cssi/SciSciGPT-SciSciNet huggingface dataset:
Quantitative Bi-Lipschitz embeddings of bounded curvature manifolds and orbifolds

We construct bi-Lipschitz embeddings into Euclidean space for bounded-diameter subsets of manifolds and orbifolds of bounded curvature. The distortion and dimension of such embeddings is bounded by diameter, curvature and dimension alone. We also construct global bi-Lipschitz embeddings for spaces of the form ℝ n ∕ Γ , where Γ is a discrete group acting properly discontinuously and by isometries on ℝ n . This generalizes results of Naor and Khot. Our approach is based on analyzing the structure of a bounded-curvature manifold at various scales by specializing methods from collapsing theory to a certain class of model spaces. In the process, we develop tools to prove collapsing theory results using algebraic techniques.
Efficient Computation of Power, Force, and Torque in BEM Scattering Calculations

We present concise, computationally efficient formulas for several quantities of interest—including absorbed and scattered power, optical force (radiation pressure), and torque—in scattering calculations performed using the boundary-element method (BEM) [also known as the method of moments (MoM)]. Our formulas compute the quantities of interest directly from the BEM surface currents with no need ever to compute the scattered electromagnetic fields. We derive our new formulas and demonstrate their effectiveness by computing power, force, and torque (PFT) in a number of example geometries. Free, open-source software implementations of our formulas are available for download online.
The topology of toric symplectic manifolds

This is a collection of results on the topology of toric symplectic manifolds. Using an idea of Borisov, we show that a closed symplectic manifold supports at most a finite number of toric structures. Further, the product of two projective spaces of complex dimension at least two (and with a standard product symplectic form) has a unique toric structure. We then discuss various constructions, using wedging to build a monotone toric symplectic manifold whose center is not the unique point displaceable by probes, and bundles and blow ups to form manifolds with more than one toric structure. The bundle construction uses the McDuff–Tolman concept of mass linear function. Using Timorin’s description of the cohomology algebra via the volume function we develop a cohomological criterion for a function to be mass linear, and explain its relation to Shelukhin’s higher codimension barycenters.
Quantum Mechanics in Phase Space

Ever since Werner Heisenberg's 1927 paper on uncertainty, there has been considerable hesitancy in simultaneously considering positions and momenta in quantum contexts, since these are incompatible observables. But this persistent discomfort with addressing positions and momenta jointly in the quantum world is not really warranted, as was first fully appreciated by Hilbrand Groenewold and Jose Moyal in the 1940s. While the formalism for quantum mechanics in phase space was wholly cast at that time, it was not completely understood nor widely known — much less generally accepted — until the late 20th century.
Linear-Sample Learning of Low-Rank Distributions

Many latent-variable applications, including community detection, collaborative filtering, genomic analysis, and NLP, model data as generated by low-rank matrices. Yet despite considerable research, except for very special cases, the number of samples required to efficiently recover the underlying matrices has not been known. We determine the onset of learning in several common latent-variable settings. For all of them, we show that learning $k\times k$, rank-$r$, matrices to normalized $L_{1}$ distance $\epsilon$ requires $\Omega(\frac{kr}{\epsilon^2})$ samples, and propose an algorithm that uses ${\cal O}(\frac{kr}{\epsilon^2}\log^2\frac r\epsilon)$ samples, a number linear in the high dimension, and nearly linear in the, typically low, rank. The algorithm improves on existing spectral techniques and runs in polynomial time. The proofs establish new results on the rapid convergence of the spectral distance between the model and observation matrices, and may be of independent interest.
Electronic properties of the FeSe/STO interface from first-principle calculations

We perform first-principle calculations of the FeSe monolayer on STO with the focus on three central aspects. First, compared to experiment, the bulk lattice constant of FeSe is too small in LDA, PBEsol and Perdew–Burgke–Ernzerhof (PBE) type exchange-correlation (xc) functionals while in bulk SrTiO3 (STO) LDA over-binds, PBE under-binds and PBEsol agrees best with experiment. Thus, the strain in the FeSe monolayer on STO depends on the xc functional and, especially in the non-magnetic state, is strongly overestimated and best described in PBEsol. In agreement with earlier work, we find that the band structure of the checkerboard antiferromagnetic configuration agrees best with experiment where, in addition, the relative strain on FeSe is best described. Second, our focus is on the crystal structure of the interface itself. The FeSe/STO distance depends weakly on the presence of magnetism and PBE results agree best with recent experimental data. We find that a double -layer below the FeSe relaxes to a structure in disagreement with experimental data. On the other hand, considering the effect of oxygen-vacancies in the single terminated slab within the virtual crystal approximation, in agreement with recent experiment, the FeSe monolayer Ti layer distance increases for a small vacancy concentration (<20%). Third, we investigate the charge-transfer to FeSe due to oxygen-vacancies in STO. Interestingly, we find negligible charge transfer for small concentrations—only above 20% a significant charge transfer is observed.
Stochastic homogenization of viscous superquadratic Hamilton–Jacobi equations in dynamic random environment

