cssi/SciSciGPT-SciSciNet huggingface dataset:
Outcomes of microvascular decompression for trigeminal neuralgia with purely venous compression: A systematic review and meta-analysis.

Abstract Objective Microvascular decompression (MVD) is a commonly-used treatment option for medically-refractory trigeminal neuralgia (TN) with arterial neurovascular compression. Pain control and recurrence rates after MVD in patients with purely venous compression are not well understood. In this systematic review and meta-analysis, we studied outcomes after MVD in patients with purely venous compression and reviewed the operative management in these patients. Methods We performed a systematic review and meta-analysis following the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines. We searched PubMed, Google Scholar, and Scopus databases for studies reporting surgical outcomes after MVD for purely venous compression. Pain control and recurrence rates were extracted and summarized. Studies that reported outcomes after mobilization/decompression compared with coagulation/transection of compressive veins were reviewed. Results We identified and included 24 studies with a total of 330 patients in this study. 75.6 % of patients achieved a Barrow Neurological Institute (BNI) I pain score with a mean follow-up of 38.0 months. Pain recurred in 23.1 % of patients at a mean follow-up of 51.4 months. There was no significant difference in pain control outcomes between patients with mobilization/decompression and patients with coagulation/transection of compressive veins. Conclusion After MVD in patients with venous compression alone, pain control rates were similar to those reported for arterial compression, though recurrence rates were higher. There was no difference between vein coagulation/transection compared to mobilization/decompression. Further studies are needed to determine the optimal treatment paradigm for patients with purely venous compression.
The Eyes and Ears of the Authoritarian Regime: Mass Reporting in China

It is widely acknowledged that official surveillance and control over Chinese citizens have been intensifying since President Xi Jinping came to power in late 2012. What is alarming is the authorit...
Neural Sequences as an Optimal Dynamical Regime for the Readout of Time

Summary Converging evidence suggests that the brain encodes time through dynamically changing patterns of neural activity, including neural sequences, ramping activity, and complex spatiotemporal dynamics. However, the potential computational significance and advantage of these different regimes have remained unaddressed. We combined large-scale recordings and modeling to compare population dynamics between premotor cortex and striatum in mice performing a two-interval timing task. Conventional decoders revealed that the dynamics within each area encoded time equally well; however, the dynamics in striatum exhibited a higher degree of sequentiality. Analysis of premotor and striatal dynamics, together with a large set of simulated prototypical dynamical regimes, revealed that regimes with higher sequentiality allowed a biologically constrained artificial downstream network to better read out time. These results suggest that, although different strategies exist for encoding time in the brain, neural sequences represent an ideal and flexible dynamical regime for enabling downstream areas to read out this information.
Frieze vectors and unitary friezes

Let Q be a quiver without loops and 2-cycles, let A(Q) be the corresponding cluster algebra and let x be a cluster. We introduce a new class of integer vectors which we call frieze vectors relative to x. These frieze vectors are defined as solutions of certain Diophantine equations given by the cluster variables in the cluster algebra. We show that every cluster gives rise to a frieze vector and that the frieze vector determines the cluster. We also study friezes of type Q as homomorphisms from the cluster algebra to an arbitrary integral domain. In particular, we show that every positive integral frieze of affine Dynkin type A is unitary, which means it is obtained by specializing each cluster variable in one cluster to the constant 1. This completes the answer to the question of unitarity for all positive integral friezes of Dynkin and affine Dynkin types.
NIMBus: a negative binomial regression based Integrative Method for mutation Burden Analysis

Identifying frequently mutated regions is a key approach to discover DNA elements influencing cancer progression. However, it is challenging to identify these burdened regions due to mutation rate heterogeneity across the genome and across different individuals. Moreover, it is known that this heterogeneity partially stems from genomic confounding factors, such as replication timing and chromatin organization. The increasing availability of cancer whole genome sequences and functional genomics data from the Encyclopedia of DNA Elements (ENCODE) may help address these issues. We developed a negative binomial regression-based Integrative Method for mutation Burden analysiS (NIMBus). Our approach addresses the over-dispersion of mutation count statistics by (1) using a Gamma–Poisson mixture model to capture the mutation-rate heterogeneity across different individuals and (2) estimating regional background mutation rates by regressing the varying local mutation counts against genomic features extracted from ENCODE. We applied NIMBus to whole-genome cancer sequences from the PanCancer Analysis of Whole Genomes project (PCAWG) and other cohorts. It successfully identified well-known coding and noncoding drivers, such as TP53 and the TERT promoter. To further characterize the burdening of non-coding regions, we used NIMBus to screen transcription factor binding sites in promoter regions that intersect DNase I hypersensitive sites (DHSs). This analysis identified mutational hotspots that potentially disrupt gene regulatory networks in cancer. We also compare this method to other mutation burden analysis methods. NIMBus is a powerful tool to identify mutational hotspots. The NIMBus software and results are available as an online resource at github.gersteinlab.org/nimbus.
Measurements of Entangled Two-Photon Absorption in Organic Molecules with CW-Pumped Type-I Spontaneous Parametric Down-Conversion

