cssi/SciSciGPT-SciSciNet huggingface dataset:
The case for emulating insect brains using anatomical “wiring diagrams” equipped with biophysical models of neuronal activity

Developing whole-brain emulation (WBE) technology would provide immense benefits across neuroscience, biomedicine, artificial intelligence, and robotics. At this time, constructing a simulated human brain lacks feasibility due to limited experimental data and limited computational resources. However, I suggest that progress toward this goal might be accelerated by working toward an intermediate objective, namely insect brain emulation (IBE). More specifically, this would entail creating biologically realistic simulations of entire insect nervous systems along with more approximate simulations of non-neuronal insect physiology to make “virtual insects.” I argue that this could be realistically achievable within the next 20 years. I propose that developing emulations of insect brains will galvanize the global community of scientists, businesspeople, and policymakers toward pursuing the loftier goal of emulating the human brain. By demonstrating that WBE is possible via IBE, simulating mammalian brains and eventually the human brain may no longer be viewed as too radically ambitious to deserve substantial funding and resources. Furthermore, IBE will facilitate dramatic advances in cognitive neuroscience, artificial intelligence, and robotics through studies performed using virtual insects.
Evidence for a T Tauri Phase in Young Brown Dwarfs

As part of a multifaceted program to investigate the origin and early evolution of substellar objects, we present high-resolution Keck optical spectra of 14 very low mass sources in the IC 348 young cluster and the Taurus star-forming cloud. All of our targets, which span a range of spectral types from M5 to M8, exhibit moderate to very strong Hα emission. In half of the IC 348 objects, the Hα profiles are broad and asymmetric, indicative of ongoing accretion. Of these, IC 348-355 (M8) is the lowest mass object to date to show accretion-like Hα. Three of our ~M6 IC 348 targets with broad Hα also harbor broad O I (8446 A) and Ca II (8662 A) emission, and one shows broad He I (6678 A) emission; these features are usually seen in strongly accreting classical T Tauri stars. We find that in very low mass accretors, the Hα profile may be somewhat narrower than that in higher mass stars. We propose that low accretion rates combined with small infall velocities at very low masses can conspire to produce this effect. In the nonaccretors in our sample, Hα emission is commensurate with, or higher than, saturated levels in field M dwarfs of similar spectral type. Our results constitute the most compelling evidence to date that young brown dwarfs undergo a T Tauri-like accretion phase similar to that in stars. This is consistent with a common origin for most low-mass stars, brown dwarfs, and isolated planetary mass objects.
Lattices and Their Consistent Quantification

This paper introduces the order-theoretic concept of lattices along with the concept of consistent quantification where lattice elements are mapped to real numbers in such a way that preserves some aspect of the order-theoretic structure. Symmetries, such as associativity, constrain consistent quantification and lead to a constraint equation known as the sum rule. Distributivity in distributive lattices also constrains consistent quantification and leads to a product rule. The sum and product rules, which are familiar from, but not unique to, probability theory, arise from the fact that logical statements form a distributive (Boolean) lattice, which exhibits the requisite symmetries.
Online learning in optical tomography: a stochastic approach

We study the inverse problem of radiative transfer equation (RTE) using stochastic gradient descent method (SGD) in this paper. Mathematically, optical tomography amounts to recovering the optical parameters in RTE using the incoming–outgoing pair of light intensity. We formulate it as a PDE-constraint optimization problem, where the mismatch of computed and measured outgoing data is minimized with same initial data and RTE constraint. The memory and computation cost it requires, however, is typically prohibitive, especially in high dimensional space. Smart iterative solvers that only use partial information in each step is called for thereafter. Stochastic gradient descent method is an online learning algorithm that randomly selects data for minimizing the mismatch. It requires minimum memory and computation, and advances fast, therefore perfectly serves the purpose. In this paper we formulate the problem, in both nonlinear and its linearized setting, apply SGD algorithm and analyze the convergence performance.
REVERSAL OF FORTUNE: INCREASED STAR FORMATION EFFICIENCIES IN THE EARLY HISTORIES OF DWARF GALAXIES?

On dwarf galaxy scales, the different shapes of the galaxy stellar mass function and the dark halo mass function require a star-formation efficiency (SFE) in these systems that is currently more than 1 dex lower than that of Milky Way-size halos. Here, we argue that this trend may actually be reversed at high redshift. Specifically, by combining the resolved star-formation histories of nearby isolated dwarfs with the simulated mass-growth rates of dark matter halos, we show that the assembly of these systems occurs in two phases: (1) an early, fast halo accretion phase with a rapidly deepening potential well, characterized by a high SFE; and (2) a late, slow halo accretion phase where, perhaps as a consequence of reionization, the SFE is low. Nearby dwarfs have more old stars than predicted by assuming a constant or decreasing SFE with redshift, a behavior that appears to deviate qualitatively from the trends seen among more massive systems. Taken at face value, the data suggest that at sufficiently early epochs, dwarf galaxy halos above the atomic cooling mass limit can be among the most efficient sites of star formation in the universe.
Quantum production of black holes