We study the qualitative homogenization of second-order Hamilton–Jacobi equations in space-time stationary ergodic random environments. Assuming that the Hamiltonian is convex and superquadratic in the momentum variable (gradient), we establish a homogenization result and characterize the effective Hamiltonian for arbitrary (possibly degenerate) elliptic diffusion matrices. The result extends previous work that required uniform ellipticity and space-time homogeneity for the diffusion.
Fitting the HiRes Spectra and Monocular Composition

In the first section, we discuss our fits to the latest HiRes monocular spectra. We find that the best fit for the extragalactic component has a spectral index of γ = -2.38±0.04 with a distribution of sources varying with a evolution parameter m = 2.8 ± 0.3. In the second section, we discuss preliminary results from a new composition measurement using HiRes monocular data. We find a predominantly light spectrum above 1017.6 eV.
Time-Reversal Symmetry, Anomalies, and Dualities in (2+1)$d$

We study continuum quantum field theories in 2+1 dimensions withtime-reversal symmetry $\cal T$. The standard relation ${\cal T}^2=(-1)^F$ issatisfied on all the "perturbative operators" i.e. polynomials in thefundamental fields and their derivatives. However, we find that it is often thecase that acting on more complicated operators ${\cal T}^2=(-1)^F {\cal M}$with $\cal M$ a non-trivial global symmetry. For example, acting on monopoleoperators, $\cal M$ could be $\pm1$ depending on the magnetic charge. We studyin detail $U(1)$ gauge theories with fermions of various charges. Such amodification of the time-reversal algebra happens when the number of odd chargefermions is $2 ~{\rm mod}~4$, e.g. in QED with two fermions. Our work alsoclarifies the dynamics of QED with fermions of higher charges. In particular,we argue that the long-distance behavior of QED with a single fermion of charge$2$ is a free theory consisting of a Dirac fermion and a decoupled topologicalquantum field theory. The extension to an arbitrary even charge isstraightforward. The generalization of these abelian theories to $SO(N)$ gaugetheories with fermions in the vector or in two-index tensor representationsleads to new results and new consistency conditions on previously suggestedscenarios for the dynamics of these theories. Among these new results is asurprising non-abelian symmetry involving time-reversal.
Design Algorithms of Driving-Induced Nonreciprocal Components

In the quest for ultimate control of wave propagation, the authors propose a design scheme that allows them to efficiently construct reconfigurable nonreciprocal components with optimal performance and minimal structural complexity. The method utilizes an effective time-independent Hamiltonian formalism within the framework of Floquet-scattering engineering. It allows the user to design driving protocols with optimal nonreciprocal response. This scheme is applicable in a variety of physical settings, ranging from acoustics and thermal transport to electromagnetic and matter waves.
A principled approach to GraphQL query cost analysis

The landscape of web APIs is evolving to meet new client requirements and to facilitate how providers fulfill them. A recent web API model is GraphQL, which is both a query language and a runtime. Using GraphQL, client queries express the data they want to retrieve or mutate, and servers respond with exactly those data or changes. GraphQL’s expressiveness is risky for service providers because clients can succinctly request stupendous amounts of data, and responding to overly complex queries can be costly or disrupt service availability. Recent empirical work has shown that many service providers are at risk. Using traditional API management methods is not sufficient, and practitioners lack principled means of estimating and measuring the cost of the GraphQL queries they receive. In this work, we present a linear-time GraphQL query analysis that can measure the cost of a query without executing it. Our approach can be applied in a separate API management layer and used with arbitrary GraphQL backends. In contrast to existing static approaches, our analysis supports common GraphQL conventions that affect query cost, and our analysis is provably correct based on our formal specification of GraphQL semantics. We demonstrate the potential of our approach using a novel GraphQL query-response corpus for two commercial GraphQL APIs. Our query analysis consistently obtains upper cost bounds, tight enough relative to the true response sizes to be actionable for service providers. In contrast, existing static GraphQL query analyses exhibit over-estimates and under-estimates because they fail to support GraphQL conventions.
A new interpretation of three-dimensional particle geometry: M-A-V-L

Abstract This study provides a new interpretation of 3D particle geometry that unravels the ‘interrelation’ of the four geometry parameters, i.e., morphology M, surface area A, volume V, and size L, for which a new formula, M = A/V × L/6, is introduced to translate the 3D particle morphology as a function of surface area, volume, and size. The A/V × L of a sphere is invariably 6, which is placed in the denominator of the formula, and therefore M indicates a relative morphological irregularity compared to the sphere. The minimum possible value of M is clearly one, and M may range approximately to three for coarse-grained mineral particles. Furthermore, the proposed formula, M = A/V × L/6, enables to graphically preserve the four parameters’ relations when plotting the geometry parameter distributions. This study demonstrates the approach with two plot spaces that represent (i) L vs. M and (ii) A/V vs. V, where A/V works as the messenger between these two spaces as A/V = M/L × 6. Therefore, this approach helps comprehensively address the four-dimensional aspects of the 3D particle geometry and better understand the parameters’ combined influence on the mechanical behavior of granular materials.
Multi-robot Dubins Coverage with Autonomous Surface Vehicles

