cssi/SciSciGPT-SciSciNet huggingface dataset:
Non-autoregressive time-series methods for stable parametric reduced-order models

Advection-dominated dynamical systems, characterized by partial differential equations, are found in applications ranging from weather forecasting to engineering design where accuracy and robustness are crucial. There has been significant interest in the use of techniques borrowed from machine learning to reduce the computational expense and/or improve the accuracy of predictions for these systems. These rely on the identification of a basis that reduces the dimensionality of the problem and the subsequent use of time series and sequential learning methods to forecast the evolution of the reduced state. Often, however, machine-learned predictions after reduced-basis projection are plagued by issues of stability stemming from incomplete capture of multiscale processes as well as due to error growth for long forecast durations. To address these issues, we have developed a non-autoregressive time series approach for predicting linear reduced-basis time histories of forward models. In particular, we demonstrate that non-autoregressive counterparts of sequential learning methods such as long short-term memory (LSTM) considerably improve the stability of machine-learned reduced-order models. We evaluate our approach on the inviscid shallow water equations and show that a non-autoregressive variant of the standard LSTM approach that is bidirectional in the principal component directions obtains the best accuracy for recreating the nonlinear dynamics of partial observations. Moreover—and critical for many applications of these surrogates—inference times are reduced by three orders of magnitude using our approach, compared with both the equation-based Galerkin projection method and the standard LSTM approach.
Impact of inflammatory bowel disease on radical prostatectomy outcomes and costs of care.

Abstract Background Recent studies suggest an association between prostate cancer and inflammatory bowel disease (IBD). Our objectives were to investigate clinical and financial impacts of IBD on radical prostatectomy (RP) and to determine the impact of surgical approach on our findings. Methods The Premier Hospital Database was queried for patients who underwent RP from 2003 to 2017. Multivariable logistic regression models were used to determine the independent impact of IBD on complications and readmission rates. We determined 90-day readmissions and examined 90-day hospital costs adjusted to 2019 US dollars with multivariable quantile regression models. Results Our study population included 262,189 men with prostate cancer, including 3,408 (1.3%) with IBD. There were higher odds for any complication for IBD patients compared with non-IBD controls for RP (15.64% vs. 10.66%). Patients with IBD had overall complication rates of 14.1% (P Conclusions The IBD cohort who underwent MIS had the highest complication rates. Hospital readmissions and surgical costs were significantly higher for the IBD cohort who underwent RP between 2013 and 2017, when a minimally invasive approach was more prevalent than an open approach. These findings may be important when deciding which surgical approach to take when performing RP on men with IBD.
Ramification of wild automorphisms of Laurent series fields

Let $K$ be a complete discrete valuation field with residue class field $k$, where both are of positive characteristic $p$. Then the group of wild automorphisms of $K$ can be identified with the group under composition of formal power series over $k$ with no constant term and $X$-coefficient $1$. Under the hypothesis that $p > b^2$, we compute the first nontrivial coefficient of the $p$th iterate of a power series over $k$ of the form $f = X + \sum_{i \geq 1} a_iX^{b+i}$. As a result, we obtain a necessary and sufficient condition for an automorphism to be ``$b$-ramified,'' having lower ramification numbers of the form $i_n(f) = b(1 + \cdots + p^n)$. This is a vast generalization of Nordqvist's 2017 theorem on $2$-ramified power series, as well as the analogous result for minimally ramified power series which proved to be useful for arithmetic dynamics in a 2013 paper of Lindahl on linearization discs in $\mathbf{C}_p$ and a 2015 result of Lindahl--Rivera-Letelier on optimal cycles over nonarchimedean fields of positive residue characteristic. The success of our computation is also promising progress towards a generalization of Lindahl--Nordqvist's 2018 theorem bounding the norm of periodic points of $2$-ramified power series.
Parallel Batch-Dynamic Trees via Change Propagation.

The dynamic trees problem is to maintain a forest subject to edge insertions and deletions while facilitating queries such as connectivity, path weights, and subtree weights. Dynamic trees are a fundamental building block of a large number of graph algorithms. Although traditionally studied in the single-update setting, dynamic algorithms capable of supporting batches of updates are increasingly relevant today due to the emergence of rapidly evolving dynamic datasets. Since processing updates on a single processor is often unrealistic for large batches of updates, designing parallel batch-dynamic algorithms that achieve provably low span is important for many applications. In this work, we design the first work-efficient parallel batch-dynamic algorithm for dynamic trees that is capable of supporting both path queries and subtree queries, as well as a variety of non-local queries. To achieve this, we propose a framework for algorithmically dynamizing static round-synchronous algorithms that allows us to obtain parallel batch-dynamic algorithms with good bounds on their work and span. In our framework, the algorithm designer can apply the technique to any suitably defined static algorithm. We then obtain theoretical guarantees for algorithms in our framework by defining the notion of a computation distance between two executions of the underlying algorithm. Our dynamic trees algorithm is obtained by applying our dynamization framework to the parallel tree contraction algorithm of Miller and Reif, and then performing a novel analysis of the computation distance of this algorithm under batch updates. We show that $k$ updates can be performed in $O(k \log(1+n/k))$ work in expectation, which matches an existing algorithm of Tseng et al. while providing support for a substantially larger number of queries and applications.
Primo: integration of multiple GWAS and omics QTL summary statistics for elucidation of molecular mechanisms of trait-associated SNPs and detection of pleiotropy in complex traits

