cssi/SciSciGPT-SciSciNet huggingface dataset:
A hybrid approach for using programming exercises in introductory physics

Incorporating computer programming exercises into introductory physics is a delicate task that involves a number of choices that may have an effect on student learning. We present a “hybrid” approach that speaks to a number of common concerns regarding cognitive load which arise when using programming exercises in introductory physics classes where many students are absolute beginner programmers. This “hybrid” approach provides the student with a highly interactive web-based visualization, not unlike a PhET or Physlet interactive, but importantly the student is shown only the subset of the code where the initial conditions are set and the system variables are evolved. We highlight results from a coding activity that resembles the classic game Asteroids. The goals of this activity are to show how a simple 1D code can be modified into a 2D code, and to reinforce ideas about the relationship between force, velocity, and acceleration vectors. Survey results from four semesters of introductory physics classes at the Ohio State University's Marion campus, in which a high percentage of the students are weak or absolute beginner programmers, provide evidence that most students can complete coding tasks without severe difficulty. Other survey results are promising for future work where conceptual learning will be assessed in a direct way using metrics like the Animated Force Concept Inventory [Dancy and Beichner, Phys. Rev. Spec. Top. Phys. Educ. 2, 010104 (2006)]. The exercise highlighted here and others from our group are available for general use at http://compadre.org/PICUP.Incorporating computer programming exercises into introductory physics is a delicate task that involves a number of choices that may have an effect on student learning. We present a “hybrid” approach that speaks to a number of common concerns regarding cognitive load which arise when using programming exercises in introductory physics classes where many students are absolute beginner programmers. This “hybrid” approach provides the student with a highly interactive web-based visualization, not unlike a PhET or Physlet interactive, but importantly the student is shown only the subset of the code where the initial conditions are set and the system variables are evolved. We highlight results from a coding activity that resembles the classic game Asteroids. The goals of this activity are to show how a simple 1D code can be modified into a 2D code, and to reinforce ideas about the relationship between force, velocity, and acceleration vectors. Survey results from four semesters of introductory physics classes ...
On the Search for Quasar Light Echoes

The UV radiation from a quasar leaves a characteristic pattern in the distribution of ionized hydrogen throughout the surrounding space. This pattern or light echo propagates through the intergalactic medium at the speed of light, and can be observed by its imprint on the Lyα forest spectra of background sources. As the echo persists after the quasar has switched off, it offers the possibility of searching for dead quasars, and constraining their luminosities and lifetimes. We outline a technique to search for and characterize these light echoes. To test the method, we create artificial Lyα forest spectra from cosmological simulations at z = 3, apply light echoes and search for them. We show how the simulations can also be used to quantify the significance level of any detection. We find that light echoes from the brightest quasars could be found in observational data. With absorption-line spectra of 100 redshift z ~ 3–3.5 quasars or galaxies in a 1 deg2 area, we expect that ~10 echoes from quasars with B-band luminosities LB = 3 × 1045 ergs−1 exist that could be found at 95% confidence, assuming a quasar lifetime of ~107 yr. Even a null result from such a search would have interesting implications for our understanding of quasar luminosities and lifetimes.
An infinite swampland of U(1) charge spectra in 6D supergravity theories

We analyze the anomaly constraints on 6D supergravity theories with a single abelian U(1) gauge factor. For theories with charges restricted to q = ±1, ±2 and no tensor multiplets, anomaly-free models match those models that can be realized from F-theory compactifications almost perfectly. For theories with tensor multiplets or with larger charges, the F-theory constraints are less well understood. We show, however, that there is an infinite class of distinct massless charge spectra in the “swampland” of theories that satisfy all known quantum consistency conditions but do not admit a realization through F-theory or any other known approach to string compactification. We also compare the spectra of charged matter in abelian theories with those that can be realized from breaking nonabelian SU(2) and higher rank gauge symmetries.
A Nutritional Label for Rankings

Algorithmic decisions often result in scoring and ranking individuals to determine credit worthiness, qualifications for college admissions and employment, and compatibility as dating partners. While automatic and seemingly objective, ranking algorithms can discriminate against individuals and protected groups, and exhibit low diversity. Furthermore, ranked results are often unstable -- small changes in the input data or in the ranking methodology may lead to drastic changes in the output, making the result uninformative and easy to manipulate. Similar concerns apply in cases where items other than individuals are ranked, including colleges, academic departments, or products. Despite the ubiquity of rankers, there is, to the best of our knowledge, no technical work that focuses on making rankers transparent. In this demonstration we present Ranking Facts, a Web-based application that generates a "nutritional label" for rankings. Ranking Facts is made up of a collection of visual widgets that implement our latest research results on fairness, stability, and transparency for rankings, and that communicate details of the ranking methodology, or of the output, to the end user. We will showcase Ranking Facts on real datasets from different domains, including college rankings, criminal risk assessment, and financial services.
Phenomenological constraints on the Higgs as pseudo-Goldstone boson mechanism in supersymmetric GUT theories

