cssi/SciSciGPT-SciSciNet huggingface dataset:
Weighted minimizer sampling improves long read mapping.

MOTIVATION In this era of exponential data growth, minimizer sampling has become a standard algorithmic technique for rapid genome sequence comparison. This technique yields a sub-linear representation of sequences, enabling their comparison in reduced space and time. A key property of the minimizer technique is that if two sequences share a substring of a specified length, then they can be guaranteed to have a matching minimizer. However, because the k-mer distribution in eukaryotic genomes is highly uneven, minimizer-based tools (e.g. Minimap2, Mashmap) opt to discard the most frequently occurring minimizers from the genome to avoid excessive false positives. By doing so, the underlying guarantee is lost and accuracy is reduced in repetitive genomic regions. RESULTS We introduce a novel weighted-minimizer sampling algorithm. A unique feature of the proposed algorithm is that it performs minimizer sampling while considering a weight for each k-mer; i.e. the higher the weight of a k-mer, the more likely it is to be selected. By down-weighting frequently occurring k-mers, we are able to meet both objectives: (i) avoid excessive false-positive matches and (ii) maintain the minimizer match guarantee. We tested our algorithm, Winnowmap, using both simulated and real long-read data and compared it to a state-of-the-art long read mapper, Minimap2. Our results demonstrate a reduction in the mapping error-rate from 0.14% to 0.06% in the recently finished human X chromosome (154.3 Mbp), and from 3.6% to 0% within the highly repetitive X centromere (3.1 Mbp). Winnowmap improves mapping accuracy within repeats and achieves these results with sparser sampling, leading to better index compression and competitive runtimes. AVAILABILITY AND IMPLEMENTATION Winnowmap is built on top of the Minimap2 codebase and is available at https://github.com/marbl/winnowmap.
H2O and Other Volatiles in the Moon, 50 Years and on

In the fifty years since the first lunar sample return, the investigation of H2O in the Moon has experienced several stages of developments and paradigms. In the early years since Apollo sample ret...
An Adversarial Model for Attack Vector Vulnerability Analysis on Power and Gas Delivery Operations

Abstract Power systems often rely on natural gas pipeline networks to supply fuel for gas-fired generation. Market inefficiencies and a lack of formal coordination between the wholesale power and gas delivery infrastructures may magnify the broader impact of a cyber-attack on a natural gas pipeline. In this study we present a model that can be used to quantify the impact of cyber-attacks on electricity and gas delivery operations. We model activation of cyber-attack vectors that attempt to gain access to pipeline gas compressor controls using a continuous-time Markov chain over a state space based on the gas operator Industrial Control System firewall zone partition. Our approach evaluates the operating states and decision-making in the networks using physically realistic and operationally representative models. We summarize these models, the sequence of analyses used to quantify the impacts of a cyber-incident, and propose a Monte Carlo simulation approach to quantify the resulting effect on the reliability of the bulk power system by the increase in operational cost. The methodology is applied to a case study of interacting power, gas, and cyber test networks.
A unified picture of Galactic and cosmological fast radio bursts

The discovery of a fast radio burst (FRB) in our galaxy associated with a magnetar (neutron star with strong magnetic field) has provided a critical piece of information to help us finally understand these enigmatic transients. We show that the volumetric rate of Galactic-FRB like events is consistent with the faint end of the cosmological FRB rate, and hence they most likely belong to the same class of transients. The Galactic FRB had an accompanying X-ray burst but many X-ray bursts from the same object had no radio counterpart. Their relative rates suggest that for every FRB there are roughly 100 to 1000 X-ray bursts. The radio lightcurve of the galactic FRB had two spikes separated by 30 ms in the 400-800 MHz frequency band. This is an important clue and highly constraining of the class of models where the radio emission is produced outside the light-cylinder of the magnetar. We suggest that magnetic disturbances close to the magnetar surface propagate to a distance of a few tens of neutron star radii where they damp and produce radio emission. The coincident hard X-ray spikes associated with the two FRB pulses seen in this burst and the flux ratio between the two frequency bands can be understood in this scenario. This model provides a unified picture for faint bursts like the Galactic FRB as well as the bright events seen at cosmological distances.
Low-Rank Covariance Function Estimation for Multidimensional Functional Data

Multidimensional function data arise from many fields nowadays. The covariance function plays an important role in the analysis of such increasingly common data. In this article, we propose a novel...
Optical Frequency Comb Calibrated near Infrared Solar Heterodyne Spectroscopy

We perform heterodyne spectroscopy at 1.56 μm with a tunable laser and thermal radiation from the Sun. The laser tuning is calibrated with a frequency comb, providing a simple spectrometer with resolving power of 2, 000, 000.
Hidden heterogeneity and its influence on dengue vaccination impact.

