cssi/SciSciGPT-SciSciNet huggingface dataset:
Modification of Point Defects in Quartz for Device Applications

Impurity centers in quartz play a significant role in the behavior of precision crystal resonators subjected to ionizing radiation. The substitutional Al center, charge compensated by Na, Li, H or a hole, is now known to be the primary contributing factor in most radiation-induced effects. Acoustic loss measurements, ESR measurements, optical studies and IR studies of these defects, over extended temperature ranges, have contributed substantially to our understanding of the impurity centers’ role. Radiation-induced frequency and acoustic loss changes in quartz crystal resonators are now understood in terms of the evolving character of the defect center in a radiation field. This understanding has prompted material modification efforts such as high temperature electrolysis and doping technologies which permit, for instance, the fabrication of frequency control devices that are little affected by hostile environments.
M-Cube: a millimeter-wave massive MIMO software radio

Millimeter-wave (mmWave) technologies represent a cornerstone for emerging wireless network infrastructure, and for RF sensing systems in security, health, and automotive domains. Through a MIMO array of phased arrays with hundreds of antenna elements, mmWave can boost wireless bit-rates to 100+ Gbps, and potentially achieve near-vision sensing resolution. However, the lack of an experimental platform has been impeding research in this field. This paper fills the gap with M3 (M-Cube), the first mmWave massive MIMO software radio. M3 features a fully reconfigurable array of phased arrays, with up to 8 RF chains and 288 antenna elements. Despite the orders of magnitude larger antenna arrays, its cost is orders of magnitude lower, even when compared with state-of-the-art single RF chain mmWave software radios. The key design principle behind M3 is to hijack a low-cost commodity 802.11ad radio, separate the control path and data path inside, regenerate the phased array control signals, and recreate the data signals using a programmable baseband. Extensive experiments have demonstrated the effectiveness of the M3 design, and its usefulness for research in mmWave massive MIMO communication and sensing.
The long-run impact of bombing Vietnam

Abstract We investigate the impact of U.S. bombing on later economic development in Vietnam. The Vietnam War featured the most intense bombing campaign in military history and had massive humanitarian costs. We use a unique U.S. military dataset containing bombing intensity at the district level (N = 584) to assess whether the war damage led to persistent local poverty traps. We compare the heavily bombed districts to other districts controlling for district demographic and geographic characteristics, and use an instrumental variable approach exploiting distance to the 17th parallel demilitarized zone. U.S. bombing does not have negative impacts on local poverty rates, consumption levels, infrastructure, literacy or population density through 2002. This finding indicates that even the most intense bombing in human history did not generate local poverty traps in Vietnam.
Downlink Asynchronous Non-Orthogonal Multiple Access With Quantizer Optimization

In this letter, we study a two-user downlink asynchronous non-orthogonal multiple access (ANOMA) with limited feedback. We employ the max-min criterion for the power allocation and derive the closed-form expressions for the upper and lower bounds of the max-min rate. It is demonstrated that ANOMA can achieve the same or even higher average max-min rate with a lower feedback rate compared with non-orthogonal multiple access (NOMA). Moreover, we propose a quantizer optimization algorithm which applies to both NOMA and ANOMA. Simulation results show that the optimized quantizer significantly improves the average max-min rate compared with the conventional uniform quantizer, especially in the scenario with a low feedback rate.
A space-time smooth artificial viscosity method with wavelet noise indicator and shock collision scheme, Part 2: The 2-D case