Abstract There are few robust solutions to the doublet-triplet splitting problem in supersymmetric GUT theories. One of the more promising solutions is the Higgs as pseudo-Goldstone boson mechanism. In its minimal implementation, such a solution places an additional restriction on the parameter space of the minimal supersymmetric standard model. A testable consequence of this constraint is an equation for tan β. We present this restriction and study its solutions in order to constrain the allowed parameter space. Thus the assumptions on the GUT scale Higgs sector should yield testable predictions for weak scale physics. If the SUSY parameters are measured then it should be possible to check the predictions, yielding insight into GUT scale physics.
Efficient and Extensible Policy Mining for Relationship-Based Access Control

Relationship-based access control (ReBAC) is a flexible and expressive framework that allows policies to be expressed in terms of chains of relationship between entities as well as attributes of entities. ReBAC policy mining algorithms have a potential to significantly reduce the cost of migration from legacy access control systems to ReBAC, by partially automating the development of a ReBAC policy. Existing ReBAC policy mining algorithms support a policy language with a limited set of operators; this limits their applicability. This paper presents a ReBAC policy mining algorithm designed to be both (1) easily extensible (to support additional policy language features) and (2) scalable. The algorithm is based on Bui et al.'s evolutionary algorithm for ReBAC policy mining algorithm. First, we simplify their algorithm, in order to make it easier to extend and provide a methodology that extends it to handle new policy language features. However, extending the policy language increases the search space of candidate policies explored by the evolutionary algorithm, thus causes longer running time and/or worse results. To address the problem, we enhance the algorithm with a feature selection phase. The enhancement utilizes a neural network to identify useful features. We use the result of feature selection to reduce the evolutionary algorithm's search space. The new algorithm is easy to extend and, as shown by our experiments, is more efficient and produces better policies.
$N^*$ Structure and Strong QCD

In attempting to match QCD with Nature, it is necessary to confront the many complexities of strong, nonlinear dynamics in relativistic quantum field theory, e.g. the loss of particle number conservation, the frame and scale dependence of the explanations and interpretations of observable processes, and the evolving character of the relevant degrees-of-freedom. The peculiarities of QCD ensure that it is also the only known fundamental theory with the capacity to sustain massless elementary degrees-of-freedom, gluons and quarks; and yet gluons and quarks are predicted to acquire mass dynamically so that the only massless systems in QCD are its composite Nambu–Goldstone bosons. All other everyday bound states possess nuclear-size masses, far in excess of anything that can directly be tied to the Higgs boson. These observations highlight fundamental questions within the Standard Model: what is the source of the mass for the vast bulk of visible matter in the Universe, how is its appearance connected with confinement; how is this mass distributed within hadrons and does the distribution differ from one hadron to another? This contribution sketches insights drawn using modern methods for the continuum bound-state problem in QCD, and how they have been informed by empirical information on the hadron spectrum and nucleon-to-resonance transition form factors.
Temperature Driven Structural Phase Transition in Tetragonal-Like BiFeO3

Highly strained BiFeO3 exhibits a "tetragonal-like, monoclinic" crystal structure found only in epitaxial films (with an out-of-plane lattice parameter exceeding the in-plane value by >20%). Previous work has shown that this phase is properly described as an MC monoclinic structure at room temperature [with a (010)pc symmetry plane, which contains the ferroelectric polarization]. Here, we show detailed temperature-dependent X-ray diffraction data that reveal a structural phase transition at ~100 °C to a high-temperature MA phase ["tetragonal-like" but with a (110)pc symmetry plane]. These results indicate that the ferroelectric properties and domain structures of the strained BiFeO3 are strongly temperature dependent.
The GammeV suite of experimental searches for axion-like particles

We report on the design and results of the GammeV search for axion-like particles and for chameleon particles. We also discuss plans for an improved experiment to search for chameleon particles, one which is sensitive to both cosmological and power-law chameleon models. Plans for an improved axion-like particle search using coupled resonant cavities are also presented. This experiment will be more sensitive to axion-like particles than stellar astrophysical models or current helioscope experiments.
A homotopy-theoretic view of Bott–Taubes integrals and knot spaces

We construct cohomology classes in the space of knots by considering a bundle over this space and "integrating along the fiber" classes coming from the cohomology of configuration spaces using a Pontrjagin-Thom construction. The bundle we consider is essentially the one considered by Bott and Taubes, who integrated differential forms along the fiber to get knot invariants. By doing this "integration" homotopy-theoretically, we are able to produce integral cohomology classes. We then show how this integration is compatible with the homology operations on the space of long knots, as studied by Budney and Cohen. In particular we derive a product formula for evaluations of cohomology classes on homology classes, with respect to connect-sum of knots.
Parity violation in the Cosmic Microwave Background from a pseudoscalar inflaton

