cssi/SciSciGPT-SciSciNet huggingface dataset:
Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm

In response to anticipated shortages of ventilators caused by the COVID-19 pandemic, many organizations have designed low-cost emergency ventilators. Many of these devices are pressure-cycled pneumatic ventilators, which are easy to produce but often do not include the sensing or alarm features found on commercial ventilators. This work reports a low-cost, easy-to-produce electronic sensor and alarm system for pressure-cycled ventilators that estimates clinically useful metrics such as pressure and respiratory rate and sounds an alarm when the ventilator malfunctions. A low-complexity signal processing algorithm uses a pair of nonlinear recursive envelope trackers to monitor the signal from an electronic pressure sensor connected to the patient airway. The algorithm, inspired by those used in hearing aids, requires little memory and performs only a few calculations on each sample so that it can run on nearly any microcontroller.
Simulation pipeline for traffic evacuation in urban areas and emergency traffic management policy improvements through case studies

Abstract Traffic evacuation plays a critical role in saving lives in devastating disasters such as hurricanes, wildfires, floods, etc. An ability to evaluate evacuation plans in advance for these rare events, including identifying traffic flow bottlenecks, improving traffic management policies, and understanding the robustness of the traffic management policy are critical for emergency management. Given the rareness of such events and the corresponding lack of real data, traffic simulation provides a flexible and versatile approach for such scenarios, and furthermore allows dynamic interaction with the simulated evacuation. In this paper, we build a traffic simulation pipeline to explore the above problems, covering many aspects of evacuation, including map creation, demand generation, vehicle behavior, bottleneck identification, traffic management policy improvement, and results analysis. We apply the pipeline to two cases studies in California. The first is Paradise, which was destroyed by a large wildfire in 2018 and experienced catastrophic traffic jams during the evacuation. The second is Mill Valley, which has high risk of wildfire and potential traffic issues since the city is situated in a narrow valley.
A soft X-ray map of the Perseus cluster of galaxies

We present a 0.5--3 keV X-ray map of the Perseus cluster of galaxies. The map, combining profiles obtained by the Columbia and Berkeley groups, was derived using the ART mapping algorithm. The map shows a region (9' x 15') of strong emission centered near NGC 1275 plus a new feature: a highly elongated emission region which lies along the line of bright galaxies that dominates the core of the cluster. The data are compared with various models that include point and diffuse sources. One model which adequately represents the data is the superposition of a point source at NGC 1275 and an isothermal ellipsoid resulting from the bremsstrahlung emission of cluster gas. The ellipsoid has a major core radius of 20'.5 and a minor core radius of 5'.5 consistent with the values obtained from galaxy counts. All acceptable models provide evidence for a compact source (<3' FMHM) at NGC 1275 containing 25 ( +- 10) percent of the total emission. Since the diffuse X-ray and radio components have radically different morphologies, it is unlikely that the emissions arise from a common source as proposed in inverse Compton models. (AIP)
Learning from trading activity in laboratory security markets with higher-order uncertainty

Abstract This experiment examines forecasting behavior under varying information conditions to assess the extent to which traders in security markets incorporate information in trading activity to resolve fundamental uncertainty and to resolve higher-order uncertainty. Fundamental uncertainty refers to a trader's uncertainty about liquidation value of the asset while higher-order uncertainty refers to uncertainty about the beliefs of other traders about liquidation value of the asset. I find that in an experimental security market, subjects incorporate the information contained in trading activity to the extent of about 88% to resolve both fundamental uncertainty and higher-order uncertainty. When a piece of public information (the information content of which is comparable to the information contained in trading activity) is made available to the subjects, then also the incorporation of available information remains in about the same range as reported with the first set of experiments. The inability and / or refusal to incorporate 100% of the information contained in trading activity is almost entirely attributable to an inability and / or refusal to Bayesian update. The refusal to Bayesian update is consistent with several other theories and allows post-trading forecasts to be significantly correlated with pre-trading forecasts.
Feature Transformation and Simulation of Short Term Price Variability in Reinforcement Learning for Portfolio Management

Reinforcement learning has been shown capable of learning optimal strategies from imperfect information environments in order to create robust decision support systems. This paper shows that two automatic feature transformation techniques - Bayesian recurrent neural network (BRNN) for modelling future price trends and Generative Adversarial Networks (GANs) for modelling short-term realistic price variability - are able to improve the performance of reinforcement learning agents in solving portfolio management problem effectively, when measured in terms of increasing profitability and reducing risks.
Chemoselective α-Sulfidation of Amides Using Sulfoxide Reagents.

The direct α-sulfidation of tertiary amides using sulfoxide reagents under electrophilic amide activation conditions is described. Employing convenient and readily available reagents, selective fun...
Pre-HAART CD4+ T-lymphocytes as biomarkers of post-HAART immune recovery in HIV-infected children with or without TB co-infection.

