cssi/SciSciGPT-SciSciNet huggingface dataset:
Data Acquisition for the New Muon $g$-$2$ Experiment at Fermilab

A new measurement of the anomalous magnetic moment of the muon,aμ≡ (g – 2)/2, will be performed at the Fermi National Accelerator Laboratory. The most recent measurement, performed at Brookhaven National Laboratory and completed in 2001, shows a 3.3-3.6 standard deviation discrepancy with the Standard Model predictions for aμ. The new measurement will accumulate 21 times those statistics, measuring aμ to 140 ppb and reducing the uncertainty by a factor of 4.The data acquisition system for this experiment must have the ability to record deadtime-free records from 700 μs muon spills at a raw data rate of 18 GB per second. Data will be collected using 1296 channels of μTCA-based 800 MHz, 12 bit waveform digitizers and processed in a layered array of networked commodity processors with 24 GPUs working in parallel to perform a fast recording and processing of detector signals during the spill. The system will be controlled using the MIDAS data acquisition software package. The described data acquisition system is currently being constructed, and will be fully operational before the start of the experiment in 2017.
Discriminant formulas and applications

The discriminant is a classical invariant associated to algebras which are finite over their centers. It was shown recently by several authors that if the discriminant of A is “sufficiently nontrivial” then it can be used to answer some difficult questions about A. Two such questions are: What is the automorphism group of A? Is A Zariski cancellative? We use the discriminant to study these questions for a class of (generalized) quantum Weyl algebras. Along the way, we give criteria for when such an algebra is finite over its center and prove two conjectures of Ceken, Wang, Palmieri and Zhang.
Remarks on the Hölder-continuity of solutions to parabolic equations with conic singularities

This is a note on [10] and [5]. Using their work line by line, we prove the Holder-continuity of solutions to linear parabolic equations of mixed type, assuming the coefficient of ∂ ∂t has time-derivative bounded from above. On a Kahler manifold, this Holder estimate works when the metrics possess conic singularities along a normal crossing divisor.
Unconventional symmetries of Fermi liquid and Cooper pairing properties with electric and magnetic dipolar fermions

The rapid experimental progress of ultra-cold dipolar fermions opens up a whole new opportunity to investigate novel many-body physics of fermions. In this article, we review theoretical studies of the Fermi liquid theory and Cooper pairing instabilities of both electric and magnetic dipolar fermionic systems from the perspective of unconventional symmetries. When the electric dipole moments are aligned by the external electric field, their interactions exhibit the explicit dr2−3z2 anisotropy. The Fermi liquid properties, including the single-particle spectra, thermodynamic susceptibilities and collective excitations, are all affected by this anisotropy. The electric dipolar interaction provides a mechanism for the unconventional spin triplet Cooper pairing, which is different from the usual spin-fluctuation mechanism in solids and the superfluid 3 He. Furthermore, the competition between pairing instabilities in the singlet and triplet channels gives rise to a novel time-reversal symmetry breaking superfluid state. Unlike electric dipole moments which are induced by electric fields and unquantized, magnetic dipole moments are intrinsic proportional to the hyperfine-spin operators with a Lande factor. Its effects even manifest in unpolarized systems exhibiting an isotropic but spin‐orbit coupled nature. The resultant spin‐orbit coupled Fermi liquid theory supports a collective sound mode exhibiting a topologically non-trivial spin distribution over the Fermi surface. It also leads to a novel p-wave spin triplet Cooper pairing state whose spin and orbital angular momentum are entangled to the total angular momentum J = 1 dubbed the J-triplet pairing. This J-triplet pairing phase is different from both the spin‐orbit coupled 3 He-B phase with J = 0 and the spin‐orbit decoupled 3 He-A phase.
Indirect Detection Signatures for the Origin of Asymmetric Dark Matter

We study the decay signatures of Asymmetric Dark Matter (ADM) via higher dimension operators which are responsible for generating the primordial dark matter (DM) asymmetry. Since the signatures are sensitive both to the nature of the higher dimension operator generating the DM asymmetry and to the sign of the baryon or lepton number that the DM carries, indirect detection may provide a window into the nature of the mechanism which generates the DM asymmetry. We consider in particular dimension-6 fermionic operators of the form $$ \mathcal{O} $$ ADM = X $$ \mathcal{O} $$ B−L /M 2, where $$ \mathcal{O} $$ B−L = u c d c d c , lle c , qld c (or operators related through a Hermitian conjugate) with the scale M around or just below the GUT scale. We derive constraints on ADM particles both in the natural mass range (around a few GeV), as well as in the range between 100 GeV to 10 TeV. For light ADM, we focus on constraints from both the low energy gamma ray data and proton/antiproton fluxes. For heavy ADM, we consider γ-rays and proton/anti-proton fluxes, and we fit e + /e − data from AMS-02 and H.E.S.S. (neglecting the Fermi charged particle fluxes which disagree with AMS-02 below 100 GeV). We show that, although the best fit regions from electron/positron measurement are still in tension with other channels on account of the H.E.S.S. measurement at high energies, compared to an ordinary symmetric dark matter scenario, the decay of DM with a primordial asymmetry reduces the tension. Better measurement of the flux at high energy will be necessary to draw a definite conclusion about the viability of decaying DM as source for the signals.
Parallel Batch-Dynamic Graph Connectivity