To provide a comprehensive mechanistic interpretation of how known trait-associated SNPs affect complex traits, we propose a method, Primo, for integrative analysis of GWAS summary statistics with multiple sets of omics QTL summary statistics from different cellular conditions or studies. Primo examines association patterns of SNPs to complex and omics traits. In gene regions harboring known susceptibility loci, Primo performs conditional association analysis to account for linkage disequilibrium. Primo allows for unknown study heterogeneity and sample correlations. We show two applications using Primo to examine the molecular mechanisms of known susceptibility loci and to detect and interpret pleiotropic effects.
Generators, spanning sets and existence of twisted modules for a grading-restricted vertex (super)algebra

For a grading-restricted vertex superalgebra V and an automorphism g of V, we give a linearly independent set of generators of the universal lower-bounded generalized g-twisted V-module Mˆ[g]B constructed by the author in Huang (Commun Math Phys 377:909–945 (2020)). We prove that there exist irreducible lower-bounded generalized g-twisted V-modules by showing that there exists a maximal proper submodule of Mˆ[g]B for a one-dimensional space M. We then give several spanning sets of Mˆ[g]B and discuss the relations among elements of the spanning sets. Assuming that V is a Mobius vertex superalgebra (to make sure that lowest weights make sense) and that P(V) (the set of all numbers of the form R(α)∈[0,1) for α∈C such that e2πiα is an eigenvalue of g) has no accumulation point in R (to make sure that irreducible lower-bounded generalized g-twisted V-modules have lowest weights). Under suitable additional conditions, which hold when the twisted zero-mode algebra or the twisted Zhu’s algebra is finite dimensional, we prove that there exists an irreducible grading-restricted generalized g-twisted V-module, which is in fact an irreducible ordinary g-twisted V-module when g is of finite order. We also prove that every lower-bounded generalized module with an action of g for the fixed-point subalgebra Vg of V under g can be extended to a lower-bounded generalized g-twisted V-module.
Maple's Quantum Chemistry Package in the Chemistry Classroom.

An introduction to the Quantum Chemistry Package (QCP), implemented in the computer algebra system Maple, is presented. The QCP combines sophisticated electronic structure methods and Maple’s easy-...
Effect of Flow-Induced Molecular Alignment on Welding and Strength of Polymer Interfaces

Structures formed by fused filament fabrication are often substantially weaker than those made with conventional techniques and fail at the welds between successive layers. One factor that may infl...
Robotic Grasping using Deep Reinforcement Learning

In this work, we present a deep reinforcement learning based method to solve the problem of robotic grasping using visio-motor feedback. The use of a deep learning based approach reduces the complexity caused by the use of hand-designed features. Our method uses an off-policy reinforcement learning framework to learn the grasping policy. We use the double deep Q-learning framework along with a novel GraspQ-Network to output grasp probabilities used to learn grasps that maximize the pick success. We propose a visual servoing mechanism that uses a multi-view camera setup that observes the scene which contains the objects of interest. We performed experiments using a Baxter Gazebo simulated environment as well as on the actual robot. The results show that our proposed method outperforms the baseline Q-learning framework and increases grasping accuracy by adapting a multi-view model in comparison to a single-view model.
The high volume return premium and economic fundamentals

Abstract Extending Kaniel et al. (2012) and many others, we present the first empirical evidence that indicates the high volume return premium is linked to economic fundamentals. The volume premium has strong predictive power for future industrial production growth and other macroeconomic indicators with or without controls for common equity pricing factors and business cycle variables. However, only a small portion of the volume premium can be attributed to its comovement with equity return factors and economic risk factors. Mispricing-based factor models also fail to adequately explain the return anomaly.
Nonlinear Transform Coding

We review a class of methods that can be collected under the name nonlinear transform coding (NTC), which over the past few years have become competitive with the best linear transform codecs for images, and have superseded them in terms of rate–distortion performance under established perceptual quality metrics such as MS-SSIM. We assess the empirical rate–distortion performance of NTC with the help of simple example sources, for which the optimal performance of a vector quantizer is easier to estimate than with natural data sources. To this end, we introduce a novel variant of entropy-constrained vector quantization. We provide an analysis of various forms of stochastic optimization techniques for NTC models; review architectures of transforms based on artificial neural networks, as well as learned entropy models; and provide a direct comparison of a number of methods to parameterize the rate–distortion trade-off of nonlinear transforms, introducing a simplified one.
The Zariski cancellation problem for Poisson algebras