Infection with the Human Immunodeficiency Virus (HIV) dramatically increases the risk of developing active tuberculosis (TB). Several studies have indicated that co-infection with TB increases the risk of HIV progression and death. Sub-Saharan Africa bears the brunt of these dual epidemics, with about 2.4 million HIV-infected people living with TB. The main objective of our study was to assess whether the pre-HAART CD4+ T-lymphocyte counts and percentages could serve as biomarkers for post-HAART treatment immune-recovery in HIV-positive children with and without TB co-infection. The data analyzed in this retrospective study were collected from a cohort of 305 HIV-infected children being treated with HAART. A Lehmann family of ROC curves were used to assess the diagnostic performance of pre- HAART treatment CD4+ T-lymphocyte count and percentage as biomarkers for post-HAART immune recovery. The Kaplan–Meier estimator was used to compare differences in post-HAART recovery times between patients with and without TB co-infection. We found that the diagnostic performance of both pre-HARRT treatment CD4+ T-lymphocyte count and percentage was comparable and achieved accuracies as high as 74%. Furthermore, the predictive capability of pre-HAART CD4+ T-lymphocyte count and percentage were slightly better in TB-negative patients. Our analyses also indicate that TB-negative patients have a shorter recovery time compared to the TB-positive patients. Pre-HAART CD4+ T-lymphocyte count and percentage are stronger predictors of immune recovery in TB-negative pediatric patients, suggesting that TB co-infection complicates the treatment of HIV in this cohort. These findings suggest that the detection and treatment of TB is essential for the effectiveness of HAART in HIV-infected pediatric patients.
PhD Forum: Enabling Autonomic IoT for Smart Urban Services

The development of autonomous cyber-physical systems (CPS) and advances towards the fifth generation (5G) of wireless technology is promising to revolutionize many industry verticals such as healthcare, transportation, energy, retail services, building automation, education, etc., leading to the realization of the smart city paradigm. The Internet of things (IoT), enables powerful and unprecedented capabilities for intelligent and autonomous operation. We leverage ideas from network science, optimization & decision theory, incentive mechanism design, and data science/machine learning to achieve key design goals such as efficiency, security & resilience, and economics in IoT-enabled urban systems.
Macroeconomic Factors Do Influence Aggregate Stock Returns

Stock market returns are significantly correlated with inflation and money growth. The impact of real macroeconomic variables on aggregate equity returns has been difficult to establish, perhaps because their effects are neither linear nor time invariant. We estimate a GARCH model of daily equity returns, where realized returns and their conditional volatility depend on 17 macro series' announcements. We find six candidates for priced factors: three nominal (CPI, PPI, and a Monetary Aggregate) and three real (Balance of Trade, Employment Report, and Housing Starts). Popular measures of overall economic activity, such as Industrial Production or GNP are not represented. Copyright 2002, Oxford University Press.
A novel topology-guided attack and its countermeasure towards secure logic locking

The outsourcing of the design and manufacturing of integrated circuits (ICs) in the current horizontal semiconductor integration flow has posed various security threats due to the presence of untrusted entities, such as overproduction of ICs, sale of out-of-specification/rejected ICs, and piracy of Intellectual Properties (IPs). Consequently, logic locking emerged as one of the prominent design for trust techniques. Unfortunately, these locking techniques are now inclined to achieve complete Boolean satisfiability (SAT) resiliency after the seminal work published in Subramanyan et al. (in: International Symposium on Hardware 907 Oriented Security and Trust, pp 137–143, 2015). In this paper, we propose a novel oracle-less attack that is based on the topological analysis of the locked netlist even though it is SAT-resilient. The attack relies on identifying and constructing unit functions with a hypothesis key to be searched in the entire netlist to find its replica. The proposed graph search algorithm efficiently finds the duplicate functions in the netlist, making it a self-referencing attack. This proposed attack is extremely efficient and can determine the secret key within a few minutes. We have also proposed a countermeasure to make the circuit resilient against this topology-guided attack to progress toward a secure logic locking technique.
Synthesis of Cyclopentenones with Reverse Pauson-Khand Regiocontrol via Ni-Catalyzed C-C Activation of Cyclopropanone.

A formal [3 + 2] cycloaddition between cyclopropanone and alkynes via Ni-catalyzed C–C bond activation has been developed, where 1-sulfonylcyclopropanols are employed as key precursors of cycloprop...
Control Hardware-in-the-loop for Voltage Controlled Inverters with Unbalanced and Non-linear Loads in Stand-alone Photovoltaic (PV) Islanded Microgrids

Unbalanced and nonlinear loads connected to micro grids (MG) with local distributed energy resources (DERs) are two of the leading causes of power quality problems. Nonlinear loads introduce voltage and current harmonics, and single phase loads can cause voltage and current imbalances in a three phase network. This paper presents a hierarchical control scheme for voltage controlled photovoltaic (PV) inverters with unbalanced and nonlinear loads in micro-grids. The hierarchical control consists of primary control, voltage compensation control (VCC) and a DC voltage regulator (VR). The primary control scheme controls active and reactive power sharing and the VCC regulates the unbalanced voltage and harmonics distortion. The effectiveness of the scheme is verified using Opal-RT real-time simulation and experimentally using control hardware-in-the-loop. The voltage distortion at point of common coupling (PCC) decreased from 6.38 percent to 1.91 percent after compensation, while the unbalanced and harmonic load are shared proportionally among the DG units.
Efficient optimal reconstruction of linear fields and band-powers from cosmological data