Abstract We give a path integral expression for the quantum amplitude to produce a black hole from particle collisions. When expanded about an appropriate classical solution it yields the leading order contribution to the production amplitude in a curvature expansion. Classical solutions describing black hole production resulting from two particle scattering at non-zero impact parameter, combined with our formalism, indicate a geometric cross section for the quantum process. In TeV gravity scenarios these solutions may exhibit large curvatures, but (modulo a mild assumption about quantum gravity) corrections to the semi-classical cross section are small.
The quartic Fermat equation in Hilbert class fields of imaginary quadratic fields

It is shown that the quartic Fermat equation x4 + y4 = 1 has nontrivial integral solutions in the Hilbert class field Σ of any quadratic field whose discriminant satisfies -d ≡ 1 (mod 8). A corollary is that the quartic Fermat equation has no nontrivial solution in , for p (> 7) a prime congruent to 7 (mod 8), but does have a nontrivial solution in the odd degree extension Σ of K. These solutions arise from explicit formulas for the points of order 4 on elliptic curves in Tate normal form. The solutions are studied in detail and the results are applied to prove several properties of the Weber singular moduli introduced by Yui and Zagier.
The fourth moment of Dirichlet L-functions

We compute the fourth moment of Dirichlet L-functions at the central point for prime moduli, with a power savings in the error term.
On the verge of an astronomy CubeSat revolution

CubeSats are small satellites built in standard sizes and form factors, which have been growing in popularity but have thus far been largely ignored within the field of astronomy. When deployed as space-based telescopes, they enable science experiments not possible with existing or planned large space missions, filling several key gaps in astronomical research. Unlike expensive and highly sought after space telescopes such as the Hubble Space Telescope, whose time must be shared among many instruments and science programs, CubeSats can monitor sources for weeks or months at time, and at wavelengths not accessible from the ground such as the ultraviolet, far-infrared and low-frequency radio. Science cases for CubeSats being developed now include a wide variety of astrophysical experiments, including exoplanets, stars, black holes and radio transients. Achieving high-impact astronomical research with CubeSats is becoming increasingly feasible with advances in technologies such as precision pointing, compact sensitive detectors and the miniaturization of propulsion systems. CubeSats may also pair with the large space- and ground-based telescopes to provide complementary data to better explain the physical processes observed. CubeSats, a standardized subgroup of small satellites, are a cheap and flexible solution to perform astronomical observations from space that is just starting to be exploited. This Perspective presents an overview of their advantages and of the current and planned projects.
Eye in the Sky: Drone-Based Object Tracking and 3D Localization

Drones, or general UAVs, equipped with a single camera have been widely deployed to a broad range of applications, such as aerial photography, fast goods delivery and most importantly, surveillance. Despite the great progress achieved in computer vision algorithms, these algorithms are not usually optimized for dealing with images or video sequences acquired by drones, due to various challenges such as occlusion, fast camera motion and pose variation. In this paper, a drone-based multi-object tracking and 3D localization scheme is proposed based on the deep learning based object detection. We first combine a multi-object tracking method called TrackletNet Tracker (TNT) which utilizes temporal and appearance information to track detected objects located on the ground for UAV applications. Then, we are also able to localize the tracked ground objects based on the group plane estimated from the Multi-View Stereo technique. The system deployed on the drone can not only detect and track the objects in a scene, but can also localize their 3D coordinates in meters with respect to the drone camera. The experiments have proved our tracker can reliably handle most of the detected objects captured by drones and achieve favorable 3D localization performance when compared with the state-of-the-art methods.
New Limits on Gamma-Ray Emission from Galaxy Clusters

Galaxy clusters are predicted to produce γ-rays through cosmic ray interactions and/or dark matter annihilation, potentially detectable by the Fermi Large Area Telescope (Fermi-LAT). We present a new, independent stacking analysis of Fermi-LAT photon count maps using the 78 richest nearby clusters (z < 0.12) from the Two Micron All Sky Survey cluster catalog. We obtain the lowest limit on the photon flux to date, 2.3 × 10–11 photons cm–2 s–1 (95% confidence) per cluster in the 0.8-100 GeV band, which corresponds to a luminosity limit of 3.5 × 1044 photons s–1. We also constrain the emission limits in a range of narrower energy bands. Scaling to recent cosmic ray acceleration and γ-ray emission models, we find that cosmic rays represent a negligible contribution to the intra-cluster energy density and gas pressure.
Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach.