In large scale coverage operations, such as marine exploration or aerial monitoring, single robot approaches are not ideal, as they may take too long to cover a large area. In such scenarios, multi-robot approaches are preferable. Furthermore, several real world vehicles are non-holonomic, but can be modeled using Dubins vehicle kinematics. This paper focuses on environmental monitoring of aquatic environments using Autonomous Surface Vehicles (ASVs). In particular, we propose a novel approach for solving the problem of complete coverage of a known environment by a multi-robot team consisting of Dubins vehicles. It is worth noting that both multi-robot coverage and Dubins vehicle coverage are NP-complete problems. As such, we present two heuristics methods based on a variant of the traveling salesman problem-k-TSP-formulation and clustering algorithms that efficiently solve the problem. The proposed methods are tested both in simulations to assess their scalability and with a team of ASVs operating on a 200 km2 lake to ensure their applicability in real world.
Degree of irrationality of very general abelian surfaces

The degree of irrationality of a projective variety X is defined to be the smallest degree of a rational dominant map to a projective space of the same dimension. For abelian surfaces, Yoshihara computed this invariant in specific cases, while Stapleton gave a sublinear upper bound for very general polarized abelian surfaces ( A , L ) of degree d . Somewhat surprisingly, we show that the degree of irrationality of a very general polarized abelian surface is uniformly bounded above by 4, independently of the degree of the polarization. This result disproves part of a conjecture of Bastianelli, De Poi, Ein, Lazarsfeld, and Ullery.
The Circumgalactic Medium in Massive Halos

This chapter presents a review of the current state of knowledge on the cool (T ∼ 104 K) halo gas content around massive galaxies at z ≈ 0. 2–2. Over the last decade, significant progress has been made in characterizing the cool circumgalactic gas in massive halos of M h ≈ 1012–14 M⊙ at intermediate redshifts using absorption spectroscopy. Systematic studies of halo gas around massive galaxies beyond the nearby universe are made possible by large spectroscopic samples of galaxies and quasars in public archives. In addition to accurate and precise constraints for the incidence of cool gas in massive halos, detailed characterizations of gas kinematics and chemical compositions around massive quiescent galaxies at z ≈ 0. 5 have also been obtained. Combining all available measurements shows that infalling clouds from external sources are likely the primary source of cool gas detected at \(d\gtrsim 100\) kpc from massive quiescent galaxies. The origin of the gas closer in is currently less certain, but SNe Ia driven winds appear to contribute significantly to cool gas found at d < 100 kpc. In contrast, cool gas observed at \(d\lesssim 200\) kpc from luminous quasars appears to be intimately connected to quasar activities on parsec scales. The observed strong correlation between cool gas covering fraction in quasar host halos and quasar bolometric luminosity remains a puzzle. Combining absorption-line studies with spatially resolved emission measurements of both gas and galaxies is the necessary next step to address remaining questions.
A spectroscopic analysis of the galactic globular cluster NGC 6273 (M19)

A combined effort utilizing spectroscopy and photometry has revealed the existence of a new globular cluster class. These “anomalous” clusters, which we refer to as “iron-complex” clusters, are differentiated from normal clusters by exhibiting large (≳0.10 dex) intrinsic metallicity dispersions, complex sub-giant branches, and correlated [Fe/H] and s-process enhancements. In order to further investigate this phenomenon, we have measured radial velocities and chemical abundances for red giant branch stars in the massive, but scarcely studied, globular cluster NGC 6273. The velocities and abundances were determined using high resolution (R ∼ 27,000) spectra obtained with the Michigan/Magellan Fiber System (M2FS) and MSpec spectrograph on the Magellan–Clay 6.5 m telescope at Las Campanas Observatory. We find that NGC 6273 has an average heliocentric radial velocity of +144.49 km s−1 (σ = 9.64 km s−1) and an extended metallicity distribution ([Fe/H] = −1.80 to −1.30) composed of at least two distinct stellar populations. Although the two dominant populations have similar [Na/Fe], [Al/Fe], and [α/Fe] abundance patterns, the more metal-rich stars exhibit significant [La/Fe] enhancements. The [La/Eu] data indicate that the increase in [La/Fe] is due to almost pure s-process enrichment. A third more metal-rich population with low [X/Fe] ratios may also be present. Therefore, NGC 6273 joins clusters such as ω Centauri, M2, M22, and NGC 5286 as a new class of iron-complex clusters exhibiting complicated star formation histories.
SHOCKS AND THERMAL CONDUCTION FRONTS IN RETRACTING RECONNECTED FLUX TUBES

We present a model for plasma heating produced by time-dependent, spatially localized reconnection within a flare current sheet separating skewed magnetic fields. The reconnection creates flux tubes of new connectivity which subsequently retract at Alfvenic speeds from the reconnection site. Heating occurs in gas-dynamic shocks (GDSs) which develop inside these tubes. Here we present generalized thin flux tube equations for the dynamics of reconnected flux tubes, including pressure-driven parallel dynamics as well as temperature-dependent, anisotropic viscosity and thermal conductivity. The evolution of tubes embedded in a uniform, skewed magnetic field, following reconnection in a patch, is studied through numerical solutions of these equations, for solar coronal conditions. Even though viscosity and thermal conductivity are negligible in the quiet solar corona, the strong GDSs generated by compressing plasma inside reconnected flux tubes generate large velocity and temperature gradients along the tube, rendering the diffusive processes dominant. They determine the thickness of the shock that evolves up to a steady state value, although this condition may not be reached in the short times involved in a flare. For realistic solar coronal parameters, this steady state shock thickness might be as long as the entire flux tube. For strong shocks at low Prandtl numbers, typical of the solar corona, the GDS consists of an isothermal sub-shock where all the compression and cooling occur, preceded by a thermal front where the temperature increases and most of the heating occurs. We estimate the length of each of these sub-regions and the speed of their propagation.
Data Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation

Data augmentation is proven to be effective in many NLU tasks, especially for those suffering from data scarcity. In this paper, we present a powerful and easy to deploy text augmentation framework, Data Boost, which augments data through reinforcement learning guided conditional generation. We evaluate Data Boost on three diverse text classification tasks under five different classifier architectures. The result shows that Data Boost can boost the performance of classifiers especially in low-resource data scenarios. For instance, Data Boost improves F1 for the three tasks by 8.7% on average when given only 10% of the whole data for training. We also compare Data Boost with six prior text augmentation methods. Through human evaluations (N=178), we confirm that Data Boost augmentation has comparable quality as the original data with respect to readability and class consistency.
DYNAMICS OF THE SHARP EDGES OF BROAD PLANETARY RINGS

This paper describes a model of a broad planetary ring whose sharp edge is confined by a satellite’s mth Lindblad resonance (LR). This model uses the streamline formalism of Borderies et al. to calculate the ring’s internal forces, namely, ring gravity, pressure, and viscosity. The model also allows for the possibility of a drag force that can affect small ring particles directly, and large ring particles indirectly via collisions with the small. The model calculates the streamlines’ forced eccentricities e, their longitudes of periapse ˜ ω, and the surface density σ throughout the perturbed ring. This model is then applied to the outer edge of Saturn’s B ring, which is maintained by an m = 2 inner LR with the satellite Mimas. A suite of ring models are used to illustrate how a ring’s perturbed state depends on the ring’s physical properties: its surface density, its viscosity, the ring particles’ dispersion velocity, and the strength of the hypothetical drag force. A comparison of simulations with the outer B ring’s observed properties suggests that the ring’s surface density there is 10 σ 280 gm cm −2 in the ring’s outermost ∼40 km. The ring’s sharp edge identifies the site where the ring’s viscous torque precisely counterbalances the perturbing satellite’s gravitational torque on the ring. However, an examination of several seemingly conventional viscous B ring models shows that they all fail, by wide margins, to balance these torques at the ring’s outer edge. This is partly due to the ring’s self-gravity, which tends to reduce forced eccentricities near the resonance. But this is also due to the fact that a viscous ring tends to be nearly peri-aligned with the satellite. Both effects conspire to reduce the satellite’s torque on the ring, which in turn makes the ring’s edge more difficult to maintain. Nonetheless, the following shows that a torque balance can still be achieved in a viscous B ring, but only in an extreme case where the ratio of the ring’s bulk/ shear viscosities satisfy νb/νs ∼ 10 4 . However, if the dissipation of the ring’s forced motions is instead dominated by a weak drag force, then the satellite can exert a much stronger torque across a wider annulus in the ring, which can successfully counterbalance the ring’s viscous torque there. We also show how this streamline model can be adapted to study other interesting ring phenomena, such as narrow eccentric ringlets and nonlinear spiral density waves.
The discrete noise of magnons

We report experimental results, which show that the low-frequency noise of magnonic devices is dominated by the random telegraph signal noise rather than 1/f noise—a striking contrast to many electronic devices ( f is a frequency). It was also found that the noise level of surface magnons depends strongly on the power level, increasing sharply at the on-set of nonlinear dissipation. The presence of the random telegraph signal noise suggests that the current fluctuations involve random discrete macro events caused by an individual macro-scale fluctuator. We anticipate that our results will help in developing the next generation of magnonic devices for information processing and sensing.
On the maintenance of an attached leading-edge vortex via model bird alula

Researchers have hypothesized that the post-stall lift benefit of bird’s alular feathers, or alula, stems from the maintenance of an attached leading-edge vortex (LEV) over their thin-profiled, outer hand wing. Here, we investigate the connection between the alula and LEV attachment via flow measurements in a wind tunnel. We show that a model alula, whose wetted area is 1 % that of the wing, stabilizes a recirculatory aft-tilted LEV on a steadily translating unswept wing at post-stall angles of attack. The attached vortex is the result of the alula’s ability to smoothly merge otherwise separate leading- and side-edge vortical flows. We identify two key processes that facilitate this merging: (i) the steering of spanwise vorticity generated at the wing’s leading edge back to the wing plane and (ii) an aft-located wall jet of high-magnitude root-to-tip spanwise flow ( that of the free-stream velocity). The former feature induces LEV roll-up while the latter tilts LEV vorticity aft and evacuates this flow toward the wing tip via an outboard vorticity flux. We identify the alula’s streamwise position (relative to the leading edge of the thin wing) as important for vortex steering and the alula’s cant angle as important for high-magnitude spanwise flow generation. These findings advance our understanding of the likely ways birds leverage LEVs to augment slow flight.
OPTIMIZING PULSAR TIMING ARRAYS TO MAXIMIZE GRAVITATIONAL WAVE SINGLE-SOURCE DETECTION: A FIRST CUT