Author(s): Horowitz, B; Seljak, U; Aslanyan, G | Abstract: We present an efficient implementation of Wiener filtering of real-space linear field and optimal quadratic estimator of its power spectrum Band-powers. We first recast the field reconstruction into an optimization problem, which we solve using quasi-Newton optimization. We then recast the power spectrum estimation into the field marginalization problem, from which we obtain an expression that depends on the field reconstruction solution and a determinant term. We develop a novel simulation based method for the latter. We extend the simulations formalism to provide the covariance matrix for the power spectrum. We develop a flexible framework that can be used on a variety of cosmological fields and present results for a variety of test cases, using simulated examples of projected density fields, projected shear maps from galaxy lensing, and observed Cosmic Microwave Background (CMB) temperature anisotropies, with a wide range of map incompleteness and variable noise. For smaller cases where direct numerical inversion is possible, we show that our solution matches that created by direct Wiener Filtering at a fraction of the overall computation cost. Even more significant reduction of computational is achieved by this implementation of optimal quadratic estimator due to the fast evaluation of the Hessian matrix. This technique allows for accurate map and power spectrum reconstruction with complex masks and nontrivial noise properties.
The invariant measures of some infinite interval exchange maps

We classify the locally finite ergodic invariant measures of certain infinite interval exchange transformations (IETs). These transformations naturally arise from return maps of the straight-line flow on certain translation surfaces, and the study of the invariant measures for these IETs is equivalent to the study of invariant measures for the straight-line flow in some direction on these translation surfaces. For the surfaces and directions to which our methods apply, we can characterize the locally finite ergodic invariant measures of the straight-line flow in a set of directions of Hausdorff dimension larger than 1 . We promote this characterization to a classification in some cases. For instance, when the surfaces admit a cocompact action by a nilpotent group, we prove each ergodic invariant measure for the straight-line flow is a Maharam measure, and we describe precisely which Maharam measures arise. When the surfaces under consideration are of finite area, the straight-line flows in the directions we understand are uniquely ergodic. Our methods apply to translation surfaces admitting multitwists in a pair of cylinder decompositions in nonparallel directions. 37E05; 37E20, 37A40
Protons in High Density Neutron Matter

We discuss the possible implication of the recent predictions of two new properties of high momentum distribution of nucleons in asymmetric nuclei for neutron star dynamics. The first property is about the approximate scaling relation between proton and neutron high momentum distributions weighted by their relative fractions (xp and xn) in the nucleus. The second is the existence of inverse proportionality of the high momentum distribution strength of protons and neutrons to xp/n. Based on these predictions we model the high momentum distribution functions for asymmetric nuclei and demonstrate that it describes reasonably well the high momentum characteristics of light nuclei. We also extrapolate our results to heavy nuclei as well as infinite nuclear matter and calculate the relative fractions of protons and neutrons with momenta above kF. Our results indicate that for neutron stars starting at three nuclear saturation densities the protons with xp = 1/9 will populate mostly the high momentum tail of the momentum distribution while only 2% of the neutrons will do so. Such a situation may have many implications for different observations of neutron stars which we discuss.
The habitable zone of Kepler-16: impact of binarity and climate models

We continue to investigate the binary system Kepler-16, consisting of a K-type main-sequence star, a red dwarf and a circumbinary Saturnian planet. As part of our study, we describe the system's habitable zone based on different climate models. We also report on stability investigations for possible Earth-mass Trojans while expanding a previous study by B. L. Quarles and collaborators given in 2012. For the climate models, we carefully consider the relevance of the system's parameters. Furthermore, we pursue new stability simulations for the Earth-mass objects starting along the orbit of Kepler-16b. The eccentricity distribution as obtained prefers values close to circular, whereas the inclination distribution remains flat. The stable solutions are distributed near the co-orbital Lagrangian points, thus enhancing the plausibility that Earth-mass Trojans might be able to exist in the Kepler-16(AB) system.
Chromatic adaptation transform by spectral reconstruction