Entangled photons exhibit strong nonclassical frequency and time correlations simultaneously, which allow them to excite and extract information about molecules in new ways compared to classical sp...
Walking Drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters

When walking along a city street, you might encounter a range of scents and odors, from the smells of coffee and food to those of exhaust fumes and garbage. The odors are swept to your nose by air currents that move scents in two different ways. They carry them downwind in a process called advection, but they also mix them chaotically with clean air in a process called turbulence. What results is an odor plume: a complex ever-changing structure resembling the smoke rising from a chimney. Within a plume, areas of highly concentrated odor particles break up into smaller parcels as they travel further from the odor source. This means that the concentration of the odor does not vary along a smooth gradient. Instead, the odor arrives in brief and unpredictable bursts. Despite this complexity, insects are able to use odor plumes with remarkable ease to navigate towards food sources. But how do they do this? Answering this question has proved challenging because odor plumes are usually invisible. Over the years, scientists have come up with a number of creative solutions to this problem, including releasing soap bubbles together with odors, or using wind tunnels to generate simpler, straight plumes in known locations. These approaches have shown that when insects encounter an odor, they surge upwind towards its source. When they lose track of the odor, they cast themselves crosswind in an effort to regain contact. But this does not explain how insects are able to navigate irregular odor plumes, in which both the timing and location of the odor bursts are unpredictable. Demir, Kadakia et al. have now bridged this gap by showing how fruit flies are attracted to smoke, an odorant that is also visible. By injecting irregular smoke plumes into a custom-built wind tunnel, and then imaging flies as they walked through it, Demir, Kadakia et al. showed that flies make random halts when navigating the plume. Each time they stop, they use the timing of the odor bursts reaching them to decide when to start moving again. Rather than turning every time they detect an odor, flies initiate turns at random times. When several odor bursts arrive in a short time, the flies tend to orient these turns upwind rather than downwind. Flies therefore rely on a different strategy to navigate irregular odor plumes than the ‘surge and cast’ method they use for regular odor streams. Successful navigation through complex irregular plumes involves a degree of random behavior. This helps the flies gather information about an unpredictable environment as they search for the source of the odor. These findings may help to understand how other insects use odor to navigate in the real world, for example, how mosquitoes track down human hosts.
Dimensional interpolation for metallic hydrogen

We employ a simple and mostly accurate dimensional interpolation formula using dimensional limits D = 1 and D = ∞ to obtain D = 3 ground-state energy of metallic hydrogen. We also present results describing the phase transitions for different symmetries of three-dimensional structure lattices. The interpolation formula not only predicts fairly accurate energies but also predicts a correct functional form of the energy as a function of the lattice parameters. That allows us to calculate different physical quantities such as the bulk modulus, Debye temperature, and critical transition temperature, from the gradient and the curvature of the energy curve as a function of the lattice parameters. These theoretical calculations suggest that metallic hydrogen is a likely candidate for high temperature superconductivity. The dimensional interpolation formula is robust and might be useful to obtain the energies of complex many-body systems.
Broadband high-resolution molecular spectroscopy with interleaved mid-infrared frequency combs.

Traditionally, there has been a trade-off in spectroscopic measurements between high resolution, broadband coverage, and acquisition time. Originally envisioned for precision spectroscopy of the hydrogen atom in the ultraviolet, optical frequency combs are now commonly used for probing molecular ro-vibrational transitions throughout broad spectral bands in the mid-infrared providing superior resolution, speed, and the capability of referencing to the primary frequency standards. Here we demonstrate the acquisition of 2.5 million spectral data points over the continuous wavelength range of 3.17-5.13 µm (frequency span 1200 cm-1, sampling point spacing 13-21 MHz), via interleaving comb-tooth-resolved spectra acquired with a highly-coherent broadband dual-frequency-comb system based on optical subharmonic generation. With the original comb-line spacing of 115 MHz, overlaying eight spectra with gradually shifted comb lines we fully resolve the amplitude and phase spectra of molecules with narrow Doppler lines, such as carbon disulfide (CS2) and its three isotopologues.
Unsupervised Metric Learning in Presence of Missing Data

For many machine learning tasks, the input data lie on a low-dimensional manifold embedded in a high-dimensional space and, because of this high-dimensional structure, most algorithms inefficient. The typical solution is to reduce the dimension of the input data using a standard dimension reduction algorithms such as ISOMAP, LAPLACIAN EIGENMAPS or LLEs. This approach, however, does not always work in practice as these algorithms require that we have somewhat ideal data. Unfortunately, most data sets either have missing entries or unacceptably noisy values. That is, real data are far from ideal and we cannot use these algorithms directly.In this paper, we focus on the case when we have missing data. Some techniques, such as matrix completion, can be used to fill in missing data but these methods do not capture the non-linear structure of the manifold. Here, we present a new algorithm MR-MISSING that extends these previous algorithms and can be used to compute low dimensional representation on data sets with missing entries. We demonstrate the effectiveness of our algorithm by running three different experiments. We visually verify the effectiveness of our algorithm on synthetic manifolds, we numerically compare our projections against those computed by first filling in data using nlPCA and mDRUR on the MNIST data set, and we also show that we can do classification on MNIST with missing data. We also provide a theoretical guarantee for MR-MISSING under some simplifying assumptions.
The spin of holographic electrons at nonzero density and temperature

