cssi/SciSciGPT-SciSciNet huggingface dataset:
A new numerical approach to the solution of PDEs with optimal accuracy on irregular domains and Cartesian meshes—Part 1: the derivations for the wave, heat and Poisson equations in the 1-D and 2-D cases

A new numerical approach for the time-dependent wave and heat equations as well as for the time-independent Poisson equation on irregular domains has been developed. Trivial Cartesian meshes and simple 9-point stencil equations with unknown coefficients are used for 2-D irregular domains. The calculation of the coefficients of the stencil equations is based on the minimization of the local truncation error of the stencil equations and yields the optimal order of accuracy. The treatment of the Dirichlet and Neumann boundary conditions in the new approach is related to the development of high-order boundary conditions with the stencils that include the same or a smaller number of grid points compared to that for the regular 9-point internal stencils. At similar 9-point stencils, the accuracy of the new approach is two orders higher than that for the linear finite elements. The numerical results for irregular domains in Part 2 of the paper also show that at the same number of degrees of freedom, the new approach is even much more accurate than the quadratic and cubic finite elements with much wider stencils. Similar to our recent results on regular domains, the order of the accuracy of the new approach for the Poisson equation on irregular domains with square Cartesian meshes is higher than that with rectangular Cartesian meshes. The new approach can be directly applied to other partial differential equations.
Mixed-Integer Linear Programming Models for Multi-Robot Non-Adversarial Search

In this letter, we consider the Multi-Robot Efficient Search Path Planning (MESPP) problem, where a team of robots is deployed in a graph-represented environment to capture a moving target within a given deadline. We prove this problem to be NP-hard, and present the first set of Mixed-Integer Linear Programming (MILP) models to tackle the MESPP problem. Our models are the first to encompass multiple searchers, arbitrary capture ranges, and false negatives simultaneously. While state-of-the-art algorithms for MESPP are based on simple path enumeration, the adoption of MILP as a planning paradigm allows to leverage the powerful techniques of modern solvers, yielding better computational performance and, as a consequence, longer planning horizons. The models are designed for computing optimal solutions offline, but can be easily adapted for a distributed online approach. Our simulations show that it is possible to achieve 98% decrease in computational time relative to the previous state-of-the-art. We also show that the distributed approach performs nearly as well as the centralized, within 6% in the settings studied in this letter, with the advantage of requiring significant less time – an important consideration in practical search missions.
DeepTriage: Automated Transfer Assistance for Incidents in Cloud Services

As cloud services are growing and generating high revenues, the cost of downtime in these services is becoming significantly expensive. To reduce loss and service downtime, a critical primary step is to execute incident triage, the process of assigning a service incident to the correct responsible team, in a timely manner. An incorrect assignment risks additional incident reroutings and increases its time to mitigate by 10x. However, automated incident triage in large cloud services faces many challenges: (1) a highly imbalanced incident distribution from a large number of teams, (2) wide variety in formats of input data or data sources, (3) scaling to meet production-grade requirements, and (4) gaining engineers' trust in using machine learning recommendations. To address these challenges, we introduce DeepTriage, an intelligent incident transfer service combining multiple machine learning techniques - gradient boosted classifiers, clustering methods, and deep neural networks - in an ensemble to recommend the responsible team to triage an incident. Experimental results on real incidents in Microsoft Azure show that our service achieves 82.9% F1 score. For highly impacted incidents, DeepTriage achieves F1 score from 76.3% -- 91.3%. We have applied best practices and state-of-the-art frameworks to scale DeepTriage to handle incident routing for all cloud services. DeepTriage has been deployed in Azure since October 2017 and is used by thousands of teams daily.
Coupling silicon vacancy centers in a thin diamond membrane to a silica optical microresonator

We report the development of a composite cavity QED system, in which silicon vacancy centers in a diamond membrane as thin as 100 nm couple to optical whispering gallery modes (WGMs) of a silica microsphere with a diameter of order 50 µm. The membrane induces a linewidth broadening of 3 MHz for equatorial and off-resonant WGMs, while the overall linewidth of the composite system remains below 40 MHz. Photoluminescence experiments in the cavity QED setting demonstrate the efficient coupling of optical emissions from silicon vacancy centers into the WGMs. Additional analysis indicates that the composite system can be used to achieve the good cavity limit in cavity QED, enabling an experimental platform for applications such as state transfer between spins and photons.
Higher-form gauge symmetries in multipole topological phases

