting tasks – compared to a non-depleted control group –significantly reduce auditors’ cognitive processing in the form of auditors’ ability to generate plausible alternative hypotheses for client-provided explanations for trends. Finally, I find that depleting tasks reduce auditors’ confidence in task performance, when compared to a non-depleted control group.
Securitization in China: Déjà Vu?

In China, securitization has been promoted as a means of reducing reliance on the shadow banking system and ensuring that enough credit keeps flowing to a slowing economy. A cure for China?s banking woes may, in fact, be the instrument that nearly brought down the global financial system—securitized products. The author examines the history and structure of the Chinese securitization market. Whereas the U.S. securitization market developed as a means to accelerate liquidity, the Chinese securitization market was initially established to deal with non-performing loans. The article discusses the pre- and post-2008 Chinese securitization market and provides an overview of newer securitized products being introduced to China in an effort to boost confidence in the banking sector.
Cyberspace as place and the tragedy of the digital anticommons

Cyberspace was once thought to be the modern equivalent of the Western Frontier, a place where land was free for the taking. This is true no longer. This Article argues that we are enclosing cyberspace and imposing private property conceptions upon it. As a result, we are creating a digital anticommons where suboptimal use of Internet resources will be the norm. Part I shows why initial discussions of the CYBERSPACE AS PLACE metaphor have confused the descriptive question of how we think about cyberspace with the normative question of how we should regulate cyberspace. It suggests that we can bracket the normative question and still answer the descriptive question of whether we think of cyberspace as a place. Part II examines the lessons of recent cognitive science studies, and demonstrates the importance of physical metaphors within our cognitive system. It then reviews the evidence of our use of the physical metaphor, CYBERSPACE AS PLACE, in understanding online communication environments. Part III focuses on this metaphor's unacknowledged and unrecognized influence on the development of the legal framework for the Internet. It examines tortious, criminal, and constitutional law responses to cyberspace, and concludes that the CYBERSPACE AS PLACE metaphor exercises a strong and unrecognized influence on the regulatory regimes of cyberspace. Part IV details why the effects of that metaphor's use - including the idea that there is property online, and that this property should be privately owned, parceled out, and exploited - are extremely troubling. Though private ownership of resources is not itself problematic, it can lead to the opposite of the tragedy of the commons: the tragedy of the anticommons. Anticommons property occurs when multiple parties have an effective right to prevent others from using a given resource, and as a result no one has an effective right of use. Part IV argues that this is precisely where the CYBERSPACE AS PLACE metaphor leads. We are moving towards a digital anticommons, where no one will be allowed to access competitors' cyberspace "assets" without a license or other transactionally expensive or impossible permission mechanism. This Article explains how the CYBERSPACE AS PLACE metaphor leads to undesirable private control of the previously commons-like Internet and the emergence of a digital anticommons. As we all stake out our little claims in cyberspace, we destroy the cyberspace commons.
The Creativity Mystique and the Rhetoric of Mood Disorders

Many contemporary scientific researchers are interested in drawing associations between mental illness and creativity. These studies have contributed to the popular image of the "mad genius," an image whose history stretches back as far as Plato and Aristotle. Recently, a new rhetorical manifestation of the mad genius image has emerged, what I call the creativity mystique of mood disorders. The creativity mystique, a product of the era of modern psychiatry, suggests not only that mood disorders are sources of creative genius, but also that medical treatment should take patient creativity into account. The texts I study here demonstrate a rhetorical shift from arguments for correlation between mood disorders and creativity (in the most conservative of the studies, published for traditional scientific audiences), to arguments for a causal link from mood disorders to creativity (most prevalent in fringe literature texts and pop-science texts), to arguments for inverse-causation, that is, a causal link from creativity to mood disorders (only found in fringe literature and pop-science texts). These arguments shift from more conservative to more controversial as the intended audience of the writing shifts from the scientific to the lay. As I demonstrate below, this rhetorical shift reveals how the creativity mystique has influenced research, diagnoses, and treatment of mood disorders.
Illicit drug use and educational attainment

This paper uses data from the National Education Longitudinal Study to estimate the association between illicit drug use during high school and the number of years of schooling completed. The analysis accounts for the possibility that drug use is endogenous using two methods: (1) by controlling for individual-level characteristics measured before high school entrance; and (2) by using an instrumental variables method, with state drug policies and 8th grade school characteristics as identifying variables. Findings suggest that marijuana use and cocaine use in high school are associated with reductions in the number of years of schooling completed.
The Challenges of Achieving Open-Source Sharing of Biobank Data