Given a document and a target aspect (e.g., a topic of interest), aspect-based abstractive summarization attempts to generate a summary with respect to the aspect. Previous studies usually assume a small pre-defined set of aspects and fall short of summarizing on other diverse topics. In this work, we study summarizing on \emph{arbitrary} aspects relevant to the document, which significantly expands the application of the task in practice. Due to the lack of supervision data, we develop a new weak supervision construction method and an aspect modeling scheme, both of which integrate rich external knowledge sources such as ConceptNet and Wikipedia. Experiments show our approach achieves performance boosts on summarizing both real and synthetic documents given pre-defined or arbitrary aspects.
Theoretical characterization of structural disorder in the tetramer model structure of eumelanin

Eumelanin is regarded to be an attractive candidate material for biomedical applications. Despite many theoretical studies exploring the structure of eumelanin, an exact mapping of the energetic landscape of the very large phase space of eumelanin is still elusive. In this work, we implement a piecewise Ising model to predict formation enthalpies of eumelanin single and double tetramers, and demonstrate its superior predictive and generalizable capabilities. We believe this model will prove very useful in theoretically characterizing the many unique properties attributed to its disorder. The modular nature of the predictive Ising model built up in this work is well-suited for analysis and characterization of a larger phase space of eumelanin polymers, including hexamers and octomers, as well as larger stacked structures, such as potential triple and quadruple eumelanin tetramers. Absorbance data can be incorporated with populationwide predictions of polymer abundance to produce weighted-average predictions of broadband absorbance of bulk eumelanin.
Shape, structure, and morphology in planetary nebulae

A revival over the past two decades in planetary nebula (PN) morphological studies springs from a combination of factors, including the advent of wide-area, high dynamic range detectors; the growing archives of high resolution images from the X-ray to the sub-mm; and the advent of sophisticated models of the co-evolution of PNe and their central stars. Yet the story of PN formation from their immediate precursors, the AGB stars, is not yet fully written. PN morphology continues to inspire, provide context for physical interpretation, and serve as an ultimate standard of comparison for many investigations in this area of astrophysics. After a brief review of the remarkable successes of PN morphology, I summarize how this tool has been employed over the last half-decade to advance our understanding of PNe.
The Kozai-Lidov Mechanism in Hydrodynamical Disks. III. Effects of Disk Mass and Self-gravity

Previously we showed that a substantially misaligned viscous accretion disk with pressure that orbits around one component of a binary system can undergo global damped Kozai–Lidov (KL) oscillations. These oscillations produce periodic exchanges of the disk eccentricity with inclination. The disk KL mechanism is quite robust and operates over a wide range of binary and disk parameters. However, the effects of self-gravity, which are expected to suppress the KL oscillations for sufficiently massive disks, were ignored. Here, we analyze the effects of disk self-gravity by means of hydrodynamic simulations and compare the results with the expectations of analytic theory. The disk mass required for suppression in the simulations is a few percent of the mass of the central star and this roughly agrees with an analytical estimate. The conditions for suppression of the KL oscillations in the simulations are close to requiring that the disk be gravitationally unstable. We discuss some implications of our results for the dynamics of protoplanetary disks and the related planet formation.
On the stability of fermionic non-isothermal dark matter halos

The stability of isothermal dark matter halos has been widely studied before. In this paper, we investigate the stability of non-isothermal fermionic dark matter halos. We show that in the presence of temperature gradient, the force due to the pressure has both inward and outward components. In some regions of halos, the inward force that provides stability is due to the pressure rather than gravity. Moreover, it is shown that higher temperature gradients lead to halos with lower mass and size. We prove that if the temperature is left as a free positive profile, one can place no phase-space lower bound on the mass of dark matter. For halos that are in the low degeneracy classic domain, we derive an analytic expression of their temperature in terms of their mass density and place an upper bound on the mass of dark matter by requiring that temperature is not negative. We then use the Burkert mass profile for the Milky Way to show that if the central temperature of the halo is a few Kelvins, the mass of dark matter cannot exceed a few keV.
Optimization of NANOGrav's Time Allocation for Maximum Sensitivity to Single Sources

Pulsar timing arrays (PTAs) are a collection of precisely timed millisecond pulsars (MSPs) that can search for gravitational waves (GWs) in the nanohertz frequency range by observing characteristic signatures in the timing residuals. The sensitivity of a PTA depends on the direction of the propagating GW source, the timing accuracy of the pulsars, and the allocation of the available observing time. The goal of this paper is to determine the optimal time allocation strategy among the MSPs in the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) for a single source of GW under a particular set of assumptions. We consider both an isotropic distribution of sources across the sky and a specific source in the Virgo cluster. This work improves on previous efforts by modeling the effect of intrinsic spin noise for each pulsar. We find that, in general, the array is optimized by maximizing time spent on the best-timed pulsars, with sensitivity improvements typically ranging from a factor of 1.5 to 4.
Theoretical analysis of the characteristic impedance in metal–insulator–metal plasmonic transmission lines