Abstract This is the second part to our companion paper [18] . Herein, we generalize to two space dimensions the C-method developed in [20] , [18] for adding localized, space-time smooth artificial viscosity to nonlinear systems of conservation laws that propagate shock waves, rarefaction waves, and contact discontinuities. For gas dynamics, the C-method couples the Euler equations to scalar reaction-diffusion equations, which we call C-equations, whose solutions serve as space-time smooth artificial viscosity indicators for shocks and contacts. We develop a high-order numerical algorithm for gas dynamics in 2-D which can accurately simulate the Rayleigh-Taylor (RT) instability with Kelvin-Helmholtz (KH) roll-up of the contact discontinuity, as well as shock collision and bounce-back. Solutions to our C-equations not only indicate the location of the shocks and contacts, but also track the geometry of the evolving fronts. This allows us to implement both directionally isotropic and anisotropic artificial viscosity schemes, the latter adding diffusion only in directions tangential to the evolving front. We additionally produce a novel shock collision indicator function, which naturally activates during shock collision, and then smoothly deactivates. Moreover, we implement a high-frequency 2-D wavelet-based noise detector together with an efficient and localized noise removal algorithm. To test the methodology, we use a highly simplified WENO-based discretization scheme. We provide numerical results for some classical 2-D test problems, including the RT problem, the Noh problem, a circular explosion problem from the Liska & Wendroff [13] review paper, the Sedov blast wave problem, the double Mach 10 reflection test, and a shock-wall collision problem. In particular, we show that our artificial viscosity method can eliminate the wall-heating phenomenon for the Noh problem, and thereby produce an accurate, non-oscillatory solution, even though our simplified WENO-type scheme fails to run for this problem.
The Cascade Transformer: an Application for Efficient Answer Sentence Selection

Large transformer-based language models have been shown to be very effective in many classification tasks. However, their computational complexity prevents their use in applications requiring the classification of a large set of candidates. While previous works have investigated approaches to reduce model size, relatively little attention has been paid to techniques to improve batch throughput during inference. In this paper, we introduce the Cascade Transformer, a simple yet effective technique to adapt transformer-based models into a cascade of rankers. Each ranker is used to prune a subset of candidates in a batch, thus dramatically increasing throughput at inference time. Partial encodings from the transformer model are shared among rerankers, providing further speed-up. When compared to a state-of-the-art transformer model, our approach reduces computation by 37% with almost no impact on accuracy, as measured on two English Question Answering datasets.
Extending the Spacing between the Shine–Dalgarno Sequence and P-Site Codon Reduces the Rate of mRNA Translocation

By forming base-pairing interactions with the 3′ end of 16S rRNA, mRNA Shine–Dalgarno (SD) sequences positioned upstream of open reading frames facilitate translation initiation. During the elongation phase of protein synthesis, intragenic SD-like sequences stimulate ribosome frameshifting and may also slow down ribosome movement along mRNA. Here, we show that the length of the spacer between the SD sequence and P-site codon strongly affects the rate of ribosome translocation. Increasing the spacer length beyond 6 nt destabilizes mRNA–tRNA–ribosome interactions and results in a 5- to 10-fold reduction of the translocation rate. These observations suggest that during translation, the spacer between the SD sequence and P-site codon undergoes structural rearrangements, which slow down mRNA translocation and promote mRNA frameshifting.
Interaction is necessary for distributed learning with privacy or communication constraints

Local differential privacy (LDP) is a model where users send privatized data to an untrusted central server whose goal it to solve some data analysis task. In the non-interactive version of this model the protocol consists of a single round in which a server sends requests to all users then receives their responses. This version is deployed in industry due to its practical advantages and has attracted significant research interest. Our main result is an exponential lower bound on the number of samples necessary to solve the standard task of learning a large-margin linear separator in the non-interactive LDP model. Via a standard reduction this lower bound implies an exponential lower bound for stochastic convex optimization and specifically, for learning linear models with a convex, Lipschitz and smooth loss. These results answer the questions posed by Smith, Thakurta, and Upadhyay (IEEE Symposium on Security and Privacy 2017) and Daniely and Feldman (NeurIPS 2019). Our lower bound relies on a new technique for constructing pairs of distributions with nearly matching moments but whose supports can be nearly separated by a large margin hyperplane. These lower bounds also hold in the model where communication from each user is limited and follow from a lower bound on learning using non-adaptive statistical queries.
Summary and Future Work

