cssi/SciSciGPT-SciSciNet huggingface dataset:
An Analytical Model for Efficient Indoor THz Access Point Deployment

Ultra-densification of user equipment (UE) and access points (APs) are anticipated to take a toll on the future spectrum needs. Higher frequency bands, such as mmWave (30-300GHz) and THz spectrum (0.3-10THz), can be used to cater to the high-throughput needs of ultra-dense networks. These high-frequency bands have a tremendous amount of green-filed contiguous spectrum, ranging in hundreds of GHz. However, these bands, especially the THz bands, face numerous challenges, such as high spreading, absorption, and penetration losses. To combat these challenges, the THz-APs need to be either equipped with high transmit power, high antenna gains (i.e., narrow antenna beams), or limit the communication to short-ranges. All of these factors are bounded due to technical or economic challenges, which will result in a “distance-power dilemma” while deciding on the deployment strategy of THz-APs. In this paper, we present an analytical model to deploy THz-APs in an indoor setting efficiently. We further show through extensive numerical analysis, the optimal number of APs and optimal room length for different blocks of the THz spectrum. Furthermore, these THz-APs need to be efficiently packed to avoid outages due to handoffs, which can add more complexity to the dilemma. To mitigate the packing problem, we propose two solutions over the optimal solution: (a) Radius Increase, and (b) Repeater Assistance, and present an analytical model for each.
Online Continuous DR-Submodular Maximization with Long-Term Budget Constraints.

In this paper, we study a class of online optimization problems with long-term budget constraints where the objective functions are not necessarily concave (nor convex) but they instead satisfy the Diminishing Returns (DR) property. Specifically, a sequence of monotone DR-submodular objective functions $\{f_t(x)\}_{t=1}^T$ and monotone linear budget functions $\{\langle p_t,x \rangle \}_{t=1}^T$ arrive over time and assuming a total targeted budget $B_T$, the goal is to choose points $x_t$ at each time $t\in\{1,\dots,T\}$, without knowing $f_t$ and $p_t$ on that step, to achieve sub-linear regret bound while the total budget violation $\sum_{t=1}^T \langle p_t,x_t \rangle -B_T$ is sub-linear as well. Prior work has shown that achieving sub-linear regret is impossible if the budget functions are chosen adversarially. Therefore, we modify the notion of regret by comparing the agent against a $(1-\frac{1}{e})$-approximation to the best fixed decision in hindsight which satisfies the budget constraint proportionally over any window of length $W$. We propose the Online Saddle Point Hybrid Gradient (OSPHG) algorithm to solve this class of online problems. For $W=T$, we recover the aforementioned impossibility result. However, when $W=o(T)$, we show that it is possible to obtain sub-linear bounds for both the $(1-\frac{1}{e})$-regret and the total budget violation.
Local comparative advantage: Trade costs and the pattern of trade

When there are costs of trade, such as transport or other costs, the pattern of trade may not be well described by the usual measures of comparative advantage, which simply compare a country’s costs or autarky prices to those of the world. Instead, a better comparison takes into account the costs of trade. This paper shows first, in an example, how trade patterns can vary with costs of trade. It then provides restatements of the law of comparative advantage, first in a Ricardian model with trade costs, then extending a 1980 result due to Deardorff and to Dixit and Norman to include trade costs explicitly in a general framework. It uses this latter result to derive two correlations relating trade patterns to measures of comparative advantage that take account of both autarky prices and the costs of trade. Finally, the paper examines the solution to a trade model with product differentiation in order to make the potential role of trade costs more explicit, both algebraically and graphically. With product differentiation either by country or by firm, net trade in an industry, both bilaterally and globally, depends on a country’s costs of both production and trade relative to an index of those costs for other countries.
Toward universal testing of dynamic network models.

Numerous networks in the real world change over time, in the sense that nodes and edges enter and leave the networks. Various dynamic random graph models have been proposed to explain the macroscopic properties of these systems and to provide a foundation for statistical inferences and predictions. It is of interest to have a rigorous way to determine how well these models match observed networks. We thus ask the following goodness of fit question: given a sequence of observations/snapshots of a growing random graph, along with a candidate model M, can we determine whether the snapshots came from M or from some arbitrary alternative model that is well-separated from M in some natural metric? We formulate this problem precisely and boil it down to goodness of fit testing for graph-valued, infinite-state Markov processes and exhibit and analyze a universal test based on non-stationary sampling for a natural class of models.
Prediction of epilepsy development in traumatic brain injury patients from diffusion weighted MRI