We study the Green’s function of a gauge invariant fermionic operator in a strongly coupled field theory at nonzero temperature and density using a dual gravity description. The gravity model contains a charged black hole in four dimensional anti-de Sitter space and probe charged fermions. In particular, we consider the effects of the spin of these probe fermions on the properties of the Green’s function. There exists a spin-orbit coupling between the spin of an electron and the electric field of a Reissner-Nordstrom black hole. On the field theory side, this coupling leads to a Rashba like dispersion relation. We also study the effects of spin on the damping term in the dispersion relation by considering how the spin affects the placement of the fermionic quasinormal modes in the complex frequency plane in a WKB limit. An appendix contains some exact solutions of the Dirac equation in terms of Heun polynomials.
Locally accurate MPS approximations for ground states of one-dimensional gapped local Hamiltonians

A key feature of ground states of gapped local 1D Hamiltonians is their relatively low entanglement --- they are well approximated by matrix product states (MPS) with bond dimension scaling polynomially in the length $N$ of the chain, while general states require a bond dimension scaling exponentially. We show that the bond dimension of these MPS approximations can be improved to a constant, independent of the chain length, if we relax our notion of approximation to be more local: for all length-$k$ segments of the chain, the reduced density matrices of our approximations are $\epsilon$-close to those of the exact state. If the state is a ground state of a gapped local Hamiltonian, the bond dimension of the approximation scales like $(k/\epsilon)^{1+o(1)}$, and at the expense of worse but still $\text{poly}(k,1/\epsilon)$ scaling of the bond dimension, we give an alternate construction with the additional features that it can be generated by a constant-depth quantum circuit with nearest-neighbor gates, and that it applies generally for any state with exponentially decaying correlations. For a completely general state, we give an approximation with bond dimension $\exp(O(k/\epsilon))$, which is exponentially worse, but still independent of $N$. Then, we consider the prospect of designing an algorithm to find a local approximation for ground states of gapped local 1D Hamiltonians. When the Hamiltonian is translationally invariant, we show that the ability to find $O(1)$-accurate local approximations to the ground state in $T(N)$ time implies the ability to estimate the ground state energy to $O(1)$ precision in $O(T(N)\log(N))$ time.
Phase Transitions in a Driven Lattice Gas with Anisotropic Interactions

The Ising lattice gas, with its well known equilibrium properties, displays a number of surprising phenomena when driven into nonequilibrium steady states. We study such a model with anisotropic interparticle interactions (J ||≠J ⊥), using both Monte Carlo simulations and high temperature series techniques. Under saturation drive, the shift in the transition temperature can be both positive and negative, depending on the ratio J ||/J ⊥! For finite drives, both first- and second-order transitions are observed. Some aspects of the phase diagram can be predicted by investigating the two-point correlation function at the first nontrivial order of a high-temperature series expansion.
Estimating Spectra from Photometry

Measuring the physical properties of galaxies such as redshift frequently requires the use of spectral energy distributions (SEDs). SED template sets are, however, often small in number and cover limited portions of photometric color space. Here we present a new method to estimate SEDs as a function of color from a small training set of template SEDs. We first cover the mathematical background behind the technique before demonstrating our ability to reconstruct spectra based upon colors and then compare our results to other common interpolation and extrapolation methods. When the photometric filters and spectra overlap, we show that the error in the estimated spectra is reduced by more than 65% compared to the more commonly used techniques. We also show an expansion of the method to wavelengths beyond the range of the photometric filters. Finally, we demonstrate the usefulness of our technique by generating 50 additional SED templates from an original set of 10 and by applying the new set to photometric redshift estimation. We are able to reduce the photometric redshifts standard deviation by at least 22.0% and the outlier rejected bias by over 86.2% compared to original set for z ≤ 3.
HETEROGENEITY IN SHORT GAMMA-RAY BURSTS