We study the Zariski cancellation problem for Poisson algebras asking whether $A[t]\cong B[t]$ implies $A\cong B$ when $A$ and $B$ are Poisson algebras. We resolve this affirmatively in the cases when $A$ and $B$ are both connected graded Poisson algebras finitely generated in degree one without degree one Poisson central elements and when $A$ is a Poisson integral domain of Krull dimension two with nontrivial Poisson bracket. We further introduce Poisson analogues of the Makar-Limanov invariant and the discriminant to deal with the Zariski cancellation problem for other families of Poisson algebras.
Augmenting visual SLAM with Wi-Fi sensing for indoor applications

Recent trends have accelerated the development of spatial applications on mobile devices and robots. These include navigation, augmented reality, human–robot interaction, and others. A key enabling technology for such applications is the understanding of the device’s location and the map of the surrounding environment. This generic problem, referred to as Simultaneous Localization and Mapping (SLAM), is an extensively researched topic in robotics. However, visual SLAM algorithms face several challenges including perceptual aliasing and high computational cost. These challenges affect the accuracy, efficiency, and viability of visual SLAM algorithms, especially for long-term SLAM, and their use in resource-constrained mobile devices. A parallel trend is the ubiquity of Wi-Fi routers for quick Internet access in most urban environments. Most robots and mobile devices are equipped with a Wi-Fi radio as well. We propose a method to utilize Wi-Fi received signal strength to alleviate the challenges faced by visual SLAM algorithms. To demonstrate the utility of this idea, this work makes the following contributions: (i) We propose a generic way to integrate Wi-Fi sensing into visual SLAM algorithms, (ii) We integrate such sensing into three well-known SLAM algorithms, (iii) Using four distinct datasets, we demonstrate the performance of such augmentation in comparison to the original visual algorithms and (iv) We compare our work to Wi-Fi augmented FABMAP algorithm. Overall, we show that our approach can improve the accuracy of visual SLAM algorithms by 11% on average and reduce computation time on average by 15% to 25%.
Physics of reverse annealing in high-resistivity Chandra ACIS CCDs

After launch, the Advanced CCD Imaging Spectrometer (ACIS), a focal plane instrument on the Chandra Xray Observatory, suffered radiation damage from exposure to soft protons during passages through the Earth's radiation belts. An effect of the damage was to increase the charge transfer inefficiency (CTI) of the front illuminated CCDs. As part of the initial damage assessment, the focal plane was warmed from the operating temperature of -100° C to +30° C which unexpectedly further increased the CTI. We report results of ACIS CCD irradiation experiments in the lab aimed at better understanding this reverse annealing process. Six CCDs were irradiated cold by protons ranging in energy from 100 keV to 400 keV, and then subjected to simulated bakeouts in one of three annealing cycles. We present results of these lab experiments, compare them to our previous experiences on the ground and in flight, and derive limits on the annealing time constants.
Characterizing a four-qubit planar lattice for arbitrary error detection

Quantum error correction will be a necessary component towards realizing scalable quantum computers with physical qubits. Theoretically, it is possible to perform arbitrarily long computations if the error rate is below a threshold value. The two-dimensional surface code permits relatively high fault-tolerant thresholds at the ~1% level, and only requires a latticed network of qubits with nearest-neighbor interactions. Superconducting qubits have continued to steadily improve in coherence, gate, and readout fidelities, to become a leading candidate for implementation into larger quantum networks. Here we describe characterization experiments and calibration of a system of four superconducting qubits arranged in a planar lattice, amenable to the surface code. Insights into the particular qubit design and comparison between simulated parameters and experimentally determined parameters are given. Single- and two-qubit gate tune-up procedures are described and results for simultaneously benchmarking pairs of two-qubit gates are given. All controls are eventually used for an arbitrary error detection protocol described in separate work [Corcoles et al., Nature Communications, 6, 2015].
On the Baryon Fractions in Clusters and Groups of Galaxies