Abstract In this article we study field-theoretical aspects of multipolar topological insulators. Previous research has shown that such systems naturally couple to higher-rank tensor gauge fields that arise as a result of gauging dipole or subsystem U ( 1 ) symmetries. Here we propose a complementary framework using electric higher-form symmetries. We utilize the fact that gauging 1-form electric symmetries results in a 2-form gauge field which couples naturally to extended line-like objects: Wilson lines. In our context the Wilson lines are electric flux lines associated to the electric polarization of the system. This allows us to define a generalized 2-form Peierls’ substitution for dipoles that shows that the off-diagonal components of a rank-2 tensor gauge field A i j can arise as a lattice Peierls factor generated by the background antisymmetric 2-form gauge field. This framework has immediate applications: (i) it allows us to construct a manifestly topological quadrupolar response action given by a Dixmier–Douady invariant – a generalization of a Chern number for 2-form gauge fields – which makes plain the quantization of the quadrupole moment in the presence of certain crystal symmetries; (ii) it allows for a clearer interpretation of the rank-2 Berry phase calculation of the quadrupole moment; (iii) it allows for a proof of a generic Lieb–Schultz–Mattis theorem for dipole-conserving systems.
Theta-functions on noncommutative tori

Ordinary theta functions can be considered as holomorphic sections of line bundles over tori. We show that one can define generalized theta functions as holomorphic elements of projective modules over noncommutative tori (theta vectors). The theory of these new objects is not only more general, but also much simpler than the theory of ordinary theta-functions. It seems that the theory of theta vectors should be closely related to Manin's theory of quantized theta functions, but we don't analyze this relation.
Robust Active Site Design of Single-Atom Catalysts for Electrochemical Ammonia Synthesis

Electrochemical ammonia synthesis forms a key part of sustainable chemical synthesis. Single-atom catalysts have emerged as a promising class of electrocatalysts that could be capable of electroche...
Product systems of C*-correspondences and Takai duality

We establish the Hao–Ng isomorphism for generalized gauge actions of locally compact abelian groups on product systems over abelian lattice orders and we then use it to explore Takai duality in this context. As an application we generalize some recent work of Schafhauser.
A New MRAM-Based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision

The excellent performance of modern deep neural networks (DNNs) comes at an often prohibitive training cost, limiting the rapid development of DNN innovations and raising various environmental concerns. To reduce the dominant data movement cost of training, process in-memory (PIM) has emerged as a promising solution as it alleviates the need to access DNN weights. However, state-of-the-art PIM DNN training accelerators employ either analog/mixed signal computing which has limited precision or digital computing based on a memory technology that supports limited logic functions and thus requires complicated procedure to realize floating point computation. In this paper, we propose a spin orbit torque magnetic random access memory (SOT-MRAM) based digital PIM accelerator that supports floating point precision. Specifically, this new accelerator features an innovative (1) SOT-MRAM cell, (2) full addition design, and (3) floating point computation. Experiment results show that the proposed SOT-MRAM PIM based DNN training accelerator can achieve 3.3×, 1.8×, and 2.5× improvement in terms of energy, latency, and area, respectively, compared with a state-of-the-art PIM based DNN training accelerator.
Analytical model for electrohydrodynamic thrust.

Electrohydrodynamic (EHD) thrust is produced when ionized fluid is accelerated in an electric field due to the momentum transfer between the charged species and neutral molecules. We extend the pre...
Global geometry on moduli of local systems for surfaces with boundary

We show that every coarse moduli space, parametrizing complex special linear rank-2 local systems with fixed boundary traces on a surface with nonempty boundary, is log Calabi–Yau in that it has a normal projective compactification with trivial log canonical divisor. We connect this to a novel symmetry of generating series for counts of essential multicurves on the surface.
Domain Adaptation for Ultrasound Beamforming

Ultrasound B-Mode images are created from data obtained from each element in the transducer array in a process called beamforming. The beamforming goal is to enhance signals from specified spatial locations, while reducing signal from all other locations. On clinical systems, beamforming is accomplished with the delay-and-sum (DAS) algorithm. DAS is efficient but fails in patients with high noise levels, so various adaptive beamformers have been proposed. Recently, deep learning methods have been developed for this task. With deep learning methods, beamforming is typically framed as a regression problem, where clean, ground-truth data is known, and usually simulated. For in vivo data, however, it is extremely difficult to collect ground truth information, and deep networks trained on simulated data underperform when applied to in vivo data, due to domain shift between simulated and in vivo data. In this work, we show how to correct for domain shift by learning deep network beamformers that leverage both simulated data, and unlabeled in vivo data, via a novel domain adaption scheme. A challenge in our scenario is that domain shift exists both for noisy input, and clean output. We address this challenge by extending cycle-consistent generative adversarial networks, where we leverage maps between synthetic simulation and real in vivo domains to ensure that the learned beamformers capture the distribution of both noisy and clean in vivo data. We obtain consistent in vivo image quality improvements compared to existing beamforming techniques, when applying our approach to simulated anechoic cysts and in vivo liver data.
Prevention of liver cancer.