We analyze the Swift/BAT sample of short gamma-ray bursts, using an objective Bayesian Block procedure to extract temporal descriptors of the bursts' initial pulse complexes (IPCs). The sample comprises 12 and 41 bursts with and without extended emission (EE) components, respectively. IPCs of non-EE bursts are dominated by single pulse structures, while EE bursts tend to have two or more pulse structures. The medians of characteristic timescales - durations, pulse structure widths, and peak intervals - for EE bursts are factors of approx 2-3 longer than for non-EE bursts. A trend previously reported by Hakkila and colleagues unifying long and short bursts - the anti-correlation of pulse intensity and width - continues in the two short burst groups, with non-EE bursts extending to more intense, narrower pulses. In addition we find that preceding and succeeding pulse intensities are anti-correlated with pulse interval. We also examine the short burst X-ray afterglows as observed by the Swift/XRT. The median flux of the initial XRT detections for EE bursts (approx 6 X 10(exp -10) erg / sq cm/ s) is approx > 20 x brighter than for non-EE bursts, and the median X-ray afterglow duration for EE bursts (approx 60,000 s) is approx 30 x longer than for non-EE bursts. The tendency for EE bursts toward longer prompt-emission timescales and higher initial X-ray afterglow fluxes implies larger energy injections powering the afterglows. The longer-lasting X-ray afterglows of EE bursts may suggest that a significant fraction explode into more dense environments than non-EE bursts, or that the sometimes-dominant EE component efficiently p()wers the afterglow. Combined, these results favor different progenitors for EE and non-EE short bursts.
Model Selection in Contextual Stochastic Bandit Problems

We study model selection in stochastic bandit problems. Our approach relies on a master algorithm that selects its actions among candidate base algorithms. While this problem is studied for specific classes of stochastic base algorithms, our objective is to provide a method that can work with more general classes of stochastic base algorithms. We propose a master algorithm inspired by CORRAL \cite{DBLP:conf/colt/AgarwalLNS17} and introduce a novel and generic smoothing transformation for stochastic bandit algorithms that permits us to obtain $O(\sqrt{T})$ regret guarantees for a wide class of base algorithms when working along with our master. We exhibit a lower bound showing that even when one of the base algorithms has $O(\log T)$ regret, in general it is impossible to get better than $\Omega(\sqrt{T})$ regret in model selection, even asymptotically. We apply our algorithm to choose among different values of $\epsilon$ for the $\epsilon$-greedy algorithm, and to choose between the $k$-armed UCB and linear UCB algorithms. Our empirical studies further confirm the effectiveness of our model-selection method.
The quantum Sabine law for resonances in transmission problems

We prove a quantum version of the Sabine law from acoustics describing the location of resonances in transmission problems. This work extends the author's previous work to a broader class of systems. Our main applications are to scattering by transparent obstacles, scattering by highly frequency dependent delta potentials, and boundary stabilized wave equations. We give a sharp characterization of the resonance free regions in terms of dynamical quantities. In particular, we relate the imaginary part of resonances or generalized eigenvalues to the chord lengths and reflectivity coefficients for the ray dynamics, thus proving a quantum version of the Sabine law.
Examining Tatooine: Atmospheric Models of Neptune-like Circumbinary Planets

Circumbinary planets experience a time-varying irradiation pattern as they orbit their two host stars. In this work, we present the first detailed study of the atmospheric effects of this irradiation pattern on known and hypothetical gaseous circumbinary planets. Using both a one-dimensional energy balance model (EBM) and a three-dimensional general circulation model (GCM), we look at the temperature differences between circumbinary planets and their equivalent single-star cases in order to determine the nature of the atmospheres of these planets. We find that for circumbinary planets on stable orbits around their host stars, temperature differences are on average no more than 1.0% in the most extreme cases. Based on detailed modeling with the GCM, we find that these temperature differences are not large enough to excite circulation differences between the two cases. We conclude that gaseous circumbinary planets can be treated as their equivalent single-star case in future atmospheric modeling efforts.
3D and some other things missing from the theory of massive Star Evolution

This is a sketch of a 321D approximation which is nonlocal, and thus has nonzero fluxes of KE (to be published in more detail elsewhere). We plan to add this as an option to MESA. Inclusion of KE fluxes seems to help resolve the solar abundance problem (Asplund et al. 2009 ). Smaller cores may ease the explosion problems with core collapse supernova simulations.
Pairing glue activation in cuprates within the quantum critical regime

A grand challenge in many-body quantum physics is to explain the apparent connection between quantum criticality and high-temperature superconductivity in the cuprates and similar systems, such as the iron pnictides and chalcogenides. Here we argue that the quantum-critical regime plays an essential role in activating a strong-pairing mechanism: although pairing bosons create a symmetry-breaking instability which suppresses pairing, the combination of these broken-symmetry states within the critical regime can restore this symmetry for the paired quasiparticles. This condition is shown to be met within a large-U ansatz. A hidden quantum phase transition then arises between a Fermi-liquid and a non–Fermi-liquid broken-symmetry striped state, and a critical regime in which the broken-symmetry states are combined.
Structure of transition metal clusters: A force-biased Monte Carlo approach