Post-traumatic epilepsy (PTE) is a life-long complication of traumatic brain injury (TBI) and is a major public health problem that has an estimated incidence that ranges from 2% -- 50%, depending on the severity of the TBI. Currently, the patho-mechanism that induces epileptogenesis in TBI patients is unclear, and one of the most challenging goals in the epilepsy community is to predict which TBI patients will develop epilepsy. In this work, we used diffusion weighted imaging (DWI) of 14 TBI patients recruited in the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) to measure and analyze fractional anisotropy (FA), obtained from tract-based spatial statistic (TBSS) analysis. Then we used these measurements to train two support vector machine (SVM) models to predict which TBI patients have developed epilepsy. Our approach, tested on these 14 patients with a leave-two-out cross-validation, allowed us to obtain an accuracy of 0.857 ± 0.18 (with a 95% level of confidence), demonstrating it to be potentially promising for the early characterization of PTE.
Root anatomy based on root cross-section image analysis with deep learning

Abstract Aboveground plant efficiency has improved significantly in recent years, and the improvement has led to a steady increase in global food production. The improvement of belowground plant efficiency has potential to further increase food production. However, belowground plant roots are harder to study, due to inherent challenges presented by root phenotyping. Several tools for identifying root anatomical features in root cross-section images have been proposed. However, existing tools are not fully automated and require significant human effort to produce accurate results. To address this limitation, we use a fully automated approach, specifically, the Faster Region-based Convolutional Neural Network (Faster R-CNN), to identify anatomical traits in root cross-section images. By training Faster R-CNN models on root cross-section images, we can detect objects such as root, stele and late metaxylem, and predict rectangular bounding boxes around such objects. Subsequently, the bounding boxes can be used to estimate the root diameter, stele diameter, late metaxylem number, and average diameter. Experimental evaluation using standard object detection metrics, such as intersection-over-union and mean average precision, has shown that the Faster R-CNN models trained on rice root cross-section images can accurately detect root, stele and late metaxylem objects. Furthermore, the results have shown that the measurements estimated based on predicted bounding boxes have small root mean square error when compared with the corresponding ground truth values, suggesting that Faster R-CNN can be used to accurately detect anatomical features. Finally, a comparison with Mask R-CNN, an instance segmentation approach, has shown that the Faster R-CNN network produces overall better results given a small training set. A webserver for performing root anatomy using the Faster R-CNN models trained on rice images, and a link to a GitHub repository containing a copy of the Faster R-CNN code are made available to the research community. The labeled images used for training and evaluating the Faster R-CNN models are also available from the GitHub repository.
The index of nilpotent Lie poset algebras

Abstract We establish combinatorial formulas for the index of a class of matrix Lie algebras whose matrix forms are encoded by strict partial orderings. Our methods are linear algebraic.
mmWave Channel Estimation via Approximate Message Passing with Side Information

This work considers millimeter-wave channel estimation in a setting where parameters of the underlying mmWave channels are varying dynamically over time and there is a single drifting path. In this setting, channel estimates at time block k can be used as side information (SI) when estimating the channel at block k + 1. To estimate channel parameters, we employ an SI-aided (complex) approximate message passing algorithm and compare its performance to a benchmark based on orthogonal matching pursuit.
Buckling Down On Torus Fractures: Has Evolving Evidence Affected Practice?

Purpose: Pediatric torus fractures of the wrist have traditionally been managed with cast immobilization and regularly scheduled radiographic and clinical examinations. Recent evidence supports a ‘minimalist’ approach to these injuries with splint immobilization and limited follow-up. Provider utilization of this strategy has not been re-evaluated. The present study sought to examine the management of these injuries in current practice at a single institution. We hypothesized that aspects of ‘traditional’ management remain common despite the evidence …
An experimentally validated heat and mass transfer model for wax deposition from flowing oil onto a cold surface

A new transport model is proposed for paraffin wax deposition onto a cold finger from flowing wax-containing oils. The model solves transient energy and mass balances simultaneously for a reversible first-order kinetic rate for precipitation of pseudo-single-component wax, and the effects of yield stress using a critical solid wax concentration to withstand flow-induced stress at the deposit-fluid interface, Cpi. The model can predict the time evolution of the deposit thickness, and the spatial and temporal evolution of temperature and wax concentration and was validated using experiments involving a cylindrical cold finger. We found that for oils with Cpi close to zero, the deposit thickness growth is dominated by heat transfer. However, mass transfer cannot be neglected as diffusion of wax into the deposit continues to take place even after the deposit has stopped growing. For oils with non-zero Cpi, the deposit growth is slow and accompanied by occasional sloughing.
Active cloaking in Stokes flows via reinforcement learning

Hydrodynamic signatures at the Stokes regime, pertinent to motility of micro-swimmers, have a long-range nature. This implies that movements of an object in such a viscosity-dominated regime can be felt tens of body-lengths away and significantly alter dynamics of the surrounding environment. Here, we devise a systematic methodology to actively cloak swimming objects within any arbitrarily crowded suspension of micro-swimmers. Specifically, our approach is to conceal the target swimmer throughout its motion using cooperative flocks of swimming agents equipped with adaptive decision-making intelligence. Through a reinforcement learning algorithm, the cloaking agents experientially learn an optimal adaptive behaviour policy in the presence of flow-mediated interactions. This artificial intelligence enables them to dynamically adjust their swimming actions, so as to optimally form and robustly retain any desired arrangement around the moving object without disturbing it from its original path. Therefore, the presented active cloaking approach not only is robust against disturbances, but also is non-invasive to motion of the cloaked object. We then further generalize the proposed approach and demonstrate how our cloaking agents can be readily used, in any region of interest, to realize hydrodynamic invisibility cloaks around any number of arbitrary intruders.
Surveillance, stigma & sociotechnical design for HIV