Hepatocellular carcinoma (HCC) is among the most prevalent and deadly cancers worldwide. Prominent risk factors for HCC include viral hepatitis infection; dietary exposure to hepatotoxic contaminants such as aflatoxins; alcoholism; smoking; and male gender. This review highlights ongoing efforts in HCC prevention. Strategies include vaccination against, and treatment of, viral hepatitis infection. In addition to interferon α, an acyclic retinoid (all-trans-3,7,11, 15-tetramethyl-2,4,6,10,14-hexadecapentanoic acid), glycyrrhizin and ginseng are currently under clinical investigation for HCC prevention in Japanese hepatitis C patients. Several recent clinical studies in a Chinese region of pervasive aflatoxin contamination also support the approach of favorably altering aflatoxin metabolism and excretion using the chemopreventive agents oltipraz or chlorophyllin. Agents exhibiting chemopreventive efficacy in preclinical HCC models include vitamins A, D, and E, herbal extracts, a 5α-reductase inhibitor, green tea, and D-limonene. Efforts to elucidate the molecular lesions and processes underlying HCC development have identified several putative molecular targets for preventive interventions. These include genes and gene products controlling viral replication, carcinogen metabolism, signal transduction, cell-cycle arrest, apoptosis, proliferation, and oxidative stress.
Wasm/k: delimited continuations for WebAssembly

WebAssembly is designed to be an alternative to JavaScript that is a safe, portable, and efficient compilation target for a variety of languages. The performance of high-level languages depends not only on the underlying performance of WebAssembly, but also on the quality of the generated WebAssembly code. In this paper, we identify several features of high-level languages that current approaches can only compile to WebAssembly by generating complex and inefficient code. We argue that these problems could be addressed if WebAssembly natively supported first-class continuations. We then present Wasm/k, which extends WebAssembly with delimited continuations. Wasm/k introduces no new value types, and thus does not require significant changes to the WebAssembly type system (validation). Wasm/k is safe, even in the presence of foreign function calls (e.g., to and from JavaScript). Finally, Wasm/k is amenable to efficient implementation: we implement Wasm/k as a local change to Wasmtime, an existing WebAssembly JIT. We evaluate Wasm/k by implementing C/k, which adds delimited continuations to C/C++. C/k uses Emscripten and its implementation serves as a case study on how to use Wasm/k in a compiler that targets WebAssembly. We present several case studies using C/k, and show that on implementing green threads, it can outperform the state-of-the-art approach Asyncify with an 18% improvement in performance and a 30% improvement in code size.
The Phonetic Bases of Vocal Expressed Emotion: Natural versus Acted.

Can vocal emotions be emulated? This question has been a recurrent concern of the speech community, and has also been vigorously investigated. It has been fueled further by its link to the issue of validity of acted emotion databases. Much of the speech and vocal emotion research has relied on acted emotion databases as valid proxies for studying natural emotions. To create models that generalize to natural settings, it is crucial to work with valid prototypes -- ones that can be assumed to reliably represent natural emotions. More concretely, it is important to study emulated emotions against natural emotions in terms of their physiological, and psychological concomitants. In this paper, we present an on-scale systematic study of the differences between natural and acted vocal emotions. We use a self-attention based emotion classification model to understand the phonetic bases of emotions by discovering the most 'attended' phonemes for each class of emotions. We then compare these attended-phonemes in their importance and distribution across acted and natural classes. Our tests show significant differences in the manner and choice of phonemes in acted and natural speech, concluding moderate to low validity and value in using acted speech databases for emotion classification tasks.
The Academic Achievement Gap in Grades 3 to 8

Abstract Using data for North Carolina public school students in grades 3 to 8, we examine achievement gaps between white students and students from other racial and ethnic groups. We focus on cohorts of students who stay in the state's public schools for all six years. While the black-white gaps are sizable and robust, both Hispanic and Asian students tend to gain on whites as they progress in school. Beyond simple mean differences, we find that the racial gaps in math between low-performing students have tended to shrink as students progress through school, while those for high-performing students have generally widened.
Vehicle Energy Dataset (VED), A Large-Scale Dataset for Vehicle Energy Consumption Research

We present Vehicle Energy Dataset (VED), a large-scale dataset of fuel and energy data collected from 383 personal cars in Ann Arbor, Michigan, USA. This open dataset captures GPS trajectories of vehicles along with their time-series data of fuel, energy, speed, and auxiliary power usage. A diverse fleet consisting of 264 gasoline vehicles, 92 HEVs, and 27 PHEV/EVs drove in real-world from Nov, 2017 to Nov, 2018, where the data were collected through onboard OBD-II loggers. Driving scenarios range from highways to traffic-dense downtown area in various driving conditions and seasons. In total, VED accumulates approximately 374,000 miles. We discuss participant privacy protection and develop a method to de-identify personally identifiable information while preserving the quality of the data. We present a number of case studies with the dataset to demonstrate how VED can be utilized for vehicle energy and behavior studies. The case studies investigate the impacts of factors known to affect fuel economy and identify energy-saving opportunities that hybrid-electric vehicles and eco-driving techniques can provide. Potential research opportunities include data-driven vehicle energy consumption modeling, driver behavior modeling, calibration of traffic simulators, optimal route choice modeling, prediction of human driver behaviors, and decision making of self-driving cars. We believe that VED can be an instrumental asset to the development of future automotive technologies. The dataset can be accessed at https://github.com/gsoh/VED.
Thermodynamic competition between membrane protein oligomeric states