Abstract The CYD-TDV vaccine was recently developed to combat dengue, a mosquito-borne viral disease that afflicts millions of people each year throughout the tropical and subtropical world. Its rollout has been complicated by recent findings that vaccinees with no prior exposure to dengue virus (DENV) experience an elevated risk of severe disease in response to their first DENV infection subsequent to vaccination. As a result of these findings, guidelines for use of CYD-TDV now require serological screening prior to vaccination to establish that an individual does not fall into this high-risk category. These complications mean that the public health impact of CYD-TDV vaccination is expected to be higher in areas with higher transmission. One important practical difficulty with tailoring vaccination policy to local transmission contexts is that DENV transmission is spatially heterogeneous, even at the scale of neighborhoods or blocks within a city. This raises the question of whether models based on data that average over spatial heterogeneity in transmission could fail to capture important aspects of CYD-TDV impact in spatially heterogeneous populations. We explored this question with a deterministic model of DENV transmission and CYD-TDV vaccination in a population comprised of two communities with differing transmission intensities. Compared to the full model, a version of the model based on the average of the two communities failed to capture benefits of targeting the intervention to the high-transmission community, which resulted in greater impact in both communities than we observed under even coverage. In addition, the model based on the average of the two communities substantially overestimated impact among vaccinated individuals in the low-transmission community. In the event that the specificity of serological screening is not high, this result suggests that models that ignore spatial heterogeneity could overlook the potential for harm to this segment of the population.
AutoHOOT: Automatic High-Order Optimization for Tensors

High-order optimization methods, including Newton's method and its variants as well as alternating minimization methods, dominate the optimization algorithms for tensor decompositions and tensor networks. These tensor methods are used for data analysis and simulation of quantum systems. In this work, we introduce AutoHOOT, the first automatic differentiation (AD) framework targeting at high-order optimization for tensor computations. AutoHOOT takes input tensor computation expressions and generates optimized derivative expressions. In particular, AutoHOOT contains a new explicit Jacobian / Hessian expression generation kernel whose outputs maintain the input tensors' granularity and are easy to optimize. The expressions are then optimized by both the traditional compiler optimization techniques and specific tensor algebra transformations. Experimental results show that AutoHOOT achieves competitive CPU and GPU performance for both tensor decomposition and tensor network applications compared to existing AD software and other tensor computation libraries with manually written kernels. The tensor methods generated by AutoHOOT are also well-parallelizable, and we demonstrate good scalability on a distributed memory supercomputer.
Non-equilibrium steady state conductivity in cyclo[18]carbon and its boron nitride analogue.

A ring-shaped carbon allotrope was recently synthesized for the first time, reinvigorating theoretical interest in this class of molecules. The dual π structure of these molecules allows for the possibility of novel electronic properties. In this work we use reduced density matrix theory to study the electronic structure and conductivity of cyclo[18]carbon and its boron nitride analogue, B9N9. The variational 2-RDM method replicates the experimental polyynic geometry of cyclo[18]carbon. We use a current-constrained 1-electron reduced density matrix (1-RDM) theory with Hartree–Fock molecular orbitals and energies to compute the molecular conductance in two cases: (1) conductance in the plane of the molecule and (2) conductance around the molecular ring as potentially driven by a magnetic field through the molecule's center. In-plane conductance is greater than conductance around the ring, but cyclo[18]carbon is slightly more conductive than B9N9 for both in-the-plane and in-the-ring conduction. The computed conductance per molecular orbital provides insight into how the orbitals—their energies and densities—drive the conduction.
The essential spectrum of periodically stationary solutions of the complex Ginzburg–Landau equation

We establish the existence and regularity properties of a monodromy operator for the linearization of the cubic–quintic complex Ginzburg–Landau equation about a periodically stationary (breather) solution. We derive a formula for the essential spectrum of the monodromy operator in terms of that of the associated asymptotic linear differential operator. This result is obtained using the theory of analytic semigroups under the assumption that the Ginzburg–Landau equation includes a spectral filtering (diffusion) term. We discuss applications to the stability of periodically stationary pulses in ultrafast fiber lasers.
Valuing economic impact reductions of nutrient pollution from livestock waste.

Abstract Nutrient pollution from livestock waste impacts both fresh and marine coastal waters. Harmful algae blooms (HABs) are a common ecosystem-level response to such pollution that is detrimental to both aquatic life and human health and that generates economic losses (e.g., property values and lost tourism). Waste treatment and management technologies are not well established practices due, in part, to the difficulty to attribute economic value to associated social and environmental impacts of nutrient pollution. In this work, we propose a computational framework to quantify the economic impacts of HABs. We demonstrate the advantage of quantifying these impacts through a case study on livestock waste management in the Upper Yahara watershed region (in the state of Wisconsin, USA). Our analysis reveals that every excess kilogram of phosphorus runoff from livestock waste results in total economic losses of 74.5 USD. Furthermore, we use a coordinated market analysis to demonstrate that this economic impact provides a strong enough incentive to activate a nutrient management and valorization market that can help balance phosphorus within the study area. The proposed framework can help state, tribes, and federal regulatory agencies develop regulatory and non-regulatory policies to mitigate the impacts of nutrient pollution.
Damping Functions correct over‐dissipation of the Smagorinsky Model

