cssi/SciSciGPT-SciSciNet huggingface dataset:
The Liquid Metallic Hydrogen Model of the Sun and the Solar Atmosphere I. Continuous Emission and Condensed Matter Within the Chromosphere

The K-corona, a significant portion of the solar atmosphere, displays a continuous spectrum which closely parallels photospheric emission, though without the presence of overlying Fraunhofer lines. The E-corona exists in the same region and is characterized by weak emission lines from highly ionized atoms. For instance, the famous green emission line from coronium (FeXIV) is part of the E-corona. The F-corona exists beyond the K/E-corona and, like the photospheric spectrum, is characterized by Fraunhofer lines. The F-corona represents photospheric light scattered by dust particles in the interplanetary medium. Within the gaseous models of the Sun, the K-corona is viewed as photospheric radiation which has been scattered by relativistic electrons. This scattering is thought to broaden the Fraunhofer lines of the solar spectrum such that they can no longer be detected in the K-corona. Thus, the gaseous models of the Sun account for the appearance of the K-corona by distorting photospheric light, since they are unable to have recourse to condensed matter to directly produce such radiation. Conversely, it is now advanced that the continuous emission of the K-corona and associated emission lines from the E-corona must be interpreted as manifestations of the same phenomenon: condensed matter exists in the corona. It is well-known that the Sun expels large amounts of material from its surface in the form of flares and coronal mass ejections. Given a liquid metallic hydrogen model of the Sun, it is logical to assume that such matter, which exists in the condensed state on the solar surface, continues to manifest its nature once expelled into the corona. Therefore, the continuous spectrum of the K-corona provides the twenty-seventh line of evidence that the Sun is composed of condensed matter.
Optimal Resource Allocation for Elastic and Inelastic Jobs

Modern data centers are tasked with processing heterogeneous workloads consisting of various classes of jobs. These classes differ in their arrival rates, size distributions, and job parallelizability. With respect to parallelizability, some jobs are elastic, meaning they can parallelize linearly across any number of servers. Other jobs are inelastic, meaning they can only run on a single server. Although job classes can differ drastically, they are typically forced to share a single cluster. When sharing a cluster among heterogeneous jobs, one must decide how to allocate servers to each job at every moment in time. In this paper, we design and analyze allocation policies which aim to minimize the mean response time across jobs, where a job's response time is the time from when it arrives until it completes. We model this problem in a stochastic setting where each job may be elastic or inelastic. Job sizes are drawn from exponential distributions, but are unknown to the system. We show that, in the common case where elastic jobs are larger on average than inelastic jobs, the optimal allocation policy is Inelastic-First, giving inelastic jobs preemptive priority over elastic jobs. We obtain this result by introducing a novel sample path argument. We also show that there exist cases where Elastic-First (giving priority to elastic jobs) performs better than Inelastic-First. We provide the first analysis of mean response time under both Elastic-First and Inelastic-First by leveraging techniques for solving high-dimensional Markov chains.
Cooperative Highway Work Zone Merge Control Based on Reinforcement Learning in a Connected and Automated Environment

Given the aging infrastructure and the anticipated growing number of highway work zones in the U.S.A., it is important to investigate work zone merge control, which is critical for improving work z...
Assembly of a patchy protein into variable 2D lattices via tunable multiscale interactions.

Self-assembly of molecular building blocks into higher-order structures is exploited in living systems to create functional complexity and represents a powerful strategy for constructing new materials. As nanoscale building blocks, proteins offer unique advantages, including monodispersity and atomically tunable interactions. Yet, control of protein self-assembly has been limited compared to inorganic or polymeric nanoparticles, which lack such attributes. Here, we report modular self-assembly of an engineered protein into four physicochemically distinct, precisely patterned 2D crystals via control of four classes of interactions spanning Angstrom to several-nanometer length scales. We relate the resulting structures to the underlying free-energy landscape by combining in-situ atomic force microscopy observations of assembly with thermodynamic analyses of protein-protein and -surface interactions. Our results demonstrate rich phase behavior obtainable from a single, highly patchy protein when interactions acting over multiple length scales are exploited and predict unusual bulk-scale properties for protein-based materials that ensue from such control.
From pseudo-rotations to holomorphic curves via quantum Steenrod squares

In the context of symplectic dynamics, pseudo-rotations are Hamiltonian diffeomorphisms with finite and minimal possible number of periodic orbits. These maps are of interest in both dynamics and symplectic topology. We show that a closed, monotone symplectic manifold, which admits a non-degenerate pseudo-rotation, must have a deformed quantum Steenrod square of the top degree element, and hence non-trivial holomorphic spheres. This result (partially) generalizes a recent work by Shelukhin and complements the results by the authors on non-vanishing Gromov-Witten invariants of manifolds admitting pseudo-rotations.
Composing and decomposing op-based CRDTs with semidirect products