Pulsar Timing Arrays (PTAs) use high accuracy timing of a collection of low timing noise pulsars to search for gravitational waves (GWs) in the microhertz to nanohertz frequency band. The sensitivity of such a PTA depends on (1) the direction of the GW source, (2) the timing accuracy of the pulsars in the array, and (3) how the available observing time is allocated among those pulsars. Here, we present a simple way to calculate the sensitivity of the PTA as a function of direction of a single GW source, based only on the location and root-mean-square residual of the pulsars in the array. We use this calculation to suggest future strategies for the current North American Nanohertz Observatory for Gravitational Waves PTA in its goal of detecting single GW sources. We also investigate the effects of an additional pulsar on the array sensitivity, with the goal of suggesting where PTA pulsar searches might be best directed. We demonstrate that, in the case of single GW sources, if we are interested in maximizing the volume of space to which PTAs are sensitive, there exists a slight advantage to finding a new pulsar near where the array is already most sensitive. Further, the study suggests that more observing time should be dedicated to the already low-noise pulsars in order to have the greatest positive effect on the PTA sensitivity. We have made a Web-based sensitivity mapping tool available.
Four-dimensional /N=4, /SO(4) gauged supergravity from /D=11

Abstract We construct the complete and explicit non-linear Kaluza–Klein Ansatz for deriving the bosonic sector of the standard N =4 SO (4) gauged four-dimensional supergravity from the reduction of D =11 supergravity on S 7 . This provides a way of interpreting all bosonic solutions of the four-dimensional gauged theory as exact solutions in eleven-dimensional supergravity. We discuss certain limiting forms of the Kaluza–Klein reduction, and compare them with related forms in the Freedman–Schwarz N =4 SU (2)× SU (2) gauged theory. This leads us to the result that the Freedman–Schwarz model is in fact a singular limiting case of the standard SO (4) gauged supergravity. We show that in this limit, our Ansatz for getting the SO (4) gauged theory as an S 7 reduction from D =11 indeed reduces to an S 3 × S 3 reduction from D =10, which makes contact with previous results in the literature. We also show that there is no distinction to be made between having equal or unequal values for the gauge coupling constants g and g of the two SU (2) gauge-group factors in the standard N =4 SO (4) gauged supergravity, whilst by contrast the ratio of g to g is a non-trivial parameter of the Freedman–Schwarz model.
Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations

Many real-world systems, such as moving planets, can be considered as multi-agent dynamic systems, where objects interact with each other and co-evolve along with the time. Such dynamics is usually difficult to capture, and understanding and predicting the dynamics based on observed trajectories of objects become a critical research problem in many domains. Most existing algorithms, however, assume the observations are regularly sampled and all the objects can be fully observed at each sampling time, which is impractical for many applications. In this paper, we propose to learn system dynamics from irregularly-sampled partial observations with underlying graph structure for the first time. To tackle the above challenge, we present LG-ODE, a latent ordinary differential equation generative model for modeling multi-agent dynamic system with known graph structure. It can simultaneously learn the embedding of high dimensional trajectories and infer continuous latent system dynamics. Our model employs a novel encoder parameterized by a graph neural network that can infer initial states in an unsupervised way from irregularly-sampled partial observations of structural objects and utilizes neuralODE to infer arbitrarily complex continuous-time latent dynamics. Experiments on motion capture, spring system, and charged particle datasets demonstrate the effectiveness of our approach.
Continuous Activity Maximization in Online Social Networks

Activity maximization is a task of seeking a small subset of users in a given social network that makes the expected total activity benefit maximized. This is a generalization of many real applications. In this paper, we extend activity maximization problem to that under the general marketing strategy $\boldsymbol{x}$ , which is a $d$ -dimensional vector from a lattice space and has probability $h_u(\boldsymbol{x})$ to activate a node $u$ as a seed. Based on that, we propose the continuous activity maximization (CAM) problem, where the domain is continuous and the seed set we select conforms to a certain probability distribution. It is a new topic to study the problem about information diffusion under the lattice constraint, thus, we address the problem systematically here. First, we analyze the hardness of CAM and how to compute the objective function of CAM accurately and effectively. We prove this objective function is monotone, but not DR-submodular and not DR-supermodular. Then, we develop a monotone and DR-submodular lower bound and upper bound of CAM, and apply sampling techniques to design three unbiased estimators for CAM, its lower bound and upper bound. Next, adapted from IMM algorithm and sandwich approximation framework, we obtain a data-dependent approximation ratio. This process can be considered as a general method to solve those maximization problem on lattice but not DR-submodular. Last, we conduct experiments on three real-world datasets to evaluate the correctness and effectiveness of our proposed algorithms.
X-Ray, UV and Optical Observations of Classical Cepheids: New Insights into Cepheid Evolution, and the Heating and Dynamics of Their Atmospheres