We present a force-biased Monte Carlo (FMC) method for structural modeling of transition metal clusters of Fe, Ni, and Cu with 5 to 60 atoms. By employing the Finnis-Sinclair potential for Fe and the Sutton-Chen potential for Ni and Cu, the total energy of the clusters is minimized using a method that utilizes atomic forces in Monte Carlo simulations. The structural configurations of the clusters obtained from this biased Monte Carlo approach are analyzed and compared with the same from the Cambridge Cluster Database (CCD). The results show that the total-energy of the FMC clusters is very close to the corresponding value of the CCD clusters as listed in the Cambridge Cluster Database. A comparison of the FMC and CCD clusters is presented by computing the pair-correlation function, the bond-angle distribution, and the distribution of atomic-coordination numbers in the first-coordination shell, which provide information about the two-body and three-body correlation functions, the local atomic structure, and the bonding environment of the atoms in the clusters.
Scaling laws and universality in the choice of election candidates

Nowadays there is an increasing interest of physicists in finding regularities related to social phenomena. This interest is clearly motivated by applications that a statistical mechanical description of the human behavior may have in our society. By using this framework, we address this work to cover an open question related to elections: the choice of elections candidates (candidature process). Our analysis reveals that, apart from the social motivations, this system displays features of traditional out-of-equilibrium physical phenomena such as scale-free statistics and universality. Basically, we found a non-linear (power law) mean correspondence between the number of candidates and the size of the electorate (number of voters), and also that this choice has a multiplicative underlying process (lognormal behavior). The universality of our findings is supported by data from 16 elections from 5 countries. In addition, we show that aspects of scale-free network can be connected to this universal behavior.
Frequent Spin Reorientation of Galaxies due to Local Interactions

We study the evolution of angular momenta of M * = 1010-1012 M ? galaxies utilizing large-scale ultra-high resolution cosmological hydrodynamic simulations and find that the spin of the stellar component changes direction frequently because of interactions with nearby systems, such as major mergers, minor mergers, significant gas inflows, and torques. The rate and nature of change of spin direction cannot be accounted for by large-scale tidal torques, because the rates of the latter fall short by orders of magnitude and because the apparent random swings of the spin direction are inconsistent with the alignment by linear density field. The implications for galaxy formation as well as the intrinsic alignment of galaxies are profound. Assuming the large-scale tidal field is the sole alignment agent, a new picture emerging is that intrinsic alignment of galaxies would be a balance between slow large-scale coherent torquing and fast spin reorientation by local interactions. What is still open is whether other processes, such as feeding galaxies with gas and stars along filaments or sheets, introduce coherence for spin directions of galaxies along the respective structures.
Unimodularity of Invariant Random Subgroups

An invariant random subgroup H≤G is a random closed subgroup whose law is invariant to conjugation by all elements of G. When G is locally compact and second countable, we show that for every invariant random subgroup H≤G there almost surely exists an invariant measure on G/H. Equivalently, the modular function of H is almost surely equal to the modular function of G, restricted to H. We use this result to construct invariant measures on orbit equivalence relations of measure preserving actions. Additionally, we prove a mass transport principle for discrete or compact invariant random subgroups.
Physical Origins of Gas Motions in Galaxy Cluster Cores: Interpreting Hitomi Observations of the Perseus Cluster

The Hitomi X-ray satellite has provided the first direct measurements of the plasma velocity dispersion in a galaxy cluster. It finds a relatively "quiescent" gas with a line-of-sight velocity dispersion ~ 160 km/s, at 30 kpc to 60 kpc from the cluster center. This is surprising given the presence of jets and X-ray cavities that indicates on-going activity and feedback from the active galactic nucleus (AGN) at the cluster center. Using a set of mock Hitomi observations generated from a suite of state-of-the-art cosmological cluster simulations, and an isolated but higher resolution simulation of gas physics in the cluster core, including the effects of cooling and AGN feedback, we examine the likelihood of Hitomi detecting a cluster with the observed velocities. As long as the Perseus has not experienced a major merger in the last few gigayears, and AGN feedback is operating in a "gentle" mode, we reproduce the level of gas motions observed by Hitomi. The frequent mechanical AGN feedback generates net line-of-sight velocity dispersions ~100-200 km/s, bracketing the values measured in the Perseus core. The large-scale velocity shear observed across the core, on the other hand, is generated mainly by cosmic accretion such as mergers. We discuss the implications of these results for AGN feedback physics and cluster cosmology and progress that needs to be made in both simulations and observations, including a Hitomi re-flight and calorimeter-based instruments with higher spatial resolution.
A new set of generators and a physical interpretation for the SU (3) finite subgroup D(9,1,1;2,1,1)

After 100 years of effort, the classification of all the finite subgroups of \(SU(3)\) is yet incomplete. The most recently updated list can be found in Ludl (J Phys A Math Theory 44:255204, 2011), where the structure of the series \((C)\) and \((D)\) of \(SU(3)\)-subgroups is studied. We provide a minimal set of generators for one of these groups which has order \(162\). These generators appear up to phase as the image of an irreducible unitary braid group representation issued from the Jones–Kauffman version of \(SU(2)\) Chern–Simons theory at level \(4\). In light of these new generators, we study the structure of the group in detail and recover the fact that it is isomorphic to the semidirect product \(\mathbb Z _9\times \mathbb Z _3\rtimes S_3\) with respect to conjugation.
State sum invariants of three manifolds from spherical multi-fusion categories