Operation-based Conflict-free Replicated Data Types (CRDTs) are eventually consistent replicated data types that automatically resolve conflicts between concurrent operations. Op-based CRDTs must be designed differently for each data type, and current designs use ad-hoc techniques to handle concurrent operations that do not naturally commute. We present a new construction, the semidirect product of op-based CRDTs, which combines the operations of two CRDTs into one while handling conflicts between their concurrent operations in a uniform way. We demonstrate the construction's utility by using it to construct novel CRDTs, as well as decomposing several existing CRDTs as semidirect products of simpler CRDTs. Although it reproduces common CRDT semantics, the semidirect product can be viewed as a restricted kind of operational transformation, thus forming a bridge between these two opposing techniques for constructing replicated data types.
On the Capacity of Locally Decodable Codes

A locally decodable code (LDC) maps $K$ source symbols, each of size $L_{w}$ bits, to $M$ coded symbols, each of size $L_{x}$ bits, such that each source symbol can be decoded from $N \leq M$ coded symbols. A perfectly smooth LDC further requires that each coded symbol is uniformly accessed when we decode any one of the messages. The ratio $L_{w}/L_{x}$ is called the symbol rate of an LDC. The highest possible symbol rate for a class of LDCs is called the capacity of that class. It is shown that given $K, N$ , the maximum value of capacity of perfectly smooth LDCs, maximized over all code lengths $M$ , is $C^{*}=N\left ({1+1/N+1/N^{2}+\cdots +1/N^{K-1}}\right)^{-1}$ . Furthermore, given $K, N$ , the minimum code length $M$ for which the capacity of a perfectly smooth LDC is $C^{*}$ is shown to be $M = N^{K}$ . Both of these results generalize to a broader class of LDCs, called universal LDCs. The results are then translated into the context of PIRmax, i.e., Private Information Retrieval subject to maximum (rather than average) download cost metric. It is shown that the minimum upload cost of capacity achieving PIRmax schemes is $(K-1)\log N$ . The results also generalize to a variation of the PIR problem, known as Repudiative Information Retrieval (RIR).
Local plurisubharmonic defining functions on the boundary

Necessary conditions for a domain $\Omega\subset \mathbb C^n$ admitting a local plurisubharmonic defining function on the boundary are given. In tandem, we give an algorithm to construct a local plurisubharmonic defining function on the boundary when one exists. In some cases we show that the necessary conditions are also sufficient.
A direct approach for function approximation on data defined manifolds.

Abstract In much of the literature on function approximation by deep networks, the function is assumed to be defined on some known domain, such as a cube or a sphere. In practice, the data might not be dense on these domains, and therefore, the approximation theory results are observed to be too conservative. In manifold learning, one assumes instead that the data is sampled from an unknown manifold; i.e., the manifold is defined by the data itself. Function approximation on this unknown manifold is then a two stage procedure: first, one approximates the Laplace–Beltrami operator (and its eigen-decomposition) on this manifold using a graph Laplacian, and next, approximates the target function using the eigen-functions. Alternatively, one estimates first some atlas on the manifold and then uses local approximation techniques based on the local coordinate charts. In this paper, we propose a more direct approach to function approximation on unknown, data defined manifolds without computing the eigen-decomposition of some operator or an atlas for the manifold, and without any kind of training in the classical sense. Our constructions are universal; i.e., do not require the knowledge of any prior on the target function other than continuity on the manifold. We estimate the degree of approximation. For smooth functions, the estimates do not suffer from the so-called saturation phenomenon. We demonstrate via a property called good propagation of errors how the results can be lifted for function approximation using deep networks where each channel evaluates a Gaussian network on a possibly unknown manifold.
Iterated dominance revisited

Epistemic justifications of solution concepts often refer to type structures that are sufficiently rich. One important notion of richness is that of a complete type structure, i.e., a type structure that induces all possible beliefs about types. For instance, it is often said that, in a complete type structure, the set of strategies consistent with rationality and common belief of rationality are the set of strategies that survive iterated dominance. This paper shows that this classic result is false, absent certain topological conditions on the type structure. In particular, it provides an example of a finite game and a complete type structure in which there is no state consistent with rationality and common belief of rationality. This arises because the complete type structure does not induce all hierarchies of beliefs—despite inducing all beliefs about types. This raises the question: Which beliefs does a complete type structure induce? We provide several positive results that speak to that question. However, we also show that, within ZFC, one cannot show that a complete structure induces all second-order beliefs.
N$^*$ Experiments and what they tell us about Strong QCD Physics

I give an overview on experimental studies of the spectrum and the structure of the excited states of the nucleon and what we can learn about their in ternal structure. One focus is on the efforts to obtain a more complete picture of the light-quark baryon exci tation spectrum employing electromagnetic beams that will allow us to draw some conclusions on the symme tries underlying the spectrum. For the higher mass ex citations, the full employment of coupled channel ap proaches is essential when searching for new excited states in the large amounts of data already accumulated in different channels involving a variety of polarization observables. The other focus is on the study of transition form factors and helicity amplitudes and their de pendences on Q 2 , especially on some of the more promi nent resonances, especially Δ(1232)3/2+ , N (1440)1/2+ , and negative parity states N (1535)1/2- , and N (1675)5/2- .These were obtained in pion and eta electroproduction experi ments off proton targets and have already led to further insights in the active degrees-of-freedom as a function of the distance scale involved.
Access to Substance Use Disorder Treatment During COVID-19: Implications from Reduced Local Jail Populations