Online dating and hookup platforms have fundamentally changed people’s day-to-day practices of sex and love — but exist in tension with older social and medicolegal norms. This is particularly the case for people with HIV, who are frequently stigmatized, surveilled, ostracized, and incarcerated because of their status. Efforts to make intimate platforms “work” for HIV frequently focus on user-to-user interactions and disclosure of one’s HIV status but elide both the structural forces at work in regulating sex and the involvement of the state in queer lives. In an effort to foreground these forces and this involvement, we analyze the approaches that intimate platforms have taken in designing for HIV disclosure through a content analysis of 50 current platforms. We argue that the implicit reinforcement of stereotypes about who HIV is or is not a concern for, along with the failure to consider state practices when designing for data disclosure, opens up serious risks for HIV-positive and otherwise marginalized people. While we have no panacea for the tension between disclosure and risk, we point to bottom-up, communal, and queer approaches to design as a way of potentially making that tension easier to safely navigate.
Multi-Model Resilient Observer under False Data Injection Attacks

In this paper, we present the concept of boosting the resiliency of optimization-based observers for cyber-physical systems (CPS) using auxiliary sources of information. Due to the tight coupling of physics, communication and computation, a malicious agent can exploit multiple inherent vulnerabilities in order to inject stealthy signals into the measurement process. The problem setting considers the scenario in which an attacker strategically corrupts portions of the data in order to force wrong state estimates which could have catastrophic consequences. The goal of the proposed observer is to compute the true states in-spite of the adversarial corruption. In the formulation, we use a measurement prior distribution generated by the auxiliary model to refine the feasible region of a traditional compressive sensing-based regression problem. A constrained optimization-based observer is developed using $l_{1}$ -minimization scheme. Numerical experiments show that the solution of the resulting problem recovers the true states of the system. The developed algorithm is evaluated through a numerical simulation example of the IEEE 14-bus system.
Generating transition states of isomerization reactions with deep learning

Lack of quality data and difficulty generating these data hinder quantitative understanding of reaction kinetics. Specifically, conventional methods to generate transition state structures are deficient in speed, accuracy, or scope. We describe a novel method to generate three-dimensional transition state structures for isomerization reactions using reactant and product geometries. Our approach relies on a graph neural network to predict the transition state distance matrix and a least squares optimization to reconstruct the coordinates based on which entries of the distance matrix the model perceives to be important. We feed the structures generated by our algorithm through a rigorous quantum mechanics workflow to ensure the predicted transition state corresponds to the ground truth reactant and product. In both generating viable geometries and predicting accurate transition states, our method achieves excellent results. We envision workflows like this, which combine neural networks and quantum chemistry calculations, will become the preferred methods for computing chemical reactions.
Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images

Existing interactive visualization tools for deep learning are mostly applied to the training, debugging, and refinement of neural network models working on natural images. However, visual analytics tools are lacking for the specific application of x-ray image classification with multiple structural attributes. In this paper, we present an interactive system for domain scientists to visually study the multiple attributes learning models applied to x-ray scattering images. It allows domain scientists to interactively explore this important type of scientific images in embedded spaces that are defined on the model prediction output, the actual labels, and the discovered feature space of neural networks. Users are allowed to flexibly select instance images, their clusters, and compare them regarding the specified visual representation of attributes. The exploration is guided by the manifestation of model performance related to mutual relationships among attributes, which often affect the learning accuracy and effectiveness. The system thus supports domain scientists to improve the training dataset and model, find questionable attributes labels, and identify outlier images or spurious data clusters. Case studies and scientists feedback demonstrate its functionalities and usefulness.
Density estimation on a network