The adoption of cloud computing by the U.S. government, including the Department of Defense, is proceeding quickly [1, 4, 8, 9] and is likely to become widespread [5]. As government becomes more comfortable with the technology, mission‐oriented cloud computing seems inevitable. However, security remains a top threat to the use of clouds for dependable and trustworthy computing [6], even as FedRAMP [7] and other standards converge to a common set of requirements, as discussed in this chapter. The cloud computing environment is maturing, but we are observing the rise of new aspects of cloud computing – like mobiles interconnected into clouds, real‐time concerns, edge computing, and machine learning – that are challenging the existing techniques for testing, validation, verification, robustness, and resistance to attack. As reflected in this book, academia and industry are attempting to respond quickly to rapidly changing cloud technologies, as driven by the value of these technologies in today's society.The preceding chapters of this book have touched on many of the concerns arising from cloud technology: survivability, risks, benefits, detection, security, scalability, workloads, performance, resource management, validation and verification, theoretical problems, and certification. In this last chapter, we will consider what has been learned since 2007 and what issues and obstacles remain in any mission‐critical system deployment on cloud computing.
The set of non-uniquely ergodic d-IETs has Hausdorff codimension 1/2

We show that the set of not uniquely ergodic d-IETs with permutation in the Rauzy class of the hyperelliptic permutation has Hausdorff dimension $$d-\frac{3}{2} $$ [in the $$(d-1)$$ -dimension space of d-IETs] for $$d\ge 5$$ . For $$d=4$$ this was shown by Athreya–Chaika and for $$d\in \{2,3\}$$ the set is known to have dimension $$d-2$$ . This provides lower bounds on the Hausdorff dimension of non-weakly mixing IETs and, with input from Al-Saqban et al. (Exceptional directions for the Teichmuller geodesic flow and Hausdorff dimension, 2017. arXiv:1711.10542 ), identifies the Hausdorff dimension of non-weakly mixing IETs with permutation $$(d,d-1,\ldots ,2,1)$$ when d is odd.
Dual electrocatalysis enables enantioselective hydrocyanation of conjugated alkenes

Chiral nitriles and their derivatives are prevalent in pharmaceuticals and bioactive compounds. Enantioselective alkene hydrocyanation represents a convenient and efficient approach for synthesizing these molecules. However, a generally applicable method featuring a broad substrate scope and high functional group tolerance remains elusive. Here, we address this long-standing synthetic problem using dual electrocatalysis. Using this strategy, we leverage electrochemistry to seamlessly combine two canonical radical reactions-cobalt-mediated hydrogen-atom transfer and copper-promoted radical cyanation-to accomplish highly enantioselective hydrocyanation without the need for stoichiometric oxidants. We also harness electrochemistry's unique feature of precise potential control to optimize the chemoselectivity of challenging substrates. Computational analysis uncovers the origin of enantio-induction, for which the chiral catalyst imparts a combination of attractive and repulsive non-covalent interactions to direct the enantio-determining C-CN bond formation. This work demonstrates the power of electrochemistry in accessing new chemical space and providing solutions to pertinent challenges in synthetic chemistry.
On Optimal Ordering in the Optimal Stopping Problem

Consider a player who can probe a sequence of n independent random variables X1, . . . , Xn with known distributions. After observing (the realized value of) Xi, the player needs to decide whether to stop and earn reward Xi, or reject the reward and probe the next variable Xi+1. The goal is to maximize the expected reward at the stopping time. This is an instance of the optimal stopping problem, which is a fundamental problem studied from many different aspects in mathematics, statistics, and computer science, and has found a wide variety of applications in sequential decision making and mechanism design. When the order in which the random variables X1,...,Xnare probed is fixed, the optimal stopping strategy can be found by solving a simple dynamic program. Under this strategy, at every step i, the player would compare the realized value of the current random variable Xi to the expected reward (under the optimal strategy for the remaining subproblem) from the remaining variables Xi+1, . . .,Xn, and stop if the former is greater than the latter. In this paper, we focus on the relatively less studied question of optimizing the order in which the random variables should be probed. Specifically, besides choosing a stopping strategy, if the player is free to choose the order in which the random variables are probed, then which ordering would maximize the expected reward at the stopping time? The optimal ordering problem has been previously studied in mathematics and statistics literature in the 80's (e.g., Gilat[6], Hill and Hordijk[8], and Hill[7]). However the focus there has been on analytically characterizing the optimal order for some special structured cases (like Bernoulli and exponential distributions). One difficulty in such a study is that the nature of this problem changes significantly depending on the type of distributions considered. For example, when distributions are Bernoulli or exponential, the optimal ordering can be found analytically [8], but, the problem remains nontrivial for uniform distributions.
Two-phase Free Boundary Problems in Convex Domains