Many states have responded to the spread of COVID-19 by implementing policies which have led to a dramatic reduction in jail populations. We consider the benefits associated with providing the population of individuals who would, but for these policies, be incarcerated with substance use disorder (SUD) treatment. We discuss problems that may prevent this population from receiving SUD treatment as well as policies which may mitigate these problems.
Focusing on Bandwidth: Achromatic Metalens Limits

We derive fundamental bandwidth limits on achromatic optical metalenses, regardless of their implementation. Specifically, we discuss the product between achievable time delay and bandwidth, and apply well-established bounds on this product to a general focusing system.
Phase-synchronization properties of laminar cylinder wake for periodic external forcings

We investigate the synchronization properties of the two-dimensional periodic flow over a circular cylinder using the principles of phase-reduction theory. The influence of harmonic external forcings on the wake dynamics, together with the possible synchronization of the vortex shedding behind the cylinder to these forcings, is determined by evaluating the phase response of the system to weak impulse perturbations. These horizontal and vertical perturbations are added at different phase values over a period, in order to develop a linear one-dimensional model with respect to the limit cycle that describes the high-dimensional and nonlinear dynamics of the fluid flow via only a single scalar phase variable. This model is then utilized to acquire the theoretical conditions for the synchronization between the cylinder wake and the harmonic forcings added in the global near-wake region. Valuable insights are gained by comparing the findings of the present research against those rendered by the dynamic mode decomposition and adjoint analysis of the wake dynamics in earlier works. The present analysis reveals regions in the flow which enable phase synchronization or desynchronization to periodic excitations for applications such as active flow control and fluid-structure interactions.
Simultaneous Denoising and Motion Estimation for Low-Dose Gated PET Using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning

Gating is commonly used in PET imaging to reduce respiratory motion blurring and facilitate more sophisticated motion correction methods. In the applications of low dose PET, however, reducing injection dose causes increased noise and reduces signal-to-noise ratio (SNR), subsequently corrupting the motion estimation/correction steps, causing inferior image quality. To tackle these issues, we first propose a Siamese adversarial network (SAN) that can efficiently recover high dose gated image volume from low dose gated image volume. To ensure the appearance consistency between the recovered gated volumes, we then utilize a pre-trained motion estimation network incorporated into SAN that enables the constraint of gate-to-gate (G2G) consistency. With high-quality recovered gated volumes, gate-to-gate motion vectors can be simultaneously outputted from the motion estimation network. Comprehensive evaluations on a low dose gated PET dataset of 29 subjects demonstrate that our method can effectively recover the low dose gated PET volumes, with an average PSNR of 37.16 and SSIM of 0.97, and simultaneously generate robust motion estimation that could benefit subsequent motion corrections.
Limiting behavior of sequences of properly embedded minimal disks

We develop a theory of “minimal $\theta$-graphs” and characterize the behavior of limit laminations of such surfaces, including an understanding of their limit leaves and their curvature blow-up sets. We use this to prove that it is possible to realize families of catenoids in euclidean space as limit leaves of sequences of embedded minimal disks, even when there is no curvature blow-up. Our methods work in a more general Riemannian setting, including hyperbolic space. This allows us to establish the existence of a complete, simply connected, minimal surface in hyperbolic space that is not properly embedded.
Effect of the Surface-Stimulated Mode on the Kinetics of Homogeneous Crystal Nucleation in Droplets

The thermodynamics of surface-stimulated crystal nucleation demonstrates that if at least one of the facets of the crystal is only partially wettable by its melt, then it is thermodynamically more favorable for the nucleus to form with that facet at the droplet surface rather than within the droplet. So far, however, the kinetic aspects of this phenomenon had not been studied at all. In the present paper, a kinetic theory of homogenous crystal nucleation in unary droplets is proposed by taking into account that a crystal nucleus can form not only in the volume-based mode (with all its facets within the droplet) but also in the surface-stimulated one (with one of its facets at the droplet surface). The theory advocates that even in the surface-stimulated mode crystal nuclei initially emerge (as subcritical clusters) homogeneously in the subsurface layer, not “pseudo-heterogeneously” at the surface. A homogeneously emerged subcritical crystal can become a surface-stimulated nucleus due to density and struct...
scarlet: Source separation in multi-band images by Constrained Matrix Factorization