A color appearance model (CAM) is an advanced colorimetric tool used to predict color appearance under a wide variety of viewing conditions. A chromatic adaptation transform (CAT) is an integral part of a CAM. Its role is to predict "corresponding colors," that is, a pair of colors that have the same color appearance when viewed under different illuminants, after partial or full adaptation to each illuminant. Modern CATs perform well when applied to a limited range of illuminant pairs and a limited range of source (test) colors. However, they can fail if operated outside these ranges. For imaging applications, it is important to have a CAT that can operate on any real color and illuminant pair without failure. This paper proposes a new CAT that does not operate on the standard von Kries model of adaptation. Instead it relies on spectral reconstruction and how these reconstructions behave with respect to different illuminants. It is demonstrated that the proposed CAT is immune to some of the limitations of existing CATs (such as producing colors with negative tristimulus values). The proposed CAT does not use established empirical corresponding-color datasets to optimize performance, as most modern CATs do, yet it performs as well as or better than the most recent CATs when tested against the corresponding-color datasets. This increase in robustness comes at the expense of additional complexity and computational effort. If robustness is of prime importance, then the proposed method may be justifiable.
Tracking Neptune’s Migration History through High-perihelion Resonant Trans-Neptunian Objects

Recently, Sheppard et al. presented the discovery of seven new trans-Neptunian objects with moderate eccentricities, perihelia beyond 40 au, and semimajor axes beyond 50 au. Like the few previously known objects on similar orbits, these objects' semimajor axes are just beyond the Kuiper Belt edge and clustered around Neptunian mean motion resonances (MMRs). These objects likely obtained their observed orbits while trapped within MMRs, when the Kozai?Lidov mechanism raised their perihelia and weakened Neptune's dynamical influence. Using numerical simulations that model the production of this population, we find that high-perihelion objects near Neptunian MMRs can constrain the nature and timescale of Neptune's past orbital migration. In particular, the population near the 3:1 MMR (near 62 au) is especially useful due to its large population and short dynamical evolution timescale. If Neptune finishes migrating within ~100 Myr or less, we predict that over 90% of high-perihelion objects near the 3:1 MMR will have semimajor axes within 1 au of each other, very near the modern resonance's center. On the other hand, if Neptune's migration takes ~300 Myr, we expect ~50% of this population to reside in dynamically fossilized orbits over ~1 au closer to the Sun than the modern resonance. We highlight 2015 KH162 as a likely member of this fossilized 3:1 population. Under any plausible migration scenario, nearly all high-perihelion objects in resonances beyond the 4:1 MMR (near 76 au) reach their orbits well after Neptune stops migrating and compose a recently generated, dynamically active population.
Complexity of random smooth functions on the high-dimensional sphere

We analyze the landscape of general smooth Gaussian functions on the sphere in dimension N, when N is large. We give an explicit formula for the asymptotic complexity of the mean number of critical points of finite and diverging index at any level of energy and for the mean Euler characteristic of level sets. We then find two possible scenarios for the bottom landscape, one that has a layered structure of critical values and a strong correlation between indexes and critical values and another where even at levels below the limiting ground state energy the mean number of local minima is exponentially large. We end the paper by discussing how these results can be interpreted in the language of spin glasses models.
Gauge B–L model of radiative neutrino mass with multipartite dark matter

We propose an extension of the Standard Model of quarks and leptons to include gauge B–L symmetry with an exotic array of neutral fermion singlets for anomaly cancellation. With the addition of suitable scalars also transforming under U(1)B–L, this becomes a model of radiative seesaw neutrino mass with possible multipartite dark matter. If leptoquark fermions are added, necessarily also transforming under U(1)B–L, the diphoton excess at 750 GeV, recently observed at the Large Hadron Collider, may also be explained.
PRODUCT DECOMPOSITION OF PERIODIC FUNCTIONS IN QUANTUM SIGNAL PROCESSING

In some embodiments, one or more unitary-valued functions are generated by a classical computer generating using projectors with a predetermined number of significant bits. A quantum computing device is then configured to implement the one or more unitary-valued functions. In further embodiments, a quantum circuit description for implementing quantum signal processing that decomposes complex-valued periodic functions is generated by a classical computer, wherein the generating further includes representing approximate polynomials in a Fourier series with rational coefficients. A quantum computing device is then configured to implement a quantum circuit defined by the quantum circuit description.
On McMullen's and other inequalities for the Thurston norm of link complements

In a recent paper, McMullen showed an inequality between the Thurston norm and the Alexander norm of a 3-manifold. This generalizes the well-known fact that twice the genus of a knot is bounded from below by the degree of the Alexander polynomial. We extend the Bennequin inequality for links to an inequality for all points of the Thurston norm, if the manifold is a link complement. We compare these two inequalities on two classes of closed braids. In an additional section we discuss a conjectured inequality due to Morton for certain points of the Thurston norm. We prove Morton's conjecture for closed 3-braids. AMS Classication 57M25; 57M27, 57M50
Wavelet Analysis of the New Solar Neutrino Capture Rate Data for the Homestake Experiment