We propose a closed form formulation for the impedance of the metal–insulator–metal (MIM) plasmonic transmission lines by solving the Maxwell’s equations. We provide approximations for thin and thick insulator layers sandwiched between metallic layers. In the case of very thin dielectric layer, the surface waves on both interfaces are strongly coupled resulting in an almost linear dependence of the impedance of the plasmonic transmission line on the thickness of the insulator layer. On the other hand, for very thick insulator layer, the impedance does not vary with the insulator layer thickness due to the weak-coupling/decoupling of the surface waves on each metal–insulator interface. We demonstrate the effectiveness of our proposed formulation using two test scenarios, namely, almost zero reflection in T-junction and reflection from line discontinuity in the design of Bragg reflectors, where we compare our formulation against previously published results.
A thermodynamic framework to develop rate-type models for fluids without instantaneous elasticity

In this paper, we apply the thermodynamic framework recently put into place by Rajagopal and co-workers, to develop rate-type models for viscoelastic fluids which do not possess instantaneous elasticity. To illustrate the capabilities of such models, we make a specific choice for the specific Helmholtz potential and the rate of dissipation and consider the creep and stress relaxation response associated with the model. Given specific forms for the Helmholtz potential and the rate of dissipation, the rate of dissipation is maximized with the constraint that the difference between the stress power and the rate of change of Helmholtz potential is equal to the rate of dissipation and any other constraint that may be applicable such as incompressibility. We show that the class of models that are developed exhibit fluid-like characteristics, when none of the material moduli that appear in the model are not zero, and are incapable of instantaneous elastic response. They also include Maxwell-like and Kelvin-Voigt-like viscoelastic materials (when certain material moduli take special values).
Hyperbolicity of asymmetric lemon billiards

Asymmetric lemon billiards was introduced in [CMZZ], where the billiard table $Q(r,b,R)$ is the intersection of two round disks with radii $r\le R$, respectively, and $b$ measures the distance between the two centers. It is conjectured [BZZ] that the asymmetric lemon billiards is hyperbolic when the arc $\Gamma_r$ is a major arc and $R$ is large. In this paper we prove this conjecture for sufficiently large $R$.
An isoperimetric inequality for fundamental tones of free plates with nonzero Poisson’s ratio

We establish a partial generalization of a prior isoperimetric inequality for the fundamental tone (first nonzero eigenvalue) of the free plate to that of plates of nonzero Poisson’s ratio. Given a tension and a Poisson’s ratio , the free plate eigenvalues and eigenfunctions are determined by the equation together with certain natural boundary conditions which involve both and . The boundary conditions are complicated but arise naturally from the plate Rayleigh quotient. We prove the free plate isoperimetric inequality, previously shown in the case, holds for certain nonzero and positive . We conjecture that the inequality holds for all dimensions, , and relevant values of , and discuss numerical and analytic support of this conjecture.
Extending homotopy theories across adjunctions

Constructions of spectra from symmetric monoidal categories are typically functorial with respect to strict structure-preserving maps, but often the maps of interest are merely lax monoidal. We describe conditions under which one can transport the weak equivalences from one category to another with the same objects and a broader class of maps. Under mild hypotheses this process produces an equivalence of homotopy theories. We describe examples including algebras over an operad, such as symmetric monoidal categories and $n$-fold monoidal categories; and diagram categories, such as $\Gamma$-categories.
Ergodic Considerations in the Gravitational Potential of the Milky Way

A method is proposed for constraining the Galactic gravitational potential from high-precision observations of the phase space coordinates of a system of relaxed tracers. The method relies on an "ergodic" assumption that the observations are representative of the state of the system at any other time. The observed coordinates serve as initial conditions for moving the tracers forward in time in an assumed model for the gravitational field. The validity of the model is assessed by the statistical equivalence between the observations and the distribution of tracers at randomly selected times. The applicability of this ergodic method is not restricted by any assumption on the form or symmetry of the potential. However, it requires high-precision observations as those that will be obtained from missions such as Space Interferometry Mission and Global Astrometry Interferometer for Astrophysics.
Classes on Compactifications of the Moduli Space of Curves Through Solutions to the Quantum Master Equation

In this paper we describe a construction which produces classes in compactifications of the moduli space of curves. This construction extends a construction of Kontsevich which produces classes in the open moduli space from the initial data of a cyclic A∞-algebra. The initial data for our construction are what we call a ‘quantum A∞-algebra’, which arises as a type of deformation of a cyclic A∞-algebra. The deformation theory for these structures is described explicitly. We construct a family of examples of quantum A∞-algebras which extend a family of cyclic A∞-algebras, introduced by Kontsevich, which are known to produce all the kappa classes using his construction.
Quenched Invariance Principles for the Discrete Fourier Transforms of a Stationary Process