If the inflaton is a pseudoscalar, then it naturally interacts with gauge fields through the coupling ∝ Fμν μν. Through this coupling, the rolling inflaton produces quanta of the gauge field, that in their turn source the tensor components of the metric perturbations. Due to the parity-violating nature of the system, the right- and the left-handed tensor modes have different amplitudes. Such an asymmetry manifests itself in the form of non-vanishing TB and EB correlation functions in the Cosmic Microwave Background (CMB). We compute the amplitude of the parity-violating tensor modes and we discuss two scenarios, consistent with the current data, where parity-violating CMB correlation functions will be detectable in future experiments.
Optimal temporal logic planning in probabilistic semantic maps

This paper considers robot motion planning under temporal logic constraints in probabilistic maps obtained by semantic simultaneous localization and mapping (SLAM). The uncertainty in a map distribution presents a great challenge for obtaining correctness guarantees with respect to the linear temporal logic (LTL) specification. We show that the problem can be formulated as an optimal control problem in which both the semantic map and the logic formula evaluation are stochastic. Our first contribution is to reduce the stochastic control problem for a subclass of LTL to a deterministic shortest path problem by introducing a confidence parameter δ. A robot trajectory obtained from the deterministic problem is guaranteed to have minimum cost and to satisfy the logic specification in the true environment with probability δ. Our second contribution is to design an admissible heuristic function that guides the planning in the deterministic problem towards satisfying the temporal logic specification. This allows us to obtain an optimal and very efficient solution using the A* algorithm. The performance and correctness of our approach are demonstrated in a simulated semantic environment using a differential-drive robot.
From Super-Earths to Mini-Neptunes: Implications of a Surface on Atmospheric Circulation

It is well known that planets with radii between that of Earth and Neptune have been the most commonly detected to-date. To classify these planets as either terrestrial or gaseous, typically we turn to mass-radius relations and composition curves to determine the likelihood of such a planet being rocky or gaseous. While these methods have set a likely transition radius of approximately 1.5 R$_{\oplus}$, we cannot expect that any change between terrestrial and gaseous compositions will be a sharp cut-off, and composition curve predictions result in ambiguous designations for planets right near this transition radius. In this work we present 3D general circulation models of transition planets, wherein we study the effects of a surface on observable quantities such as the latitudinal variations and eclipse depths. We present our updated GCM, validated on the circulation of Earth, before discussing our modeling choices for this transition planet. Finally, we discuss the results of this study and explore the prospects of detecting the presence of a surface through observations of secondary eclipses in the future.
Steady state thermodynamics of two qubits strongly coupled to bosonic environments

When a quantum system is placed in thermal environments, we often assume that the system relaxes to the Gibbs state in which decoherence takes place in the system energy eigenbasis. However, when the coupling between the system and the environments is strong, the stationary state is not necessarily the Gibbs state due to environment-induced decoherence which can be interpreted as continuous measurement by the environments. Based on the einselection proposed by Zurek, we postulate that the Gibbs state is projected onto the pointer basis due to the continuous measurement. We justify the proposition by exact numerical simulation of a pair of coupled qubits interacting with boson gases. Furthermore, we demonstrate that heat conduction in non-equilibrium steady states can be suppressed in the strong coupling limit also by the environment-induced decoherence.
How to Get Less Helium and More Neutrinos from BBN

We discuss BBN in the presence of a non-minimally coupled quintessence model. In some of these models, the gravitational constant and cosmic expansion rate are smaller than standard model predicts. The Helium abundance is then smaller, possibly resolve the marginal disagreement between theory and observation. Furthermore, the constraint on neutrino species may also be relaxed.
Protecting superconducting qubits from phonon mediated decay

For quantum computing to become fault tolerant, the underlying quantum bits must be effectively isolated from the noisy environment. It is well known that including an electromagnetic bandgap around the qubit operating frequency improves coherence for superconducting circuits. However, investigations of bandgaps to other environmental coupling mechanisms remain largely unexplored. Here, we present a method to enhance the coherence of superconducting circuits by introducing a phononic bandgap around the device operating frequency. The phononic bandgaps block resonant decay of defect states within the gapped frequency range, removing the electromagnetic coupling to phonons at the gap frequencies. We construct a multiscale model that derives the decrease in the density of states due to the bandgap and the resulting increase in defect state T1 times. We demonstrate that emission rates from in-plane defect states can be suppressed by up to two orders of magnitude. We combine these simulations with theory for resonators operating in the continuous-wave regime and show that improvements in quality factors are expected by up to the enhancement in defect T1 times. Furthermore, we use full master equation simulation to demonstrate the suppression of qubit energy relaxation even when interacting with 200 defect states. We conclude with an exploration of device implementation including tradeoffs between fabrication complexity and qubit performance.
Hyperviscosity and statistical equilibria of Euler turbulence on the torus and the sphere