Wavelet analysis offers an alternative to Fourier based time- series analysis and is particularly useful when spectral features are time dependent. We analyze the solar neutrino capture rate of the radiochemical Homestake chlorine experiment with abbreviated Morlet wavelets, using Foster's (AJ, 111,1709(1996)) rescaled wavelet technique. We emphasize the complementarity of wavelet analysis to Fourier analysis. Wavelet analysis confirms the results of previously undertaken Fourier analysis. The Homestake data seem to contain a harmonic content with periodicities of 4.76 yr, 1.89 yr, 0.85 yr, and 0.51 yr. Wavelet analysis reveals that the 4.76 yr and 1.89 yr periods show an almost constant behavior over the 25 yr Homestake data record, while the 0.85 yr and 0.51 yr periods exhibit a transient phenomenon. The analysis does not show strong evidence for a period of the solar 11 yr cycle.
Beta decays and non-standard interactions in the LHC era

Abstract We consider the role of precision measurements of beta decays and light meson semi-leptonic decays in probing physics beyond the Standard Model in the LHC era. We describe all low-energy charged-current processes within and beyond the Standard Model using an effective field theory framework. We first discuss the theoretical hadronic input which in these precision tests plays a crucial role in setting the baseline for new physics searches. We then review the current and upcoming constraints on the various non-standard operators from the study of decay rates, spectra, and correlations in a broad array of light-quark systems. We finally discuss the interplay with LHC searches, both within models and in an effective theory approach. Our discussion illustrates the independent yet complementary nature of precision beta decay measurements as probes of new physics, showing them to be of continuing importance throughout the LHC era.
Effects of self-calibration of intrinsic alignment on cosmological parameter constraints from future cosmic shear surveys

Intrinsic alignments (IA) of galaxies have been recognized as one of the most serious contaminants to weak lensing. These systematics need to be isolated and mitigated in order for ongoing and future lensing surveys to reach their full potential. The IA self-calibration (SC) method was shown in previous studies to be able to reduce the GI contamination by up to a factor of 10 for the 2-point and 3-point correlations. The SC method does not require the assumption of an IA model in its working and can extract the GI signal from the same photo-z survey offering the possibility to test and understand structure formation scenarios and their relationship to IA models. In this paper, we study the effects of the IA SC mitigation method on the precision and accuracy of cosmological parameter constraints from future cosmic shear surveys LSST, WFIRST and Euclid. We perform analytical and numerical calculations to estimate the loss of precision and the residual bias in the best fit cosmological parameters after the self-calibration is performed. We take into account uncertainties from photometric redshifts and the galaxy bias. We find that the confidence contours are slightly inflated from applying the SC method itself while a significant increase is due to the inclusion of the photo-z uncertainties. The bias of cosmological parameters is reduced from several-σ, when IA is not corrected for, to below 1-σ after SC is applied. These numbers are comparable to those resulting from applying the method of marginalizing over IA model parameters despite the fact that the two methods operate very differently. We conclude that implementing the SC for these future cosmic-shear surveys will not only allow one to efficiently mitigate the GI contaminant but also help to understand their modeling and link to structure formation.
Nucleosynthesis in Hot and Dense Media

We study the finite temperature and density effects on beta decay rates to compute their contributions to nucleosynthesis. QED type corrections to beta decay from the hot and dense background are estimated in terms of the statistical corrections to the self-mass of an electron. For this purpose, we re-examine the hot and dense background contributions to the electron mass and compute its effect to the beta decay rate, helium yield, energy density of the universe as well as the change in neutrino temperature from the first order contribution to the self-mass of electrons during these processes. We explicitly show that the thermal contribution to the helium abundance at T = m of a cooling universe (0.045 percent) is higher than the corresponding contribution to helium abundance of a heating universe (0.031 percent) due to the existence of hot fermions before the beginning of nucleosynthesis and their absence after the nucleosynthesis, in the early universe. Thermal contribution to helium abundance was a simple quadratic function of temperature, before and after the nucleosynthesis. However, this quadratic behavior was not the same before the decoupling temperature due to weak interactions; so the nucleosynthesis did not even start before the universe had cooled down to the neutrino decoupling temperatures and QED became a dominant theory in the presence of a high concentration of charged fermions. It is also explicitly shown that the chemical potential in the core of supermassive and superdense stars affect beta decay and their helium abundance but the background contributions depend on the ratio between temperature and chemical potential and not the chemical potential or temperature only. We calculate the hot and dense background contributions for m = T = μ. It has been noticed that temperature plays a role in regulating parameter in an extremely dense systems. Therefore, for extremely dense systems, temperature has to be large enough to get the expected value of helium production in the stellar cores.
Power Generation from a Radiative Thermal Source Using a Large-Area Infrared Rectenna