In this paper, we study batch parallel algorithms for the dynamic connectivity problem, a fundamental problem that has received considerable attention in the sequential setting. The best sequential algorithm for dynamic connectivity is the elegant level-set algorithm of Holm, de Lichtenberg and Thorup (HDT), which achieves O(log2 n) amortized time per edge insertion or deletion, and O(log n) time per query. We design a parallel batch-dynamic connectivity algorithm that is work-efficient with respect to the HDT algorithm for small batch sizes, and is asymptotically faster when the average batch size is sufficiently large. Given a sequence of batched updates, where Δ is the average batch size of all deletions, our algorithm achieves O(log n log(1+n / Δ)) expected amortized work per edge insertion and deletion and O(log3 n) depth w.h.p. Our algorithm answers a batch of k connectivity queries in O(k log(1 + n/k)) expected work and O(log n) depth w.h.p. To the best of our knowledge, our algorithm is the first parallel batch-dynamic algorithm for connectivity.
An explicit electron-vibron model for olfactory inelastic electron transfer spectroscopy

The vibrational theory of olfaction was posited to explain subtle effects in the sense of smell inexplicable by models in which a molecular structure alone determines an odorant’s smell. Amazingly, behavioral and neurophysiological evidence suggests that humans and some insects can be trained to distinguish isotopologue molecules that are related by the substitution of isotopes for certain atoms, such as a hydrogen-to-deuterium substitution. How is it possible to smell a neutron? The physics of olfaction may explain this isotopomer effect. Inelastic electron transfer spectroscopy (IETS) has been proposed as a candidate mechanism for such subtle olfactory effects: the vibrational spectrum of an appropriately quantized odorant molecule may enhance a transfer rate in the discriminating electron transfer (ET) process. In contrast to other semiclassical or quantum-master-equation-based models of olfactory IETS, the model presented here explicitly treats the dynamics of a dominant odorant vibrational mode, which provides an indirect dissipative path from the electron to the thermal environment. A direct dissipative path to the environment is also included. Within this model, a calculation of the ET rate is developed, along with a calculation of power dissipation to the thermal environment. Under very weak direct dissipative coupling, spectroscopic behaviors of the indirect path are revealed, and the resulting ET rate exhibits resonant peaks at certain odorant frequencies. Resonant peaks in the ET rate also correlate to peaks in power dissipation. Spectroscopic behaviors are masked by strong direct dissipative coupling. Results support a rate-based discrimination between a preferred ligand and an isotopomer if indirect dissipative coupling dominates.
Using Big Bang Nucleosynthesis to extend CMB probes of neutrino physics

We present calculations showing that upcoming Cosmic Microwave Background (CMB) experiments will have the power to improve on current constraints on neutrino masses and provide new limits on neutrino degeneracy parameters. The latter could surpass those derived from Big Bang Nucleosynthesis (BBN) and the observationally-inferred primordial helium abundance. These conclusions derive from our Monte Carlo Markov Chain (MCMC) simulations which incorporate a full BBN nuclear reaction network. This provides a self-consistent treatment of the helium abundance, the baryon number, the three individual neutrino degeneracy parameters and other cosmological parameters. Our analysis focuses on the effects of gravitational lensing on CMB constraints on neutrino rest mass and degeneracy parameter. We find for the PLANCK experiment that total (summed) neutrino mass Mν > 0.29 eV could be ruled out at 2σ or better. Likewise neutrino degeneracy parameters ξνe > 0.11 and |ξνμ/τ| > 0.49 could be detected or ruled out at 2σ confidence, or better. For POLARBEAR we find that the corresponding detectable values are Mν > 0.75 eV, ξνe > 0.62, and |ξνμ/τ| > 1.1, while for EPIC we obtain Mν > 0.20 eV, ξνe > 0.045, and |ξνμ/τ| > 0.29. Our forcast for EPIC demonstrates that CMB observations have the potential to set constraints on neutrino degeneracy parameters which are better than BBN-derived limits and an order of magnitude better than current WMAP-derived limits.
Turbulent Cascade Direction and Lagrangian Time-Asymmetry