Abstract We present the source separation framework scarlet for multi-band images, which is based on a generalization of the Non-negative Matrix Factorization to alternative and several simultaneous constraints. Our approach describes the observed scene as a mixture of components with compact spatial support and uniform spectra over their support. We present the algorithm to perform the matrix factorization and introduce constraints that are useful for optical images of stars and distinct stellar populations in galaxies, in particular symmetry and monotonicity with respect to the source peak position. We also derive the treatment of correlated noise and convolutions with band-dependent point spread functions, rendering our approach applicable to coadded images observed under variable seeing conditions. scarlet thus yields a PSF-matched photometry measurement with an optimally chosen weight function given by the mean morphology in all available bands. We demonstrate the performance of scarlet for deblending crowded extragalactic scenes and on an AGN jet–host galaxy separation problem in deep 5-band imaging from the Hyper Suprime-Cam Strategic Survey Program. Using simulations with prominent crowding we show that scarlet yields superior results to the HSC-SDSS deblender for the recovery of total fluxes, colors, and morphologies. Due to its non-parametric nature, a conceptual limitation of scarlet is its sensitivity to undetected sources or multiple stellar population within detected sources, but an iterative strategy that adds components at the location of significant residuals appears promising. The code is implemented in Python with C++ extensions and is available at https://github.com/fred3m/scarlet .
Pinwheels and nullhomologous surgery on 4–manifolds with b+ = 1

We present a method for finding embedded nullhomologous tori in standard 4-manifolds which can be utilized to change their smooth structure. As an application, we show how to obtain infinite families of simply connected smooth 4-manifolds with b^+ = 1 and b^- = 2,...,7, via surgery on nullhomologous tori embedded in the standard manifolds CP^2 # k (-CP^2), k=2,...,7.
Embeddings and immersions of tropical curves

We construct immersions of trivalent abstract tropical curves in the Euclidean plane and embeddings of all abstract tropical curves in higher dimensional Euclidean space. Since not all curves have an embedding in the plane, we define the tropical crossing number of an abstract tropical curve to be the minimum number of self-intersections, counted with multiplicity, over all its immersions in the plane. We show that the tropical crossing number is at most quadratic in the number of edges and this bound is sharp. For curves of genus up to two, we systematically compute the crossing number. Finally, we use our immersed tropical curves to construct totally faithful nodal algebraic curves via lifting results of Mikhalkin and Shustin.
Controlling Nanogap Quantum Dot Photoconductivity through Optoelectronic Trap Manipulation

Nanoscale devices are being extensively studied for their tunable electronic and optical properties, but the influence of impurities and defects is amplified at these length scales and can lead to poorly understood variations in characteristics of semiconducting materials. By performing a large ensemble of photoconductivity measurements in nanogaps bridged by core-shell CdSe/ZnS semiconductor nanocrystals, we discover optoelectronic methods for affecting solid-state charge trap populations. We introduce a model that unifies previous work and transforms the problem of irreproducibility in nanocrystal electronic properties into a reproducible and robust photocurrent response due to trap state manipulation. Because traps dominate many physical processes, these findings may lead to improved performance and device tunability for various nanoscale applications through the control and optimization of impurities and defects.
LongHCPulse: Long-Pulse Heat Capacity on a Quantum Design PPMS

This paper presents LongHCPulse: software which enables heat capacity to be collected on a Quantum Design PPMS using a long-pulse method. This method, wherein heat capacity is computed from the time derivative of sample temperature over long (30 min) measurement times, is necessary for probing first-order transitions and shortens the measurement time by a factor of five. LongHCPulse also includes plotting utilities based on the Matplotlib library. I illustrate the use of LongHCPulse with the example of data taken on $$\mathrm{Yb_{2}Ti_{2}O_{7}}$$ , $$\mathrm{KNi_{2}Se_{2}}$$ , and $$\mathrm Na_2Ti_3Cl_8$$ , comparing the results to the standard semi-adiabatic method.
Moving basepoints and the induced automorphisms of link Floer homology

Given an l–component pointed oriented link .L;p/ in an oriented three-manifold Y , one can construct its link Floer chain complex CFL.Y;L;p/ over the polynomial ring F2ŒU1; : : : ;Ul  . Moving the basepoint pi 2Li once around the link component Li induces an automorphism of CFL.Y;L;p/ . We study a (possibly different) automorphism of CFL.Y;L;p/ defined explicitly in terms of holomorphic disks; for links in S , we show that these two automorphisms are the same.
Community Archaeology at the Trowel's Edge

The Public Archaeology Facility's (PAF) Community Archaeology Program (CAP) at Binghamton University began 25 years ago in response to intense community interest in participating in archaeology. Although non-archaeologists have unlimited access to programming and social media about archaeology, there is more limited access to professionally supervised opportunities. PAF developed CAP to provide non-archaeologists with the opportunity to participate in highly supervised archaeological research projects to share in the process of discovery at the “trowel's edge.” CAP recognizes the challenges and critiques of community programs and mitigates these by creating a climate of ethical practice. Our goal is to educate individuals about the presence of a rich and fascinating past in their own communities and create the sweat equity that can result in advocates for preservation. We operate under the principles that the heritage story embedded in an artifact is worthy of our respect and protection, and that an educated public is more likely to support the preservation of this heritage. Making a connection to people through artifacts builds not only a deeper understanding of the past but also an empathy for preservation. In this article, we introduce the program and reflect on the 25-year history of CAP and future directions.
The Near-Infrared Photometric Properties of Bright Giants in the Central Regions of the Galactic Bulge