Converting infrared radiation from a thermal source into electrical power, via a $t\phantom{\rule{0}{0ex}}h\phantom{\rule{0}{0ex}}e\phantom{\rule{0}{0ex}}r\phantom{\rule{0}{0ex}}m\phantom{\rule{0}{0ex}}o\phantom{\rule{0}{0ex}}p\phantom{\rule{0}{0ex}}h\phantom{\rule{0}{0ex}}o\phantom{\rule{0}{0ex}}t\phantom{\rule{0}{0ex}}o\phantom{\rule{0}{0ex}}v\phantom{\rule{0}{0ex}}o\phantom{\rule{0}{0ex}}l\phantom{\rule{0}{0ex}}t\phantom{\rule{0}{0ex}}a\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}c$ device, is important for energy harvesting and micropower applications. The authors present a large-area broadband infrared antenna-coupled tunnel-diode rectifier that directly converts infrared radiation into electrical power. The antenna resonantly enhances and couples IR light to an extreme-subwavelength tunnel barrier, leading to large induced photon-assisted tunneling currents. Peak electrical power is observed when the load resistance is matched to that of the diode. This direct conversion of thermal IR to electrical power using a scalable CMOS process seems quite promising.
The Buffer Gas Beam: An Intense, Cold, and Slow Source for Atoms and Molecules

Beams of atoms and molecules are stalwart tools for spectroscopy and studies of collisional processes. The supersonic expansion technique can create cold beams of many species of atoms and molecules. However, the resulting beam is typically moving at a speed of 300−600 m s^(−1) in the laboratory frame and, for a large class of species, has insufficient flux (i.e., brightness) for important applications. In contrast, buffer gas beams can be a superior method in many cases, producing cold and relatively slow atoms and molecules (see Figure 1) in the laboratory frame with high brightness and great versatility. There are basic differences between supersonic and buffer gas cooled beams regarding particular technological advantages and constraints. At present, it is clear that not all of the possible variations on the buffer gas method have been studied. In this review, we will present a survey of the current state of the art in buffer gas beams, and explore some of the possible future directions that these new methods might take.
Building MSSM flux vacua

We construct N=1 and N=0 chiral four-dimensional vacua of flux compactification in Type IIB string theory. These vacua have the common features that they are free of tadpole instabilities (both NSNS and RR) even for models with N=0 supersymmetry. In addition, the dilaton/complex structure moduli are stabilised and the supergravity background metric is warped. We present an example in which the low energy spectrum contains the MSSM spectrum with three generations of chiral matter. In the N=0 models, the background fluxes which stabilise the moduli also induce soft supersymmetry breaking terms in the gauge and chiral sectors of the theory, while satisfying the equation of motion. We also discuss some phenomenological features of these three generation MSSM flux vacua. Our techniques apply to other closed string backgrounds as well and, in fact, also allow to find new N=1 D-brane models which were believed not to exist. Finally, we discuss in detail the consistency conditions of these flux compactifications. Cancellation of K-theory charges puts additional constraints on the consistency of the models, which render some chiral D-brane models in the literature inconsistent.
Iterative Updating of Model Error for Bayesian Inversion

In computational inverse problems, it is common that a detailed and accurate forward model is approximated by a computationally less challenging substitute. The model reduction may be necessary to meet constraints in computing time when optimization algorithms are used to find a single estimate, or to speed up Markov chain Monte Carlo (MCMC) calculations in the Bayesian framework. The use of an approximate model introduces a discrepancy, or modeling error, that may have a detrimental effect on the solution of the ill-posed inverse problem, or it may severely distort the estimate of the posterior distribution. In the Bayesian paradigm, the modeling error can be considered as a random variable, and by using an estimate of the probability distribution of the unknown, one may estimate the probability distribution of the modeling error and incorporate it into the inversion. We introduce an algorithm which iterates this idea to update the distribution of the model error, leading to a sequence of posterior distributions that are demonstrated empirically to capture the underlying truth with increasing accuracy. Since the algorithm is not based on rejections, it requires only limited full model evaluations. We show analytically that, in the linear Gaussian case, the algorithm converges geometrically fast with respect to the number of iterations when the data is finite dimensional. For more general models, we introduce particle approximations of the iteratively generated sequence of distributions; we also prove that each element of the sequence converges in the large particle limit under a simplifying assumption. We show numerically that, as in the linear case, rapid convergence occurs with respect to the number of iterations. Additionally, we show through computed examples that point estimates obtained from this iterative algorithm are superior to those obtained by neglecting the model error.
Spectral fluctuations in the Sachdev-Ye-Kitaev model

We present a detailed quantitative analysis of spectral correlations in the Sachdev-Ye-Kitaev (SYK) model. We find that the deviations from universal Random Matrix Theory (RMT) behavior are due to a small number of long-wavelength fluctuations (of the order of the number of Majorana fermions N) from one realization of the ensemble to the next one. These modes can be parameterized effectively in terms of Q-Hermite orthogonal polynomials, the main contribution being due to scale fluctuations for which we give a simple analytical estimate. Our numerical results for N = 32 show that only the lowest eight polynomials are needed to eliminate the nonuniversal part of the spectral fluctuations. The covariance matrix of the coefficients of this expansion can be obtained analytically from low-order double-trace moments. We evaluate the covariance matrix of the first six moments and find that it agrees with the numerics. We also analyze the spectral correlations in terms of a nonlinear σ-model, which is derived through a Fierz transformation, and evaluate the one and two-point spectral correlation functions to two-loop order. The wide correlator is given by the sum of the universal RMT result and corrections whose lowest-order term corresponds to scale fluctuations. However, the loop expansion of the σ-model results in an ill-behaved expansion of the resolvent, and it gives universal RMT fluctuations not only for q = 4 or higher even q-body interactions, but also for the q = 2 SYK model albeit with a much smaller Thouless energy while the correct result in this case should have been Poisson statistics. In our numerical studies we analyze the number variance and spectral form factor for N = 32 and q = 4. We show that the quadratic deviation of the number variance for large energies appears as a peak for small times in the spectral form factor. After eliminating the long-wavelength fluctuations, we find quantitative agreement with RMT up to an exponentially large number of level spacings for the number variance or exponentially short times in the case of the spectral form factor.
Black holes at the centers of nearby dwarf galaxies