We establish Lagrangian formulae for energy conservation anomalies involving the discrepancy between short-time two-particle dispersion forward and backward in time. These results are facilitated by a rigorous version of the Ott–Mann–Gawȩdzki relation, sometimes described as a “Lagrangian analogue of the 4 / 5-law.” In particular, we prove that for weak solutions of the Euler equations, the Lagrangian forward/backward dispersion measure matches onto the energy defect (Onsager in Nuovo Cimento (Supplemento) 6:279–287, 1949; Duchon and Robert in Nonlinearity 13(1):249–255, 2000) in the sense of distributions. For strong limits of $$d\ge 3$$ -dimensional Navier–Stokes solutions, the defect distribution coincides with the viscous dissipation anomaly. The Lagrangian formula shows that particles released into a 3d turbulent flow will initially disperse faster backward in time than forward, in agreement with recent theoretical predictions of Jucha et al. (Phys Rev Lett 113(5):054501, 2014). In two dimensions, we consider strong limits of solutions of the forced Euler equations with increasingly high-wave number forcing as a model of an ideal inverse cascade regime. We show that the same Lagrangian dispersion measure matches onto the anomalous input from the infinite-frequency force. As forcing typically acts as an energy source, this leads to the prediction that particles in 2d typically disperse faster forward in time than backward, which is opposite to that which occurs in 3d. Time asymmetry of the Lagrangian dispersion is thereby closely tied to the direction of the turbulent cascade, downscale in $$d\ge 3$$ and upscale in $$d=2$$ . These conclusions lend support to the conjecture of Eyink and Drivas (J Stat Phys 158(2):386–432, 2015) that a similar connection holds for time asymmetry of Richardson two-particle dispersion and cascade direction.
Tunability of electronic and optical properties of the Ba–Zr–S system via dimensional reduction

Transition metal sulfide perovskites offer lower band gaps and greater tunability than oxides, along with other desirable properties for applications. Here, we explore dimensional reduction as a tuning strategy using the Ruddlesden–Popper phases in the Ba–Zr–S system as a model. The three-dimensional perovskite BaZrS3 is a direct gap semiconductor, with a band gap of 1.5 eV suitable for solar photovoltaic application. However, the three known members of the Ruddlesden–Popper series, are all indirect gap materials, and additionally have lower fundamental band gaps. This is accompanied in the case of Ba2ZrS4 by a band structure that is more favorable for carrier transport for oriented samples. The layered Ruddlesden–Popper compounds show significantly anisotropic optical properties, as may be expected. The optical spectra show tails at low energy, which may complicate experimental characterization of these materials.
Self-force: Computational Strategies

Building on substantial foundational progress in understanding the effect of a small body’s self-field on its own motion, the past 15 years has seen the emergence of several strategies for explicitly computing self-field corrections to the equations of motion of a small, point-like charge. These approaches broadly fall into three categories: (i) mode-sum regularization, (ii) effective source approaches and (iii) worldline convolution methods. This paper reviews the various approaches and gives details of how each one is implemented in practice, highlighting some of the key features in each case.
Geometric models of twisted differential K-theory I

This is the first in a series of papers constructing geometric models of twisted differential K-theory. In this paper we construct a model of even twisted differential K-theory when the underlying topological twist represents a torsion class. By differential twists we will mean smooth U(1)-gerbes with connection, and we use twisted vector bundles with connection as cocycles. The model we construct satisfies the axioms of Kahle and Valentino, including functoriality, naturality of twists, and the hexagon diagram. This paper confirms a long-standing hypothetical idea that twisted vector bundles with connection define twisted differential K-theory.
Beyond the limits of conventional Stark deceleration

The authors propose a strategy for Stark decelerators and provide a proof-of-principle of its functioning. The paper highlights its effect on the coupling between transverse and longitudinal motion and shows its influence over the hydroxyl radical flux.
A stochastic reorganizational bath model for electronic energy transfer

Environmentally induced fluctuations of the optical gap play a crucial role in electronic energy transfer dynamics. One of the simplest approaches to incorporate such fluctuations in energy transfer dynamics is the well known Haken-Strobl-Reineker (HSR) model, in which the energy-gap fluctuation is approximated as white noise. Recently, several groups have employed molecular dynamics simulations and excited-state calculations in conjunction to account for excitation energies' thermal fluctuations. On the other hand, since the original work of HSR, many groups have employed stochastic models to simulate the same transfer dynamics. Here, we discuss a rigorous connection between the stochastic and the atomistic bath models. If the phonon bath is treated classically, time evolution of the exciton-phonon system can be described by Ehrenfest dynamics. To establish the relationship between the stochastic and atomistic bath models, we employ a projection operator technique to derive the generalized Langevin equations for the energy-gap fluctuations. The stochastic bath model can be obtained as an approximation of the atomistic Ehrenfest equations via the generalized Langevin approach. Based on this connection, we propose a novel scheme to take account of reorganization effects within the framework of stochastic models. The proposed scheme provides a better description of the population dynamics especially in the regime of strong exciton-phonon coupling. Finally, we discuss the effect of the bath reorganization in the absorption and fluorescence spectra of ideal J-aggregates in terms of the Stokes shifts. We find a simple expression that relates the reorganization contribution to the Stokes shifts - the reorganization shift - to the ideal or non-ideal exciton delocalization in a J-aggregate. The reorganization shift can be described by three parameters: the monomer reorganization energy, the relaxation time of the optical gap, and the exciton delocalization length. This simple relationship allows one to understand the physical origin of the Stokes shifts in molecular aggregates.
An Improved Distance to NGC 4258 and Its Implications for the Hubble Constant