We present the baryon fractions of 2MASS groups and clusters as a function of cluster richness using total and gas masses measured from stacked ROSAT X-ray data and stellar masses estimated from the infrared galaxy catalogs. We detect X-ray emission even in the outskirts of clusters, beyond r 200 for richness classes with X-ray temperatures above 1?keV. This enables us to more accurately determine the total gas mass in these groups and clusters. We find that the optically selected groups and clusters have flatter temperature profiles and higher stellar-to-gas mass ratios than the individually studied, X-ray bright clusters. We also find that the stellar mass in poor groups with temperatures below 1?keV is comparable to the gas mass in these systems. Combining these results with individual measurements for clusters, groups, and galaxies from the literature, we find a break in the baryon fraction at ~1?keV. Above this temperature, the baryon fraction scales with temperature as fb T 0.20?0.03. We see significantly smaller baryon fractions below this temperature and the baryon fraction of poor groups joins smoothly onto that of systems with still shallower potential wells such as normal and dwarf galaxies where the baryon fraction scales with the inferred velocity dispersion as fb ?1.6. The small scatter in the baryon fraction at any given potential well depth favors a universal baryon loss mechanism and a preheating model for the baryon loss. The scatter is, however, larger for less massive systems. Finally, we note that although the broken power-law relation can be inferred from data points in the literature alone, the consistency between the baryon fractions for poor groups and massive galaxies inspires us to fit the two categories of objects (galaxies and clusters) with one relation.
The locus of plane quartics with a hyperflex

Using the results of Dalla Piazza, Fiorentino and Salvati Manni, we determine an explicit modular form defining the locus of plane quartics with a hyperflex among all plane quartics. As a result, we provide a direct way to compute the divisor class of the locus of plane quartics with a hyperflex within $\overline{\mathcal{M}_3}$, first obtained by Cukierman in 1989. Moreover, the knowledge of such an explicit modular form also allows us to describe explicitly the boundary of the hyperflex locus in $\overline{\mathcal{M}_3}$. As an example, we show that the locus of banana curves (two irreducible components intersecting at two nodes) is contained in the closure of the hyperflex locus. We also identify an explicit modular form defining the locus of Clebsch quartics and use it to recompute the class of this divisor, first obtained by Ottaviani and Sernesi.
Dynamics of a driven confined polyelectrolyte solution

The transport of polyelectrolytes confined by oppositely charged surfaces and driven by a constant electric field is of interest in studies of DNA separation according to size. Using molecular dynamics simulations that include the surface polarization effect, we find that the mobilities of the polyelectrolytes and their counterions change non-monotonically with the confinement surface charge density. For an optimum value of the confinement charge density, efficient separation of polyelectrolytes can be achieved over a wide range of polyelectrolyte charge due to the differential friction imparted by oppositely charged confinement on the polyelectrolyte chains. Furthermore, by altering the placement of the charged confinement counterions, enhanced polyelectrolyte separation can be achieved by utilizing the surface polarization effect due to dielectric mismatch between the media inside and outside the confinement.
Signalling and obfuscation for congestion control

We aim to reduce the social cost of congestion in many smart city applications. In our model of congestion, agents interact over limited resources after receiving signals from a central agent that observes the state of congestion in real time. Under natural models of agent populations, we develop new signalling schemes and show that by introducing a non-trivial amount of uncertainty in the signals, we reduce the social cost of congestion, i.e., improve social welfare. The signalling schemes are efficient in terms of both communication and computation, and are consistent with past observations of the congestion. Moreover, the resulting population dynamics converge under reasonable assumptions.
First point-spread function and x-ray phase-contrast imaging results with an 88-mm diameter single crystal

In this study, we report initial demonstrations of the use of single crystals in indirect x-ray imaging with a benchtop implementation of propagation-based x-ray phase-contrast imaging. Based on single Gaussian peak fits to the x-ray images, we observed a four times smaller system point-spread function (PSF) with the 50-µm thick single crystal scintillators than with the reference polycrystalline phosphor/scintillator. Fiber-optic plate depth-of-focus and Al reflective-coating aspects are also elucidated. Guided by the results from the 25-mm diameter crystal samples, we report additionally the first results with a unique 88-mm diameter single crystal bonded to a fiber optic plate and coupled to the large format CCD. Both PSF and x-ray phase-contrast imaging data are quantified and presented.
TASEP on a Ring in Sub-relaxation Time Scale

Interacting particle systems in the KPZ universality class on a ring of size L with O(L) number of particles are expected to change from KPZ dynamics to equilibrium dynamics at the so-called relaxation time scale $$t=O(L^{3/2})$$ . In particular the system size is expected to have little effect to the particle fluctuations in the sub-relaxation time scale $$1\ll t\ll L^{3/2}$$ . We prove that this is indeed the case for the totally asymmetric simple exclusion process (TASEP) with two types of initial conditions. For flat initial condition, we show that the particle fluctuations are given by the Airy $$_1$$ process as in the infinite TASEP with flat initial condition. On the other hand, the TASEP on a ring with step initial condition is equivalent to the periodic TASEP with a certain shock initial condition. We compute the fluctuations explicitly both away from and near the shocks for the infinite TASEP with same initial condition, and then show that the periodic TASEP has same fluctuations in the sub-relaxation time scale.
Convex optimization in identification of stable non-linear state space models