Images recorded through broadband (JHK) and narrowband (CO and 2.2 μm continuum) filters are used to investigate the photometric properties of bright (K ≤ 13.5) stars in a 6' × 6' field centered on the Sgr A complex. The giant branch ridge lines in the (K, J - K) and (K, H - K) color-magnitude diagrams are well matched by the Baade's window (BW) M giant sequence if the mean extinction is AK ~ 2.8 mag. Extinction measurements for individual stars are estimated using the MK versus infrared color relations defined by M giants in BW, and the majority of stars have AK between 2.0 and 3.5 mag. The extinction is locally high in the Sgr A complex, where AK ~ 3.1 mag. Reddening-corrected CO indexes, CO0, are derived for over 1300 stars with J, H, and K brightnesses and for over 5300 stars with H and K brightnesses. The distribution of CO0 values for stars with K0 between 11.25 and 7.25 can be reproduced using the MK-CO0 relation defined by M giants in BW. The data thus suggest that the most metal-rich giants in the central regions of the bulge and in BW have similar photometric properties and 2.3 μm CO strengths. Hence, it appears that the central region of the bulge does not contain a population of stars that are significantly more metal-rich than what is seen in BW.
Incorporating Prior Knowledge for Quantifying and Reducing Model-Form Uncertainty in RANS Simulations

Simulations based on Reynolds-Averaged Navier--Stokes (RANS) models have been used to support high-consequence decisions related to turbulent flows. Apart from the deterministic model predictions, the decision makers are often equally concerned about the predictions confidence. Among the uncertainties in RANS simulations, the model-form uncertainty is an important or even a dominant source. Therefore, quantifying and reducing the model-form uncertainties in RANS simulations are of critical importance to make risk-informed decisions. Researchers in statistics communities have made efforts on this issue by considering numerical models as black boxes. However, this physics-neutral approach is not a most efficient use of data, and is not practical for most engineering problems. Recently, we proposed an open-box, Bayesian framework for quantifying and reducing model-form uncertainties in RANS simulations by incorporating observation data and physics-prior knowledge. It can incorporate the information from the vast body of existing empirical knowledge with mathematical rigor, which enables a more efficient usage of data. In this work, we examine the merits of incorporating various types of prior knowledge in the uncertainties quantification and reduction in RANS simulations. The result demonstrates that informative physics-based prior plays an important role in improving the quantification of model-form uncertainties, particularly when the observation data are limited. Moreover, it suggests that the proposed Bayesian framework is an effective way to incorporate empirical knowledge from various sources.
Conservative Initial Mapping For Multidimensional Simulations of Stellar Explosions

Mapping one-dimensional stellar profiles onto multidimensional grids as initial conditions for hydrodynamics calculations can lead to numerical artifacts, one of the most severe of which is the violation of conservation laws for physical quantities such as energy and mass. Here we introduce a numerical scheme for mapping one-dimensional spherically-symmetric data onto multidimensional meshes so that these physical quantities are conserved. We validate our scheme by porting a realistic 1D Lagrangian stellar profile to the new multidimensional Eulerian hydro code CASTRO. Our results show that all important features in the profiles are reproduced on the new grid and that conservation laws are enforced at all resolutions after mapping.
Emergent network modularity

We introduce a network growth model based on complete redirection: a new node randomly selects an existing target node, but attaches to a random neighbor of this target. For undirected networks, this simple growth rule generates unusual, highly modular networks. Individual network realizations typically contain multiple macrohubs---nodes whose degree scales linearly with the number of nodes $N$. The size of the network "nucleus"---the set of nodes of degree greater than one---grows sublinearly with $N$ and thus constitutes a vanishingly small fraction of the network. The network therefore consists almost entirely of leaves (nodes of degree one) as $N\to\infty$.
Spin Relaxation of Conduction Electrons in Semiconductors Due to Interaction with Nuclear Spins

Relaxation of conduction electron spins in semiconductors owing to the hyperfine interaction with spin-1/2 nuclei, in zero applied magnetic field, is investigated. We calculate the electron spin relaxation time scales in order to evaluate the importance of this relaxation mechanism. Master equations for the electron spin density matrix are derived and solved. Polarized nuclear spins can be used to polarize the electrons in spintronic devices.
BOUNDS ON BLACK HOLE SPINS