Abstract A novel approach is proposed for density estimation on a network. Nonparametric density estimation on a network is formulated as a nonparametric regression problem by binning. Nonparametric regression using local polynomial kernel-weighted least squares have been studied rigorously, and its asymptotic properties make it superior to kernel estimators such as the Nadaraya–Watson estimator. When applied to a network, the best estimator near a vertex depends on the amount of smoothness at the vertex. Often, there are no compelling reasons to assume that a density will be continuous or discontinuous at a vertex, hence a data driven approach is proposed. To estimate the density in a neighborhood of a vertex, a two-step procedure is proposed. The first step of this pretest estimator fits a separate local polynomial regression on each edge using data only on that edge, and then tests for equality of the estimates at the vertex. If the null hypothesis is not rejected, then the second step re-estimates the regression function in a small neighborhood of the vertex, subject to a joint equality constraint. Since the derivative of the density may be discontinuous at the vertex, a piecewise polynomial local regression estimate is used to model the change in slope. The special case of local piecewise linear regression is studied in detail and the leading bias and variance terms are derived using weighted least squares theory. The proposed approach will remove the bias near a vertex that has been noted for existing methods, which typically do not allow for discontinuity at vertices. For a fixed network, the proposed method scales sub-linearly with sample size and it can be extended to regression and varying coefficient models on a network. The working of the proposed model is demonstrated by simulation studies and applications to a dendrite network dataset.
REVISITING WITH CHANDRA THE SCALING RELATIONS OF THE X-RAY EMISSION COMPONENTS (BINARIES, NUCLEI, AND HOT GAS) OF EARLY-TYPE GALAXIES

We have selected a sample of 30 normal (non-cD) early-type galaxies, for all of which optical spectroscopy is available and which have been observed with Chandra to a depth such as to ensure the detection of bright low-mass X-ray binaries (LMXBs) with LX > 1038 erg s–1. This sample includes a larger fraction of gas-poor galaxies than previously studied samples and covers a wide range of stellar luminosity (LK ), velocity dispersion (σ*), globular cluster specific frequency (SN ), and stellar age. We derive X-ray luminosities (or upper limits) from the different significant X-ray components of these galaxies: nuclei, detected and undetected LMXBs, coronally active binaries (ABs), cataclysmic variables (CVs), and hot gas. The ABs and CVs contribution is estimated from the LX -LK scaling relation of M31 and M32. The contribution of undetected LMXBs is estimated both by fitting the spectra of the unresolved X-ray emission and by extrapolating the LMXB X-ray luminosity function. On average, the X-ray luminosity of LMXBs is a factor of ~10 higher than that of ABs+CVs. By spectral fitting the emission (also considering gas emission in the regions of point sources), we estimate the contribution of the hot gas. We find our sample equally divided among galaxies with LX (gas) > LX (LMXB), LX (ABCV) ≤ LX (gas) ≤ LX (LMXB), and LX (gas) 240 km s–1, where it may be related to the analogous correlation found in cD galaxies and groups/clusters. However, the gas-poor galaxies with the shallowest potentials (σ* < 200 km s–1) also follow this relation, contrary to the expected anti-correlation in a simple outflow/wind scenario. Galaxies with intermediate values of σ* instead tend to have the same kT, while LX (gas) spans a factor of ~20; among these galaxies, we find a moderate, positive correlation between LX (gas) and the average stellar age, possibly suggesting a transition from halo retention to outflow caused by rejuvenated star formation associated with recent mergers.
Transport of CO in Protoplanetary Disks: Consequences of Pebble Formation, Settling, and Radial Drift

Current models of (exo)planet formation often rely on a large influx of so-called `pebbles' from the outer disk into the planet formation region. In this paper, we investigate how the formation of pebbles in the cold outer regions of protoplanetary disks and their subsequent migration to the inner disk can alter the gas-phase CO distribution both interior and exterior to the midplane CO snowline. By simulating the resulting CO abundances in the midplane as well as the warm surface layer, we identify observable signatures of large-scale pebble formation and migration that can be used as `smoking guns' for these important processes. Specifically, we find that after $1\mathrm{~Myr}$, the formation and settling of icy pebbles results in the removal of up to $80\%$ of the CO vapor in the warm ($T>22\mathrm{~K}$) disk layers outside the CO snowline, while the radial migration of pebbles results in the generation of a plume of CO vapor interior the snowline, increasing the CO abundance by a factor ${\sim}2{-}6$ depending on the strength of the turbulence and the sizes of the individual pebbles. The absence of this plume of CO vapor in young nearby disks could indicate efficient conversion of CO into a more refractory species, or a reduction in the radial mass flux of pebbles by, for example, disk inhomogeneities or early planetesimal formation.
A Lagrangian method for reactive transport with solid/aqueous chemical phase interaction

Abstract A significant drawback of Lagrangian (particle-tracking) reactive transport models has been their inability to properly simulate interactions between solid and liquid chemical phases, such as dissolution and precipitation reactions. This work addresses that problem by implementing a mass-transfer algorithm between mobile and immobile sets of particles that allows aqueous species of reactant that are undergoing transport to interact with stationary solid species. This mass-transfer algorithm is demonstrated to solve the diffusion equation for an arbitrarily small level of diffusion and thus does not introduce any spurious mixing. The algorithm can be combined with random walks to simulate the desired total level of diffusion in a reactive transport system.
MADNESS IN VECTOR SPACES

We consider maximal almost disjoint families of block subspaces of countable vector spaces, focusing on questions of their size and definability. We prove that the minimum infinite cardinality of such a family cannot be decided in ZFC and that the “spectrum” of cardinalities of mad families of subspaces can be made arbitrarily large, in analogy to results for mad families on ω. We apply the author’s local Ramsey theory for vector spaces [32] to give partial results concerning their definability.
A new class of electrically tunable metamaterial terahertz modulators