A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state data, with a performance objective defined as a measure of robustness of the simulation error with respect to equation errors. Basic definitions and analytical results are presented. The utility of the method is illustrated on a simple simulation example as well as experimental recordings from a live neuron.
Semi-holographic Fermi liquids

We show that the universal physics of recent holographic non-Fermi liquid models is captured by a semi-holographic description, in which a dynamical boundary field is coupled to a strongly coupled conformal sector having a gravity dual. This allows various generalizations, such as a dynamical exponent and lattice and impurity effects. We examine possible relevant deformations, including multi-trace terms and spin-orbit effects. We discuss the matching onto the UV theory of the earlier work, and an alternate description in which the boundary field is integrated out.
Avalanche dynamics for active matter in heterogeneous media

Using numerical simulations, we examine the dynamics of active matter run-and-tumble disks moving in a disordered array of obstacles. As a function of increasing active disk density and activity, we find a transition from a completely clogged state to a continuous flowing phase, and in the large activity limit, we observe an intermittent state where the motion occurs in avalanches that are power law distributed in size with an exponent of $\beta = 1.46$. In contrast, in the thermal or low activity limit we find bursts of motion that are not broadly distributed in size. We argue that in the highly active regime, the system reaches a self-jamming state due to the activity-induced self-clustering, and that the intermittent dynamics is similar to that found in the yielding of amorphous solids. Our results show that activity is another route by which particulate systems can be tuned to a nonequilibrium critical state.
Some properties of the phase diagram for mixed p-spin glasses

In this paper we study the Parisi variational problem for mixed p-spin glasses with Ising spins. Our starting point is a characterization of Parisi measures whose origin lies in the first order optimality conditions for the Parisi functional, which is known to be strictly convex. Using this characterization, we study the phase diagram in the temperature-external field plane. We begin by deriving self-consistency conditions for Parisi measures that generalize those of de Almeida and Thouless to all levels of Replica Symmetry Breaking (RSB) and all models. As a consequence, we conjecture that for all models the Replica Symmetric phase is the region determined by the natural analogue of the de Almeida–Thouless condition. We show that for all models, the complement of this region is in the RSB phase. Furthermore, we show that the conjectured phase boundary is exactly the phase boundary in the plane less a bounded set. In the case of the Sherrington–Kirkpatrick model, we extend this last result to show that this bounded set does not contain the critical point at zero external field.
Characterization of Line-Consistent Signed Graphs

The line graph of a graph with signed edges carries vertex signs. A vertex-signed graph is consistent if every circle (cycle, circuit) has positive vertex-sign product. Acharya, Acharya, and Sinha recently characterized line-consistent signed graphs, i.e., edge-signed graphs whose line graphs, with the naturally induced vertex signature, are consistent. Their proof applies Hoede's relatively difficult characterization of consistent vertex-signed graphs. We give a simple proof that does not depend on Hoede's theorem as well as a structural description of line-consistent signed graphs.
Transient compressible flow in a compliant viscoelastic tube

Motivated by problems arising in the pneumatic actuation of controllers for micro-electromechanical systems, labs-on-a-chip or biomimetic soft robots, and the study of microrheology of both gases and soft solids, we analyze the transient fluid–structure interactions (FSIs) between a viscoelastic tube conveying compressible flow at low Reynolds number. We express the density of the fluid as a linear function of the pressure, and we use the lubrication approximation to further simplify the fluid dynamics problem. On the other hand, the structural mechanics is governed by a modified Donnell shell theory accounting for Kelvin–Voigt-type linearly viscoelastic mechanical response. The fluid and structural mechanics problems are coupled through the tube’s radial deformation and the hydrodynamic pressure. For small compressibility numbers and weak coupling, the equations are solved analytically via a perturbation expansion. Three illustrative problems are analyzed. First, we obtain exact (but implicit) solutions for the pressure for steady flow conditions. Second, we solve the transient problem of impulsive pressurization of the tube’s inlet. Third, we analyze the transient response to an oscillatory inlet pressure. We show that an oscillatory inlet pressure leads to acoustic streaming in the tube, attributed to the nonlinear pressure gradient induced by the interplay of FSI and compressibility. Furthermore, we demonstrate an enhancement in the volumetric flow rate due to FSI coupling. The hydrodynamic pressure oscillations are shown to exhibit a low-pass frequency response (when averaging over the period of oscillations), while the frequency response of the tube deformation is similar to that of a bandpass filter.
Maass wave forms, quantum modular forms and Hecke operators

We prove that Cohen’s Maass wave form and Li–Ngo–Rhoades’ Maass wave form are Hecke eigenforms with respect to certain Hecke operators. As a corollary, we find new identities of the pth coefficients of these Maass wave forms in terms of pth root of unity.
THE EVOLUTION OF HETERGENEOUS “CLUMPY JETS”: A PARAMETER STUDY