We study the regularity of minimizers of a two-phase free boundary problem. For a class of n-dimensional convex domains, we establish the Lipschitz continuity of the minimizer up to the fixed boundary under Neumann boundary conditions. Our proof uses an almost monotonicity formula for the Alt–Caffarelli–Friedman functional restricted to the convex domain. This requires a variant of the classical Friedland–Hayman inequality for geodesically convex subsets of the sphere with Neumann boundary conditions. To apply this inequality, in addition to convexity, we require a Dini condition governing the rate at which the fixed boundary converges to its limit cone at each boundary point.
Quantum toroidal and shuffle algebras

Abstract In this paper, we prove that the quantum toroidal algebra U q , q ‾ ( gl ¨ n ) is isomorphic to the double shuffle algebra of Feigin and Odesskii for the cyclic quiver. The shuffle algebra viewpoint will allow us to prove a factorization formula for the universal R−matrix of the quantum toroidal algebra.
Balancibility: Existence and uniqueness of power flow solutions under voltage balance requirements

Abstract In distribution systems, power injection variability due to growing penetrations of distributed energy resources (DERs) and dispatchable loads can lead to power quality issues such as severe voltage unbalance. To ensure safe operation of phase-balance-sensitive components such as three-phase motor loads, the amount of voltage unbalance must be maintained within specified limits for a range of uncertain loading conditions. This paper builds on existing “solvability conditions” that characterize operating regions for which the power flow equations are guaranteed to admit a unique high-voltage solution. We extend these existing solvability conditions to be applicable to distribution systems and augment them with a “balancibility” condition that quantifies an operating region within which a unique, adequately balanced power flow solution exists. To build this condition, we consider different unbalance definitions and derive closed-form representations through reformulations or safe approximations. Using case studies, we evaluate these closed-form representations and compare the balancibility conditions associated with different unbalance definitions.
KINETIC THEORY OF THE SHARP LEADING EDGE PROBLEM II. HYPERSONIC FLOW

The hypersonic leading edge problem is studied within the framework of the kinetic theory of gases. The Boltzmann equation with the Bhatnagar–Gross–Krook model is used as the governing equation. The method of discrete ordinates developed by Huang and previously applied to the supersonic flow case is extended and applied to the present problem. The local molecular distribution functions for the entire flow field have been calculated for M∞ = 5, 10, and 20, and thus the complete flow field has been generated for Tw = T∞, 0.1 T0, and 0.15 T0. The calculated results clearly define the structure of shock waves and offer considerable insight into the behavior of a rarefied gas flow as it traverses the complete spectrum of flow regimes from near free molecular to continuum. Results for shock position, surface pressure, and the slip velocity at plate are found to be in reasonably good agreement with the experimental data of Becker and Boylan, Harbour and Lewis, McCrosky, Bogdonoff, and McDougall, and Becker. The calculated local molecular velocity distribution functions which are useful in the direct comparison with the molecular beam experimental results are also presented.
Visible-Light-Initiated Free-Radical Polymerization by Homomolecular Triplet-Triplet Annihilation

Summary Polymerization reactions initiated by ultraviolet light are ubiquitous in scores of industrial applications but would markedly benefit from visible-light activation to overcome stability, energy consumption, light penetration, and sample geometry limitations. The current work leverages visible-light-driven homomolecular triplet-triplet annihilation (TTA) in zinc(II) meso-tetraphenylporphyrin (ZnTPP) to initiate facile free-radical polymerization in trimethylolpropane triacrylate (TMPTA) and methyl acrylate (MA) monomers through ultrafast electron transfer quenching. Selective Q-band (S1) excitation of ZnTPP in the green or yellow sensitizes TTA occurring between two 3ZnTPP∗ energized chromophores, ultimately generating the highly reducing S2 excited state on one ZnTPP molecule (Ered = −2.13 V versus saturated calomel electrode, SCE). Subsequently, this S2 state engages in electron transfer with TMPTA or MA, thereby initiating the radical polymerization process. Bimolecular electron transfer was confirmed through optically gated fluorescence upconversion. FT-IR and EPR spin-trapping experiments verified visible-light-initiated polymerization leading to the formation of well-defined macro- and microscopic objects.
Quantized surface magnetism and higher-order topology: Application to the Hopf insulator