Switchable metamaterials offer unique solutions for efficiently manipulating electromagnetic waves, particularly for terahertz waves, which has been difficult since naturally occurring materials rarely respond to terahertz frequencies controllably. However, few terahertz modulators demonstrated to date exhibit simultaneously low attenuation and high modulation depth. In this letter we propose a new class of electrically-tunable terahertz metamaterial modulators employing metallic frequency-selective-surfaces (FSS) in conjunction with capacitively-tunable layers of electrons, promising near 100% modulation depth and < 15% attenuation. The fundamental departure in our design from the prior art is tuning enabled by self-gated electron layers that is independent from the metallic FSS. Our proposal is applicable to all possible electrically tunable elements including graphene, Si, MoS2, oxides etc, thus opening up myriad opportunities for realizing high performance switchable metamaterials over an ultra-wide terahertz frequency range.
Proper Motions and Shock Wave Dynamics in the HH 7-11 Stellar Jet

We have used the Hubble Space Telescope (HST) to acquire new broadband and narrowband images of the optical line emission and red continuum associated with the HH 7-11 stellar jet in the NGC 1333 star formation region. Combining the new narrowband images of Hα, [O i] λ6300, and [S ii] λ6716 allows us to measure electron densities and excitations at each point in the outflow with the spatial resolution of HST, while the I-band image traces out the boundary of the cavity evacuated by the outflow. Comparing these images with those taken ~20 yr ago yields high-precision proper motions for all the HH objects in the outflow. HH 11 is a bullet-like clump and emerges from the exciting source SVS 13A toward the Earth at 24° to the line of sight. In contrast, HH 8 and HH 10 consist of two rings of shocked gas that show no bulk proper motions, even though the emitting gas is blueshifted. The HH 8 rings are expanding with time. These shocks mark places where ambient material located along the path of the jet redirects the outflow. HH 7 consists of multiple shells and emits strongly in H2 in what appears to be a terminal bow shock for the outflow, implying that the jet has yet to fully break out of its nascent cloud core. The jet largely fragments into clumps by the time it reaches HH 7. As in the case of HH 110, deflection from ambient material plays a key role in producing observable shock waves in the HH 7-11 outflow.
A Dolbeault-Hilbert complex for a variety with isolated singular points

Given a compact Hermitian complex space with isolated singular points, we construct a Dolbeault-type Hilbert complex whose cohomology is isomorphic to the cohomology of the structure sheaf. We show that the corresponding K-homology class coincides with the one constructed by Baum, Fulton and MacPherson.
A NOTE ON THE ZAKHAROV-SHABAT TOPOLOGICAL MODEL

In this note I discuss some features of the topological theory obtained from the Zakharov-Shabat (or general hierarchy, and comment on some possible physical and/or mathematical interpretations of it.
Exact expressions for the mobility and electrophoretic mobility of a weakly charged sphere in a simple electrolyte

We present (asymptotically) exact expressions for the mobility and electrophoretic mobility of a weakly charged spherical particle in a 1 : 1 electrolyte solution. This is done by analytically solv ...
Gravitational lensing and the variability of G

The four observables associated with gravitational lensing of distant quasars by intervening galaxies-image splittings, relative amplifications, time delays, and optical depths-provide separate measures of the strength of the gravitational constant G at cosmological distances. These allow one, in principle, to factor out unknown lensing parameters to directly probe the variation of G over cosmological time. We estimate constraints on Ġ which may be derivable by this method both now and in the future
Coherent Quantum Channel Discrimination

This paper introduces coherent quantum channel discrimination as a coherent version of conventional quantum channel discrimination. Coherent channel discrimination is phrased here as a quantum interactive proof system between a verifier and a prover, wherein the goal of the prover is to distinguish two channels called in superposition in order to distill a Bell state at the end. The key measure considered here is the success probability of distilling a Bell state, and I prove that this success probability does not increase under the action of a quantum super-channel, thus establishing this measure as a fundamental measure of channel distinguishability. Also, I establish some bounds on this success probability in terms of the success probability of conventional channel discrimination. Finally, I provide an explicit semi-definite program that can compute the success probability.
Cosmic strings and primordial black holes

Cosmic strings and primordial black holes (PBHs) commonly and naturally form in many scenarios describing the early universe. Here we show that if both cosmic strings and PBHs are present, their interaction leads to a range of interesting consequences. At the time of their formation, the PBHs get attached to the strings and influence their evolution, leading to the formation of black-hole-string networks and commonly to the suppression of loop production in a range of redshifts. Subsequently, reconnections within the network give rise to small nets made of several black holes and connecting strings. The number of black holes in the network as well as the stability of the nets depend on the topological properties of the strings. The nets oscillate and shrink exponentially due to the emission of gravitational waves. This leads to potentially observable string-driven mergers of PBHs. The strings can keep PBHs from galactic halos, making the current bounds on PBHs not generally applicable. Alternatively, heavy PBHs can drag low-tension strings into the centers of galaxies. The superconducting strings can appear as radio filaments pointing towards supermassive black holes.
Compressive Deconvolution in Random Mask Imaging