Several recent biomedical research initiatives have sought to make their data freely accessible to others to stimulate innovation. Many of these initiatives have adopted the “open source” model that has achieved prominence in the computing industry. With respect to genomics research, open access models of data release have become common and most large funding bodies now require researchers to deposit their data in centralized repositories. In particular, biobanks, which are organised collections of biological samples and corresponding data, benefit from the implementation of open source principles. Several obstacles loom, however, as barriers to widespread implementation of open source principles in the field of biomedical research. These include the reluctance among researchers to share their data; the challenge of crafting appropriate publication and intellectual property policies; the difficulties in affording informed consent, privacy, and confidentiality to research participants when data is shared so widely; controversy surrounding the issues of commercialization and benefit-sharing; and the complexity of establishing a suitable infrastructure. This article examines each of these and considers an alternative approach, “fair access” biobanks.
Reconsidering the Harvard Medical Practice Study conclusions about the validity of medical malpractice claims.

Over fifteen years after first reporting to the State of New York, the Harvard Medical Practice Study (HMPS) continues to have a significant impact in medical malpractice policy debates. In those debates the HMPS has come to stand for four main propositions. First, "medical injury . . . accounts for more deaths than all other kinds of accidents combined" and "more than a quarter of those were caused by substandard care." Second, the vast majority of people who are injured as a result of substandard care do not file a claim. Third, "a substantial majority of malpractice claims filed are not based on provider carelessness or even iatrogenic injury." Fourth, "whether negligence or a medical injury had occurred . . . bore little relation to the outcome of the claims." In light of this continuing reliance on the HMPS and the follow-up closed claim study, this article reviews the evidence regarding their findings about the validity of medical malpractice claims. The results of this review are as follows: First, the finding that most eligible people do not bring medical malpractice claims is well supported and confirmed by other studies using both similar and very different research methods. Second, the finding that most medical malpractice claims are not based on either iatrogenic injury or provider negligence stands on a small and precarious empirical base. Indeed, the HMPS data are as likely to support a very different finding, namely that most malpractice claims are reasonably related to medical management injuries and provider negligence. Finally, the finding from the follow-up closed claim study rests on an even weaker base and is contradicted by a large body of research on closed medical malpractice claims. In fact, the research reviewed in part IIIB of this article suggests that the legal system filters out most of the weaker claims.
The theory of trade policy and trade agreements: A critique

During the past half century multilateral trade liberalization has reduced tariffs to historically low levels. The Received Theory of trade policy, based solely on terms-of-trade externalities between national governments, offers an explanation that has become the conventional wisdom among international trade theorists. This paper uses a simple version of the Grossman–Helpman Protection-for-Sale Model (a central example of the Received Theory) to examine the consistency of the implications of this theory with actual trade policy. The conclusion is that the theory is dramatically inconsistent with reality. Furthermore, terms-of-trade externalities — the central component of the Received Theory — are the sole cause of this inconsistency. Empirical work seeming to confirm the Protection-for-Sale model actually does not do that, but instead offers support for a generic political-economy view of trade policy.
Low quality as a signal of high quality

If a product has two dimensions of quality, one observable and one not, a firm can use observable quality as a signal of unobservable quality. The correlation between consumers' valuation of high quality in each dimension is a key determinant of the feasibility of such signaling. A firm may use price alone as a signal, or price and quality together. Both signals tend to be used when the market is very uninformed, whereas price signaling alone tends to be used when the market is moderately informed. If high observable quality is inexpensive to provide, then it cannot signal high unobservable quality, and low observable quality is always an indication that unobservable quality is high.
The Microstructure of the “Flash Crash”: Flow Toxicity, Liquidity Crashes, and the Probability of Informed Trading

The “flash crash” of May 6, 2010, was the second-largest point swing (1,010.14 points) and the biggest one-day point decline (998.5 points) in the history of the Dow Jones Industrial Average. For a few minutes, $1 trillion in market value vanished. In this article, the authors argue that the flash crash was the result of the new dynamics at play in the current market structure. They highlight the role played by order toxicity in affecting liquidity provision, and they show that a measure of this toxicity, the volume synchronized probability of informed trading (VPIN), captures the increasing toxicity of the order flow in the hours and days prior to collapse. Because the flash crash might have been avoided had liquidity providers remained in the marketplace, a solution is proposed in the form of a “VPIN contract” that would allow liquidity providers to dynamically monitor and manage their risks.