We investigate the role discrete clumps embedded in an astrophysical jet play on the jet's morphology and line emission characteristics. By varying clumps' size, density, position, and velocity, we cover a range of parameter space motivated by observations of objects such as the Herbig-Haro object HH 34. We here extend the results presented in Yirak et al., including how analysis of individual observations may lead to spurious sinusoidal variation whose parameters vary widely over time, owing chiefly to interactions between clumps. The goodness of fits, while poor in all simulations, are best when clump-clump collisions are minimal. Our results indicate that a large velocity dispersion leads to a clump-clump collision-dominated flow which disrupts the jet beam. Finally, we present synthetic emission images of Hα and [S II] and note an excess of [S II] emission along the jet length as compared to observations. This suggests that observed beams undergo earlier processing, if they are present at all.
Spectral angle based unary energy functions for spatial-spectral hyperspectral classification using Markov random fields

In this paper, we propose and compare two spectral angle based approaches for spatial-spectral classification. Our methods use the spectral angle to generate unary energies in a grid-structured Markov random field defined over the pixel labels of a hyperspectral image. The first approach is to use the exponential spectral angle mapper (ESAM) kernel/covariance function, a spectral angle based function, with the support vector machine and the Gaussian process classifier. The second approach is to directly use the minimum spectral angle between the test pixel and the training pixels as the unary energy. We compare the proposed methods with the state-of-the-art Markov random field methods that use support vector machines and Gaussian processes with squared exponential kernel/covariance function. In our experiments with two datasets, it is seen that using minimum spectral angle as unary energy produces better or comparable results to the existing methods at a smaller running time.
Moduli Spaces of Stable Pairs

We construct a moduli space of stable pairs over a smooth projective variety, parametrizing morphisms from a fixed coherent sheaf to a varying sheaf of fixed topological type, subject to a stability condition. This generalizes the notion used by Pandharipande and Thomas, following Le Potier, where the fixed sheaf is the structure sheaf of the variety. We then describe the relevant deformation and obstruction theories. We also show the existence of the virtual fundamental class in special cases.
A metric Kan–Thurston theorem

For every simplicial complex X we construct a locally CAT(0) cubical complex T(X), a cellular isometric involution tau on T(X) and a map t from T(X) to X with the following properties: t is equivariant for tau; t is a homology isomorphism; the induced map from the quotient space T(X)/tau to X is a homotopy equivalence; the induced map from the tau-fixed point set in T(X) to X is a homology isomorphism. The construction is functorial in X. One corollary is an equivariant Kan-Thurston theorem: every connected proper G-CW-complex has the same equivariant homology as the classifying space for proper actions of some other group. From this we obtain extensions of a theorem of Quillen on the spectrum of a (Borel) equivariant cohomology ring and of a result of Block concerning assembly conjectures. Another corollary of our main result is that there can be no algorithm to decide whether a CAT(0) cubical group is generated by torsion. In appendices we prove some foundational results concerning cubical complexes, notably in the infinite-dimensional case. We characterize the cubical complexes for which the natural metric is complete; we establish Gromov's criterion for infinite-dimensional cubical complexes; we show that every CAT(0) cube complex is cubical; we deduce that the second cubical subdivision of any locally CAT(0) cube complex is cubical. [A version of this paper was submitted in September 2010. This is a revised version I made in April 2011 (improvements to some material in the appendices).]
A general-purpose machine learning framework for predicting properties of inorganic materials

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method for partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability. Researchers in the United States have developed a versatile machine learning framework to aid the search for novel materials. Led by Christopher Wolverton and Logan Ward from Northwestern University, the researchers used machine learning techniques trained against known material data to generate models that predict the specific properties of new materials. The utility of the technique was demonstrated through searches for novel crystalline compounds for photovoltaic applications, and for metallic glass alloys based on the probability of glass formation for ternary alloys. New models can be created by optimizing the machine learning algorithm and partitioning input data to maximize the prediction accuracy for specific parameters. The technique has the potential to automate and accelerate the search for new functional materials using the large libraries of material data now available to researchers.
Black Hole Continuum Spectra as a Test of General Relativity: Quadratic Gravity