To broaden the understanding of classical Cepheid structure, evolution and atmospheres, we have extended our continuing secret lives of Cepheids program by obtaining XMM/Chandra X-ray observations, and Hubble space telescope (HST) / cosmic origins spectrograph (COS) FUV-UV spectra of the bright, nearby Cepheids Polaris, δ Cep and β Dor. Previous studies made with the international ultraviolet explorer (IUE) showed a limited number of UV emission lines in Cepheids. The well-known problem presented by scattered light contamination in IUE spectra for bright stars, along with the excellent sensitivity & resolution combination offered by HST/COS, motivated this study, and the spectra obtained were much more rich and complex than we had ever anticipated. Numerous emission lines, indicating 104 K up to ~3 × 105 K plasmas, have been observed, showing Cepheids to have complex, dynamic outer atmospheres that also vary with the photospheric pulsation period. The FUV line emissions peak in the phase range φ ≈ 0.8-1.0 and vary by factors as large as 10×. A more complete picture of Cepheid outer atmospheres is accomplished when the HST/COS results are combined with X-ray observations that we have obtained of the same stars with XMM-Newton & Chandra. The Cepheids detected to date have X-ray luminosities of log LX ≈ 28.5-29.1 ergs/sec, and plasma temperatures in the 2–8 × 106 K range. Given the phase-timing of the enhanced emissions, the most plausible explanation is the formation of a pulsation-induced shocks that excite (and heat) the atmospheric plasmas surrounding the photosphere. A pulsation-driven α2 equivalent dynamo mechanism is also a viable and interesting alternative. However, the tight phase-space of enhanced emission (peaking near 0.8-1.0 φ) favor the shock heating mechanism hypothesis.
PS1-10jh: The disruption of a main-sequence star of near-solar composition

When a star comes within a critical distance to a supermassive black hole (SMBH), immense tidal forces disrupt the star, resulting in a stream of debris that falls back onto the SMBH and powers a luminous flare. In this paper, we perform hydrodynamical simulations of the disruption of a main-sequence star by an SMBH to characterize the evolution of the debris stream after a tidal disruption. We demonstrate that this debris stream is confined by self-gravity in the two directions perpendicular to the original direction of the star's travel and as a consequence has a negligible surface area and makes almost no contribution to either the continuum or line emission. We therefore propose that any observed emission lines are not the result of photoionization in this unbound debris, but are produced in the region above and below the forming elliptical accretion disk, analogous to the broad-line region (BLR) in steadily accreting active galactic nuclei. As each line within a BLR is observationally linked to a particular location in the accretion disk, we suggest that the absence of a line indicates that the accretion disk does not yet extend to the distance required to produce that line. This model can be used to understand the spectral properties of the tidal disruption event PS1-10jh, for which He II lines are observed, but the Balmer series and He I are not. Using a maximum likelihood analysis, we show that the disruption of a main-sequence star of near-solar composition can reproduce this event.
Immense Magnetic Response of Exciplex Light Emission due to Correlated Spin-Charge Dynamics

Light-emitting diodes are in widespread use in both commercial and residential settings. New research shows that applying a small magnetic field to some devices can boost their luminescence efficiency.
MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals

Given multiple input signals, how can we infer node importance in a knowledge graph (KG)? Node importance estimation is a crucial and challenging task that can benefit a lot of applications including recommendation, search, and query disambiguation. A key challenge towards this goal is how to effectively use input from different sources. On the one hand, a KG is a rich source of information, with multiple types of nodes and edges. On the other hand, there are external input signals, such as the number of votes or pageviews, which can directly tell us about the importance of entities in a KG. While several methods have been developed to tackle this problem, their use of these external signals has been limited as they are not designed to consider multiple signals simultaneously. In this paper, we develop an end-to-end model MultiImport, which infers latent node importance from multiple, potentially overlapping, input signals. MultiImport is a latent variable model that captures the relation between node importance and input signals, and effectively learns from multiple signals with potential conflicts. Also, MultiImport provides an effective estimator based on attentive graph neural networks. We ran experiments on real-world KGs to show that MultiImport handles several challenges involved with inferring node importance from multiple input signals, and consistently outperforms existing methods, achieving up to 23.7% higher NDCG@100 than the state-of-the-art method.
Syntactically Supervised Transformers for Faster Neural Machine Translation

Standard decoders for neural machine translation autoregressively generate a single target token per timestep, which slows inference especially for long outputs. While architectural advances such as the Transformer fully parallelize the decoder computations at training time, inference still proceeds sequentially. Recent developments in non- and semi-autoregressive decoding produce multiple tokens per timestep independently of the others, which improves inference speed but deteriorates translation quality. In this work, we propose the syntactically supervised Transformer (SynST), which first autoregressively predicts a chunked parse tree before generating all of the target tokens in one shot conditioned on the predicted parse. A series of controlled experiments demonstrates that SynST decodes sentences ~5x faster than the baseline autoregressive Transformer while achieving higher BLEU scores than most competing methods on En-De and En-Fr datasets.
Optical Demonstration of THz, Dual-Polarization Sensitive Microwave Kinetic Inductance Detectors