We investigate the problem of reconstructing signals from a subsampled convolution of their modulated versions and a known filter. The problem is studied as applies to a specific imaging architecture that relies on spatial phase modulation by randomly coded “masks.” The diversity induced by the random masks is deemed to improve the conditioning of the deconvolution problem while maintaining sampling efficiency. We analyze a linear model of the imaging system, where the joint effect of the spatial modulation, blurring, and spatial subsampling is represented concisely by a measurement matrix. We provide a bound on the conditioning of this measurement matrix in terms of the number of masks $K$ , the dimension (i.e., the pixel count) of the scene image $L$ , and certain characteristics of the blurring kernel and subsampling operator. The derived bound shows that the stable deconvolution is possible with high probability even if the number of masks (i.e., $K$ ) is as small as $\frac{L\log L}{N}$ , meaning that the total number of (scalar) measurements is within a logarithmic factor of the image size. Furthermore, beyond a critical number of masks determined by the extent of blurring and subsampling, use of every additional mask improves the conditioning of the measurement matrix. We also consider a more interesting scenario where the target image is known to be sparse. We show that under mild conditions on the blurring kernel, with high probability the measurement matrix is a restricted isometry when the number of masks is within a logarithmic factor of the sparsity of the scene image. Therefore, the scene image can be reconstructed using any of the well-known sparse recovery algorithms such as the basis pursuit. The bound on the required number of masks grows linearly in sparsity of the scene image but logarithmically in its ambient dimension. The bound provides a quantitative view of the effect of the blurring and subsampling on the required number of masks, which is critical for designing efficient imaging systems.
MAKE SUPER-EARTHS, NOT JUPITERS: ACCRETING NEBULAR GAS ONTO SOLID CORES AT 0.1 AU AND BEYOND

Close-in super-Earths having radii 1-4 R {sub ⊕} may possess hydrogen atmospheres comprising a few percent by mass of their rocky cores. We determine the conditions under which such atmospheres can be accreted by cores from their parent circumstellar disks. Accretion from the nebula is problematic because it is too efficient: we find that 10 M {sub ⊕} cores embedded in solar metallicity disks tend to undergo runaway gas accretion and explode into Jupiters, irrespective of orbital location. The threat of runaway is especially dire at ∼0.1 AU, where solids may coagulate on timescales orders of magnitude shorter than gas clearing times; thus nascent atmospheres on close-in orbits are unlikely to be supported against collapse by planetesimal accretion. The time to runaway accretion is well approximated by the cooling time of the atmosphere's innermost convective zone, whose extent is controlled by where H{sub 2} dissociates. Insofar as the temperatures characterizing H{sub 2} dissociation are universal, timescales for core instability tend not to vary with orbital distance—and to be alarmingly short for 10 M {sub ⊕} cores. Nevertheless, in the thicket of parameter space, we identify two scenarios, not mutually exclusive, that can reproduce the preponderance of percent-by-mass atmospheres for super-Earths atmore » ∼0.1 AU, while still ensuring the formation of Jupiters at ≳ 1 AU. Scenario (a): planets form in disks with dust-to-gas ratios that range from ∼20× solar at 0.1 AU to ∼2× solar at 5 AU. Scenario (b): the final assembly of super-Earth cores from mergers of proto-cores—a process that completes quickly at ∼0.1 AU once begun—is delayed by gas dynamical friction until just before disk gas dissipates completely. Both scenarios predict that the occurrence rate for super-Earths versus orbital distance, and the corresponding rate for Jupiters, should trend in opposite directions, as the former population is transformed into the latter: as gas giants become more frequent from ∼1 to 10 AU, super-Earths should become more rare.« less
Higgsed Gauge-flation

We study a variant of Gauge-flation where the gauge symmetry is spontaneously broken by a Higgs sector. We work in the Stueckelberg limit and demonstrate that the dynamics remain (catastrophically) unstable for cases where the gauge field masses satisfy γ < 2, where γ = g 2 ψ 2/H 2, g is the gauge coupling, ψ is the gauge field vacuum expectation value, and H is the Hubble rate. We compute the spectrum of density fluctuations and gravitational waves, and show that the model can produce observationally viable spectra. The background gauge field texture violates parity, resulting in a chiral gravitational wave spectrum. This arises due to an exponential enhancement of one polarization of the spin-2 fluctuation of the gauge field. Higgsed Gauge-flation can produce observable gravitational waves at inflationary energy scales well below the GUT scale.
Neutrino mixing and cosmology