Self-assembly of protein monomers into distinct membrane protein oligomers provides a general mechanism for diversity in the molecular architectures, and resulting biological functions, of membrane proteins. We develop a general physical framework describing the thermodynamic competition between different oligomeric states of membrane proteins. Using the mechanosensitive channel of large conductance as a model system, we show how the dominant oligomeric states of membrane proteins emerge from the interplay of protein concentration in the cell membrane, protein-induced lipid bilayer deformations, and direct monomer-monomer interactions. Our results suggest general physical mechanisms and principles underlying regulation of protein function via control of membrane protein oligomeric state.
The Motion of a Body in Newtonian Theories

A theorem due to Bob Geroch and Pong Soo Jang ["Motion of a Body in General Relativity." Journal of Mathematical Physics 16(1), (1975)] provides the sense in which the geodesic principle has the status of a theorem in General Relativity (GR). Here we show that a similar theorem holds in the context of geometrized Newtonian gravitation (often called Newton-Cartan theory). It follows that in Newtonian gravitation, as in GR, inertial motion can be derived from other central principles of the theory.
EVIDENCE AGAINST DARK MATTER HALOS SURROUNDING THE GLOBULAR CLUSTERS MGC1 AND NGC 2419

The conjecture that the ancient globular clusters (GCs) formed at the center of their own dark matter (DM) halos was first proposed by Peebles in 1984 and has recently been revived to explain the puzzling abundance patterns observed within many GCs. In this paper, we demonstrate that the outer stellar density profile of isolated GCs is very sensitive to the presence of an extended dark halo. The GCs NGC 2419, located at 90 kpc from the center of our Galaxy, and MGC1, located at ~200 kpc from the center of M31, are ideal laboratories for testing the scenario that GCs formed at the centers of massive dark halos. Comparing analytic models to observations of these GCs, we conclude that these GCs cannot be embedded within dark halos with a virial mass greater than 106 M ☉, or, equivalently, the DM halo-mass-to-stellar mass ratio must be M DM/M * < 1. If these GCs have indeed orbited within weak tidal fields throughout their lifetimes, then these limits imply that these GCs did not form within their own dark halos. Recent observations of an extended stellar halo in the GC NGC 1851 are also interpreted in the context of our analytic models. Implications of these results for the formation of GCs are briefly discussed.
Elastic functional principal component regression

We study regression using functional predictors in situations where these functions contain both phase and amplitude variability. In other words, the functions are misaligned due to errors in time measurements, and these errors can significantly degrade both model estimation and prediction performance. The current techniques either ignore the phase variability, or handle it via pre-processing, i.e., use an off-the-shelf technique for functional alignment and phase removal. We develop a functional principal component regression model which has comprehensive approach in handling phase and amplitude variability. The model utilizes a mathematical representation of the data known as the square-root slope function. These functions preserve the $\mathbf{L}^2$ norm under warping and are ideally suited for simultaneous estimation of regression and warping parameters. Using both simulated and real-world data sets, we demonstrate our approach and evaluate its prediction performance relative to current models. In addition, we propose an extension to functional logistic and multinomial logistic regression
Theory of Orbital Magnetization in Solids

In this review article, we survey the relatively new theory of orbital magnetization in solids — often referred to as the "modern theory of orbital magnetization" — and its applications. Surprisingly, while the calculation of the orbital magnetization in finite systems such as atoms and molecules is straight forward, in extended systems or solids it has long eluded calculations owing to the fact that the position operator is ill-defined in such a context. Approaches that overcome this problem were first developed in 2005 and in the first part of this review we present the main ideas reaching from a Wannier function approach to semi-classical and finite-temperature formalisms. In the second part, we describe practical aspects of calculating the orbital magnetization, such as taking k-space derivatives, a formalism for pseudopotentials, a single k-point derivation, a Wannier interpolation scheme, and DFT specific aspects. We then show results of recent calculations on Fe, Co, and Ni. In the last part of this review, we focus on direct applications of the orbital magnetization. In particular, we will review how properties such as the nuclear magnetic resonance shielding tensor and the electron paramagnetic resonance g-tensor can be elegantly calculated in terms of a derivative of the orbital magnetization.
Preconditioned Data Sparsification for Big Data With Applications to PCA and K-Means

We analyze a compression scheme for large data sets that randomly keeps a small percentage of the components of each data sample. The benefit is that the output is a sparse matrix, and therefore, subsequent processing, such as principal component analysis (PCA) or K-means, is significantly faster, especially in a distributed-data setting. Furthermore, the sampling is single-pass and applicable to streaming data. The sampling mechanism is a variant of previous methods proposed in the literature combined with a randomized preconditioning to smooth the data. We provide guarantees for PCA in terms of the covariance matrix, and guarantees for K-means in terms of the error in the center estimators at a given step. We present numerical evidence to show both that our bounds are nearly tight and that our algorithms provide a real benefit when applied to standard test data sets, as well as providing certain benefits over related sampling approaches.
A General Algorithm for Deciding Transportability of Experimental Results