In this paper we study the asymptotic behaviour of the normalized cadlag functions generated by the discrete Fourier transforms of a stationary process, started at a point. We prove several quenched invariance principles valid under mild, classical assumptions. These results provide answers to the question of the validity of the quenched functional central limit theorem for the discrete Fourier transforms of the corresponding processes, guaranteeing and describing asymptotic distributions for almost all frequencies. We show that the Hannan condition guarantees the existence of quenched asymptotic distributions at all frequencies, and in this case we describe in terms of limits the asymptotic distribution at any given frequency. We give also a quenched functional limit theorem for averaged frequencies, valid under no special assumption other than a mild regularity condition. We also show that, assuming regularity, the Hannan condition can be weakened and the asymptotic distributions still exist in the quenched sense for all frequencies different from 0. As a corollary we show that, in combination with a generalized weakly-mixing case, these Hannan-like conditions imply that the description of the asymptotic distributions valid in the general case for almost every frequency can fail only for finitely many frequencies corresponding to rational rotations. The proofs are based on martingale approximations and combine results from Ergodic Theory of recent and classical origin, estimates for the maxima of partial sums associated to these processes inspired in work by contemporary authors, and several facts from Harmonic Analysis and Functional Analysis.
Cosmic Censorship for Some Spatially Homogeneous Cosmological Models

Abstract The global properties of spatially homogeneous cosmological models with collisionless matter are studied. It is shown that as long as the mean curvature of the hypersurfaces of homogeneity remains finite no singularity can occur in finite proper time as measured by observers whose worldlines are orthogonal to these hypersurfaces. Strong cosmic censorship is then proved for the Bianchi I, Bianchi IX, and Kantowski-Sachs symmetry classes.
Measuring the Viewing Angle of GW170817 with Electromagnetic and Gravitational Waves

The joint detection of gravitational waves (GWs) and electromagnetic (EM) radiation from the binary neutron star merger GW170817 ushered in a new era of multi-messenger astronomy. Joint GW-EM observations can be used to measure the parameters of the binary with better precision than either observation alone. Here, we use joint GW-EM observations to measure the viewing angle of GW170817, the angle between the binary's angular momentum and the line of sight. We combine a direct measurement of the distance to the host galaxy of GW170817 (NGC 4993) of $40.7\pm 2.36$ Mpc with the Laser Interferometer Gravitational-wave Observatory (LIGO)/Virgo GW data and find that the viewing angle is $32^{+10}_{-13}\,\pm 1.7$ degrees (90% confidence, statistical, and systematic errors). We place a conservative lower limit on the viewing angle of $\ge 13^\circ$, which is robust to the choice of prior. This measurement provides a constraint on models of the prompt $\gamma$-ray and radio/X-ray afterglow emission associated with the merger; for example, it is consistent with the off-axis viewing angle inferred for a structured jet model. We provide for the first time the full posterior samples from Bayesian parameter estimation of LIGO/Virgo data to enable further analysis by the community.
Matter couplings and equivalence principles for soft scalars

Scalar effective field theories with enhanced soft limits behave in many ways like gauge theories and gravity. In particular, symmetries fix the structure of interactions and the tree-level S-matrix in both types of theories. We explore how this analogy persists in the presence of matter by considering theories with additional fields coupled to the Dirac-Born-Infeld (DBI) scalar or the special galileon in a way that is consistent with their symmetries. Using purely on-shell arguments, we show that these theories obey analogues of the S-matrix equivalence principle whereby all matter fields must couple to the DBI scalar or the special galileon through a particular quartic vertex with a universal coupling. These equivalence principles imply the universality of the leading double soft theorems in these theories, which are scalar analogues of Weinberg’s gravitational soft theorem, and can be used to rule out interactions with massless higher-spin fields when combined with analogues of the generalized Weinberg-Witten theorem. We verify in several examples that amplitudes with external matter fields nontrivially exhibit enhanced single soft limits and we show that such amplitudes can be constructed using soft recursion relations when they have sufficiently many external DBI or special galileon legs, including amplitudes with massive higher-spin fields. As part of our analysis we construct a recently conjectured special galileon-vector effective field theory.
More analytic bootstrap: nonperturbative effects and fermions

We develop the analytic bootstrap in several directions. First, we discuss the appearance of nonperturbative effects in the Lorentzian inversion formula, which are exponentially suppressed at large spin but important at finite spin. We show that these effects are important for precision applications of the analytic bootstrap in the context of the 3d Ising and O(2) models. In the former they allow us to reproduce the spin-2 stress tensor with error at the 10−5 level while in the latter requiring that we reproduce the stress tensor allows us to predict the coupling to the leading charge-2 operator. We also extend perturbative calculations in the lightcone bootstrap to fermion 4-point functions in 3d, predicting the leading and subleading asymptotic behavior for the double-twist operators built out of two fermions.
Index theory of the de Rham complex on manifolds with periodic ends

We study the de Rham complex on a smooth manifold with a periodic end modeled on an infinite cyclic cover X→X. The completion of this complex in exponentially weighted L2 norms is Fredholm for all but finitely many exceptional weights determined by the eigenvalues of the covering translation map H∗(X)→H∗(X). We calculate the index of this weighted de Rham complex for all weights away from the exceptional ones.
Using Affective Features from Media Content Metadata for Better Movie Recommendations.