Coherent structures such as jets and vortices appear in two-dimensional (2D) turbulence. To gain insight into both numerical simulation and equilibrium statistical mechanical descriptions of 2D Euler flows, the Euler equation with added hyperviscosity is integrated forward in time on the square torus and on the sphere. Coherent structures that form are compared against a hierarchy of truncated Miller–Robert–Sommeria equilibria. The energy-circulation-enstrophy MRS-2 description produces a complete condensation of energy to the largest scales, and in the absence of rotation correctly predicts the number and polarity of coherent vortices. Perturbative imposition of the quartic Casimir constraint improves agreement with numerical simulation by sharpening the cores and transferring some energy to smaller-scale modes. MRS-2 cannot explain qualitative changes due to rotation, but descriptions that conserve higher Casimirs beyond enstrophy have the potential to do so. The result is in agreement with the somewhat paradoxical observation that hyperviscosity helps to remedy the non-conservation of the third and higher Casimirs in numerical simulation. For a rotating sphere, numerical simulation also demonstrates that coherent structures found at late times depend on initial conditions, limiting the usefulness of statistical mechanics.
Soft photon hair on Schwarzschild horizon from a Wilson line perspective

We develop a unified framework for the construction of soft dressings at boundaries of spacetime, such as the null infinity of Minkowski spacetime and the horizon of a Schwarzschild black hole. The construction is based on an old proposal of Mandelstam for quantizing QED and considers matter fields dressed by Wilson lines. Along time-like paths, the Wilson lines puncturing the boundary are the analogs of flat space Faddeev-Kulish dressings. We focus on the Schwarzschild black hole where our framework provides a quantum-field-theoretical perspective of the Hawking-Perry-Strominger viewpoint that black holes carry soft hair, through a study of the Wilson line dressings, localized on the horizon.
On a Triply Periodic Polyhedral Surface Whose Vertices are Weierstrass Points

In this paper, we will construct an example of a closed Riemann surface X that can be realized as a quotient of a triply periodic polyhedral surface $$\Pi \subset \mathbb {R}^3$$ where the Weierstrass points of X coincide with the vertices of $$\Pi .$$ First we construct $$\Pi $$ by attaching Platonic solids in a periodic manner and consider the surface of this solid. Due to periodicity we can find a compact quotient of this surface. The symmetries of X allow us to construct hyperbolic structures and various translation structures on X that are compatible with its conformal type. The translation structures are the geometric representations of the holomorphic 1-forms of X. Via the basis of 1-forms we find an explicit algebraic description of the surface that suggests the Fermat’s quartic. Moreover the 1-forms allow us to identify the Weierstrass points.
Refractive index of a transparent liquid measured with a concave mirror

This paper describes the spherical concave mirror method for measuring the index of refraction of transparent liquids based on locating the actual and apparent radii of curvature of the mirror. We derived the refractive index equation using Snell's law and the small-angle approximation.
Control Improvisation with Probabilistic Temporal Specifications

We consider the problem of generating randomized control sequences for complex networked systems typically actuated by human agents. Our approach leverages a concept known as control improvisation, which is based on a combination of data-driven learning and controller synthesis from formal specifications. We learn from existing data a generative model (for instance, an explicit-duration hidden Markov model, or EDHMM) and then supervise this model in order to guarantee that the generated sequences satisfy some desirable specifications given in Probabilistic Computation Tree Logic (PCTL). We present an implementation of our approach and apply it to the problem of mimicking the use of lighting appliances in a residential unit, with potential applications to home security and resource management. We present experimental results showing that our approach produces realistic control sequences, similar to recorded data based on human actuation, while satisfying suitable formal requirements.
PROPERTIES OF TURBULENCE IN THE VERY LOCAL INTERSTELLAR CLOUDS