NGC 4258 is a critical galaxy for establishing the extragalactic distance scale and estimating the Hubble constant (Ho). Water masers in the nucleus of the galaxy orbit about its supermassive black hole, and very long baseline interferometric observations of their positions, velocities, and accelerations can be modeled to give a geometric estimate of the angular-diameter distance to the galaxy. We have improved the technique to obtain model parameter values, reducing both statistical and systematic uncertainties compared to previous analyses. We find the distance to NGC 4258 to be 7.576 +/- 0.082 (stat.) +/- 0.076 (sys.) Mpc. Using this as the sole source of calibration of the Cepheid-SN Ia distance ladder results in Ho = 72.0 +/- 1.9 km/s/Mpc, and in concert with geometric distances from Milky Way parallaxes and detached eclipsing binaries in the LMC we find Ho = 73.5 +/- 1.4 km/s/Mpc. The improved distance to NGC 4258 also provides a new calibration of the tip of the red giant branch of M_{F814W} = -4.01 +/- 0.04$ mag, with reduced systematic errors for the determination of Ho compared to the LMC-based calibration, because it is measured on the same Hubble Space Telescope photometric system and through similarly low extinction as SN Ia host halos. The result is Ho = 71.1 +/- 1.9 km/s/Mpc, in good agreement with the result from the Cepheid route, and there is no difference in Ho when using the same calibration from NGC 4258 and the same SN Ia Hubble diagram intercept to start and end both distance ladders.
Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-ray Reports.

Chest X-Ray (CXR) images are commonly used for clinical screening and diagnosis. Automatically writing reports for these images can considerably lighten the workload of radiologists for summarizing descriptive findings and conclusive impressions. The complex structures between and within sections of the reports pose a great challenge to the automatic report generation. Specifically, the section Impression is a diagnostic summarization over the section Findings; and the appearance of normality dominates each section over that of abnormality. Existing studies rarely explore and consider this fundamental structure information. In this work, we propose a novel framework which exploits the structure information between and within report sections for generating CXR imaging reports. First, we propose a two-stage strategy that explicitly models the relationship between Findings and Impression. Second, we design a novel co-operative multi-agent system that implicitly captures the imbalanced distribution between abnormality and normality. Experiments on two CXR report datasets show that our method achieves state-of-the-art performance in terms of various evaluation metrics. Our results expose that the proposed approach is able to generate high-quality medical reports through integrating the structure information.
An Intrinsic Smoothing Mechanism for Gamma-Ray Burst Spectra in the Fireball Model

It is shown here that the differential Doppler shift of different patches of the blast-wave front in the fireball model at varying angles to the line of sight could provide an intrinsic smoothing mechanism for the spectra of gamma-ray bursts (GRBs) and the associated afterglows at lower energy bands. For the model parameters of interest, a blast-wave comoving frame monochromatic spectrum at ν is smoothed to have a half-width at half-maximum of ~(0.6-2.0)ν. Some other implications of this smoothing process are discussed. In particular, if the circumburster medium is uniform and electron and magnetic energies are fixed fractions of the total postshock energy with time, the observed GRB or afterglow spectra cannot be steeper than να with α=0.75-1.25, regardless of the intrinsic spectra in the comoving shock frame; i.e., a very steep electron distribution function (with p>3) could produce an observed spectrum with α~1. In addition, a generic fast-rise-slow-decay type of GRB temporal profile is expected.
Support Theorems and an Injectivity Result for Integral Moments of a Symmetric m-Tensor Field

In this work, we show an injectivity result and support theorems for integral moments of a symmetric m-tensor field on a simple, real analytic, Riemannian manifold. Integral moments of symmetric m-tensor fields were first introduced by Sharafutdinov. First we generalize a Helgason type support theorem proven by Krishnan and Stefanov (Inverse Probl Imaging 3(3):453–464, 2009). We use this extended result along with the first integral moments of a symmetric m-tensor field to prove the aforementioned results.
Monte Carlo ray-trace diffraction based on the Huygens-Fresnel principle.

The goal of this effort is to establish the conditions and limits under which the Huygens–Fresnel principle accurately describes diffraction in the Monte Carlo ray-trace (MCRT) environment. This goal is achieved by systematic intercomparison of dedicated experimental, theoretical, and numerical results. We evaluate the success of the Huygens–Fresnel principle by predicting and carefully measuring the diffraction fringes produced by both single slit and circular apertures. We then compare the results from the analytical and numerical approaches with each other and with dedicated experimental results. We conclude that use of the MCRT method to accurately describe diffraction requires that careful attention be paid to the interplay among the number of aperture points, the number of rays traced per aperture point, and the number of bins on the screen. This conclusion is supported by standard statistical analysis, including the adjusted coefficient of determination, Radj2, the rms deviation, and the reduced chi-square statistic, χv2.
A Test of Star Formation Laws in Disk Galaxies