We review the consequences of neutrino mixing in the early universe. For both active-sterile mixing or mixing between three active neutrinos only, the consequences of oscillations depend crucially upon the size of the universe's lepton number (relic neutrino asymmetry.)
Resolvent-analysis-based design of airfoil separation control

We use resolvent analysis to design active control techniques for separated flows over a NACA 0012 airfoil. Spanwise-periodic flows over the airfoil at a chord-based Reynolds number of . Near the leading edge, localized unsteady thermal actuation is introduced in an open-loop manner with two tunable parameters of actuation frequency and spanwise wavelength. To provide physics-based guidance for the effective choice of these control input parameters, we conduct global resolvent analysis on the baseline turbulent mean flows to identify the actuation frequency and wavenumber that provide large perturbation energy amplification. The present analysis also considers the use of a temporal filter to limit the time horizon for assessing the energy amplification to extend resolvent analysis to unstable base flows. We incorporate the amplification and response mode from resolvent analysis to provide a metric that quantifies momentum mixing associated with the modal structure. This metric is compared to the results from a large number of three-dimensional large-eddy simulations of open-loop controlled flows. With the agreement between the resolvent-based metric and the enhancement of aerodynamic performance found through large-eddy simulations, we demonstrate that resolvent analysis can predict the effective range of actuation frequency as well as the global response to the actuation input. We believe that the present resolvent-based approach provides a promising path towards mean flow modification by capitalizing on the dominant modal mixing.
Supernovae and the Galactic Ecosystem

Supernovae are the dominant source of stellar feedback, which plays an important role in regulating galaxy formation and evolution. While this feedback process is still quite uncertain, it is probably not due to individual supernova remnants as commonly observed. Most supernovae likely take place in low-density, hot gaseous environments, such as superbubbles and galactic bulges, and typically produce no long-lasting bright remnants. I review recent observational and theoretical work on the impact of such supernovae on galaxy ecosystems, particularly on hot gas in superbubbles and galactic spheroids.
On Ruelle’s Construction of the Thermodynamic Limit for the Classical Microcanonical Entropy

In 1969 Ruelle published his construction of the thermodynamic limit, in the sense of Fisher, for the quasi-microcanonical entropy density of classical Hamiltonian N-body systems with stable and tempered pair interactions. Here, “quasi-microcanonical” refers to the fact that he discussed the entropy defined with a regularized microcanonical measure as ln (N!−1∫χ{ℰ−▵ℰ<H<ℰ}d6NX) rather than defined with the proper microcanonical measure as ln (N!−1∫δ(ℰ−H) d6NX). Replacing δ(ℰ−H) by χ{ℰ−▵ℰ<H<ℰ} seems to have become the standard procedure for rigorous treatments of the microcanonical ensemble hence. In this note we make a very elementary technical observation to the effect that Ruelle’s proof (still based on regularization) does establish the thermodynamic limit also for the entropy density defined with the proper microcanonical measure. We also show that with only minor changes in the proof the regularization of δ(ℰ−H) is actually not needed at all.
On relative property (T) and Haagerup’s property

Abstract. Consider the following three properties for countable discrete groups G: (1) G has an infinite subgroup with relative property (T), (2) the group von Neumann algebra L(G) has a diffuse von Neumann subalgebra with relative property (T) and (3) G does not have Haagerup’s property. It is clear that (1) implies (2) and (2) implies (3). I will prove that both of the converses are false. This is joint work with Ionut Chifan.
Positivity, Rational Schur Functions, Blaschke Factors, and Other Related Results in the Grassmann Algebra

We begin a study of Schur analysis in the setting of the Grassmann algebra when the latter is completed with respect to the 1-norm. We focus on the rational case. We start with a theorem on invertibility in the completed algebra, and define a notion of positivity in this setting. We present a series of applications pertaining to Schur analysis, including a counterpart of the Schur algorithm, extension of matrices and rational functions. Other topics considered include Wiener algebra, reproducing kernels Banach modules, and Blaschke factors.
MULTIVARIATE ANALYSIS AND JACOBI ENSEMBLES: LARGEST EIGENVALUE, TRACY-WIDOM LIMITS AND RATES OF CONVERGENCE.

Abstract Let A and B be independent, central Wishart matrices in p variables with common covariance and having m and n degrees of freedom, respectively. The distribution of the largest eigenvalue of (A + B)(-1)B has numerous applications in multivariate statistics, but is difficult to calculate exactly. Suppose that m and n grow in proportion to p. We show that after centering and, scaling, the distribution is approximated to second-order, O(p(-2/3)), by the Tracy-Widom law. The results are obtained for both complex and then real-valued data by using methods of random matrix theory to study the largest eigenvalue of the Jacobi unitary and orthogonal ensembles. Asymptotic approximations of Jacobi polynomials near the largest zero play a central role.
Systematic Crosstalk Mitigation for Superconducting Qubits via Frequency-Aware Compilation