Generalizing empirical findings to new environments, settings, or populations is essential in most scientific explorations. This article treats a particular problem of generalizability, called “transportability”, defined as a license to transfer information learned in experimental studies to a different population, on which only observational studies can be conducted. Given a set of assumptions concerning commonalities and differences between the two populations, Pearl and Bareinboim [1] derived sufficient conditions that permit such transfer to take place. This article summarizes their findings and supplements them with an effective procedure for deciding when and how transportability is feasible. It establishes a necessary and sufficient condition for deciding when causal effects in the target population are estimable from both the statistical information available and the causal information transferred from the experiments. The article further provides a complete algorithm for computing the transport formula, that is, a way of combining observational and experimental information to synthesize bias-free estimate of the desired causal relation. Finally, the article examines the differences between transportability and other variants of generalizability.
Fault Localization for Declarative Models in Alloy

Fault localization is a popular research topic and many techniques have been proposed to locate faults in imperative code, e.g. C and Java. In this paper, we focus on the problem of fault localization for declarative models in Alloy – a first order relational logic with transitive closure. We introduce AlloyFL hy , the first fault localization technique for faulty Alloy models which leverages multiple test formulas. AlloyFL hy brings the traditional spectrum-based and mutation-based fault localization techniques to Alloy and combines both techniques to locate faults. To measure the effectiveness of AlloyFL hy , we define three distance metrics and use both distance-based and top-k metrics to measure the effectiveness of AlloyFL hy on 90 real faulty models. The results show that AlloyFLhy is substantially more effective than Alloy’s built-in unsat core.
Cosmological leverage from the matter power spectrum in the presence of baryon and nonlinear effects

We investigate how the use of higher wavenumbers (smaller scales) in the galaxy clustering power spectrum influences cosmological constraints. We take into account uncertainties from nonlinear density fluctuations, (scale dependent) galaxy bias, and baryonic effects. Allowing for substantially model independent uncertainties through separate fit parameters in each wavenumber bin that also allow for the redshift evolution, we quantify strong gains in dark energy and neutrino mass leverage with increasing maximum wavenumber, despite marginalizing over numerous (up to 125) extra fit parameters. The leverage is due to not only an increased number of modes but, more significantly, breaking of degeneracies beyond the linear regime.
Schubert calculus of Richardson varieties stable under spherical Levi subgroups

We observe that the expansion in the basis of Schubert cycles for H ∗(G/B) of the class of a Richardson variety stable under a spherical Levi subgroup is described by a theorem of Brion. Using this observation, along with a combinatorial model of the poset of certain symmetric subgroup orbit closures, we give positive combinatorial descriptions of certain Schubert structure constants on the full flag variety in type A. Namely, we describe $c_{u,v}^{w}$ when u and v are inverse to Grassmannian permutations with unique descents at p and q, respectively. We offer some roughly stated conjectures for similar rules in types B and D, associated to Richardson varieties stable under spherical Levi subgroups of SO(2n+1,ℂ) and SO(2n,ℂ), respectively.
Deformed cohomology of flag varieties

This paper introduces a two-parameter deformation of the cohomology of generalized flag varieties. One special case is the Belkale-Kumar deformation (used to study eigencones of Lie groups). Another picks out intersections of Schubert varieties that behave nicely under projections. Our construction yields a new proof that the Belkale-Kumar product is well-defined. This proof is shorter and more elementary than earlier proofs.
Axion kinetic misalignment and parametric resonance from inflation

Axion cold dark matter from standard misalignment typically requires a decay constant $f_a~\gtrsim~10^{11}$ GeV. Kinetic misalignment and parametric resonance easily allow lower values of $f_a$ when the radial Peccei-Quinn (PQ) symmetry breaking field takes large initial values. Here, we consider the effects of inflation on kinetic misalignment and parametric resonance. We assume that the initial PQ field value is determined by quantum fluctuations, and is set by the Hubble parameter during inflation, $H_I$, and the PQ field mass. PQ field oscillations begin before or after the completion of reheating after inflation at a temperature $T_R$. We determine the range of $f_a$ and the inflationary parameters $(H_I, T_R)$ consistent with axion dark matter for a quartic potential for the PQ field. We find that $4\times 10^8$ GeV $< f_a < 10^{11}$ GeV can consistently produce axion dark matter. A significant portion of the allowed parameter space predicts rare kaon decays, $K_L \rightarrow (\pi^0 + \rm{missing \; energy})$, and/or suppression of structure formation on small scales.
Nearby High-speed Stars in Gaia DR2

We investigate the nature of nearby (10–15 kpc) high-speed stars in the Gaia DR2 archive identified on the basis of parallax, proper motion and radial velocity. Together with a consideration of their kinematic, orbital, and photometric properties, we develop a novel strategy for evaluating whether high-speed stars are statistical outliers of the bound population or unbound stars capable of escaping the Galaxy. Out of roughly 1.5 million stars with radial velocities, proper motions, and 5σ parallaxes, we identify just over 100 high-speed stars. Of these, only two have a nearly 100% chance of being unbound, with an indication that they are not just bound outliers; both are likely hyper-runaway stars. The rest of the high-speed stars are likely statistical outliers. We use the sample of high-speed stars to demonstrate that radial velocity alone provides a poor discriminant of nearby, unbound stars. However, these stars are efficiently identified from the tangential velocity, using just parallax and proper motion. Within the full Gaia DR2 archive of stars with 5σ parallax and proper motion but no radial velocity, we identify a sample of 19 with speeds significantly larger than the local escape speed of the Milky Way based on tangential motion alone.
Causality bounds for neutron-proton scattering