We use observations of the radial profiles of the mass surface density of total, Σ g , and molecular, ΣH2, gas rotation velocity and star formation rate surface density, Σsfr, of the molecular dominated regions of 12 disk galaxies from Leroy et al. to test several star formation laws: a "Kennicutt-Schmidt power law," Σsfr = Ag Σ1.5 g,2; a "constant molecular law," Σsfr = A H2ΣH2,2; the "turbulence-regulated laws" of Krumholz & McKee (KM) and Krumholz, McKee, & Tumlinson (KMT), a "gas-Ω law," Σsfr = B ΩΣ g Ω; and a shear-driven "giant molecular cloud (GMC) collisions law," Σsfr = B CCΣ g Ω(1 – 0.7β), where β ≡ d ln v circ/d ln r. We find the constant molecular law, KMT turbulence law, and GMC collision law are the most accurate, with an rms error of a factor of 1.5 if the normalization constants are allowed to vary between galaxies. Of these three laws, the GMC collision law does not require a change in physics to account for the full range of star formation activity seen from normal galaxies to circumnuclear starbursts. A single global GMC collision law with B CC = 8.0 × 10–3, i.e., a gas consumption time of 20 orbital times for β = 0, yields an rms error of a factor of 1.8.
Euclidean Symmetry and Equivariance in Machine Learning

Understanding the role of symmetry in the physical sciences is critical for choosing an appropriate machine-learning method. While invariant models are the most prevalent symmetry-aware models, equivariant models such as Euclidean neural networks more faithfully represent physical interactions and are ready to take on challenges across the physical sciences.
Robust large-margin learning in hyperbolic space

Recently, there has been a surge of interest in representation learning in hyperbolic spaces, driven by their ability to represent hierarchical data with significantly fewer dimensions than standard Euclidean spaces. However, the viability and benefits of hyperbolic spaces for downstream machine learning tasks have received less attention. In this paper, we present, to our knowledge, the first theoretical guarantees for learning a classifier in hyperbolic rather than Euclidean space. Specifically, we consider the problem of learning a large-margin classifier for data possessing a hierarchical structure. Our first contribution is a hyperbolic perceptron algorithm, which provably converges to a separating hyperplane. We then provide an algorithm to efficiently learn a large-margin hyperplane, relying on the careful injection of adversarial examples. Finally, we prove that for hierarchical data that embeds well into hyperbolic space, the low embedding dimension ensures superior guarantees when learning the classifier directly in hyperbolic space.
“Chain” Galaxies Are Edge-On Low Surface Brightness Galaxies

Deep HST WFPC2 images have revealed a population of very narrow blue galaxies, which Cowie et al. have interpreted as being a new morphological class of intrinsically linear star forming galaxies at z = 0.5-3. We show that the same population exists in large numbers at low redshifts (z ≈ 0.03) and are actually the edge-on manifestation of low surface brightness disk galaxies.
ON LOCAL DILATATION INVARIANCE

The relationship between local Weyl scaling invariant models and local dilatation invariant actions is critically scrutinized. While actions invariant under local Weyl scalings can be constructed in a straightforward manner, actions invariant under local dilatation transformations can only be achieved in a very restrictive case. The invariant couplings of matter fields to an Abelian vector field carrying a nontrivial scaling weight can be easily built, but an invariant Abelian vector kinetic term can only be realized when the local scale symmetry is spontaneously broken.
Avoiding Side Effects in Complex Environments

Reward function specification can be difficult. Rewarding the agent for making a widget may be easy, but penalizing the multitude of possible negative side effects is hard. In toy environments, Attainable Utility Preservation (AUP) avoided side effects by penalizing shifts in the ability to achieve randomly generated goals. We scale this approach to large, randomly generated environments based on Conway's Game of Life. By preserving optimal value for a single randomly generated reward function, AUP incurs modest overhead while leading the agent to complete the specified task and avoid many side effects. Videos and code are available at this https URL.
Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems

Kernel Ridge Regression (KRR) is a fundamental method in machine learning. Given an n-by-d data matrix as input, a traditional implementation requires Θ(n2) memory to form an n-by-n kernel matrix and Θ(n3) flops to compute the final model. These time and storage costs prohibit KRR from scaling up to large datasets. For example, even on a relatively small dataset (a 520k-by-90 input requiring 357 MB), KRR requires 2 TB memory just to store the kernel matrix. The reason is that n usually is much larger than d for real-world applications. On the other hand, weak scaling becomes a problem: if we keep d and n/p fixed as p grows (p is # machines), the memory needed grows as Θ(p) per processor and the flops as Θ(p2) per processor. In the perfect weak scaling situation, both the memory needed and the flops grow as Θ(1) per processor (i.e. memory and flops are constant). The traditional Distributed KRR implementation (DKRR) only achieved 0.32% weak scaling efficiency from 96 to 1536 processors. We propose two new methods to address these problems: the Balanced KRR (BKRR) and K-means KRR (KKRR). These methods consider alternative ways to partition the input dataset into p different parts, generating p different models, and then selecting the best model among them. Compared to a conventional implementation, KKRR2 (optimized version of KKRR) improves the weak scaling efficiency from 0.32% to 38% and achieves a 591x speedup for getting the same accuracy by using the same data and the same hardware (1536 processors). BKRR2 (optimized version of BKRR) achieves a higher accuracy than the current fastest method using less training time for a variety of datasets. For the applications requiring only approximate solutions, BKRR2 improves the weak scaling efficiency to 92% and achieves 3505x speedup (theoretical speedup: 4096x).
MM algorithms for geometric and signomial programming