Observations of the continuum spectrum emitted by accretion disks around black holes allows us to infer their properties, including possibly whether black holes are described by the Kerr metric. Some modified gravity theories do not admit the Kerr metric as a solution, and thus, continuum spectrum observations could be used to constrain these theories. We here investigate whether current and next generation X-Ray observations of the black hole continuum spectrum can constrain such deviations from Einstein's theory, focusing on two well-motivated modified quadratic gravity theories: dynamical Chern-Simons gravity and Einstein-dilaton-Gauss-Bonnet gravity. We do so by determining whether the non-Kerr deviations in the continuum spectrum introduced by these theories are larger than the observational error intrinsic to the observations. We find that dynamical Chern-Simons gravity cannot be constrained better than current bounds with current or next generation continuum spectrum observations. Einstein-dilaton-Gauss-Bonnet gravity, however, may be constrained better than current bounds with next generation telescopes, as long as the systematic error inherent in the accretion disk modeling is decreased below the predicted observational error.
A stochastic-Lagrangian particle system for the Navier?Stokes equations

This paper is based on a formulation of the Navier–Stokes equations developed by Constantin and the first author (Commun. Pure Appl. Math. at press, arXiv:math.PR/0511067), where the velocity field of a viscous incompressible fluid is written as the expected value of a stochastic process. In this paper, we take N copies of the above process (each based on independent Wiener processes), and replace the expected value with 1/N times the sum over these N copies. (We note that our formulation requires one to keep track of N stochastic flows of diffeomorphisms, and not just the motion of N particles.)We prove that in two dimensions, this system of interacting diffeomorphisms has (time) global solutions with initial data in the space C1,α which consists of differentiable functions whose first derivative is α Holder continuous (see section 3 for the precise definition). Further, we show that as N → ∞ the system converges to the solution of Navier–Stokes equations on any finite interval [0, T]. However for fixed N, we prove that this system retains roughly O(1/N) times its original energy as t → ∞. Hence the limit N → ∞ and T → ∞ do not commute. For general flows, we only provide a lower bound to this effect. In the special case of shear flows, we compute the behaviour as t → ∞ explicitly.
Radio Jet-Ambient Medium Interactions on Parsec Scales in the Blazar 1055+018

As part of our study of the magnetic fields of active galactic nuclei, we have recently observed a large sample of blazars with the Very Long Baseline Array. Here we report the discovery of a striking two-component jet in the source 1055+018 that consists of an inner spine with a transverse magnetic field and a fragmentary but distinct boundary layer with a longitudinal magnetic field. The polarization distribution in the spine strongly supports shocked-jet models, while that in the boundary layer suggests interaction with the surrounding medium. This behavior suggests a new way to understand the differing polarization properties of strong- and weak-lined blazars.
Antineutrino Detectors Remain Impractical for Nuclear Explosion Monitoring

Fission explosions produce large numbers of antineutrinos. It is occasionally asked whether this distinctive, unshieldable emission could help reveal clandestine nuclear weapon explosions. The practical challenge encountered is that detectors large enough for this application are cost prohibitive, likely on the multi-billion-dollar scale. In this paper, we review several hypothetical use cases for antineutrino detectors as supplements to the seismic, infrasound, hydroacoustic, and airborne radionuclide sensors of the Comprehensive Nuclear-Test-Ban Treaty Organization’s International Monitoring System. In each case, if an anti-neutrino detector could be constructed that would compete with existing capabilities, we conclude that the cost would considerably outstrip the value it might add to the existing monitoring network, compared to the significantly lower costs for the same or superior capability.
Effects of shear-thinning viscosity and viscoelastic stresses on flagellated bacteria motility

The behavior of flagellated bacteria swimming in non-Newtonian media remains an area with contradictory and conflicting results. We report on the behavior of wild-type and smooth-swimming E. coli in Newtonian, shear-thinning, and viscoelastic media, measuring their trajectories and swimming speed using a three-dimensional real-time tracking microscope. We conclude that the speed enhancement in Methocel solution at higher concentrations is due to shear thinning and an analytical model is used to support our experimental result. We argue that shear-induced normal stresses reduce wobbling behavior during cell swimming but do not significantly affect swimming speed. However, the normal stresses play an important role in decreasing the flagellar bundling time, which changes the swimming-speed distribution. A dimensionless number, the “strangulation number” (Str) is proposed and used to characterize this effect.
Collective phenomena in ultra-relativistic nuclear collisions: anisotropic flow and more

Abstract Many features of multiparticle production in ultra-relativistic nuclear collisions reflect the collision geometry and other collision characteristics determining the initial conditions. As the initial conditions affect all the particles to a different degree, it leads to truly multiparticle effects often referred to as anisotropic collective flow. Studying anisotropic flow in nuclear collisions provides unique and invaluable information about the system evolution and the physics of multiparticle production in general. Being not able to cover all aspects of anisotropic flow in one lecture, I decided in the first part of the lecture to discuss briefly a few important and established results, and in the second part, to focus, in a little more detail, on one recent development — a recent progress in our understanding of the role of fluctuations in the initial conditions. I also discuss some future measurements that might reveal further details of the multiparticle production processes.
The AdS$_3$ Propagator and the Fate of Locality