We consider the constraints of causality and unitarity for the low-energy interactions of protons and neutrons. We derive a general theorem that non-vanishing partial-wave mixing cannot be reproduced with zero-range interactions without violating causality or unitarity. We define and calculate interaction length scales which we call the causal range and the Cauchy-Schwarz range for all spin channels up to J = 3 . For some channels we find that these length scales are as large as 5fm. We investigate the origin of these large lengths and discuss their significance for the choice of momentum cutoff scales in effective field theory and universality in many-body Fermi systems.
Does the BICEP2 observation of cosmological tensor modes imply an era of nearly planckian energy densities

BICEP2 observations, interpreted most simply, suggest an era of inflation with energy densities of order (1016 GeV)4, not far below the Planck density. However, models of TeV gravity with large extra dimensions might allow a very different interpretation involving much more modest energy scales. We discuss the viability of inflation in such models, and conclude that existing scenarios do not provide attractive alternatives to single field inflation in four dimensions. Because the detection of tensor modes strengthens our confidence that inflation occurred, it disfavors models of large extra dimensions, at least for the moment.
QUASI-QUIESCENT RADIO EMISSION FROM THE FIRST RADIO-EMITTING T DWARF

Radio detections of ultracool dwarfs provide insight into their magnetic fields and the dynamos that maintain them, especially at the very bottom of the main sequence, where other activity indicators dramatically weaken. Until recently, radio emission was only detected in the M and L dwarf regimes, but this has changed with the Arecibo detection of rapid polarized flares from the T6.5 dwarf 2MASS J10475385+2124234. Here, we report the detection of quasi-quiescent radio emission from this source at 5.8 GHz using the Karl G. Jansky Very Large Array. The spectral luminosity is L ν = (2.2 ± 0.7) × 1012 erg s–1 Hz–1, a factor of ~100 times fainter than the Arecibo flares. Our detection is the lowest luminosity yet achieved for an ultracool dwarf. Although the emission is fully consistent with being steady, unpolarized, and broad band, we find tantalizing hints for variability. We exclude the presence of short-duration flares as seen by Arecibo, although this is not unexpected given estimates of the duty cycle. Follow-up observations of this object will offer the potential to constrain its rotation period, electron density, and the strength and configuration of the magnetic field. Equally important, follow-up observations will address the question of whether the electron cyclotron maser instability, which is thought to produce the flares seen by Arecibo, also operates in the very different parameter regime of the emission we detect, or whether instead this ultracool dwarf exhibits both maser and gyrosynchrotron radiation, potentially originating from substantially different locations.
Unusual ordered phases of highly frustrated magnets: a review

We review ground states and excitations of a quantum antiferromagnet on triangular and other frustrated lattices. We pay special attention to the combined effects of magnetic field h, spatial anisotropy R and spin magnitude S. The focus of the review is on the novel collinear spin density wave and spin nematic states, which are characterized by fully gapped transverse spin excitations with Sz = ± 1. We discuss extensively the R − h phase diagram of the antiferromagnet, both in the large-S semiclassical limit and the quantum S = 1/2 limit. When possible, we point out connections with experimental findings.
Learning Character Strings via Mastermind Queries, With a Case Study Involving mtDNA

We study the degree to which a character string Q leaks details about itself any time it engages in comparison protocols with a strings provided by a querier, Bob, even if those protocols are cryptographically guaranteed to produce no additional information other than the scores that assess the degree to which Q matches strings offered by Bob. We show that such scenarios allow Bob to play variants of the game of Mastermind with Q so as to learn the complete identity of Q. We show that there are a number of efficient implementations for Bob to employ in these Mastermind attacks, depending on knowledge he has about the structure of Q, which show how quickly he can determine Q. Indeed, we show that Bob can discover Q using a number of rounds of test comparisons that is much smaller than the length of Q, under reasonable assumptions regarding the types of scores that are returned by the cryptographic protocols and whether he can use knowledge about the distribution that Q comes from. We also provide the results of a case study we performed on a database of mitochondrial DNA, showing the vulnerability of existing real-world DNA data to the Mastermind attack.
A Coincidence Search for Cosmic Neutrino and Gamma-Ray Emitting Sources Using IceCube and Fermi LAT Public Data