We identify topological aspects of the subextensive magnetic moment contributed by the surfaces of a three-dimensional crystallite---assumed to be insulating in the bulk as well as on all surface facets, with trivial Chern invariants in the bulk. The geometric component of this subextensive moment is given by its derivative with respect to the chemical potential, at zero temperature and zero field, per unit surface area, and hence corresponds to the surface magnetic compressibility. The sum of the surface compressibilities contributed by two opposite facets of a cube-shaped crystallite is quantized to an integer multiple of the fundamental constant $e/hc$; this integer is in one-to-one correspondence with the net chirality of hinge modes on the surface of the crystallite, manifesting a link with higher-order topology. The contribution by a single facet to the magnetic compressibility need not be quantized to integers; however, symmetry and/or Hilbert-space constraints can fix the single-facet compressibility to half-integer multiples of $e/hc$, as will be exemplified by the Hopf insulator.
Extracting non-canonical places

Abstract Let ( X , B ) be a log canonical pair and V be a finite set of divisorial valuations with log discrepancy in [ 0 , 1 ) . We prove that there exists a projective birational morphism π : Y → X so that the exceptional locus is divisorial, the exceptional divisors are Q -Cartier, and they correspond to elements of V . We study how two such models are related. As applications, we apply the main theorem to the study of deformations of log canonical singularities. Furthermore, we prove the existence of rationalization for log canonical singularities.
Nonnegativity-enforced Gaussian process regression

ABSTRACT Gaussian process (GP) regression is a flexible non-parametric approach to approximate complex models. In many cases, these models correspond to processes with bounded physical properties. Standard GP regression typically results in a proxy model which is unbounded for all temporal or spacial points, and thus leaves the possibility of taking on infeasible values. We propose an approach to enforce the physical constraints in a probabilistic way under the GP regression framework. In addition, this new approach reduces the variance in the resulting GP model.
Who Chooses Commitment? Evidence and Welfare Implications

This paper investigates whether offers of commitment contracts, in the form of self-imposed choice-set restrictions and penalties with no financial upside, are well-targeted tools for addressing self-control problems. In an experiment on gym attendance (N= 1;248), we examine take-up of commitment contracts, and also introduce a separate elicitation task to identify actual and perceived time inconsistency. There is high take-up of commitment contracts for greater gym attendance, resulting in significant increases in exercise. However, this is take-up is influenced both by noisy valuation and incorrect beliefs about one’s time inconsistency. Approximately half of the people who take up commitment contracts for higher gym attendance also take up commitment contracts for lower gym attendance. There is little association between commitment contract take-up and reduced-form and structural estimates of actual or perceived time inconsistency. A novel information treatment providing an exogenous shock to awareness of time inconsistency reduces demand for commitment contracts. Structural estimates of a model of quasi-hyperbolic discounting and gym attendance imply that offering our commitment contracts lowers consumer surplus, and is less socially efficient than utilizing linear exercise subsidies that achieve the same average change in behavior.
The Tolman Surface Brightness Test for the Reality of the Expansion. II. The Effect of the Point-Spread Function and Galaxy Ellipticity on the Derived Photometric Parameters

To complete the Tolman surface brightness test on the reality of the expansion of the universe, we need to measure accurately the surface brightness profiles of the high-redshift galaxy sample. To quantify this accuracy, we investigate the effects of various sizes of point-spread functions composed of telescope diffraction, CCD pixel resolutions, and ground-based seeing on the measurements of mean surface brightness for galaxies whose effective (half-light) radii range from 070 to 017. We have done the calculations using two synthetic galaxies of effective radii of 070 and 025 with point-spread functions of 01, 03, and 09, full width at half maximum. We have also compared actual observations of three high-redshift galaxies in the cluster Cl 1324+3011 (z = 0.76) made both with the ground-based Keck 10 m telescopes in seeing of about 09 and with the Hubble Space Telescope (HST) with a point-spread function that is approximately 10 times smaller. The conclusion is that HST data can be used as far into the galaxy image as a Petrosian metric radius of η = 1.3 mag, whereas the ground-based data will have systematic errors of up to 2.9 mag in the mean surface brightness at η values of less than 2.2 mag for all but the largest galaxies at redshifts of z ≈ 0.7. In the final section, we compare the differences in derived average surface brightness for nearly circular galaxy images with highly flattened images. The comparison is made by using the two reduction procedures of (1) integrating the profile curves using circular apertures, and (2) approximating an "equivalent circular" galaxy that is highly elongated by using an "effective" radius of (ab)1/2, where a and b are the semimajor and semiminor axis, respectively, of the best-fitting ellipse. The conclusion is that the two methods of reduction give nearly identical results and that either method can be used to analyze the low- and high-redshift galaxy samples used in the Tolman test.
CHISL: the combined high-resolution and imaging spectrograph for the LUVOIR surveyor