Beam powers and black hole masses of 48 extended radio sources are combined to obtain lower bounds on the spins and magnetic field strengths of supermassive black holes. This is done in the context of the models of Blandford & Znajek (1977) (the ’BZ’ model) and Meier (1999); a parameterization for bounds in the context of other models is suggested. The bounds obtained for very powerful classical double radio sources in the BZ model are consistent with black hole spins of order unity for sources at high redshift. The black hole spins are largest for the highest redshift sources and decrease for sources at lower redshift; the sources studied have redshifts between zero and two. Lower power radio sources associated with central dominant galaxies may have black hole spins that are significantly less than one. Combining this analysis with other results suggests that the maximum values of black hole spin associated with powerful radio galaxies decline from values of order unity at a redshift of 2 to values of order 0.7 at a redshift of zero, falling roughly as p (1 + z), while lower power radio sources have spin values that range from about 0.1 to 0.8. These black hole spin values decrease if the data are considered in the context of the Meier model rather than the BZ model.
The Cosmology of Sub-MeV Dark Matter

Light dark matter is a compelling experimental target in light of stringent constraints on heavier WIMPs. However, for a sub-MeV WIMP, the universe is sufficiently well understood at temperatures below 10 MeV that there is no room for it to be a thermal relic. Avoiding thermalization is itself a strong constraint with significant implications for direct detection. In this paper, we explore the space of models of sub-MeV dark matter with viable cosmologies. We discuss several representative models chosen to have large cross-sections in direct detection experiments. The parameter space of these models that is also consistent with astrophysical and lab-based limits is highly restricted for couplings to electrons but somewhat less constrained for nuclei. We find that achieving nuclear cross-sections well-above the neutrino floor necessarily predicts a new contribution to the effective number of neutrino species, ΔN eff = 0.09 that will be tested by the next generation of CMB observations. On the other hand, models with absorption signatures of dark matter are less restricted by cosmology even with future observations.
Design and analysis of machine learning exchange-correlation functionals via rotationally invariant convolutional descriptors

In this work, the authors explore a framework for developing machine-learned exchange-correlation (XC) functionals. The approach consists of two parts: a rotationally invariant model space constructed from convolutional kernels, and a neural network to predict the XC energy density. The results show that increasing the number of features in the model space leads to systematically improvable approximations to the B3LYP XC energy for 21 small molecule systems. The XC formation energy is predicted to chemical accuracy based on orbital free descriptors with a range of $l$0.2 Angstrom, suggesting this approach provides an efficient route toward semi-local approximations of hybrid functionals.
Prelude to, and Nature of the Space Photometry Revolution

It is now less than a decade since CoRoT initiated the space photometry revolution with breakthrough discoveries, and five years since Kepler started a series of similar advances. I’ll set the context for this revolution noting the status of asteroseismology and exoplanet discovery as it was 15–25 years ago in order to give perspective on why it is not mere hyperbole to claim CoRoT and Kepler fostered a revolution in our sciences. Primary events setting up the revolution will be recounted. I’ll continue with noting the major discoveries in hand, and how asteroseismology and exoplanet studies, and indeed our approach to doing science, have been forever changed thanks to these spectacular missions.
Nilpotence theorems via homological residue fields

We prove nilpotence theorems in tensor-triangulated categories using suitable Gabriel quotients of the module category, and discuss examples.
FLUCTUATION SPECTROSCOPY: A NEW PROBE OF OLD STELLAR POPULATIONS

We introduce a new method to determine the relative contributions of different types of stars to the integrated light of nearby early-type galaxies. As is well known, the surface brightness of these galaxies shows pixel-to-pixel fluctuations due to Poisson variations in the number of giant stars. Differential spectroscopy of pixels as a function of fluctuation strength ({sup f}luctuation spectroscopy{sup )} effectively measures the spectral variation of stars as a function of their luminosity, information that is otherwise difficult to obtain for individual stars outside of the Local Group. We apply this technique to the elliptical galaxy NGC 4472, using Hubble Space Telescope/Advanced Camera for Surveys imaging in six narrow-band ramp filters tuned to spectral features in the range 0.8 μm-1.0 μm. Pixels with ±5% broad-band variations show differential color variations of 0.1%-1.0% in the narrow-band filters. These variations are primarily due to the systematic increase in TiO absorption strength with increasing luminosity on the upper giant branch. The data are very well reproduced by the same Conroy and van Dokkum stellar population synthesis model that is the best fit to the integrated light, with residuals in the range 0.03%-0.09%. Models with ages or metallicities that are significantly different from themore » integrated-light values do not yield good fits. We can also rule out several modifications to the underlying model, including the presence of a significant (>3% of the light) population of late M giants. The current observations constitute a powerful test of the expected luminosities and temperatures of metal-rich giants in massive early-type galaxies. Studies of pixels with much larger (negative) fluctuations will provide unique information on main sequence stars and the stellar initial mass function.« less
Integrated Optical Polarization of nearby Galaxies

We performed an integrated optical polarization survey of 70 nearby galaxies to study the relationship between linear polarization and galaxy properties. To date this is the largest survey of its kind. The data were collected at McDonald Observatory using the Imaging Grism Polarimeter on the Otto Struve 2.1 m telescope. Most of the galaxies did not have significant level of linear polarization, where the bulk is <1%. A fraction of the galaxies showed a loose correlation between the polarization and position angle of the galaxy, indicating that dust scattering is the main source of optical polarization. The unbarred spiral galaxies are consistent with the predicted relationship with inclination from scattering models of ~sin 2 i.
Spin chains and chiral lattice fermions