This paper studies the time-averaged energy dissipation rate ⟨eSMD(u)⟩ for the combination of the Smagorinsky model and damping function. The Smagorinsky model is well known to over-damp. One common correction is to include damping functions that reduce the effects of model viscosity near walls. Mathematical analysis is given here that allows evaluation of ⟨eSMD(u)⟩ for any damping function. Moreover, the analysis motivates a modified van Driest damping. It is proven that the combination of the Smagorinsky with this modified damping function does not over-dissipate and is also consistent with Kolmogorov phenomenology. Copyright © 2017 John Wiley & Sons, Ltd.
A Case Against Spinning PAHs as the Source of the Anomalous Microwave Emission

We employ an all-sky map of the anomalous microwave emission (AME) produced by component separation of the microwave sky to study correlations between the AME and Galactic dust properties. We find that while the AME is highly correlated with all tracers of dust emission, the best predictor of the AME strength is the dust radiance. Fluctuations in the AME intensity per dust radiance are uncorrelated with fluctuations in the emission from polycyclic aromatic hydrocarbons (PAHs), casting doubt on the association between AME and PAHs. The PAH abundance is strongly correlated with the dust optical depth and dust radiance, consistent with PAH destruction in low density regions. We find that the AME intensity increases with increasing radiation field strength, at variance with predictions from the spinning dust hypothesis. Finally, the temperature-dependence of the AME per dust radiance disfavors the interpretation of the AME as thermal emission. A reconsideration of other AME carriers, such as ultrasmall silicates, and other emission mechanisms, such as magnetic dipole emission, is warranted.
Emerging Local Currency Bond Markets

In this article, the authors assess local currency bond markets in emerging market economies (EMEs). Supported by policies and laws that helped improve macroeconomic stability and creditor rights, local currency EME bond markets have grown substantially over the past decade and have provided USD-based investors with attractive returns. U.S. investors have responded by sharply increasing their holdings of EME local currency bonds, especially in EMEs with investor-friendly institutions and policies.
Analytical and Numerical Characterizations of Shannon Ordering for Discrete Memoryless Channels

This paper studies several problems concerning channel inclusion, which is a partial ordering between discrete memoryless channels (DMCs) proposed by Shannon. Specifically, majorization-based conditions are derived for channel inclusion between certain DMCs. Furthermore, under general conditions, channel equivalence defined through Shannon ordering is shown to be the same as permutation of input and output symbols. The determination of channel inclusion is considered as a convex optimization problem, and the sparsity of the weights related to the representation of the worse DMC in terms of the better one is revealed when channel inclusion holds between two DMCs. For the exploitation of this sparsity, an effective iterative algorithm is established based on modifying the orthogonal matching pursuit algorithm.
On Schmidt's Conjecture and Star Formation Scaling Laws

Ever since the pioneering work of Schmidt a half-century ago there has been great interest in finding an appropriate empirical relation that would directly link some property of interstellar gas with the process of star formation within it. Schmidt conjectured that this might take the form of a power-law relation between the rate of star formation (SFR) and the surface density of interstellar gas. However, recent observations suggest that a linear scaling relation between the total SFR and the amount of dense gas within molecular clouds appears to be the underlying physical relation that most directly connects star formation with interstellar gas from scales of individual GMCs to those encompassing entire galaxies both near and far. Although Schmidt relations are found to exist within local GMCs, there is no Schmidt relation observed between GMCs. The implications of these results for interpreting and understanding the Kennicutt-Schmidt scaling law for galaxies are discussed.
Laboratory space physics: Investigating the physics of space plasmas in the laboratory

Laboratory experiments provide a valuable complement to explore the fundamental physics of space plasmas without the limitations inherent to spacecraft measurements. Specifically, experiments overcome the restriction that spacecraft measurements are made at only one (or a few) points in space, enable greater control of the plasma conditions and applied perturbations, can be reproducible, and are orders of magnitude less expensive than launching spacecraft. Here, I highlight key open questions about the physics of space plasmas and identify the aspects of these problems that can potentially be tackled in laboratory experiments. Several past successes in laboratory space physics provide concrete examples of how complementary experiments can contribute to our understanding of physical processes at play in the solar corona, solar wind, planetary magnetospheres, and the outer boundary of the heliosphere. I present developments on the horizon of laboratory space physics, identifying velocity space as a key new frontier, highlighting new and enhanced experimental facilities, and showcasing anticipated developments to produce improved diagnostics and innovative analysis methods. A strategy for future laboratory space physics investigations will be outlined, with explicit connections to specific fundamental plasma phenomena of interest.
TaxiNLI: Taking a Ride up the NLU Hill