This paper investigates the causality in the decision making of movie recommendations through the users' affective profiles. We advocate a method of assigning emotional tags to a movie by the auto-detection of the affective features in the movie's overview. We apply a text-based Emotion Detection and Recognition model, which trained by tweets short messages and transfers the learned model to detect movie overviews' implicit affective features. We vectorized the affective movie tags to represent the mood embeddings of the movie. We obtain the user's emotional features by taking the average of all the movies' affective vectors the user has watched. We apply five-distance metrics to rank the Top-N movie recommendations against the user's emotion profile. We found Cosine Similarity distance metrics performed better than other distance metrics measures. We conclude that by replacing the top-N recommendations generated by the Recommender with the reranked recommendations list made by the Cosine Similarity distance metrics, the user will effectively get affective aware top-N recommendations while making the Recommender feels like an Emotion Aware Recommender.
Towards numerically robust multireference theories: The driven similarity renormalization group truncated to one- and two-body operators.

The first nonperturbative version of the multireference driven similarity renormalization group (MR-DSRG) theory [C. Li and F. A. Evangelista, J. Chem. Theory Comput. 11, 2097 (2015)] is introduced. The renormalization group structure of the MR-DSRG equations ensures numerical robustness and avoidance of the intruder-state problem, while the connected nature of the amplitude and energy equations guarantees size consistency and extensivity. We approximate the MR-DSRG equations by keeping only one- and two-body operators and using a linearized recursive commutator approximation of the Baker–Campbell–Hausdorff expansion [T. Yanai and G. K.-L. Chan, J. Chem. Phys. 124, 194106 (2006)]. The resulting linearized MR-DSRG scheme with one- and two-body operators [MR-LDSRG(2)] contains only 39 terms and scales as O(N2NP2NH2) where NH, NP, and N correspond to the number of hole, particle, and total orbitals, respectively. Benchmark MR-LDSRG(2) computations on the hydrogen fluoride and molecular nitrogen binding curve...
CHNS: A case study of turbulence in elastic media

Recent progress in the study of Cahn-Hilliard Navier-Stokes (CHNS) turbulence is summarized. This is an example of elastic turbulence, which can occur in elastic (i.e., self-restoring) media. Such media exhibit memory due to freezing-in laws, as does MHD, which in turn constrains the dynamics. We report new results in the theory of CHNS turbulence in 2D, with special emphasis on the role of structure (i.e., “blob”) formation and its interaction with the dual cascade. The evolution of a concentration gradient in response to a single eddy—analogous to flux expulsion in MHD—is analyzed. Lessons learned are discussed in the context of MHD and other elastic media.
MEMORIES OF MURRAY AND THE QUARK MODEL

Life at Caltech with Murray Gell-Mann in the early 1960's is remembered. Our different paths to quarks, leading to different views of their reality, are described.
Entropy and the Uncertainty Principle

We generalize, improve and unify theorems of Rumin, and Maassen–Uffink about classical entropies associated with quantum density matrices. These theorems refer to the classical entropies of the diagonals of a density matrix in two different bases. Thus, they provide a kind of uncertainty principle. Our inequalities are sharp because they are exact in the high-temperature or semi-classical limit.
Pairing in Nuclei: Exact Solutions

Pairing plays an essential role in describing nuclear spectra and attempts to describe it has a long history in nuclear physics. Many theoretical tools were developed to treat the pairing problem either exactly or at various levels of approximation. In this contribution to the proceedings of a conference honoring the career of Taka Otsuka, recent developments in the exact solutions of the pairing problem are described.
Persistent homology detects curvature

In topological data analysis, persistent homology is used to study the "shape of data". Persistent homology computations are completely characterized by a set of intervals called a bar code. It is often said that the long intervals represent the "topological signal" and the short intervals represent "noise". We give evidence to dispute this thesis, showing that the short intervals encode geometric information. Specifically, we prove that persistent homology detects the curvature of disks from which points have been sampled. We describe a general computational framework for solving inverse problems using the average persistence landscape, a continuous mapping from metric spaces with a probability measure to a Hilbert space. In the present application, the average persistence landscapes of points sampled from disks of constant curvature results in a path in this Hilbert space which may be learned using standard tools from statistical and machine learning.
Strongest postcondition semantics as the formal basis for reverse engineering