ABSTRACT NASA is currently carrying out science and technical studies to identify its next astronomy flagship mission , slated to begin development in the 2020s . It has become clear that a Large Ultraviolet/Optical/IR (LUVOIR) Surveyor mission (d primary § 12 m, u § 1000 A ± PVSHFWURVFRSLFEDQGSDVV FDQFDUU\RXWWKHODUJHVWQXPEHURI1$6$¶VH[RSODQHWDQGastrophys ics science goals over the coming decad es. The science grasp of a LUVOIR Surveyor is broad, ranging from the direct detection of potential biomarkers on rocky planets to the flow of matter into and out of galaxies and the history of star -formation across cosmic time . The re are technical chall enges for several aspects of the LUVOIR Surveyor concept, including component level technology readiness maturation and science instrument concepts for a broadly capable ultraviolet spectrograph. We present the scientific motivation for , and a preliminary design of , a multiplexed ultravi olet spectrograph to support both the exoplanet and astrophysics goals of the LU VOIR Surveyor mission concept, the Combined High -resolution and Imaging Spectrograph for the LUVOIR Surveyor (CHISL ). CHISL includes a high -resolution ( R § 120,000 ; 1000 - 1700A ) point -source spectroscopy channel and a medium resolution ( R  14 ,000 from 1000 ± 2000 A in a single observation and R ~ 2 4,000 ± 35,000 in multiple grating settings ) imaging spectroscopy channel . CHISL addresses topics ranging from characterizing the composition and structure of planet -forming disks to the feedback of matter between galaxies and the intergalactic medium. We present the CHISL concept , a small sample of representative science cases , and the primary techn ological hurdles . Technical challenges includ e high -efficiency ultraviolet coatings and high -quantum efficiency, large -format, photon counting detectors. We are actively engaged in laboratory and flight characterization efforts for all of these enabling technologies as components on sounding rocket payloads under development at the University of Colorado. We describe two payloads that are designed to be pathfinder instruments for the high -resolution (CHESS) and imaging spectroscopy (SISTINE) arms of CHIS L. We are carrying out this instrument design, characterization, and flight -testing today to support the new start of a LUVOIR Surveyor mission in the next decade. Keywords: flagship mission: LUVOIR, ultraviolet spectroscopy, suborbital payloads, s cience drivers, photon -counting detectors, optical coatings
Structure from appearance: topology with shapes, without points

A new methodological approach for the study of topology for shapes made of arrangements of lines, planes or solids is presented. Topologies for shapes are traditionally built on the classical theor...
Physics-driven regularization of deep neural networks for enhanced engineering design and analysis

In this paper, we introduce a physics-driven regularization method for training of deep neural networks (DNNs) for use in engineering design and analysis problems. In particular, we focus on prediction of a physical system, for which in addition to training data, partial or complete information on a set of governing laws is also available. These laws often appear in the form of differential equations, derived from first principles, empirically-validated laws, or domain expertise, and are usually neglected in data-driven prediction of engineering systems. We propose a training approach that utilizes the known governing laws and regularizes data-driven DNN models by penalizing divergence from those laws. The first two numerical examples are synthetic examples, where we show that in constructing a DNN model that best fits the measurements from a physical system, the use of our proposed regularization results in DNNs that are more interpretable with smaller generalization errors, compared to other common regularization methods. The last two examples concern metamodeling for a random Burgers' system and for aerodynamic analysis of passenger vehicles, where we demonstrate that the proposed regularization provides superior generalization accuracy compared to other common alternatives.
Conservation of asymptotic charges from past to future null infinity: Maxwell fields