Polarization sensitive, microwave kinetic inductance detectors (MKIDs) are under development for the next generation BLAST instrument (BLAST-TNG). BLAST-TNG is a balloon-borne submillimeter polarimeter designed to study magnetic fields in diffuse dust regions and molecular clouds. We present the design and performance of feedhorn-coupled, dual-polarization sensitive MKIDs fabricated from TiN/Ti multilayer films, which have been optimized for the 250 $$\upmu $$ m band. Measurements show effective selection of linear polarization and good electrical isolation between the orthogonally crossed X and Y detectors within a single spatial pixel. The detector cross-polar coupling is $$<$$ 3 %. Passband measurements are presented, which demonstrate that the desired band-edges (1.0–1.4 THz) have been achieved. We find a near linear response to the optical load from a blackbody source, which has been observed in previous devices fabricated from TiN. Blackbody-coupled noise measurements demonstrate that the sensitivity of the detectors is limited by photon noise when the optical load is greater than 1 pW.
GRB Progenitors and Observational Criteria

Phenomenologically, two classes of GRBs (long/soft vs. short/hard) are identified based on their γ-ray properties. The boundary between the two classes is vague. Multi-wavelength observations lead to identification of two types of GRB progenitors: one related to massive stars (Type II), and another related to compact stars (Type I). Evidence suggests that the majority of long GRBs belong to Type II, while at least the majority of nearby short GRBs belong to Type I. Nonetheless, counter examples do exist. Both long-duration Type I and short-duration Type II GRBs have been observed. In this talk, I review the complications in GRB classification and efforts in diagnosing GRB progenitors based on multiple observational criteria. In particular, I raise the caution to readily accept that all short/hard GRBs detected by BATSE are due to compact star mergers. Finally, I propose to introduce “amplitude” as the third dimension (besides “duration” and “hardness”) to quantify burst properties, and point out that the “tip-of-the-iceberg” effect may introduce confusion in defining the physical category of GRBs, especially for low-amplitude, high-redshift GRBs.
Continuous Wavelets on Compact Manifolds

Let M be a smooth compact oriented Riemannian manifold, and let Δ M be the Laplace–Beltrami operator on M. Say $${0 \neq f \in \mathcal{S}(\mathbb {R}^+)}$$ , and that f (0) = 0. For t > 0, let K t (x, y) denote the kernel of f (t 2 Δ M ). We show that K t is well-localized near the diagonal, in the sense that it satisfies estimates akin to those satisfied by the kernel of the convolution operator f (t 2Δ) on $${\mathbb {R}^n}$$ . We define continuous $${\mathcal {S}}$$ -wavelets on M, in such a manner that K t (x, y) satisfies this definition, because of its localization near the diagonal. Continuous $${\mathcal {S}}$$ -wavelets on M are analogous to continuous wavelets on $${\mathbb {R}^n}$$ in $${\mathcal {S}}$$ ( $${\mathbb {R}^n}$$ ). In particular, we are able to characterize the Holder continuous functions on M by the size of their continuous $${\mathcal {S}}$$ -wavelet transforms, for Holder exponents strictly between 0 and 1. If M is the torus $${\mathbb T^2}$$ or the sphere S 2, and f (s) = se −s (the “Mexican hat” situation), we obtain two explicit approximate formulas for K t , one to be used when t is large, and one to be used when t is small.
On Instability of the Nikodym Maximal Function Bounds over Riemannian Manifolds

We show that, for odd d, the \(L^{\frac{d+2}{2}}\) bounds of Sogge (J Am Math Soc 12:1–31, 1999) and Xi (Trans Am Math Soc 369:6351–6372, 2017) for the Nikodym maximal function over manifolds of constant sectional curvature are unstable with respect to metric perturbation, in the spirit of the work of Minicozzi and Sogge (Math Res Lett 4:221–237, 1997). A direct consequence is the instability of the bounds for the corresponding oscillatory integral operator. Furthermore, we extend our construction to show that the same phenomenon appears for any d-dimensional Riemannian manifold with a local totally geodesic submanifold of dimension \(\lceil \frac{d+1}{2}\rceil \) if \(d\ge 3\). In contrast, Sogge’s \(L^\frac{7}{3}\) bound for the Nikodym maximal function on 3-dimensional variably curved manifolds is stable with respect to metric perturbation.
Online Semi-supervised Learning in Contextual Bandits with Episodic Reward

We considered a novel practical problem of online learning with episodically revealed rewards, motivated by several real-world applications, where the contexts are nonstationary over different episodes and the reward feedbacks are not always available to the decision making agents. For this online semi-supervised learning setting, we introduced Background Episodic Reward LinUCB (BerlinUCB), a solution that easily incorporates clustering as a self-supervision module to provide useful side information when rewards are not observed. Our experiments on a variety of datasets, both in stationary and nonstationary environments of six different scenarios, demonstrated clear advantages of the proposed approach over the standard contextual bandit. Lastly, we introduced a relevant real-life example where this problem setting is especially useful. (Codes can be accessed at https://github.com/doerlbh/BerlinUCB).
Nonlinear observability via Koopman Analysis: Characterizing the role of symmetry