Reverse engineering of program code is the process of constructing a higher level abstraction of an implementation in order to facilitate the understanding of a system that may be in a “legacy” or “geriatric” state. Changing architectures and improvements in programming methods, including formal methods in software development and object-oriented programming, have prompted a need to reverse engineer and re-engineer program code. This paper describes the application of the strongest postcondition predicate transformer (sp) as the formal basis for the reverse engineering of imperative program code.
Robust determination of the chemical potential in the pole expansion and selected inversion method for solving Kohn-Sham density functional theory

Fermi operator expansion (FOE) methods are powerful alternatives to diagonalization type methods for solving Kohn-Sham density functional theory (KSDFT). One example is the pole expansion and selected inversion (PEXSI) method, which approximates the Fermi operator by rational matrix functions and reduces the computational complexity to at most quadratic scaling for solving KSDFT. Unlike diagonalization type methods, the chemical potential often cannot be directly read off from the result of a single step of evaluation of the Fermi operator. Hence multiple evaluations are needed to be sequentially performed to compute the chemical potential to ensure the correct number of electrons within a given tolerance. This hinders the performance of FOE methods in practice. In this paper, we develop an efficient and robust strategy to determine the chemical potential in the context of the PEXSI method. The main idea of the new method is not to find the exact chemical potential at each self-consistent-field (SCF) iteration but to dynamically and rigorously update the upper and lower bounds for the true chemical potential, so that the chemical potential reaches its convergence along the SCF iteration. Instead of evaluating the Fermi operator for multiple times sequentially, our method uses a two-level strategy that evaluates the Fermi operators in parallel. In the regime of full parallelization, the wall clock time of each SCF iteration is always close to the time for one single evaluation of the Fermi operator, even when the initial guess is far away from the converged solution. We demonstrate the effectiveness of the new method using examples with metallic and insulating characters, as well as results from ab initio molecular dynamics.
Rejection sampling for tempered Lévy processes

We extend the idea of tempering stable Levy processes to tempering more general classes of Levy processes. We show that the original process can be decomposed into the sum of the tempered process and an independent point process of large jumps. We then use this to set up a rejection sampling algorithm for sampling from the tempered process. A small-scale simulation study is given to help understand the performance of this algorithm.
APOGEE/Kepler Overlap Yields Orbital Solutions for a Variety of Eclipsing Binaries

Spectroscopic Eclipsing Binaries (SEBs) are fundamental benchmarks in stellar astrophysics and today are observed in breathtaking detail by missions like TESS, Kepler, and APOGEE. We develop a methodology for simultaneous analysis of high precision Kepler light curves and high resolution near-IR spectra from APOGEE and present orbital solutions and evolutionary histories for a subset of SEBs within this overlap. Radial velocities extracted from APOGEE spectra using the Broadening Function technique are combined with Kepler light curves and to yield binary orbital solutions. The Broadening Function approach yields more precise radial velocities than the standard Cross-Correlation Function, which in turn yields more precise orbital parameters and enables the identification of tertiary stars. The orbital periods of these seven SEBs range from 4 to 40 days. Four of the systems (KIC 5285607, KIC 6864859, KIC 6778289, and KIC 4285087) are well-detached binaries. The remaining three systems have apparent tertiary companions, but each exhibits two eclipses along with at least one spectroscopically varying component (KIC 6449358, KIC 6131659, and KIC 6781535). Gaia distances are available for four targets which we use to estimate temperatures of both members of these SEBs. We explore evolutionary histories in H-R diagram space and estimate ages for this subset of our sample. Finally, we consider the implications for the formation pathways of close binary systems via interactions with tertiary companions. Our methodology combined with the era of big data and observation overlap opens up the possibility of discovering and analyzing large numbers of diverse SEBs, including those with high flux ratios and those in triple systems.
Analysis of Spent Nuclear Fuel Imaging Using Multiple Coulomb Scattering of Cosmic Muons

Cosmic ray muons passing through matter lose energy from inelastic collisions with electrons and are deflected from nuclei due to multiple Coulomb scattering. The strong dependence of scattering on atomic number Z and the recent developments on position sensitive muon detectors indicate that multiple Coulomb scattering could be an excellent candidate for spent nuclear fuel imaging. Muons present significant advantages over existing monitoring and imaging techniques and can play a central role in monitoring nuclear waste and spent nuclear fuel stored in dense well shielded containers. The main purpose of this paper is to investigate the applicability of multiple Coulomb scattering for imaging of spent nuclear fuel dry casks stored within vertical and horizontal commercial storage dry casks. Calculations of muon scattering were performed for various scenarios, including vertical and horizontal fully loaded dry casks, half loaded dry casks, dry casks with one row of fuel assemblies missing, dry casks with one fuel assembly missing and empty dry casks. Various detector sizes (1.2 m $\times 1.2$ m, 2.4 m $\times 2.4$ m and 3.6 m $\times 3.6$ m) and number of muons ( $10^{5}$ , $5\cdot 10^{5}$ , $10^{6}$ and $10^{7}$ ) were used to assess the effect on image resolution. The Point-of-Closest-Approach (PoCA) algorithm was used for the reconstruction of the stored contents. The results demonstrate that multiple Coulomb scattering can be used to successfully reconstruct the dry cask contents and allow identification of all scenarios with the exception of one fuel assembly missing. In this case, an indication exists that a fuel assembly is not present; however, the resolution of the imaging algorithm was not enough to identify exact location.
Change Detection with Compressive Measurements