Using a distance-limited portion of the Sloan Digital Sky Survey (SDSS) Data Release 7, we have identified 28 active galactic nuclei (AGNs) in nearby ( Mpc) low-mass, low-luminosity dwarf galaxies. The accreting objects at the galaxy centers are expected to be intermediate-mass black holes (IMBHs) with . The AGNs were selected using several optical emission-line diagnostics after careful modeling of the continuum present in the spectra. We have limited our survey to objects with spectral characteristics similar to those of Seyfert nuclei, excluding emission-line galaxies with ambiguous spectra that could be powered by stellar processes. Thus, as a set, the host galaxies in our sample are the least massive objects in the very local universe certain to contain central black holes. Our sample is dominated by narrow-line (type 2) AGNs, and it appears to have a much lower fraction of broad-line objects than that observed for luminous, optically selected Seyfert galaxies. Given our focus on the nearest objects included in the SDSS, our survey is more sensitive to low-luminosity emission than previous optical searches for AGNs in low-mass galaxies. The [O iii] luminosities of the Seyfert nuclei in our sample have a median value of and extend down to . Using published data for broad-line IMBH candidates, we have derived an [O iii] bolometric correction of , which is significantly lower than values obtained for high-luminosity AGNs. Applying this correction to our sample, we obtain minimum black hole mass estimates that fall mainly in the 103 ?104 range, which is roughly where the predicted mass functions for different black hole seed formation scenarios overlap the most. In the stellar mass range that includes the bulk of the AGN host galaxies in our sample, we derive a lower limit on the AGN fraction of a few percent, indicating that active nuclei in dwarf galaxies are not as rare as previously thought.
Rapid field excursions and the inflationary tensor spectrum

We consider the effects of fields with suddenly changing mass on the inflationary power spectra. In this context, when a field χ becomes light, it will be excited. This process contributes to the tensor power spectrum. We compute these effects in a gauge-invariant manner, where we use a novel analytical method for evaluating the corrections to the tensor spectrum due to χ excitations. In the case of a scalar field, we show that the net impact on the tensors is small as long as the perturbative expansion is valid. Thus, in these scenarios, measurement of tensor modes is still in one-to-one correspondence with the Hubble scale.
HIGH-RESOLUTION LINEAR POLARIMETRIC IMAGING FOR THE EVENT HORIZON TELESCOPE

Images of the linear polarizations of synchrotron radiation around active galactic nuclei (AGNs) highlight their projected magnetic field lines and provide key data for understanding the physics of accretion and outflow from supermassive black holes. The highest-resolution polarimetric images of AGNs are produced with Very Long Baseline Interferometry (VLBI). Because VLBI incompletely samples the Fourier transform of the source image, any image reconstruction that fills in unmeasured spatial frequencies will not be unique and reconstruction algorithms are required. In this paper, we explore some extensions of the Maximum Entropy Method (MEM) to linear polarimetric VLBI imaging. In contrast to previous work, our polarimetric MEM algorithm combines a Stokes I imager that only uses bispectrum measurements that are immune to atmospheric phase corruption, with a joint Stokes Q and U imager that operates on robust polarimetric ratios. We demonstrate the effectiveness of our technique on 7 and 3 mm wavelength quasar observations from the VLBA and simulated 1.3 mm Event Horizon Telescope observations of Sgr A* and M87. Consistent with past studies, we find that polarimetric MEM can produce superior resolution compared to the standard CLEAN algorithm, when imaging smooth and compact source distributions. As an imaging framework, MEM is highly adaptable, allowing a range of constraints on polarization structure. Polarimetric MEM is thus an attractive choice for image reconstruction with the EHT.
Why Study Noise Due to Two Level Systems: A Suggestion for Experimentalists

Noise is often considered to be a nuisance. Here we argue that it can be a useful probe of fluctuating two level systems in glasses. It can be used to: (1) shed light on whether the fluctuations are correlated or independent events; (2) determine if there is a low temperature glass or phase transition among interacting two level systems, and if the hierarchical or droplet model can be used to describe the glassy phase; and (3) find the lower bound of the two level system relaxation rate without going to ultralow temperatures. Finally we point out that understanding noise due to two level systems is important for technological applications such as quantum qubits that use Josephson junctions.
Propagation of a squeezed optical field in a medium with superluminal group velocity.