This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.
Characterization of the Very-low-mass Secondary in the GJ 660.1AB System

We present spectroscopic analysis of the low mass binary star system GJ 660.1AB, a pair of nearby M dwarfs for which we have obtained separated near-infrared spectra (0.9-2.5 $\mu$m) with the SpeX spectrograph. The spectrum of GJ 660.1B is distinctly peculiar, with a triangular-shaped 1.7 $\mu$m peak that initially suggests it to be a low surface gravity, young brown dwarf. However, we rule out this hypothesis and determine instead that this companion is a mild subdwarf (d/sdM7) based on the subsolar metallicity of the primary, [Fe/H] = $-$0.63$\pm$0.06. Comparison of the near-infrared spectrum of GJ 660.1B to two sets of spectral models yields conflicting results, with a common effective temperature T$_{eff}$ = 2550-2650 K, but alternately low surface gravity ($\log{g}$ = 4.4$\pm$0.5 cgs) and very low metallicity ([M/H] = $-$0.96$^{+0.19}_{-0.24}$), or high surface gravity ($\log{g}$ = 5.0-5.5) and slightly subsolar metallicity ([M/H] =$-$0.20$^{+0.13}_{-0.19}$). We conjecture that insufficient condensate opacity and excessive collision induced H$_2$ absorption in the models bias them toward low surface gravities and a metallicity inconsistent with the primary, and points toward improvements needed in the spectral modeling of metal-poor, very-low mass dwarfs. The peculiar spectral characteristics of GJ 660.1B emphasize that care is needed when interpreting surface gravity features in the spectra of ultracool dwarfs.
Semisimplicity and rigidity of the Kontsevich-Zorich cocycle

We prove that invariant subbundles of the Kontsevich-Zorich cocycle respect the Hodge structure. In particular, we establish a version of Deligne semisimplicity in this context. This implies that invariant subbundles must vary polynomially on affine manifolds. All results apply to tensor powers of the cocycle and this implies that the measurable and real-analytic algebraic hulls coincide. We also prove that affine manifolds typically parametrize Jacobians with non-trivial endomorphisms. If the field of affine definition is larger than \(\mathbb {Q}\), then a factor has real multiplication. The tools involve curvature properties of the Hodge bundles and estimates from random walks. In the appendix, we explain how methods from ergodic theory imply some of the global consequences of Schmid’s work on variations of Hodge structures. We also derive the Kontsevich-Forni formula using differential geometry.
Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing

Compressed sensing is a powerful tool in applications such as magnetic resonance imaging (MRI). It enables accurate recovery of images from highly undersampled measurements by exploiting the sparsity of the images or image patches in a transform domain or dictionary. In this work, we focus on blind compressed sensing (BCS), where the underlying sparse signal model is a priori unknown, and propose a framework to simultaneously reconstruct the underlying image as well as the unknown model from highly undersampled measurements. Specifically, our model is that the patches of the underlying image(s) are approximately sparse in a transform domain. We also extend this model to a union of transforms model that better captures the diversity of features in natural images. The proposed block coordinate descent type algorithms for BCS are highly efficient, and are guaranteed to converge to at least the partial global and partial local minimizers of the highly nonconvex BCS problems. Our numerical experiments show that the proposed framework usually leads to better quality of image reconstructions in MRI compared to several recent image reconstruction methods. Importantly, the learning of a union of sparsifying transforms leads to better image reconstructions than a single adaptive transform.
Dilational Symmetry-Breaking in Thermodynamics

Using thermodynamic relations and dimensional analysis we derive a general formula for the thermodynamical trace $2\mathcal{E}-DP$ for non-relativistic systems and $\mathcal{E-DP}$ for relativistic systems, where $D$ is the number of spatial dimensions, in terms of the microscopic scales of the system within the grand canonical ensemble. We demonstrate the formula for several cases, including anomalous systems which develop scales through dimensional transmutation. Using this relation, we make explicit the connection between dimensional analysis and the virial theorem. This paper is focused mainly on the non-relativistic aspects of this relation.
FORMING PLANETESIMALS BY GRAVITATIONAL INSTABILITY. II. HOW DUST SETTLES TO ITS MARGINALLY STABLE STATE