Pre-trained Transformer-based neural architectures have consistently achieved state-of-the-art performance in the Natural Language Inference (NLI) task. Since NLI examples encompass a variety of linguistic, logical, and reasoning phenomena, it remains unclear as to which specific concepts are learnt by the trained systems and where they can achieve strong generalization. To investigate this question, we propose a taxonomic hierarchy of categories that are relevant for the NLI task. We introduce TaxiNLI, a new dataset, that has 10k examples from the MNLI dataset with these taxonomic labels. Through various experiments on TaxiNLI, we observe that whereas for certain taxonomic categories SOTA neural models have achieved near perfect accuracies—a large jump over the previous models—some categories still remain difficult. Our work adds to the growing body of literature that shows the gaps in the current NLI systems and datasets through a systematic presentation and analysis of reasoning categories.
A simplified approach to general scalar-tensor theories

The most general covariant action describing gravity coupled to a scalar field with only second order equations of motion, Horndeski's theory (also known as ``Generalized Galileons''), provides an all-encompassing model in which single scalar dark energy models may be constrained. However, the generality of the model makes it cumbersome to manipulate. In this paper, we demonstrate that when considering linear perturbations about a Friedmann-Robertson-Walker background, the theory is completely specified by only six functions of time, two of which are constrained by the background evolution. We utilise the ideas of the Effective Field Theory of Inflation/Dark Energy to explicitly construct these six functions of time in terms of the free functions appearing in Horndeski's theory. These results are used to investigate the behavior of the theory in the quasistatic approximation. We find that only four functions of time are required to completely specify the linear behavior of the theory in this limit, which can further be reduced if the background evolution is fixed. This presents a significantly reduced parameter space from the original presentation of Horndeski's theory, giving hope to the possibility of constraining the parameter space. This work provides a cross-check for previous work on linear perturbations in this theory, and also generalizes it to include spatial curvature.
MIT SuperCloud portal workspace: Enabling HPC web application deployment

The MIT SuperCloud Portal Workspace enables the secure exposure of web services running on high performance computing (HPC) systems. The portal allows users to run any web application as an HPC job and access it from their workstation while providing authentication, encryption, and access control at the system level to prevent unintended access. This capability permits users to seamlessly utilize existing and emerging tools that present their user interface as a website on an HPC system creating a portal workspace. Performance measurements indicate that the MIT SuperCloud Portal Workspace incurs marginal overhead when compared to a direct connection of the same service.
Oblique Hanle effect in semiconductor spin transport devices

Spin precession and dephasing (“Hanle effect”) provide an unambiguous means to establish the presence of spin transport in semiconductors. We compare theoretical modeling with experimental data from drift-dominated silicon spin-transport devices, illustrating the nontrivial consequences of employing oblique magnetic fields (due to misalignment or intentional, fixed in-plane field components) to measure the effects of spin precession. Model results are also calculated for Hanle measurements under conditions of diffusion-dominated transport, revealing an expected Hanle peak-widening effect induced by the presence of fixed in-plane magnetic bias fields.
Integer partitions probability distributions

Two closely related discrete probability distributions are introduced. In each case the support is a set of vectors in Rn obtained from the partitions of the fixed positive integer n. These distrib...
High-power ultrafast Yb:fiber laser frequency combs using commercially available components and basic fiber tools

We present a detailed description of the design, construction, and performance of high-power ultrafast Yb:fiber laser frequency combs in operation in our laboratory. We discuss two such laser systems: an 87 MHz, 9 W, 85 fs laser operating at 1060 nm and an 87 MHz, 80 W, 155 fs laser operating at 1035 nm. Both are constructed using low-cost, commercially available components, and can be assembled using only basic tools for cleaving and splicing single-mode fibers. We describe practical methods for achieving and characterizing low-noise single-pulse operation and long-term stability from Yb:fiber oscillators based on nonlinear polarization evolution. Stabilization of the combs using a variety of transducers, including a new method for tuning the carrier-envelope offset frequency, is discussed. High average power is achieved through chirped-pulse amplification in simple fiber amplifiers based on double-clad photonic crystal fibers. We describe the use of these combs in several applications, including ultrasensitive femtosecond time-resolved spectroscopy and cavity-enhanced high-order harmonic generation.
Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative Priors

Many problems in statistics and machine learning require the reconstruction of a rank-one signal matrix from noisy data. Enforcing additional prior information on the rank-one component is often key to guaranteeing good recovery performance. One such prior on the low-rank component is sparsity, giving rise to the sparse principal component analysis problem. Unfortunately, there is strong evidence that this problem suffers from a computational-to-statistical gap, which may be fundamental. In this work, we study an alternative prior where the low-rank component is in the range of a trained generative network. We provide a non-asymptotic analysis with optimal sample complexity, up to logarithmic factors, for rank-one matrix recovery under an expansive-Gaussian network prior. Specifically, we establish a favorable global optimization landscape for a nonlinear least squares objective, provided the number of samples is on the order of the dimensionality of the input to the generative model. This result suggests that generative priors have no computational-to-statistical gap for structured rank-one matrix recovery in the finite data, nonasymptotic regime. We present this analysis in the case of both the Wishart and Wigner spiked matrix models.
CTDPathSim: Cell line-tumor deconvoluted pathway-based similarity in the context of precision medicine in cancer