We investigated the propagation of a squeezed optical field, generated via the polarization self-rotation effect, with a sinusoidally modulated degree of squeezing through an atomic medium with anomalous dispersion. We observed the advancement of the signal propagating through a resonant Rb vapor compared to the reference signal, propagating in air. The measured advancement time grew linearly with atomic density, reaching a maximum of 11±1 μs, which corresponded to a negative group velocity of vg≈−7,000 m/s. We also confirmed that the increasing advancement was accompanied by a reduction of output squeezing levels due to optical losses, in good agreement with theoretical predictions.
Floquet-Engineered Enhancement of Coherence Times in a Driven Fluxonium Qubit

In the last two decades the development of superconducting qubits has yielded tremendous improvement, with coherence times increasing over five orders of magnitude. Theory and experiment have shown that $1/f$ noise is currently the limiting factor for qubit coherence in state-of-the-art devices. Here the authors use a qubit's Floquet states to store quantum information, mitigating $1/f$ flux noise and achieving a 40-fold improvement in coherence time. This experimental demonstration solves a longstanding, critical problem in the field, as it provides a promising approach for dynamically suppressing the ubiquitous $1/f$ noise in quantum devices.
Light-Front Holography, Color Confinement, and Supersymmetric Features of QCD

Light-Front Quantization—Dirac’s “Front Form”—provides a physical, frame-independent formalism for hadron dynamics and structure. Observables such as structure functions, transverse momentum distributions, and distribution amplitudes are defined from the hadronic light-front wavefunctions. One obtains new insights into the hadronic spectrum, light-front wavefunctions, and the functional form of the QCD running coupling in the nonperturbative domain using light-front holography—the duality between the front form and AdS5, the space of isometries of the conformal group. In addition, superconformal algebra leads to remarkable supersymmetric relations between mesons and baryons of the same parity. The mass scale $${\kappa}$$ underlying confinement and hadron masses can be connected to the parameter $${\Lambda_{\overline {MS}}}$$ in the QCD running coupling by matching the nonperturbative dynamics, as described by the effective conformal theory mapped to the light-front and its embedding in AdS space, to the perturbative QCD regime. The result is an effective coupling defined at all momenta. This matching of the high and low momentum transfer regimes determines a scale Q 0 which sets the interface between perturbative and nonperturbative hadron dynamics. The use of Q 0 to resolve the factorization scale uncertainty for structure functions and distribution amplitudes, in combination with the principle of maximal conformality for setting the renormalization scales, can greatly improve the precision of perturbative QCD predictions for collider phenomenology. The absence of vacuum excitations of the causal, frame-independent front form vacuum has important consequences for the cosmological constant. I also discuss evidence that the antishadowing of nuclear structure functions is non-universal; i.e., flavor dependent, and why shadowing and antishadowing phenomena may be incompatible with the momentum and other sum rules for nuclear parton distribution functions.
Time-variable linear polarization as a probe of the physical conditions in the compact jets of blazars

A single measurement of linear polarization of a nonthermal source provides direct information about the mean direction and level of ordering of the magnetic field. Monitoring of the polarization in blazars, combined with millimeter-wave VLBI imaging in both total and polarized intensity, has the potential to determine the geometry of the magnetic field. This is a key probe of the physical processes in the relativistic jet, such as ordered field components, turbulence, magnetic reconnections, magnetic collimation and acceleration of the jet flow, particle acceleration, and radiative processes that produce extremely luminous, highly variable nonthermal emission. Well-sampled monitoring observations of multi-waveband flux and radio-optical polarization of blazars show a variety of behavior. In some cases, the observed polarization patterns appear systematic, while in others randomness dominates. Explanations involve helical magnetic fields, turbulence, and perhaps particle acceleration that depends on the angle between the magnetic field and shock fronts that might be present. Simulations from the author's TEMZ model, with turbulent plasma crossing a standing conical shock in the jet, show that a mixture of turbulent and toroidal magnetic field can produce the level of polarization variability that is observed, even when the two field components are roughly equal.
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

We investigate the representation power of graph neural networks in the semi-supervised node classification task under heterophily or low homophily, i.e., in networks where connected nodes may have different class labels and dissimilar features. Many popular GNNs fail to generalize to this setting, and are even outperformed by models that ignore the graph structure (e.g., multilayer perceptrons). Motivated by this limitation, we identify a set of key designs -- ego- and neighbor-embedding separation, higher-order neighborhoods, and combination of intermediate representations -- that boost learning from the graph structure under heterophily. We combine them into a graph neural network, H2GCN, which we use as the base method to empirically evaluate the effectiveness of the identified designs. Going beyond the traditional benchmarks with strong homophily, our empirical analysis shows that the identified designs increase the accuracy of GNNs by up to 40% and 27% over models without them on synthetic and real networks with heterophily, respectively, and yield competitive performance under homophily.