Dust at the midplane of a circumstellar disk can become gravitationally unstable and fragment into planetesimals if the local dust-to-gas ratio μ0 ≡ ρd/ρg is sufficiently high. We simulate how dust settles in passive disks and ask how high μ0 can become. We implement a hybrid scheme that alternates between a one-dimensional code to settle dust and a three-dimensional shearing box code to test for dynamical stability. This scheme allows us to explore the behavior of small particles having short but non-zero stopping times in gas: 0 < t stop the orbital period. The streaming instability is thereby filtered out. Dust settles until Kelvin-Helmholtz-type instabilities at the top and bottom faces of the dust layer threaten to overturn the entire layer. In this state of marginal stability, μ0 = 2.9 for a disk whose bulk (height-integrated) metallicity Σd/Σg is solar—thus μ0 increases by more than two orders of magnitude from its well-mixed initial value of μ0,init = Σd/Σg = 0.015. For a disk whose bulk metallicity is 4× solar (μ0,init = Σd/Σg = 0.06), the marginally stable state has μ0 = 26.4. These maximum values of μ0, which depend on the background radial pressure gradient, are so large that gravitational instability of small particles is viable in disks whose bulk metallicities are just a few (4) times solar. Our result supports earlier studies that assumed that dust settles until the Richardson number Ri is spatially constant. Our simulations are free of this assumption but provide evidence for it within the boundaries of the dust layer, with the proviso that Ri increases with Σd/Σg in the same way that we found in Paper I. Because increasing the dust content decreases the vertical shear and increases stability, the midplane μ0 increases with Σd/Σg in a faster than linear way, so fast that modest enhancements in Σd/Σg can spawn planetesimals directly from small particles.
Given enough choice, simple local rules percolate discontinuously

There is still much to discover about the mechanisms and nature of discontinuous percolation transitions. Much of the past work considers graph evolution algorithms known as Achlioptas processes in which a single edge is added to the graph from a set of k randomly chosen candidate edges at each timestep until a giant component emerges. Several Achlioptas processes seem to yield a discontinuous percolation transition, but it was proven by Riordan and Warnke that the transition must be continuous in the thermodynamic limit. However, they also proved that if the number k(n) of candidate edges increases with the number of nodes, then the percolation transition may be discontinuous. Here we attempt to find the simplest such process which yields a discontinuous transition in the thermodynamic limit. We introduce a process which considers only the degree of candidate edges and not component size. We calculate the critical point \(t_c = (1 - \theta (\tfrac{1} {k}))n\) and rigorously show that the critical window is of size \(O\left( {\tfrac{n} {{k(n)}}} \right)\). If k(n) grows very slowly, for example k(n) = log n, the critical window is barely sublinear and hence the phasetransition is discontinuous but appears continuous in finite systems. We also present arguments that Achlioptas processes with bounded size rules will always have continuous percolation transitions even with infinite choice.
No Bel–Robinson tensor for quadratic curvature theories

We attempt to generalize the familiar covariantly conserved Bel–Robinson tensor B_(μναβ) ~ RR of GR and its recent topologically massive third derivative order counterpart B ~ RDR to quadratic curvature actions. Two very different models of current interest are examined: fourth-order D = 3 'new massive gravity' and second-order D > 4 Lanczos–Lovelock. On dimensional grounds, the candidates here become B ~ DRDR + RRR. For the D = 3 model, there indeed exist conserved B ~ ∂R∂R in the linearized limit. However, despite a plethora of available cubic terms, B cannot be extended to the full theory. The D > 4 models are not even linearizable about flat space, since their field equations are quadratic in curvature; they also have no viable B, a fact that persists even if one includes cosmological or Einstein terms to allow linearization about the resulting dS vacua. These results are an unexpected, if hardly unique, example of linearization instability.
reductus: A Stateless Python Data-Reduction Service with a Browser Frontend

The online data reduction service reductus transforms measurements in experimental science from laboratory coordinates into physically meaningful quantities with accurate estimation of uncertainties from instrumental settings and properties. This reduction process is based on a few well known transformations, but flexibility in the application of the transforms and algorithms supports flexibility in experiment design, enabling a broader range of measurements than a rigid reduction scheme for data. The user interface allows easy construction of arbitrary pipelines from well known data transforms using a visual data flow diagram. Source data are drawn from a networked, open data repository. The Python back end uses intelligent caching to store intermediate results of calculations for a highly responsive user experience. The reference implementation allows immediate reduction of measurements as they are recorded for the three neutron reflectometry instruments at the NIST Center for Neutron Research, without the need for visiting scientists to install additional software on their own computers.
PCNA Monoubiquitination Is Regulated by Diffusion of Rad6/Rad18 Complexes along RPA Filaments

Translesion DNA synthesis (TLS) enables DNA replication through damaging modifications to template DNA and requires monoubiquitination of the proliferating cell nuclear antigen (PCNA) sliding clamp by the Rad6/Rad18 complex. This posttranslational modification is critical to cell survival following exposure to DNA-damaging agents and is tightly regulated to restrict TLS to damaged DNA. Replication protein A (RPA), the major single-strand DNA (ssDNA) binding protein complex, forms filaments on ssDNA exposed at TLS sites and plays critical yet undefined roles in regulating PCNA monoubiquitination. Here, we utilize kinetic assays and single-molecule FRET microscopy to monitor PCNA monoubiquitination and Rad6/Rad18 complex dynamics on RPA filaments, respectively. Results reveal that a Rad6/Rad18 complex is recruited to an RPA filament via Rad18·RPA interactions and randomly translocates along the filament. These translocations promote productive interactions between the Rad6/Rad18 complex and the resident PCNA, significantly enhancing monoubiquitination. These results illuminate critical roles of RPA in the specificity and efficiency of PCNA monoubiquitination and represent, to the best of our knowledge, the first example of ATP-independent translocation of a protein complex along a protein filament.
Leveraging random assignment to impute missing covariates in causal studies

Baseline covariates in randomized experiments are often used in the estimation of treatment effects, for example, when estimating treatment effects within covariate-defined subgroups. In practice, ...
Fractional ridge regression: a fast, interpretable reparameterization of ridge regression.