In cancer research and drug development, human tumor-derived cell lines are used as popular model for cancer patients to evaluate the biological functions of genes, drug efficacy, side-effects, and drug metabolism. Using these cell lines, the functional relationship between genes and drug response and prediction of drug response based on genomic and chemical features have been studied. Knowing the drug response on the real patients, however, is a more important and challenging task. To tackle this challenge, some studies integrate data from primary tumors and cancer cell lines to find associations between cell lines and tumors. These studies, however, do not integrate multi-omics datasets to their full extent. Also, several studies rely on a genome-wide correlation-based approach between cell lines and bulk tumor samples without considering the heterogeneous cell population in bulk tumors. To address these gaps, we developed a computational pipeline, CTDPathSim, a pathway activity-based approach to compute similarity between primary tumor samples and cell lines at genetic, genomic, and epigenetic levels integrating multi-omics datasets. We utilized a deconvolution method to get cell type-specific DNA methylation and gene expression profiles and computed deconvoluted methylation and expression profiles of tumor samples. We assessed CTDPathSim by applying on breast and ovarian cancer data in The Cancer Genome Atlas (TCGA) and cancer cell lines data in the Cancer Cell Line Encyclopedia (CCLE) databases. Our results showed that highly similar sample-cell line pairs have similar drug response compared to lowly similar pairs in several FDA-approved cancer drugs, such as Paclitaxel, Vinorelbine and Mitomycin-c. CTDPathSim outperformed state-of-the-art methods in recapitulating the known drug responses between samples and cell lines. Also, CTDPathSim selected higher number of significant cell lines belonging to the same cancer types than other methods. Furthermore, our aligned cell lines to samples were found to be clinical biomarkers for patients' survival whereas unaligned cell lines were not. Our method could guide the selection of appropriate cell lines to be more intently serve as proxy of patient tumors and could direct the pre-clinical translation of drug testing into clinical platform towards the personalized therapies. Furthermore, this study could guide the new uses for old drugs and benefits the development of new drugs in cancer treatments.
Test for a large amount of entanglement, using few measurements

Bell-inequality violations establish that two systems share some quantum entanglement. We give a simple test to certify that two systems share an asymptotically large amount of entanglement, n EPR states. The test is efficient: unlike earlier tests that play many games, in sequence or in parallel, our test requires only one or two CHSH games. One system is directed to play a CHSH game on a random specified qubit i, and the other is told to play games on qubits {i,j}, without knowing which index is i. The test is robust: a success probability within delta of optimal guarantees distance O(n^{5/2} sqrt{delta}) from n EPR states. However, the test does not tolerate constant delta; it breaks down for delta = Omega~(1/sqrt{n}). We give an adversarial strategy that succeeds within delta of the optimum probability using only O~(delta^{-2}) EPR states.
Enhanced Abundances In Spiral Galaxies Of The Pegasus I Cluster

We study the influence of cluster environment on the chemical evolution of spiral galaxies in the Pegasus I cluster. We determine the gas-phase heavy element abundances of six galaxies in Pegasus derived from H II region spectra obtained from integral-field spectroscopy. These abundances are analyzed in the context of Virgo, whose spirals are known to show increasing interstellar metallicity as a function of H I deficiency. The galaxies in the Pegasus cluster, despite its lower density and velocity dispersion, also display gas loss due to interstellar-medium-intracluster-medium interaction, albeit to a lesser degree. Based on the abundances of three H I deficient spirals and two H I normal spirals, we observe a heavy element abundance offset of +0.13 {+-} 0.07 dex for the H I deficient galaxies. This abundance differential is consistent with the differential observed in Virgo for galaxies with a similar H I deficiency, and we observe a correlation between log (O/H) and the H I deficiency parameter DEF for the two clusters analyzed together. Our results suggest that similar environmental mechanisms are driving the heavy element enhancement in both clusters.
Longitudinal Inverted Compressibility in Super-strained Metamaterials

We develop a statistical physics theory for solid-solid phase transitions in which a metamaterial undergoes longitudinal contraction in response to increase in external tension. Such transitions, which are forbidden in thermodynamic equilibrium, have recently been shown to be possible during the decay of metastable, super-strained states. We present a first-principles model to predict these transitions and validate it using molecular dynamics simulations. Aside from its immediate mechanical implications, our theory points to a wealth of analogous inverted responses, such as inverted susceptibility or heat-capacity transitions, allowed when considering realistic scales.
Generalized Orbifold Construction for Conformal Nets