We have investigated the degree to which turbulence in the Very Local Interstellar Clouds resembles the highly studied turbulence in the solar corona and the solar wind, particularly the high-speed solar wind. The turbulence diagnostics for the Local Clouds are the absorption line widths measured along 32 lines of sight to nearby stars, yielding measurements for 53 absorption components. We have tested whether the Local Cloud turbulence has the following properties of turbulence in the solar corona or the solar wind: (1) velocity fluctuations mainly perpendicular to the average magnetic field, (2) a temperature anisotropy in the sense that the perpendicular temperature is larger than the parallel temperature (or at least enhanced relative to expectation), and (3) an ion temperature which is dependent on the ion Larmor radius, in the sense that more massive ions have higher temperatures. Our analysis of the data does not show compelling evidence for any of these properties in Local Cloud turbulence, indicating possible differences with the aforementioned heliospheric plasmas. In the case of anisotropy of velocity fluctuations, although the expected observational signature is not seen, we cannot exclude the possibility of relatively high degrees of anisotropy (anisotropy parameter {epsilon} {approx} 0.50-0.70), if some othermore » process in the Local Clouds is causing variations in the turbulent line width from one line of sight to another. We briefly consider possible reasons for differences between heliospheric turbulence and that in the Local Clouds. The apparent absence of anisotropy of the velocity fluctuations and ion temperature might be due to randomization of the interstellar magnetic field on spatial scales {approx}10 pc, but this would not explain the absence of ion mass dependence in the ion temperature. A likely explanation for the absence of temperature anisotropy and mass-proportional temperature in the Local Clouds, and the presence of these effects in the corona and high-speed solar wind, is the greater collisionality, due to ion-neutral collisions, of the partially ionized Local Cloud plasma.« less
Einstein metrics, harmonic forms, and symplectic four-manifolds

If \(M\) is the underlying smooth oriented four-manifold of a Del Pezzo surface, we consider the set of Riemannian metrics \(h\) on \(M\) such that \(W^+(\omega , \omega )> 0\), where \(W^+\) is the self-dual Weyl curvature of \(h\), and \(\omega \) is a non-trivial self-dual harmonic two-form on \((M,h)\). While this open region in the space of Riemannian metrics contains all the known Einstein metrics on \(M\), we show that it contains no others. Consequently, it contributes exactly one connected component to the moduli space of Einstein metrics on \(M\).
FROM FIRST LYAPUNOV COEFFICIENTS TO MAXIMAL CANARDS

Hopf bifurcations in fast–slow systems of ordinary differential equations can be associated with a surprisingly rapid growth of periodic orbits. This process is referred to as canard explosion. The key step in locating a canard explosion is to calculate the location of a special trajectory, called a maximal canard, in parameter space. A first-order asymptotic expansion of this location was found by Krupa and Szmolyan [2001a, 2001b, 2001c] in the framework of a "canard point"-normal-form for systems with one fast and one slow variable. We show how to compute the coefficients in this expansion using the first Lyapunov coefficient at the Hopf bifurcation thereby avoiding the use of this normal form. Our results connect the theory of canard explosions with existing numerical software, enabling easier calculations of where canard explosions occur.
Weather variation affects the dispersal of grasshoppers beyond their elevational ranges

Understanding how abiotic conditions influence dispersal patterns of organisms is important for understanding the degree to which species can track and persist in the face of changing climate.The goal of this study was to understand how weather conditions influence the dispersal pattern of multiple nonmigratory grasshopper species from lower elevation grassland habitats in which they complete their life-cycles to higher elevations that extend beyond their range limits.Using over a decade of weekly spring to late-summer field survey data along an elevational gradient, we explored how abundance and richness of dispersing grasshoppers were influenced by temperature, precipitation, and wind speed and direction. We also examined how changes in population sizes at lower elevations might influence these patterns.We observed that the abundance of dispersing grasshoppers along the gradient declined 4-fold from the foothills to the subalpine and increased with warmer conditions and when wind flow patterns were mild or in the downslope direction. Thirty-eight unique grasshopper species from lowland sites were detected as dispersers across the survey years, and warmer years and weak upslope wind conditions also increased the richness of these grasshoppers. The pattern of grasshoppers along the gradient was not sex biased. The positive effect of temperature on dispersal rates was likely explained by an increase in dispersal propensity rather than by an increase in the density of grasshoppers at low elevation sites.The results of this study support the hypothesis that the dispersal patterns of organisms are influenced by changing climatic conditions themselves and as such, that this context-dependent dispersal response should be considered when modeling and forecasting the ability of species to respond to climate change.
Neutron star mergers and how to study them

Neutron star mergers are the canonical multimessenger events: they have been observed through photons for half a century, gravitational waves since 2017, and are likely to be sources of neutrinos and cosmic rays. Studies of these events enable unique insights into astrophysics, particles in the ultrarelativistic regime, the heavy element enrichment history through cosmic time, cosmology, dense matter, and fundamental physics. Uncovering this science requires vast observational resources, unparalleled coordination, and advancements in theory and simulation, which are constrained by our current understanding of nuclear, atomic, and astroparticle physics. This review begins with a summary of our current knowledge of these events, the expected observational signatures, and estimated detection rates for the next decade. I then present the key observations necessary to advance our understanding of these sources, followed by the broad science this enables. I close with a discussion on the necessary future capabilities to fully utilize these enigmatic sources to understand our universe.
The effects of nonlinear damping on degenerate parametric amplification