The generalization of Lorentz invariance to solvable two-dimensional lattice fermion models has been formulated in terms of Baxter's corner transfer matrix. In these models, the lattice Hamiltonian and boost operator are given by fermionized nearest-neighbor Heisenberg spin chain operators. The transformation properties of the local lattice fermion operators under a boost provide a natural and precise way of generalizing the chiral structure of a continuum Dirac field to the lattice. The resulting formulation differs from both the Wilson and staggered (Kogut-Susskind) prescriptions. In particular, an axial Q 5 rotation is sitewise local, while the vector charge rotation mixes nearest neighbors on even and odd sublattices.
Key biology you should have learned in physics class: Using ideal-gas mixtures to understand biomolecular machines

The biological cell exhibits a fantastic range of behaviors, but ultimately, these are governed by a handful of physical and chemical principles. Here, we explore a simple theory, known for decades and based on the simple thermodynamics of mixtures of ideal gases, that illuminates several key functions performed within the cell. Our focus is the free-energy-driven import and export of molecules, such as nutrients and other vital compounds, via transporter proteins. Complementary to a thermodynamic picture is a description of transporters via “mass-action” chemical kinetics, which lends further insights into biological machinery and free energy use. Both thermodynamic and kinetic descriptions can shed light on the fundamental non-equilibrium aspects of transport. On the whole, our biochemical-physics discussion will remain agnostic to chemical details, but we will see how such details ultimately enter a physical description through the example of the cellular fuel ATP.
Linear in temperature resistivity in the limit of zero temperature from the time reparameterization soft mode

Abstract The most puzzling aspect of the ‘strange metal’ behavior of correlated electron compounds is that the linear in temperature resistivity often extends down to low temperatures, lower than natural microscopic energy scales. We consider recently proposed deconfined critical points (or phases) in models of electrons in large dimension lattices with random nearest-neighbor exchange interactions. The criticality is in the class of Sachdev–Ye–Kitaev models, and exhibits a time reparameterization soft mode representing gravity in dual holographic theories. We compute the low temperature resistivity in a large M limit of models with SU( M ) spin symmetry, and find that the dominant temperature dependence arises from this soft mode. The resistivity is linear in temperature down to zero temperature at the critical point, with a co-efficient universally proportional to the product of the residual resistivity and the co-efficient of the linear in temperature specific heat. We argue that the time reparameterization soft mode offers a promising and generic mechanism for resolving the strange metal puzzle.
Overcoming erasure errors with multilevel systems

We investigate the usage of highly efficient error correcting codes of multilevel systems to protect encoded quantum information from erasure errors and implementation to repetitively correct these errors. Our scheme makes use of quantum polynomial codes to encode quantum information and generalizes teleportation based error correction for multilevel systems to correct photon losses and operation errors in a fault-tolerant manner. We discuss the application of quantum polynomial codes to one-way quantum repeaters. For various types of operation errors, we identify different parameter regions where quantum polynomial codes can achieve a superior performance compared to qubit based quantum parity codes.
Potential Condensed Fuel for the Milky Way

Potential condensed clouds of gas in the Galactic halo are examined in the context of the recent models of cooling, fragmenting clouds building up the baryonic mass of the Galaxy. Five hundred and eighty-two high-velocity clouds are defined as the potential condensed clouds, and the sample's spatial and velocity distributions are presented. With the majority of the hydrogen in the clouds ionized (~85%), the clouds at a distribution of distances within 150 kpc, and their individual total masses below 107 M☉, the total mass in potentially condensed clouds is (1.1-1.4) × 109 M☉. If the tighter distance constraint of <60 kpc is adopted, this mass range drops to (4.5-6.1) × 108 M☉. The implications for the condensing cloud models, as well as feedback and additional accretion methods, are discussed.
On the minimal penalty for Markov order estimation

We show that large-scale typicality of Markov sample paths implies that the likelihood ratio statistic satisfies a law of iterated logarithm uniformly to the same scale. As a consequence, the penalized likelihood Markov order estimator is strongly consistent for penalties growing as slowly as log log n when an upper bound is imposed on the order which may grow as rapidly as log n. Our method of proof, using techniques from empirical process theory, does not rely on the explicit expression for the maximum likelihood estimator in the Markov case and could therefore be applicable in other settings.
Dynamics of strings in noncommutative gauge theory