We define a family of quantum invariants of closed oriented 3-manifolds using spherical multi-fusion categories (SMFCs). The state sum nature of this invariant leads directly to (2 + 1)-dimensional...
Rescuing neural spike train models from bad MLE

The standard approach to fitting an autoregressive spike train model is to maximize the likelihood for one-step prediction. This maximum likelihood estimation (MLE) often leads to models that perform poorly when generating samples recursively for more than one time step. Moreover, the generated spike trains can fail to capture important features of the data and even show diverging firing rates. To alleviate this, we propose to directly minimize the divergence between neural recorded and model generated spike trains using spike train kernels. We develop a method that stochastically optimizes the maximum mean discrepancy induced by the kernel. Experiments performed on both real and synthetic neural data validate the proposed approach, showing that it leads to well-behaving models. Using different combinations of spike train kernels, we show that we can control the trade-off between different features which is critical for dealing with model-mismatch.
A Discontinuous Galerkin Fast Spectral Method for Multi-Species Full Boltzmann on Streaming Multi-Processors

When the molecules of a gaseous system are far apart, say in microscale gas flows where the surface to volume ratio is high and hence the surface forces dominant, the molecule-surface interactions lead to the formation of a local thermodynamically non-equilibrium region extending few mean free paths from the surface. The dynamics of such systems is accurately described by Boltzmann equation. However, the multi-dimensional nature of Boltzmann equation presents a huge computational challenge. With the recent mathematical developments and the advent of petascale, the dynamics of full Boltzmann equation is now tractable. We present an implementation of the recently introduced multi-species discontinuous Galerkin fast spectral (DGFS) method for solving full Boltzmann on streaming multi-processors. The present implementation solves the inhomogeneous Boltzmann equation in span of few minutes, making it at least two order-of-magnitude faster than the present state-of-art stochastic method---direct simulation Monte Carlo---widely used for solving Boltzmann equation. Various performance metrics, such as weak/strong scaling have been presented. A parallel efficiency of 0.96--0.99 is demonstrated on 36 Nvidia Tesla-P100 GPUs.
Encoding robust representation for graph generation

Generative networks have made it possible to generate meaningful signals such as images and texts from simple noise. Recently, generative methods based on GAN and VAE were developed for graphs and graph signals. However, the mathematical properties of these methods are unclear, and training good generative models is difficult. This work proposes a graph generation model that uses a recent adaptation of Mallat’s scattering transform to graphs. The proposed model is naturally composed of an encoder and a decoder. The encoder is a Gaussianized graph scattering transform, which is robust to signal and graph manipulation. The decoder is a simple fully connected network that is adapted to specific tasks, such as link prediction, signal generation on graphs and full graph and signal generation. The training of our proposed system is efficient since it is only applied to the decoder and the hardware requirements are moderate. Numerical results demonstrate state-of-the-art performance of the proposed system for both link prediction and graph and signal generation.
Renormalization Group: Applications in Statistical Physics

These notes aim to provide a concise pedagogical introduction to some important applications of the renormalization group in statistical physics. After briefly reviewing the scaling approach and Ginzburg–Landau theory for critical phenomena near continuous phase transitions in thermal equilibrium, Wilsonʼs momentum shell renormalization group method is presented, and the critical exponents for the scalar Φ 4 model are determined to first order in a dimensional ϵ expansion about the upper critical dimension d c = 4 . Subsequently, the physically equivalent but technically more versatile field-theoretic formulation of the perturbational renormalization group for static critical phenomena is described. It is explained how the emergence of scale invariance connects ultraviolet divergences to infrared singularities, and the renormalization group equation is employed to compute the critical exponents for the O(n)-symmetric Landau–Ginzburg–Wilson theory to lowest non-trivial order in the ϵ expansion. The second part of this overview is devoted to field theory representations of non-linear stochastic dynamical systems, and the application of renormalization group tools to critical dynamics. Dynamic critical phenomena in systems near equilibrium are efficiently captured through Langevin stochastic equations of motion, and their mapping onto the Janssen–De Dominicis response functional, as exemplified by the field-theoretic treatment of purely relaxational models with non-conserved (model A) and conserved order parameter (model B). As examples for other universality classes, the Langevin description and scaling exponents for isotropic ferromagnets at the critical point (model J) and for driven diffusive non-equilibrium systems are discussed. Finally, an outlook is presented to scale-invariant phenomena and non-equilibrium phase transitions in interacting particle systems. It is shown how the stochastic master equation associated with chemical reactions or population dynamics models can be mapped onto imaginary-time, non-Hermitian “quantum” mechanics. In the continuum limit, this Doi–Peliti Hamiltonian is in turn represented through a coherent-state path integral action, which allows an efficient and powerful renormalization group analysis of, e.g., diffusion-limited annihilation processes, and of phase transitions from active to inactive, absorbing states.
Detection of an Optical/UV Jet/Counterjet and Multiple Spectral Components in M84