This paper considers the dynamic response of a single degree of freedom system with nonlinear stiffness and nonlinear damping that is subjected to both resonant direct excitation and resonant parametric excitation, with a general phase between the two. This generalizes and expands on previous studies of nonlinear effects on parametric amplification, notably by including the effects of nonlinear damping, which is commonly observed in a large variety of systems, including micro- and nano-scale resonators. Using the method of averaging, a thorough parameter study is carried out that describes the effects of the amplitudes and relative phase of the two forms of excitation. The effects of nonlinear damping on the parametric gain are first derived. The transitions among various topological forms of the frequency response curves, which can include isolae, dual peaks, and loops, are determined, and bifurcation analyses in parameter spaces of interest are carried out. In general, these results provide a complete picture of the system response and allow one to select drive conditions of interest that avoid bistability while providing maximum amplitude gain, maximum phase sensitivity, or a flat resonant peak, in systems with nonlinear damping.
Soft de Sitter Effective Theory

Calculating the quantum evolution of a de Sitter universe on superhorizon scales is notoriously difficult. To address this challenge, we introduce the Soft de Sitter Effective Theory (SdSET). This framework holds for superhorizon modes whose comoving momentum is far below the UV scale, which is set by the inverse comoving horizon. The SdSET is formulated using the same approach that yields the Heavy Quark Effective Theory. The degrees of freedom that capture the long wavelength dynamics are identified with the growing and decaying solutions to the equations of motion. The operator expansion is organized using a power counting scheme, and loops can be regulated while respecting the low energy symmetries. For massive quantum fields in a fixed de Sitter background, power counting implies that all interactions beyond the horizon are irrelevant. Alternatively, if the fields are very light, the leading interactions are at most marginal, and resumming the associated logarithms using (dynamical) renormalization group techniques yields the evolution equation for canonical stochastic inflation. The SdSET is also applicable to models where gravity is dynamical, including inflation. In this case, diffeomorphism invariance ensures that all interactions are irrelevant, trivially implying the all-orders conservation of adiabatic density fluctuations and gravitational waves. We briefly touch on the application to slow-roll eternal inflation by identifying novel relevant operators. This work serves to demystify many aspects of perturbation theory outside the horizon, and has a variety of applications to problems of cosmological interest.
Lead-time trajectory of CA19-9 as an anchor marker for pancreatic cancer early detection

Background & Aims There is substantial interest in liquid biopsy approaches for cancer early detection among subjects at risk, using multi-marker panels. CA19-9 is an established circulating biomarker for pancreatic cancer; however, its relevance for pancreatic cancer early detection or for monitoring subjects at risk has not been established. Methods CA19-9 levels were assessed in blinded sera from 175 subjects collected up to 5 years before diagnosis of pancreatic cancer and from 875 matched controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. For comparison of performance, CA19-9 was assayed in blinded independent sets of samples collected at diagnosis from 129 subjects with resectable pancreatic cancer and 275 controls (100 healthy subjects; 50 with chronic pancreatitis; and 125 with noncancerous pancreatic cysts). The complementary value of 2 additional protein markers, TIMP1 and LRG1, was determined. Results In the PLCO cohort, levels of CA19-9 increased exponentially starting at 2 years before diagnosis with sensitivities reaching 60% at 99% specificity within 0 to 6 months before diagnosis for all cases and 50% at 99% specificity for cases diagnosed with early-stage disease. Performance was comparable for distinguishing newly diagnosed cases with resectable pancreatic cancer from healthy controls (64% sensitivity at 99% specificity). Comparison of resectable pancreatic cancer cases to subjects with chronic pancreatitis yielded 46% sensitivity at 99% specificity and for subjects with noncancerous cysts, 30% sensitivity at 99% specificity. For prediagnostic cases below cutoff value for CA19-9, the combination with LRG1 and TIMP1 yielded an increment of 13.2% in sensitivity at 99% specificity (P = .031) in identifying cases diagnosed within 1 year of blood collection. Conclusion CA19-9 can serve as an anchor marker for pancreatic cancer early detection applications.
FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk

Recent advances in digital technology and big data have allowed FinTech (financial technology) lending to emerge as a potentially promising solution to reduce the cost of credit and increase financial inclusion. However, machine learning (ML) methods that lie at the heart of FinTech credit have remained largely a black box for the nontechnical audience. This paper contributes to the literature by discussing potential strengths and weaknesses of ML-based credit assessment through (1) presenting core ideas and the most common techniques in ML for the nontechnical audience; and (2) discussing the fundamental challenges in credit risk analysis. FinTech credit has the potential to enhance financial inclusion and outperform traditional credit scoring by (1) leveraging nontraditional data sources to improve the assessment of the borrower’s track record; (2) appraising collateral value; (3) forecasting income prospects; and (4) predicting changes in general conditions. However, because of the central role of data in ML-based analysis, data relevance should be ensured, especially in situations when a deep structural change occurs, when borrowers could counterfeit certain indicators, and when agency problems arising from information asymmetry could not be resolved. To avoid digital financial exclusion and redlining, variables that trigger discrimination should not be used to assess credit rating.
RS-Mask: Random Space Masking as an Integrated Countermeasure against Power and Fault Analysis