Let ℬ be a conformal net. We give the notion of a proper action of a finite hypergroup K acting by vacuum preserving unital completely positive (so-called stochastic) maps on ℬ which generalizes the proper action of a finite group G. Taking the fixed point under such an action gives a finite index subnet ℬK of ℬ, which generalizes the G-orbifold net. Conversely, we show that if &#x1d49c;⊂ℬ is a finite inclusion of conformal nets, then &#x1d49c; is a generalized orbifold &#x1d49c; = ℬK of the conformal net ℬ by a unique finite hypergroup K. There is a Galois correspondence between intermediate nets ℬK ⊂&#x1d49c;⊂ℬ and subhypergroups L ⊂ K given by &#x1d49c; = ℬL. In this case, the fixed point of ℬK ⊂&#x1d49c; is the generalized orbifold by the hypergroup of double cosets L∖K/L. If &#x1d49c;⊂ℬ is a finite index inclusion of completely rational nets, we show that the inclusion &#x1d49c;(I) ⊂ℬ(I) is conjugate to an intermediate subfactor of a Longo–Rehren inclusion. This implies that if ℬ is a holomorphic net, and K acts properly on ℬ, then there is a unitary fusion category ℱ which is a categorification of K and Rep(ℬK) is braided equivalent to the Drinfel’d center Z(ℱ). More generally, if ℬ is a completely rational conformal net and K acts properly on ℬ, then there is a unitary fusion category ℱ extending Rep(ℬ), such that K is given by the double cosets of the fusion ring of ℱ by the Verlinde fusion ring of ℬ and Rep(ℬK) is braided equivalent to the Muger centralizer of Rep(ℬ) in the Drinfel’d center Z(ℱ).
DETERMINACY AND INDETERMINACY OF GAMES PLAYED ON COMPLETE METRIC SPACES

Schmidt's game is a powerful tool for studying properties of certain sets which arise in Diophantine approximation theory, number theory, and dynamics. Recently, many new results have been proven using this game. In this paper we address determinacy and indeterminacy questions regarding Schmidt's game and its variations, as well as more general games played on complete metric spaces (for example fractals). We show that except for certain exceptional cases, these games are undetermined on certain sets. Judging by the vast numbers of papers utilising these games, we believe that the results in this paper will be of interest to a large audience of number theorists as well as set theorists and logicians. DOI: 10.1017/S0004972714000069
MODELING TRANSITING CIRCUMSTELLAR DISKS: CHARACTERIZING THE NEWLY DISCOVERED ECLIPSING DISK SYSTEM OGLE LMC-ECL-11893

We investigate the nature of the unusual eclipsing star OGLE LMC-ECL-11893 (OGLE J05172127-6900558) in the Large Magellanic Cloud recently reported by Dong et al. The eclipse period for this star is 468 days, and the eclipses exhibit a minimum of ∼1.4 mag, preceded by a plateau of ∼0.8 mag. Spectra and optical/IR photometry are consistent with the eclipsed star being a lightly reddened B9III star of inferred age ∼150 Myr and mass ∼4 M {sub ☉}. The disk appears to have an outer radius of ∼0.2 AU with predicted temperatures of ∼1100-1400 K. We model the eclipses as being due to either a transiting geometrically thin dust disk or gaseous accretion disk around a secondary object; the debris disk produces a better fit. We speculate on the origin of such a dense circumstellar dust disk structure orbiting a relatively old low-mass companion, and on the similarities of this system to the previously discovered EE Cep.
Limiting Measure of Lee–Yang Zeros for the Cayley Tree

This paper is devoted to an in-depth study of the limiting measure of Lee–Yang zeroes for the Ising Model on the Cayley Tree. We build on previous works of Muller-Hartmann and Zittartz (Z Phys B 22:59, 1975), Muller-Hartmann (Z Phys B 27:161–168, 1977), Barata and Marchetti (J Stat Phys 88:231–268, 1997) and Barata and Goldbaum (J Stat Phys 103:857–891, 2001), to determine the support of the limiting measure, prove that the limiting measure is not absolutely continuous with respect to Lebesgue measure, and determine the pointwise dimension of the measure at Lebesgue a.e. point on the unit circle and every temperature. The latter is related to the critical exponents for the phase transitions in the model as one crosses the unit circle at Lebesgue a.e. point, providing a global version of the “phase transition of continuous order” discovered by Muller-Hartmann–Zittartz. The key techniques are from dynamical systems because there is an explicit formula for the Lee–Yang zeros of the finite Cayley Tree of level n in terms of the n-th iterate of an expanding Blaschke Product. A subtlety arises because the conjugacies between Blaschke Products at different parameter values are not absolutely continuous.
Experimental quantum state tomography of optical fields and ultrafast statistical sampling

We review experimental work on the measurement of the quantum state of optical fields, and the relevant theoretical background. The basic technique of optical homodyne tomography is described with particular attention paid to the role played by balanced homodyne detection. We discuss some of the original single- mode squeezed-state measurements as well as recent developments including: other field states, multimode measurements, array detection, and other new homodyne schemes. We also discuss applications of state measurement techniques to an area of scientific and technological importance-the ultrafast sampling of time-resolved photon statistics.
A constellation of MicroSats to search for NEOs