E.T.M. and M.G. acknowledge NASA ADAP grant NNX15AE55G and NASA Fermi grant NNX15AU78G. M.P. acknowledges support by the L. Spitzer Postdoctoral Fellowship. M.P. would like to thank Dr. Dimitrakoudis and Prof. Mastichiadis for providing the numerical code. This paper makes use of the following ALMA data: ADS/JAO.ALMA#2013.1.00828.S and ADS/JAO.ALMA#2015.1.01170.S. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada), MOST and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ.
Sensitivity of seismically-cued antineutrino detectors to nuclear explosions

Could antineutrinos help to verify compliance with a ban on nuclear weapons testing, or provide useful information about illicit tests? Surprisingly, detectors proposed for basic physics may be capable of detecting antineutrinos from faraway nuclear tests. Seismic data is key to the analysis. This study explores how large, water-based antineutrino detectors could rapidly confirm the nuclear nature of an explosion, constrain estimates of the fission yield, and provide other forensic insight.
THE COOLING OF THE CASSIOPEIA A NEUTRON STAR AS A PROBE OF THE NUCLEAR SYMMETRY ENERGY AND NUCLEAR PASTA

X-ray observations of the neutron star (NS) in the Cas A supernova remnant over the past decade suggest the star is undergoing a rapid drop in surface temperature of ≈2%-5.5%. One explanation suggests the rapid cooling is triggered by the onset of neutron superfluidity in the core of the star, causing enhanced neutrino emission from neutron Cooper pair breaking and formation (PBF). Using consistent NS crust and core equations of state (EOSs) and compositions, we explore the sensitivity of this interpretation to the density dependence of the symmetry energy L of the EOS used, and to the presence of enhanced neutrino cooling in the bubble phases of crustal ''nuclear pasta''. Modeling cooling over a conservative range of NS masses and envelope compositions, we find L ≲ 70 MeV, competitive with terrestrial experimental constraints and other astrophysical observations. For masses near the most likely mass of M ≳ 1.65 M {sub ☉}, the constraint becomes more restrictive 35 ≲ L ≲ 55 MeV. The inclusion of the bubble cooling processes decreases the cooling rate of the star during the PBF phase, matching the observed rate only when L ≲ 45 MeV, taking all masses into consideration, corresponding to NS radii ≲ 11 km.
Asymptotics of linear waves and resonances with applications to black holes

We describe asymptotic behavior of linear waves on Kerr(–de Sitter) black holes and more general Lorentzian manifolds, providing a quantitative analysis of the ringdown phenomenon. In particular we prove that if the initial data is localized at frequencies $${\sim \lambda \gg 1}$$ , then the energy norm of the solution is bounded by $${\mathcal{O}(\lambda^{1/2} e^{-(\nu_{\min}-\varepsilon)t/2}) + \mathcal{O}(\lambda^{-\infty}), \,\,{\rm for}\,\, t \leq C \log \lambda, \,\,{\rm where}\,\, \nu_{\min}}$$ is a natural dynamical quantity. The key tool is a microlocal projector splitting the solution into a component with controlled rate of exponential decay and an $${\mathcal{O}(\lambda e^{-(\nu_{\min}-\varepsilon)t}) + \mathcal{O}(\lambda^{-\infty})}$$ remainder. This splitting generalizes expansions into quasi-normal modes available in completely integrable settings. In the case of generalized Kerr(–de Sitter) black holes satisfying certain natural conditions, quasi-normal modes are localized in bands and satisfy a precise counting law.
Triadic analysis of affiliation networks

Triadic closure has been conceptualized and measured in a variety of ways, most famously the clustering coefficient. Existing extensions to affiliation networks, however, are sensitive to repeat group attendance, which does not reflect common interpersonal interpretations of triadic closure. This paper proposes a measure of triadic closure in affiliation networks designed to control for this factor, which manifests in bipartite models as biclique proliferation. To avoid arbitrariness, the paper introduces a triadic framework for affiliation networks, within which a range of measures can be defined; it then presents a set of basic axioms that suffice to narrow this range to the one measure. An instrumental assessment compares the proposed and two existing measures for reliability, validity, redundancy, and practicality. All three measures then take part in an investigation of three empirical social networks, which illustrates their differences.
On the ATLAS top mass measurements and the potential for stealth stop contamination

The discovery of the stop — the Supersymmetric partner of the top quark — is a key goal of the physics program enabled by the Large Hadron Collider. Although much of the accessible parameter space has already been probed, all current searches assume the top mass is known. This is relevant for the “stealth stop” regime, which is characterized by decay kinematics that force the final state top quark off its mass shell; such decays would contaminate the top mass measurements. We investigate the resulting bias imparted to the template method based ATLAS approach. A careful recasting of these results shows that effect can be as large as 2.0 GeV, comparable to the current quoted uncertainty on the top mass. Thus, a robust exploration of the stealth stop splinter requires the simultaneous consideration of the impact on the top mass. Additionally, we explore the robustness of the template technique, and point out a simple strategy for improving the methodology implemented for the semi-leptonic channel.
The Full Kostant–Toda Hierarchy on the Positive Flag Variety