We present results of an archival coincidence analysis between Fermi Large Area Telescope (LAT) gamma-ray data and public neutrino data from the IceCube neutrino observatory’s 40-string (IC 40) and 59-string (IC 59) observing runs. Our analysis has the potential to detect either a statistical excess of neutrino + gamma-ray (ν + γ) emitting transients or, alternatively, individual high gamma-multiplicity events, as might be produced by a neutrino observed by IceCube coinciding with a LAT-detected gamma-ray burst. Dividing the neutrino data into three data sets by hemisphere (IC 40, IC 59-North, and IC 59-South), we construct uncorrelated null distributions by Monte Carlo scrambling of the neutrino data sets. We carry out signal-injection studies against these null distributions, demonstrating sensitivity to individual ν + γ events of sufficient gamma-ray multiplicity, and to ν + γ transient populations responsible for >13% (IC 40), >9% (IC 59-North), or >8% (IC 59-South) of the gamma-coincident neutrinos observed in these data sets, respectively. Analyzing the unscrambled neutrino data, we identify no individual high-significance neutrino + high gamma-multiplicity events and no significant deviations from the test statistic null distributions. However, we observe a similar and unexpected pattern in the IC 59-North and IC 59-South residual distributions that we conclude reflects a possible correlation (p = 7.0%) between IC 59 neutrino positions and persistently bright portions of the Fermi gamma-ray sky. This possible correlation should be readily testable using eight years of further data already collected by IceCube. We are currently working with Astrophysical Multimessenger Observatory Network (AMON) partner facilities to generate low-latency ν + γ alerts from Fermi-LAT gamma-ray and IceCube and ANTARES neutrino data and distribute these in real time to AMON follow-up partners.
MEASUREMENTS OF COSMIC RAYS WITH ICETOP/ICECUBE: STATUS AND RESULTS

The IceCube Observatory at the South Pole is composed of a cubic kilometer scale neutrino telescope buried beneath the icecap and a square-kilometer surface water Cherenkov tank detector array known as IceTop. The combination of the surface array with the in-ice detector allows the dominantly electromagnetic signal of air showers at the surface and their high-energy muon signal in the ice to be measured in coincidence. This ratio is known to carry information about the nuclear composition of the primary cosmic rays. This paper reviews the recent results from cosmic-ray measurements performed with IceTop/IceCube: energy spectrum, mass composition, anisotropy, search for PeV γ sources, detection of high energy muons to probe the initial stages of the air shower development, and study of transient events using IceTop in scaler mode.
NSV 11749: Symbiotic Nova, Not a Born-Again Red Giant

NSV 11749 is a little-studied variable star, discovered by W. J. Luyten, which had a long-duration outburst around the year 1903, reaching blue magnitude 12.5 at maximum. Following the outburst, it has apparently been quiescent at about blue magnitude 17 for the past century. It was recently suggested that NSV 11749 may have been a low- or intermediate-mass star that underwent a final helium shell flash, making it temporarily a “born-again” red giant. If so, it would be only the fourth known member of this class, along with V605 Aql, FG Sge, and V4334 Sgr. However, our newly obtained optical and near-IR spectra of the object show that it is instead a symbiotic binary, with strong Balmer and He I-II emission lines, combined with a cool red-giant companion of spectral type M1-2 III. The 1903 outburst was most likely a symbiotic nova event, of which less than a dozen are known at present.
Stronger Reflection from Black Hole Accretion Disks in Soft X-ray States

United States. National Aeronautics and Space Administration (Einstein Fellowship Grant PF5-160144)
Effects of Langmuir Turbulence on Upper Ocean Carbonate Chemistry

Effects of wave-driven Langmuir turbulence on the air-sea flux of carbon dioxide (CO$_2$) are examined using large eddy simulations featuring actively reacting carbonate chemistry in the ocean mixed layer at small scales. Four strengths of Langmuir turbulence are examined with three types of carbonate chemistry: time-dependent, instantaneous equilibrium chemistry, and no reactions. The time-dependent model is obtained by reducing a detailed eight-species chemical mechanism using computational singular perturbation analysis, resulting in a quasi-steady-state approximation for hydrogen ion (H$^+$), i.e., fixed pH. The reduced mechanism is then integrated in two half-time steps before and after the advection solve using a Runge--Kutta--Chebyshev scheme that is robust for stiff systems of differential equations. The simulations show that, as the strength of Langmuir turbulence increases, CO$_2$ fluxes are enhanced by rapid overturning of the near-surface layer, which rivals the removal rate of CO$_2$ by time-dependent reactions. Equilibrium chemistry and non-reactive models are found to bring more and less carbon, respectively, into the ocean as compared to the more realistic time-dependent model. These results have implications for Earth system models that either neglect Langmuir turbulence or use equilibrium, instead of time-dependent, chemical mechanisms.
Hierarchical Interpolative Factorization Preconditioner for Parabolic Equations