Large or even medium sized asteroids impacting the Earth can cause damage on a global scale. Existing and planned concepts for finding near-Earth objects (NEOs) with diameter of 140 m or larger would take ~15-20 years of observation to find ~90% of them. This includes both ground and space based projects. For smaller NEOs (~50-70 m in diameter), the time scale is many decades. The reason it takes so long to detect these objects is because most of the NEOs have highly elliptical orbits that bring them into the inner solar system once per orbit. If these objects cross the Earth's orbit when the Earth is on the other side of the Sun, they will not be detected by facilities on or around the Erath. A constellation of MicroSats in orbit around the Sun can dramatically reduce the time needed to find 90% of NEOs ~100-140 m in diameter.
Symmetric powers and a problem of Kollár and Larsen

We prove a conjecture of Kollar and Larsen on Zariski closed subgroups of $GL(V)$ which act irreducibly on some symmetric power $Sym^{k}(V)$ with $k \geq 4$. This conjecture has interesting implications, in particular on the holonomy group of a stable vector bundle on a smooth projective variety, as shown by the recent work of Balaji and Kollar.
AN INVESTIGATION INTO THE FERMILAB APPROACH TO HEAVY QUARKS ON THE LATTICE

We use a space-time asymmetric O(a) improved fermion action and fix the asymmetry non-perturbatively to restore the relativistic dispersion relation. We compute spectra and matrix elements of quarkonia and heavy-light mesons and compare with results obtained using a symmetric action with the Fermilab interpretation i.e. that the physics of heavy lattice quarks depends solely on their kinetic mass. We provide additional evidence to support this.
A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability

AbstractStochastic reduced models are an important tool in climate systems whose many spatial and temporal scales cannot be fully discretized or underlying physics may not be fully accounted for. O...
Implicit ligand theory: Rigorous binding free energies and thermodynamic expectations from molecular docking

A rigorous formalism for estimating noncovalent binding free energies and thermodynamic expectations from calculations in which receptor configurations are sampled independently from the ligand is derived. Due to this separation, receptor configurations only need to be sampled once, facilitating the use of binding free energy calculations in virtual screening. Demonstrative calculations on a host-guest system yield good agreement with previous free energy calculations and isothermal titration calorimetry measurements. Implicit ligand theory provides guidance on how to improve existing molecular docking algorithms and insight into the concepts of induced fit and conformational selection in noncovalent macromolecular recognition.
5d Higgs branch localization, Seiberg-Witten equations and contact geometry

In this paper we apply the idea of Higgs branch localization to 5d supersymmetric theories of vector multiplet and hypermultiplets, obtained as the rigid limit of $$ \mathcal{N} $$ = 1 supergravity with all auxiliary fields. On supersymmetric K-contact/Sasakian background, the Higgs branch BPS equations can be interpreted as 5d generalizations of the Seiberg-Witten equations. We discuss the properties and local behavior of the solutions near closed Reeb orbits. For U(1) gauge theories, which can be straight-forwardly generalized to theories whose gauge group can be completely broken, we show the suppression of the deformed Coulomb branch, and the partition function is dominated by 5d Seiberg-Witten solutions. For squashed S 5 and Y pq manifolds, we show the matching between poles in the perturbative Coulomb branch matrix model, and the bound on local winding numbers of the BPS solutions.
Lattice QCD Thermodynamics with Wilson Quarks

We review studies of QCD thermodynamics by lattice QCD simulations with dynamical Wilson quarks. After explaining the basic properties of QCD with Wilson quarks at finite temperature including the phase structure and the scaling properties around the chiral phase transition, we discuss the critical temperature, the equation of state and heavy-quark free energies.
The big problems in star formation: The star formation rate, stellar clustering, and the initial mass function

Abstract Star formation lies at the center of a web of processes that drive cosmic evolution: generation of radiant energy, synthesis of elements, formation of planets, and development of life. Decades of observations have yielded a variety of empirical rules about how it operates, but at present we have no comprehensive, quantitative theory. In this review I discuss the current state of the field of star formation, focusing on three central questions: What controls the rate at which gas in a galaxy converts to stars? What determines how those stars are clustered, and what fraction of the stellar population ends up in gravitationally-bound structures? What determines the stellar initial mass function, and does it vary with star-forming environment? I use these three questions as a lens to introduce the basics of star formation, beginning with a review of the observational phenomenology and the basic physical processes. I then review the status of current theories that attempt to solve each of the three problems, pointing out links between them and opportunities for theoretical and numerical work that crosses the scale between them. I conclude with a discussion of prospects for theoretical progress in the coming years.
Clustered Monotone Transforms for Rating Factorization