Background Ridge regression is a regularization technique that penalizes the L2-norm of the coefficients in linear regression. One of the challenges of using ridge regression is the need to set a hyperparameter (α) that controls the amount of regularization. Cross-validation is typically used to select the best α from a set of candidates. However, efficient and appropriate selection of α can be challenging. This becomes prohibitive when large amounts of data are analyzed. Because the selected α depends on the scale of the data and correlations across predictors, it is also not straightforwardly interpretable. Results The present work addresses these challenges through a novel approach to ridge regression. We propose to reparameterize ridge regression in terms of the ratio γ between the L2-norms of the regularized and unregularized coefficients. We provide an algorithm that efficiently implements this approach, called fractional ridge regression, as well as open-source software implementations in Python and matlab (https://github.com/nrdg/fracridge). We show that the proposed method is fast and scalable for large-scale data problems. In brain imaging data, we demonstrate that this approach delivers results that are straightforward to interpret and compare across models and datasets. Conclusion Fractional ridge regression has several benefits: the solutions obtained for different γ are guaranteed to vary, guarding against wasted calculations; and automatically span the relevant range of regularization, avoiding the need for arduous manual exploration. These properties make fractional ridge regression particularly suitable for analysis of large complex datasets.
Performance analysis of priority-aware NoCs with deflection routing under traffic congestion

Priority-aware networks-on-chip (NoCs) are used in industry to achieve predictable latency under different workload conditions. These NoCs incorporate deflection routing to minimize queuing resources within routers and achieve low latency during low traffic load. However, deflected packets can exacerbate congestion during high traffic load since they consume the NoC bandwidth. State-of-the-art analytical models for priority-aware NoCs ignore deflected traffic despite its significant latency impact during congestion. This paper proposes a novel analytical approach to estimate end-to-end latency of priority-aware NoCs with deflection routing under bursty and heavy traffic scenarios. Experimental evaluations show that the proposed technique outperforms alternative approaches and estimates the average latency for real applications with less than 8% error compared to cycle-accurate simulations.
Ultrashort Pulse Detection and Response Time Analysis Using Plasma-Wave Terahertz Field-Effect Transistors

We report on the response characteristics of plasmonic terahertz field-effect transistors (TeraFETs) fed with femtosecond and picosecond pulses. Varying the pulsewidth ( ${t}_{\textit {pw}}$ ) from 10−15 s to 10−10 s under a constant input power condition revealed two distinctive pulse detection modes. In the short pulse mode ( ${t}_{\textit {pw}} \ll {L}/{s}$ , where ${L}$ is the gated channel length and ${s}$ is the plasma velocity), the source-to-drain voltage response is a sharp pulse oscillatory decay preceded by a delay time on the order of ${L}/{s}$ . The plasma wave travels along the channel like the shallow water wave with a relatively narrow wave package. In the long pulse mode ( ${t}_{\textit {pw}} > {L}/{s}$ ), the response profile has two oscillatory decay processes and the propagation of plasma wave is analogous to an oscillating rod with one side fixed. The ultimate response time at the long pulse mode is significantly higher than that under the short pulse conditions. The detection conditions under the long pulse mode are close to the step response condition, and the response time conforms well to the analytical theory for the step function response. The simulated waveform agrees well with the measured pulse response. Our results show that the measurements of the pulse response enable the material parameter extraction from the pulse response data (including the effective mass, kinematic viscosity, and momentum relaxation time).
A barrier function approach to finite-time stochastic system verification and control

Abstract We study the problem of synthesizing a control strategy to enforce safety of affine-in-control stochastic dynamical systems over finite time horizons. We use stochastic control barrier functions to quantify the probability that a system exits a given safe region of the state space in finite-time and consider both continuous-time and discrete-time systems. A barrier certificate condition that bounds the expected value of the barrier function over the time horizon is recast as a sum-of-squares optimization problem for efficient numerical computation. Unlike prior works, the proposed certificate condition includes a state-dependent upper bound on the evolution of the expectation, allowing for tighter probability bounds. Two examples are presented.
WINNING PLAY IN SPECTRUM AUCTIONS

We describe factors that make bidding in large spectrum auctions complex including exposure and budget problems, the role of timing within an ascending auction, and the possibilities for price forecasting and how economic and game-theoretic analysis can assist bidders in overcoming these problems. As an example, we consider the case of the FCC's Advanced Wireless Service auction, in which a new entrant, SpectrumCo, faced all these problems yet managed to purchase nationwide coverage at a discount of roughly a third relative to the prices paid by its incumbent competitors in the same auction, saving more than a billion dollars.