We study some geometric and combinatorial aspects of the solution to the full Kostant–Toda (f-KT) hierarchy, when the initial data is given by an arbitrary point on the totally non-negative (tnn) flag variety of $${SL_n(\mathbb{R})}$$ . The f-KT flows on the tnn flag variety are complete, and we show that their asymptotics are completely determined by the cell decomposition of the tnn flag variety given by Rietsch (Total positivity and real flag varieties. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, 1998). Our results represent the first results on the asymptotics of the f-KT hierarchy (and even the f-KT lattice); moreover, our results are not confined to the generic flow, but cover non-generic flows as well. We define the f-KT flow on the weight space via the moment map, and show that the closure of each f-KT flow forms an interesting convex polytope which we call a Bruhat interval polytope. In particular, the Bruhat interval polytope for the generic flow is the permutohedron of the symmetric group $${\mathfrak{S}_n}$$ . We also prove analogous results for the full symmetric Toda hierarchy, by mapping our f-KT solutions to those of the full symmetric Toda hierarchy. In the appendix we show that Bruhat interval polytopes are generalized permutohedra, in the sense of Postnikov (Int. Math. Res. Not. IMRN (6):1026–1106, 2009).
Two New Long-period Hot Subdwarf Binaries with Dwarf Companions

Hot subdwarf stars with F-K main sequence binary companions have been known for decades, but the first orbital periods for such systems were published just recently. Current observations suggest that most have long periods, on the order of years, and that some are or once were hierarchical triple systems. As part of a survey with the Hobby-Eberly Telescope, we have been monitoring the radial velocities of several composite-spectra binaries since 2005 in order to determine their periods, velocities, and eccentricities. Here we present observations and orbital solutions for two of these systems, PG 1449+653 and PG 1701+359. Similar to the other sdB+F/G/K binaries with solved orbits, their periods are long, 909 and 734 days, respectively, and pose a challenge to current binary population synthesis models of hot subdwarf stars. Intrigued by their relatively large systemic velocities, we also present a kinematical analysis of both targets and find that neither is likely a member of the Galactic thin disk.
An algebraic analog of the virasoro group

The group of diffeomorphisms of a circle is not an infinite-dimensional algebraic group, though in many ways it acts as if it were. Here we construct an algebraic model for this object, and discuss some of its representations, which appear in the Kontsevich-Witten theory of 2D topological gravity.
HIRZEBRUCH-ZAGIER CYCLES AND TWISTED TRIPLE PRODUCT SELMER GROUPS

Let E be an elliptic curve over \({{\mathbb {Q}}}\) and A another elliptic curve over a real quadratic number field. We construct a \({{\mathbb {Q}}}\)-motive of rank 8, together with a distinguished class in the associated Bloch–Kato Selmer group, using Hirzebruch–Zagier cycles, that is, graphs of Hirzebruch–Zagier morphisms. We show that, under certain assumptions on E and A, the non-vanishing of the central critical value of the (twisted) triple product L-function attached to (E, A) implies that the dimension of the associated Bloch–Kato Selmer group of the motive is 0; and the non-vanishing of the distinguished class implies that the dimension of the associated Bloch–Kato Selmer group of the motive is 1. This can be viewed as the triple product version of Kolyvagin’s work on bounding Selmer groups of a single elliptic curve using Heegner points.
The x-ray spectrum of the plerionic system psr b1509-58/msh 15-52

We present the results of observations of the PSR B1509-58/MSH 15-52 system in X-rays (2-250 keV) by the Rossi X-Ray Timing Explorer. The spectra of the peak of the pulsed component (radio phase 0.17-0.53) is fitted by a power law of photon index 1.36±0.01, with no evidence of a high-energy spectral break seen up to ~200 keV. For the off-pulse spectral component, the spectrum from 2-250 keV is fitted by a power law of photon index 2.215±0.005. An iron emission line at 6.7 keV with an equivalent width of 129 eV improves the fit, but only at a marginal significance. Thermal bremsstrahlung and Raymond-Smith models produce much worse fits to the unpulsed data. The lack of a high-energy spectral break in the pulsed emission implies an efficiency of ≥3% in the conversion of pulsar spin-down energy to pulsed X-rays in the system.
Nef cones of Hilbert schemes of points on surfaces

Let X be a smooth projective surface of irregularity 0. The Hilbert scheme X[n] of n points on X parametrizes zero-dimensional subschemes of X of length n. We discuss general methods for studying the cone of ample divisors on X[n]. We then use these techniques to compute the cone of ample divisors on X[n] for several surfaces where the cone was previously unknown. Our examples include families of surfaces of general type and del Pezzo surfaces of degree 1. The methods rely on Bridgeland stability and the positivity lemma of Bayer and Macri.