While modern masking schemes provide provable security against passive side-channel analysis (SCA), such as power analysis, single faults can be employed to recover the secret key of ciphers even in masked implementations. In this paper, we propose random space masking (RS-Mask) as a countermeasure against both power analysis and statistical fault analysis (SFA) techniques. In the RS-Mask scheme, the distribution of all sensitive variables, faulty and/or correct values is uniform, and it therefore protects the implementations against any SFA technique that exploits the distribution of intermediate variables, including fault sensitivity analysis (FSA), statistical ineffective fault analysis (SIFA) and fault intensity map analysis (FIMA). We implement RS-Mask on AES, and show that a SIFA attack is not able to identify the correct key. We additionally show that an FPGA implementation of AES, protected with RS-Mask, is resistant to power analysis SCA using Welch’s t-test. The area of the RSMasked AES is about 3.5 times that of an unprotected AES implementation of similar architecture, and about 2 times that of a known FPGA SCA-resistant AES implementation. Finally, we introduce infective RS-Mask that provides security against differential techniques, such as differential fault analysis (DFA) and differential fault intensity analysis (DFIA), with a slight increase in overhead.
Simultaneous measurements of deforming Hinze-scale bubbles with surrounding turbulence

We experimentally investigate the breakup mechanisms and probability of Hinze-scale bubbles in turbulence. The Hinze scale is defined as the critical bubble size based on the critical mean Weber number, across which the bubble breakup probability was believed to have an abrupt transition from being dominated by turbulence stresses to being suppressed completely by the surface tension. In this work, to quantify the breakup probability of bubbles with sizes close to the Hinze scale and to examine different breakup mechanisms, both bubbles and their surrounding tracer particles were simultaneously tracked. From the experimental results, two Weber numbers, one calculated from the slip velocity between the two phases and the other acquired from local velocity gradients, are separated and fitted with models that can be linked back to turbulence characteristics. Moreover, we also provide an empirical model to link bubble deformation to the two Weber numbers by extending the relationship obtained from potential flow theory. The proposed relationship between bubble aspect ratio and the Weber numbers seems to work consistently well for a range of bubble sizes. Furthermore, the time traces of bubble aspect ratio and the two Weber numbers are connected using the linear forced oscillator model. Finally, having access to the distributions of these two Weber numbers provides a unique way to extract the breakup probability of bubbles with sizes close to the Hinze scale.
Resolution dependence of rough surface scattering using a power law roughness spectrum

Contemporary high-resolution sonar systems use broadband pulses and long arrays to achieve high resolution. It is important to understand effects that high-resolution sonar systems might have on quantitative measures of the scattered field due to the seafloor. A quantity called the broadband scattering cross section is defined, appropriate for high-resolution measurements. The dependence of the broadband scattering cross section, σbb, and the scintillation index, SI, on resolution was investigated for one-dimensional rough surfaces with power-law spectra and backscattering geometries. Using integral equations and Fourier synthesis, no resolution dependence of σbb was found. The incoherently averaged frequency-domain scattering cross section has negligible bandwidth dependence. SI increases as resolution increases, grazing angle decreases, and spectral strength increases. This trend is confirmed for center frequencies of 100 and 10 kHz, as well as for power-law spectral exponents of 1.5, 2, and 2.5. The hypothesis that local tilting at the scale of the acoustic resolution is responsible for intensity fluctuations was examined using a representative model for the effect of slopes (inspired by the composite roughness approximation). It was found that slopes are responsible in part for the fluctuations, but other effects, such as multiple scattering and shadowing may also play a role.
Fingerprint Presentation Attack Detection: A Sensor and Material Agnostic Approach

The vulnerability of automated fingerprint recognition systems to presentation attacks (PAs), i.e., spoof or altered fingers, has been a growing concern, warranting the development of accurate and efficient presentation attack detection (PAD) methods. However, one major limitation of the existing PAD solutions is their poor generalization to new PA materials and fingerprint sensors, not used in training. In this study, we propose a robust PAD solution with improved cross-material and cross-sensor generalization. Specifically, we build on top of any CNN-based architecture trained for fingerprint spoof detection combined with cross-material spoof generalization using a style transfer network wrapper. We also incorporate adversarial representation learning (ARL) in deep neural networks (DNN) to learn sensor and material invariant representations for PAD. Experimental results on LivDet 2015 and 2017 public domain datasets exhibit the effectiveness of the proposed approach.
A Quadratic Program based Control Synthesis under Spatiotemporal Constraints and Non-vanishing Disturbances