This note proposes an efficient preconditioner for solving linear and semi-linear parabolic equations. With the Crank–Nicholson time stepping method, the algebraic system of equations at each time step is solved with the conjugate gradient method, preconditioned with hierarchical interpolative factorization. Stiffness matrices arising in the discretization of parabolic equations typically have large condition numbers, and therefore preconditioning becomes essential, especially for large time steps. We propose to use the hierarchical interpolative factorization as the preconditioning for the conjugate gradient iteration. Computed only once, the hierarchical interpolative factorization offers an efficient and accurate approximate inverse of the linear system. As a result, the preconditioned conjugate gradient iteration converges in a small number of iterations. Compared to other classical exact and approximate factorizations such as Cholesky or incomplete Cholesky, the hierarchical interpolative factorization can be computed in linear time and the application of its inverse has linear complexity. Numerical experiments demonstrate the performance of the method and the reduction of conjugate gradient iterations.
Characterization of Exoplanet Atmospheres with the Optical Coronagraph on WFIRST

Wide-Field Infrared Survey Telescope (WFIRST)-CGI is a NASA technology demonstration mission that is charged with demonstrating key technologies for future exo-Earth imaging missions in space. In the process, it will obtain images and low-resolution spectra of a handful to a dozen extrasolar planets and possibly protoplanetary disks. Its unprecedented contrast levels in the optical will provide astronomers' with their first direct look at mature, Jupiter-sized planets at moderate separations. This paper addresses the question: what science can be done with such data? An analytic noise model, which is informed by the ongoing engineering developments, is used to compute maximum achievable signal-to-noise ratios and scientifically viable integration times for hypothetical star–planet systems, as well as to investigate the constraining power of various combinations of WFIRST-CGI photometric and spectral observations. This work introduces two simple models for planetary geometric albedos, which are inspired largely by the solar system's gas giants. The first planet model is a hybrid Jupiter–Neptune model, which separately treats the short and long wavelengths where chromophores and methane dominate absorption, respectively. The second planet model fixes cloud and haze properties in CoolTLusty to match Jupiter's albedo spectrum, it then perturbs only the metallicity. MCMC retrievals performed on simulated observations are used to assess the precision with which planet model parameters can be measured subject to different exposure times and observing cases. Planet radius is recovered within ±15% for all observing cases with both the hybrid model and the CoolTLusty metallicity grid. Fit results for both models' parameterizations of geometric albedo spectra demonstrate that a rough indication of the metallicity or methane content should be possible for some WFIRST-CGI targets. We conclude that real observations will likely be able to differentiate between extreme cases using these models, but will lack the precision necessary to uncover subtle trends.
SMALL x DIVERGENCES IN THE SIMILARITY RG APPROACH TO LF QCD

We study small x divergences in boost invariant similarity renormalization group approach to light-front QCD in a heavy quark–antiquark state. With the boost invariance maintained, the infrared divergences do not cancel out in the physical states, contrary to previous studies where boost invariance was violated by a choice of a renormalization scale. This may be an indication that the zero mode, or nontrivial light-cone vacuum structure, might be important for recovering full Lorentz invariance.
Coincidences with the artificial axon

The artificial axon is an excitable node built with the basic biomolecular components and supporting action potentials. Here we demonstrate coincidence firing (the AND operation) and other basic electrophysiology features such as increasing firing rates for increasing input currents. We construct the basic unit for a network by connecting two such excitable nodes through an electronic synapse, producing pre/post synaptic behavior in which one axon induces firing in another. We show that the system is well described by the Hodgkin-Huxley model of nerve excitability, and conclude with a brief outlook for realizing large networks of such low-voltage “ionics”.
Existence of Solitary Waves in One Dimensional Peridynamics

We give a rigorous proof of existence for solitary waves of a peridynamics model in one space dimension recently investigated by Silling (J. Mech. Phys. Solids 96:121–132, 2016). We adapt the variational framework developed by Friesecke and Wattis (Commun. Math. Phys. 161:391–418, 1994) for the Fermi-Pasta-Ulam-Tsingou lattice equations to treat a truncated problem which cuts off short-range interactions, then pass to the limit.
Chern class formulas for classical-type degeneracy loci

Employing a simple and direct geometric approach, we prove formulas for a large class of degeneracy loci in types B, C, and D, including those coming from all isotropic Grassmannians. The results unify and generalize previous Pfaffian and determinantal formulas. Specializing to the Grassmannian case, we recover the remarkable theta- and eta-polynomials of Buch, Kresch, Tamvakis, and Wilson. Our method yields streamlined proofs which proceed in parallel for all four classical types, substantially simplifying previous work on the subject. In an appendix, we develop some foundational algebra and prove several Pfaffian identities. Another appendix establishes a basic formula for classes in quadric bundles.
Bifurcation Curves of Two-Dimensional Quantum Walks

The quantum walk differs fundamentally from the classical random walk in a number of ways, including its linear spreading and initial condition dependent asymmetries. Using stationary phase approximations, precise asymptotics have been derived for one-dimensional two-state quantum walks, one-dimensional three-state Grover walks, and two-dimensional four-state Grover walks. Other papers have investigated asymptotic behavior of a much larger set of two-dimensional quantum walks and it has been shown that in special cases the regions of polynomial decay can be parameterized. In this paper, we show that these regions of polynomial decay are bounded by algebraic curves which can be explicitly computed. We give examples of these bifurcation curves for a number of two-dimensional quantum walks.