We recently used Virasoro symmetry considerations to propose an exact formula for a bulk proto-field ϕ in AdS3. In this paper we study the propagator 〈ϕϕ〉. We show that many techniques from the study of conformal blocks can be generalized to compute it, including the semiclassical monodromy method and both forms of the Zamolodchikov recursion relations. When the results from recursion are expanded at large central charge, they match gravitational perturbation theory for a free scalar field coupled to gravity in our chosen gauge. We find that although the propagator is finite and well-defined at long distances, its perturbative expansion in $$ {G}_N=\frac{3}{2c} $$ exhibits UV/IR mixing effects. If we nevertheless interpret 〈ϕϕ〉 as a probe of bulk locality, then when $$ {G}_{N{m}_{\phi }}\ll 1 $$ locality breaks down at the new short-distance scale $$ {\sigma}_{\ast}\sim \sqrt[4]{G_N{R}_{\mathrm{AdS}}^3} $$ . For ϕ with very large bulk mass, or at small central charge, bulk locality fails at the AdS length scale. In all cases, locality ‘breakdown’ manifests as singularities or branch cuts at spacelike separation arising from non-perturbative quantum gravitational effects.
Dynamics of Nonlinear Random Walks on Complex Networks

In this paper, we study the dynamics of nonlinear random walks. While typical random walks on networks consist of standard Markov chains whose static transition probabilities dictate the flow of random walkers through the network, nonlinear random walks consist of nonlinear Markov chains whose transition probabilities change in time depending on the current state of the system. This framework allows us to model more complex flows through networks that may depend on the current system state. For instance, under humanitarian or capitalistic direction, resource flow between institutions may be diverted preferentially to poorer or wealthier institutions, respectively. Importantly, the nonlinearity in this framework gives rise to richer dynamical behavior than occurs in linear random walks. Here we study these dynamics that arise in weakly and strongly nonlinear regimes in a family of nonlinear random walks where random walkers are biased either toward (positive bias) or away from (negative bias) nodes that currently have more random walkers. In the weakly nonlinear regime, we prove the existence and uniqueness of a stable stationary state fixed point provided that the network structure is primitive that is analogous to the stationary distribution of a typical (linear) random walk. We also present an asymptotic analysis that allows us to approximate the stationary state fixed point in the weakly nonlinear regime. We then turn our attention to the strongly nonlinear regime. For negative bias, we characterize a period-doubling bifurcation where the stationary state fixed point loses stability and gives rise to a periodic orbit below a critical value. For positive bias, we investigate the emergence of multistability of several stable stationary state fixed points.
Plasmonic resonators for enhanced diamond NV- center single photon sources

We propose a novel source of non-classical light consisting of plasmonic aperture with single-crystal diamond containing a single Nitrogen-Vacancy (NV) color center. Theoretical calculations of optimal structures show that these devices can simultaneously enhance optical pumping by a factor of 7, spontaneous emission rates by Fp ~50 (Purcell factor), and offer collection efficiencies up to 40%. These excitation and collection enhancements occur over a broad range of wavelengths (~30nm), and are independently tunable with device geometry, across the excitation (~530nm) and emission (~600-800nm) spectrum of the NV center. Implementing this system with top-down techniques in bulk diamond crystals will provide a scalable architecture for a myriad of diamond NV center applications.
Steiner triangular drop dynamics.

Steiner’s circumellipse is the unique geometric regularization of any triangle to a circumscribed ellipse with the same centroid, a regularization that motivates our introduction of the Steiner triangle as a minimal model for liquid droplet dynamics. The Steiner drop is a deforming triangle with one side making sliding contact against a planar basal support. The center of mass of the triangle is governed by Newton’s law. The resulting dynamical system lives in a four dimensional phase space and exhibits a rich one-parameter family of dynamics. Two invariant manifolds are identified with “bouncing” and “rocking” periodic motions; these intersect at the stable equilibrium and are surrounded by nested quasiperiodic motions. We study the inherently interesting dynamics and also find that this model, however minimal, can capture space–time symmetries of more realistic continuum drop models.Steiner’s circumellipse is the unique geometric regularization of any triangle to a circumscribed ellipse with the same centroid, a regularization that motivates our introduction of the Steiner triangle as a minimal model for liquid droplet dynamics. The Steiner drop is a deforming triangle with one side making sliding contact against a planar basal support. The center of mass of the triangle is governed by Newton’s law. The resulting dynamical system lives in a four dimensional phase space and exhibits a rich one-parameter family of dynamics. Two invariant manifolds are identified with “bouncing” and “rocking” periodic motions; these intersect at the stable equilibrium and are surrounded by nested quasiperiodic motions. We study the inherently interesting dynamics and also find that this model, however minimal, can capture space–time symmetries of more realistic continuum drop models.