In this paper, we study the effect of non-vanishing disturbances on the stability of fixed-time stable (FxTS) systems. We present a new result on FxTS, which allows a positive term in the time derivative of the Lyapunov function with the aim to model bounded, non-vanishing disturbances in system dynamics. We characterize the neighborhood to which the system trajectories converge, as well as the convergence time. Then, we use the new FxTS result and formulate a quadratic program (QP) that yields control inputs which drive the trajectories of a class of nonlinear, control-affine systems to a goal set in the presence of control input constraints and nonvanishing, bounded disturbances in the system dynamics. We consider an overtaking problem on a highway as a case study, and discuss how to both set up the QP and decide when to start the overtake maneuver in the presence of sensing errors.
Microelectromechanical deformable mirror development for high-contrast imaging, part 2: the impact of quantization errors on coronagraph image contrast

Stellar coronagraphs rely on deformable mirrors (DMs) to correct wavefront errors and create high-contrast images. Imperfect control of the DM limits the achievable contrast, and therefore, the DM control electronics must provide fine surface height resolution and low noise. We study the impact of quantization errors due to the DM electronics on the image contrast using experimental data from the High Contrast Imaging Testbed facility at NASA’s Jet Propulsion Laboratory. We find that the simplest analytical model gives optimistic predictions compared to real cases, with contrast up to 3 times better, which leads to DM surface height resolution requirements that are incorrectly relaxed by 70%. We show that taking into account the DM actuator shape, or influence function, improves the analytical predictions. However, we also find that end-to-end numerical simulations of the wavefront sensing and control process provide the most accurate predictions and recommend such an approach for setting robust requirements on the DM control electronics. From our experimental and numerical results, we conclude that a surface height resolution of ∼6 pm is required for imaging temperate terrestrial exoplanets around solar-type stars at wavelengths as small as 450 nm with coronagraph instruments on future space telescopes. Finally, we list the recognizable characteristics of quantization errors that may help determine if they are a limiting factor.
DISSECT: DISentangle SharablE ConTent for Multimodal Integration and Crosswise-mapping

Deep learning systems have emerged as powerful mechanisms for learning domain translation models. However, in many cases, complete information in one domain is assumed to be necessary for sufficient cross-domain prediction. In this work, we motivate a formal justification for domain-specific information separation in a simple linear case and illustrate that a self-supervised approach enables domain translation between data domains while filtering out domain-specific data features. We introduce a novel approach to identify domain- specific information from sets of unpaired measurements in complementary data domains by considering a deep learning cross-domain autoencoder architecture designed to learn shared latent representations of data while enabling domain translation. We introduce an orthogonal gate block designed to enforce orthogonality of input feature sets by explicitly removing non- sharable information specific to each domain and illustrate separability of domain-specific information on a toy dataset.
Case studies of the time-dependent potential energy surface for dynamics in cavities

The exact time-dependent potential energy surface driving the nuclear dynamics was recently shown to be a useful tool to understand and interpret the coupling of nuclei, electrons, and photons in cavity settings. Here, we provide a detailed analysis of its structure for exactly solvable systems that model two phenomena: cavity-induced suppression of proton-coupled electron-transfer and its dependence on the initial state, and cavity-induced electronic excitation. We demonstrate the inadequacy of simply using a weighted average of polaritonic surfaces to determine the dynamics. Such a weighted average misses a crucial term that redistributes energy between the nuclear and the polaritonic systems, and this term can in fact become a predominant term in determining the nuclear dynamics when several polaritonic surfaces are involved. Evolving an ensemble of classical trajectories on the exact potential energy surface reproduces the nuclear wavepacket quite accurately, while evolving on the weighted polaritonic surface fails after a short period of time. The implications and prospects for application of mixed quantum-classical methods based on this surface are discussed.
Privacy Notices as Tabula Rasa: An Empirical Investigation into How Complying with a Privacy Notice Is Related to Meeting Privacy Expectations Online

Recent privacy scholarship has focused on the failure of adequate notice and consumer choice as a tool to address consumers' privacy expectations online. However, there has not been a direct examination into how complying with a privacy notice is related to meeting privacy expectations online. This article reports the findings of two factorial vignette studies describing online consumer tracking, whereby respondents rated the degree to which online scenarios met their privacy expectations or complied with a privacy notice. The results suggest that respondents perceived the privacy notice as offering greater protections than it actually did. Perhaps most problematically, respondents projected the important factors of their privacy expectations onto the privacy notice. In other words, privacy notices became a tabula rasa for users' privacy expectations. The findings provide guidance for policy makers and firms to avoid unnecessary privacy violations caused by an overreliance on privacy notices. Considering ...