Quickest change point detection is concerned with the detection of statistical change(s) in sequences while minimizing the detection delay subject to false alarm constraints. In this letter, the problem of change point detection is studied when the decision maker only has access to compressive measurements. First, an expression for the average detection delay of Shiryaev's procedure with compressive measurements is derived in the asymptotic regime where the probability of false alarm goes to zero. Second, the dependence of the delay on the compression ratio and the signal to noise ratio is explicitly quantified. The ratio of delays with and without compression is studied under various sensing matrix constructions, including Gaussian ensembles and random projections. For a target delay ratio, a sufficient condition on the number of measurements required to meet this objective with prespecified probability is derived.
STEINBERG GROUPS AS AMALGAMS

For any root system and any commutative ring we give a relatively simple presentation of a group related to its Stein- berg group St. This includes the case of innite root systems used in Kac-Moody theory, for which the Steinberg group was dened by Tits and Morita-Rehmann. In many cases our group equals St, giving a presentation with many advantages over the usual presen- tation of St. This equality holds for all spherical root systems, all irreducible ane root systems of rank > 2, and all 3-spherical root systems. When the coecient ring satises a minor condition, the last hypothesis can be relaxed to 2-sphericity. Our presentation is dened in terms of the Dynkin diagram rather than the full root system. It is concrete, with no implicit coecients or signs. It makes manifest the exceptional diagram au- tomorphisms in characteristics 2 and 3, and their generalizations to Kac-Moody groups. And it is a Curtis-Tits style presentation: it is the direct limit of the groups coming from 1- and 2-node sub- diagrams of the Dynkin diagram. Over non-elds this description as a direct limit is new and surprising, even for nite root systems. We use it to show that many Steinberg and Kac-Moody groups over nitely-generated rings are nitely presented.
Real-time solar image classification: Assessing spectral, pixel-based approaches

In order to utilize solar imagery for real-time feature identification and large-scale data science investigations of solar structures, we need maps of the Sun where phenomena, or themes, are labeled. Since solar imagers produce observations every few minutes, it is not feasible to label all images by hand. Here, we compare three machine learning algorithms performing solar image classification using Extreme Ultraviolet (EUV) and Hα images: a maximum likelihood model assuming a single normal probability distribution for each theme from [Space Weather 10(8) : 1–16], a maximum-likelihood model with an underlying Gaussian mixtures distribution, and a random forest model. We create a small database of expert-labeled maps to train and test these algorithms. Due to the ambiguity between the labels created by different experts, a collaborative labeling is used to include all inputs. We find the random forest algorithm performs the best amongst the three algorithms. The advantages of this algorithm are best highlighted in: comparison of outputs to hand-drawn maps; response to short-term variability; and tracking long-term changes on the Sun. Our work indicates that the next generation of solar image classification algorithms would benefit significantly from using spatial structure recognition, compared to only using spectral, pixel-by-pixel brightness distributions.
Shape and Viewpoint Without Keypoints

We present a learning framework that learns to recover the 3D shape, pose and texture from a single image, trained on an image collection without any ground truth 3D shape, multi-view, camera viewpoints or keypoint supervision. We approach this highly under-constrained problem in a “analysis by synthesis” framework where the goal is to predict the likely shape, texture and camera viewpoint that could produce the image with various learned category-specific priors. Our particular contribution in this paper is a representation of the distribution over cameras, which we call “camera-multiplex”. Instead of picking a point estimate, we maintain a set of camera hypotheses that are optimized during training to best explain the image given the current shape and texture. We call our approach Unsupervised Category-Specific Mesh Reconstruction (U-CMR), and present qualitative and quantitative results on CUB, Pascal 3D and new web-scraped datasets. We obtain state-of-the-art camera prediction results and show that we can learn to predict diverse shapes and textures across objects using an image collection without any keypoint annotations or 3D ground truth. Project page: https://shubham-goel.github.io/ucmr.
Non-uniform dependence for Euler equations in Besov spaces

Abstract We prove the non-uniform continuity of the data-to-solution map of the incompressible Euler equations in Besov spaces, B p , q s , where the parameters p , q and s considered here are such that the local existence and uniqueness result holds.