Abstract This paper considers the observability of nonlinear systems from a Koopman operator theoretic perspective – and in particular – the effect of symmetry on observability. We first examine an infinite-dimensional linear system (constructed using independent Koopman eigenfunctions) and relate its observability properties to the observability of the original nonlinear system. Next, we derive an analytic relation between symmetry and nonlinear observability; it is shown that symmetry in the nonlinear dynamics is reflected in the symmetry of the corresponding Koopman eigenfunctions, as well as presence of repeated Koopman eigenvalues. We then proceed to show that loss of observability in symmetric nonlinear systems can be traced back to the presence of these repeated eigenvalues. In the case where we have a sufficient number of measurements, the nonlinear system remains unobservable when these functions have symmetries that mirror those of the dynamics. The proposed observability framework provides insights into the minimum number of measurements needed to make an unobservable nonlinear system, observable. The proposed results are then applied to a network of nano-electromechanical oscillators coupled via a symmetric interaction topology.
I-KCKT allows dissection-free RNA profiling of adult Drosophila intestinal progenitor cells.

The adult Drosophila intestinal epithelium is a model system for stem cell biology, but its utility is limited by current biochemical methods that lack cell type resolution. Here, we describe a new proximity-based profiling method that relies upon a GAL4 driver, termed intestinal-kickout-GAL4 (I-KCKT-GAL4), exclusively expressed in intestinal progenitor cells. This method used UV cross-linked whole animal frozen powder as its starting material to immunoprecipitate the RNA cargoes of transgenic epitope-tagged RNA binding proteins driven by I-KCKT-GAL4. When applied to the general mRNA-binder, poly(A)-binding protein, the RNA profile obtained by this method identified 98.8% of transcripts found after progenitor cell sorting, and had low background noise despite being derived from whole animal lysate. We also mapped the targets of the more selective RNA binder, Fragile Mental Retardation Protein, using enhanced CLIP, and report for the first time its binding motif in Drosophila cells. This method will therefore enable the RNA profiling of wildtype and mutant intestinal progenitor cells from intact flies exposed to normal and altered environments, as well as the identification of RNA-protein interactions critical for stem cell function.
Neural network dynamics underlying gamma synchronization deficits in schizophrenia.

Abstract Gamma-band (40-Hz) activity is critical for cortico-cortical transmission and the integration of information across neural networks during sensory and cognitive processing. Patients with schizophrenia show selective reductions in the capacity to support synchronized gamma-band oscillations in response to auditory stimulation presented 40-Hz. Despite widespread application of this 40-Hz auditory steady-state response (ASSR) as a translational electroencephalographic biomarker for therapeutic development for neuropsychiatric disorders, the spatiotemporal dynamics underlying the ASSR have not been fully characterized. In this study, a novel Granger causality analysis was applied to assess the propagation of gamma oscillations in response to 40-Hz steady-state stimulation across cortical sources in schizophrenia patients (n = 426) and healthy comparison subjects (n = 293). Both groups showed multiple ASSR source interactions that were broadly distributed across brain regions. Schizophrenia patients showed distinct, hierarchically sequenced connectivity abnormalities. During the response onset interval, patients exhibited abnormal increased connectivity from the inferior frontal gyrus to the superior temporal gyrus, followed by decreased connectivity from the superior temporal to the middle cingulate gyrus. In the later portion of the ASSR response (300–500 ms), patients showed significantly increased connectivity from the superior temporal to the middle frontal gyrus followed by decreased connectivity from the left superior frontal gyrus to the right superior and middle frontal gyri. These findings highlight both the orchestration of distributed multiple sources in response to simple gamma-frequency stimulation in healthy subjects as well as the patterns of deficits in the generation and maintenance of gamma-band oscillations across the temporo-frontal sources in schizophrenia patients.
Canonical and noncanonical TGF-β signaling regulate fibrous tissue differentiation in the axial skeleton

Previously, we showed that embryonic deletion of TGF-β type 2 receptor in mouse sclerotome resulted in defects in fibrous connective tissues in the spine. Here we investigated how TGF-β regulates expression of fibrous markers: Scleraxis, Fibromodulin and Adamtsl2. We showed that TGF-β stimulated expression of Scleraxis mRNA by 2 h and Fibromodulin and Adamtsl2 mRNAs by 8 h of treatment. Regulation of Scleraxis by TGF-β did not require new protein synthesis; however, protein synthesis was required for expression of Fibromodulin and Adamtsl2 indicating the necessity of an intermediate. We subsequently showed Scleraxis was a potential intermediate for TGF-β-regulated expression of Fibromodulin and Adamtsl2. The canonical effector Smad3 was not necessary for TGF-β-mediated regulation of Scleraxis. Smad3 was necessary for regulation of Fibromodulin and Adamtsl2, but not sufficient to super-induce expression with TGF-β treatment. Next, the role of several noncanonical TGF-β pathways were tested. We found that ERK1/2 was activated by TGF-β and required to regulate expression of Scleraxis, Fibromodulin, and Adamtsl2. Based on these results, we propose a model in which TGF-β regulates Scleraxis via ERK1/2 and then Scleraxis and Smad3 cooperate to regulate Fibromodulin and Adamtsl2. These results define a novel signaling mechanism for TGFβ-mediated fibrous differentiation in sclerotome.