We continue our study of solitons in noncommutative gauge theories and present an extremely simple BPS solution of = 4 U(1) noncommutative gauge theory in 4 dimensions, which describes N infinite D1-strings that pierce a D3-brane at various points, in the presence of a background B-field in the Seiberg-Witten α'→0 limit. We call this solution the N-fluxon. For N = 1 we calculate the complete spectrum of small fluctuations about the fluxon and find three kinds of modes: the fluctuations of the superstring in 10 dimensions arising from fundamental strings attached to the D1 strings, the ordinary particles of the gauge theory in 4 dimensions and a set of states with discrete spectrum, localized at the intersection point - corresponding to fundamental strings stretched between the D1-string and the D3-brane. We discuss the fluctuations about the N-fluxon as well and derive explicit expressions for the amplitudes of interactions between these various modes. We show that translations in noncommutative gauge theories are equivalent to gauge transformations (plus a constant shift of the gauge field) and discuss the implications for the translational zero modes of our solitons. We also find the dyonic versions of N-fluxon, as well as of our previous string-monopole solution.
CALCULATING ENERGY STORAGE DUE TO TOPOLOGICAL CHANGES IN EMERGING ACTIVE REGION NOAA AR 11112

The minimum current corona model provides a way to estimate stored coronal energy using the number of field lines connecting regions of positive and negative photospheric flux. This information is quantified by the net flux connecting pairs of opposing regions in a connectivity matrix. Changes in the coronal magnetic field, due to processes such as magnetic reconnection, manifest themselves as changes in the connectivity matrix. However, the connectivity matrix will also change when flux sources emerge or submerge through the photosphere, as often happens in active regions. We have developed an algorithm to estimate the changes in flux due to emergence and submergence of magnetic flux sources. These estimated changes must be accounted for in order to quantify storage and release of magnetic energy in the corona. To perform this calculation over extended periods of time, we must additionally have a consistently labeled connectivity matrix over the entire observational time span. We have therefore developed an automated tracking algorithm to generate a consistent connectivity matrix as the photospheric source regions evolve over time. We have applied this method to NOAA Active Region 11112, which underwent a GOES M2.9 class flare around 19:00 on 2010 October 16th, and calculated a lower bound on the free magnetic energy buildup of ~8.25 × 1030 erg over 3 days.
Supporting Very Large Models using Automatic Dataflow Graph Partitioning

This paper presents Tofu, a system that partitions very large DNN models across multiple GPU devices to reduce per-GPU memory footprint. Tofu is designed to partition a dataflow graph of fine-grained tensor operators used by platforms like MXNet and TensorFlow. In order to automatically partition each operator, we propose to describe the semantics of an operator in a simple language inspired by Halide. To optimally partition different operators in a dataflow graph, Tofu uses a recursive search algorithm that minimizes the total communication cost. Our experiments on an 8-GPU machine show that Tofu enables the training of very large CNN and RNN models. It also achieves 25% - 400% speedup over alternative approaches to train very large models.
Excited state mean-field theory without automatic differentiation

We present a formulation of excited state mean-field theory in which the derivatives with respect to the wave function parameters needed for wave function optimization (not to be confused with nuclear derivatives) are expressed analytically in terms of a collection of Fock-like matrices. By avoiding the use of automatic differentiation and grouping Fock builds together, we find that the number of times we must access the memory-intensive two-electron integrals can be greatly reduced. Furthermore, the new formulation allows the theory to exploit the existing strategies for efficient Fock matrix construction. We demonstrate this advantage explicitly via the shell-pair screening strategy with which we achieve a cubic overall cost scaling. Using this more efficient implementation, we also examine the theory's ability to predict charge redistribution during charge transfer excitations. Using the coupled cluster as a benchmark, we find that by capturing orbital relaxation effects and avoiding self-interaction errors, excited state mean field theory out-performs other low-cost methods when predicting the charge density changes of charge transfer excitations.
Navigating collinear superspace

We introduce a new set of effective field theory rules for constructing Lagrangians with $$ \mathcal{N} $$ = 1 supersymmetry in collinear superspace. In the standard superspace treatment, superfields are functions of the coordinates $$ \left({x}^{\mu },{\theta}^{\alpha },{\theta}^{\dagger \overset{\cdot }{\alpha }}\right) $$ , and supersymmetry preservation is manifest at the Lagrangian level in part due to the inclusion of auxiliary F- and D-term components. By contrast, collinear superspace depends on a smaller set of coordinates (xμ, η, η†), where η is a complex Grassmann number without a spinor index. This provides a formulation of supersymmetric theories that depends exclusively on propagating degrees of freedom, at the expense of obscuring Lorentz invariance and introducing inverse momentum scales. After establishing the general framework, we construct collinear superspace Lagrangians for free chiral matter and non-Abelian gauge fields. For the latter construction, an important ingredient is a superfield representation that is simultaneously chiral, anti-chiral, and real; this novel object encodes residual gauge transformations on the light cone. Additionally, we discuss a fundamental obstruction to constructing inter- acting theories with chiral matter; overcoming these issues is the subject of our companion paper, where we introduce a larger set of superfields to realize the full range of interactions compatible with $$ \mathcal{N} $$ = 1. Along the way, we provide a novel framing of reparametrization invariance using a spinor decomposition, which provides insight into this important light-cone symmetry.