Exploiting low-rank structure of the user-item rating matrix has been the crux of many recommendation engines. However, existing recommendation engines force raters with heterogeneous behavior profiles to map their intrinsic rating scales to a common rating scale (e.g. 1-5). This non-linear transformation of the rating scale shatters the low-rank structure of the rating matrix, therefore resulting in a poor fit and consequentially, poor recommendations. In this paper, we propose Clustered Monotone Transforms for Rating Factorization (CMTRF), a novel approach to perform regression up to unknown monotonic transforms over unknown population segments. Essentially, for recommendation systems, the technique searches for monotonic transformations of the rating scales resulting in a better fit. This is combined with an underlying matrix factorization regression model that couples the user-wise ratings to exploit shared low dimensional structure. The rating scale transformations can be generated for each user, for a cluster of users, or for all the users at once, forming the basis of three simple and efficient algorithms proposed in this paper, all of which alternate between transformation of the rating scales and matrix factorization regression. Despite the non-convexity, CMTRF is theoretically shown to recover a unique solution under mild conditions. Experimental results on two synthetic and seven real-world datasets show that CMTRF outperforms other state-of-the-art baselines.
Structure and Strength at Immiscible Polymer Interfaces

Thermal welding of polymer–polymer interfaces is important for integrating polymeric elements into devices. When two different polymers are joined, the strength of the weld depends critically on the degree of immiscibility. We perform large-scale molecular dynamics simulations of the structure–strength relation at immiscible polymer interfaces. Our simulations show that immiscibility arrests interdiffusion and limits the equilibrium interfacial width. Even for weakly immiscible films, the narrow interface is unable to transfer stress upon deformation as effectively as the bulk material, and chain pullout at the interface becomes the dominant failure mechanism. This greatly reduces the interfacial strength. The weak response of immiscible interfaces is shown to arise from an insufficient density of entanglements across the interface. We demonstrate that there is a threshold interfacial width below which no significant entanglements can form between opposite sides to strengthen the interface.
Hierarchies of Susy Splittings and Invisible Photinos as Dark Matter

We explore how to generate hierarchies in the splittings between superpartners. Some of the consequences are the existence of invisible components of dark matter, new inflaton candidates, invisible monopoles and a number of invisible particles that might dominate during various eras, in particular between BBN and recombination and decay subsequently.
CHEMICAL EVOLUTION IN HIERARCHICAL MODELS OF COSMIC STRUCTURE. II. THE FORMATION OF THE MILKY WAY STELLAR HALO AND THE DISTRIBUTION OF THE OLDEST STARS

This paper presents theoretical star formation and chemical enrichment histories for the stellar halo of the Milky Way (MW) based on new chemodynamical modeling. The goal of this study is to assess the extent to which metal-poor stars in the halo reflect the star formation conditions that occurred in halo progenitor galaxies at high redshift, before, and during the epoch of re-ionization. Simple prescriptions that translate dark-matter (DM) halo mass into baryonic gas budgets and star formation histories yield models that resemble the observed MW halo in its total stellar mass, metallicity distribution, and the luminosity function and chemical enrichment of dwarf satellite galaxies. These model halos in turn allow an exploration of how the populations of interest for probing the epoch of re-ionization are distributed in physical and phase space, and of how they are related to lower-redshift populations of the same metallicity. The fraction of stars dating from before a particular time or redshift depends strongly on radius within the galaxy, reflecting the "inside-out" growth of cold DM halos, and on metallicity, reflecting the general trend toward higher metallicity at later times. These results suggest that efforts to discover stars from z>6-10 should select for stars with [Fe/H] –3 and favor stars on more tightly bound orbits in the stellar halo, where the majority are from z>10 and 15%-40% are from z>15. The oldest, most metal-poor stars—those most likely to reveal the chemical abundances of the first stars—are most common in the very center of the Galaxy's halo: they are in the bulge, but not of the bulge. These models have several implications for the larger project of constraining the properties of the first stars and galaxies using data from the local universe.
Tightness of the maximum likelihood semidefinite relaxation for angular synchronization

Maximum likelihood estimation problems are, in general, intractable optimization problems. As a result, it is common to approximate the maximum likelihood estimator (MLE) using convex relaxations. In some cases, the relaxation is tight: it recovers the true MLE. Most tightness proofs only apply to situations where the MLE exactly recovers a planted solution (known to the analyst). It is then sufficient to establish that the optimality conditions hold at the planted signal. In this paper, we study an estimation problem (angular synchronization) for which the MLE is not a simple function of the planted solution, yet for which the convex relaxation is tight. To establish tightness in this context, the proof is less direct because the point at which to verify optimality conditions is not known explicitly. Angular synchronization consists in estimating a collection of n phases, given noisy measurements of the pairwise relative phases. The MLE for angular synchronization is the solution of a (hard) non-bipartite Grothendieck problem over the complex numbers. We consider a stochastic model for the data: a planted signal (that is, a ground truth set of phases) is corrupted with non-adversarial random noise. Even though the MLE does not coincide with the planted signal, we show that the classical semidefinite relaxation for it is tight, with high probability. This holds even for high levels of noise.