One of the key challenges in current Noisy Intermediate-Scale Quantum (NISQ) computers is to control a quantum system with high-fidelity quantum gates. There are many reasons a quantum gate can go wrong – for superconducting transmon qubits in particular, one major source of gate error is the unwanted crosstalk between neighboring qubits due to a phenomenon called frequency crowding. We motivate a systematic approach for understanding and mitigating the crosstalk noise when executing near-term quantum programs on superconducting NISQ computers. We present a general software solution to alleviate frequency crowding by systematically tuning qubit frequencies according to input programs, trading parallelism for higher gate fidelity when necessary. The net result is that our work dramatically improves the crosstalk resilience of tunable-qubit, fixed-coupler hardware, matching or surpassing other more complex architectural designs such as tunable-coupler systems. On NISQ benchmarks, we improve worst-case program success rate by 13.3x on average, compared to existing traditional serialization strategies.
Periodic traveling interfacial hydroelastic waves with or without mass

We study the motion of an interface between two irrotational, incompressible fluids, with elastic bending forces present; this is the hydroelastic wave problem. We prove a global bifurcation theorem for the existence of families of spatially periodic traveling waves on infinite depth. Our traveling wave formulation uses a parameterized curve, in which the waves are able to have multivalued height. This formulation and the presence of the elastic bending terms allow for the application of an abstract global bifurcation theorem of “identity plus compact” type. We furthermore perform numerical computations of these families of traveling waves, finding that, depending on the choice of parameters, the curves of traveling waves can either be unbounded, reconnect to trivial solutions, or end with a wave which has a self-intersection. Our analytical and computational methods are able to treat in a unified way the cases of positive or zero mass density along the sheet, the cases of single-valued or multivalued height, and the cases of single-fluid or interfacial waves.
Calculation of Optimized Apodizers for a Terrestrial Planet Finder Coronagraphic Telescope

ABSTRACT One of two approaches to implementing NASA’s Terrestrial Planet Finder is to build a space telescope that utilizes the techniques of coronagraphy and apodization to suppress diffraction and image exoplanets. We present a method for calculation of a telescope’s apodizer that suppresses the sidelobes of the image of a star so as to optimally detect an Earth‐like planet. Given the shape of a telescope’s aperture and given a search region for a detector, we solve an integral equation to determine an amplitude modulation (an apodizer) that suppresses the star’s energy in the focal plane search region. The method is quite general and yields as special cases the product apodizer reported by Nisenson & Papaliolios and the prolate spheroidal apodizer of Kasdin et al. and Aime et al. We show computer simulations of the apodizers and the corresponding point‐spread functions for various aperture‐detector configurations.
A Detailed Model Grid for Solid Planets from 0.1 through 100 Earth Masses

This article describes a new grid for the mass-radius relation of three-layer exoplanets within the mass range of 0.1-100 M⊕. The three layers are: Fe (-phase of iron), MgSiO3 (including both the perovskite phase, post-perovskite phase, and its dissociation at ultrahigh pressures), and H2O (including Ices Ih, III, V, VI, VII, X, and the superionic phase along the melting curve). We discuss the current state of knowledge about the equations of state (EOS) that influence these calculations and the improvements used in the new grid. For the two-layer model, we demonstrate the utility of contours on the mass-radius diagrams. Given the mass and radius input, these contours can be used to quickly determine the important physical properties of a planet including its p0 (central pressure), p1/p0 (core-mantle boundary pressure over central pressure), CMF (core mass fraction) or CRF (core radius fraction). For the three-layer model, a curve segment on the ternary diagram represents all possible relative mass proportions of the three layers for a given mass-radius input. These ternary diagrams are tabulated with the intent to make comparison to observations easier. How the presence of Fe in the mantle affects the mass-radius relations is also discussed in a separate section. A dynamic and interactive tool to characterize and illustrate the interior structure of exoplanets built upon models in this article is available online.
Imaging of Three Possible Low-redshift Analogs to High-redshift Compact Red Galaxies

As part of a larger program to identify and characterize possible low-redshift analogs to massive compact red galaxies found at high redshift, we have examined the morphologies of three low-redshift compact galaxies drawn from the sample of Trujillo et al. Using deeper and higher resolution images, we have found faint and relatively extensive outer structures in addition to the compact cores identified in the earlier measurements. One object appears to have a small companion that may be involved in an ongoing minor merger of the sort that could be responsible for building up the outer parts of these galaxies. The ages of the dominant stellar populations in these objects are found to be around 2-4 Gyr, in good agreement with the previous estimates. The presence of diffuse outer structures in these galaxies indicates that truly compact and massive red galaxies are exceedingly rare at low redshift. The relatively young stellar populations suggest that the accretion of the extensive outer material must occur essentially universally on relatively short timescales of a few billion years or less. These results confirm and extend previous suggestions that the driving mechanism behind the size evolution of high-redshift compact galaxies cannot be highly stochastic processes such as major mergers, which would inevitably leave a non-negligible fraction of survivors at low redshift.