On any asymptotically-flat spacetime, we show that the asymptotic symmetries and charges of Maxwell fields on past null infinity can be related to those on future null infinity as recently proposed by Strominger. We extend the covariant formalism of Ashtekar and Hansen by constructing a 3-manifold of both null and spatial directions of approach to spatial infinity. This allows us to systematically impose appropriate regularity conditions on the Maxwell fields near spatial infinity along null directions. The Maxwell equations on this 3-manifold and the regularity conditions imply that the relevant field quantities on past null infinity are antipodally matched to those on future null infinity. Imposing the condition that in a scattering process the total flux of charges through spatial infinity vanishes, we isolate the subalgebra of totally fluxless symmetries near spatial infinity. This subalgebra provides a natural isomorphism between the asymptotic symmetry algebras on past and future null infinity, such that the corresponding charges are equal near spatial infinity. This proves that the flux of charges is conserved from past to future null infinity in a classical scattering process of Maxwell fields. We also comment on possible extensions of our method to scattering in general relativity.
Toward Thermalization in Heavy Ion Collisions at Strong Coupling

We find the trapped surface for a collision of two sourceless shock waves in AdS5 and conclude that such collisions always lead to a creation of a black hole in the bulk. Due to holographic correspondence, in the boundary gauge theory this result proves that a thermalized medium (quark-gluon plasma) is produced in heavy ion collisions at strong coupling (albeit in $$\mathcal{N} $$ = 4 super-Yang-Mills theory). We present new evidence supporting the analytic estimate for the time of thermalization that exists in the literature and find that thermalization time is parametrically much shorter than the time of shock wave stopping, indicating that our result may be relevant for description of heavy ion collision experiments.
About Thinning Invariant Partition Structures

Bernoulli-p thinning has been well-studied for point processes. Here we consider three other cases: (1) sequences (X 1,X 2,…); (2) gaps of such sequences (X n+1−X 1) n∈ℕ; (3) partition structures. For the first case we characterize the distributions which are simultaneously invariant under Bernoulli-p thinning for all p∈(0,1]. Based on this, we make conjectures for the latter two cases, and provide a potential approach for proof. We explain the relation to spin glasses, which is complementary to important previous work of Aizenman and Ruzmaikina, Arguin, and Shkolnikov.
Percolation on hypergraphs with four-edges

We study percolation on self-dual hypergraphs that contain hyperedges with four bounding vertices, or 'four-edges', using three different generators, each containing bonds or sites with three distinct probabilities p, r, and t connecting the four vertices. We find explicit values of these probabilities that satisfy the self-duality conditions discussed by Bollobas and Riordan. This demonstrates that explicit solutions of the self-duality conditions can be found using generators containing bonds and sites with independent probabilities. These solutions also provide new examples of lattices where exact percolation critical points are known. One of the generators exhibits three distinct criticality solutions (p, r, t). We carry out Monte-Carlo simulations of two of the generators on two different hypergraphs to confirm the critical values. For the case of the hypergraph and uniform generator studied by Wierman et al, we also determine the threshold p = 0.441 374 ± 0.000 001, which falls within the tight bounds that they derived. Furthermore, we consider a generator in which all or none of the vertices can connect, and find a soluble inhomogeneous percolation system that interpolates between site percolation on the union-jack lattice and bond percolation on the square lattice.
Protein evolution is structure dependent and non-homogeneous across the tree of life

Protein sequence evolution is a complex process that varies across the tree of life and among-sites within proteins. Comparing evolutionary rate matrices for specific taxa ('clade-specific models') can reveal this variation and provide information about the basis for changes in the paterns of protein evolution over time. However, clade-specific models can only provide this information if the variation among taxa exceeds the variation among proteins. We showed this to be the case by demonstrating that clade-specific model fit could distinguish among proteins from the four taxa that we examined (vertebrates, plants, oomycetes, and yeasts). Model fit classified proteins correctly by clade of origin >70% of the time. A relatively small number of dimensions can explain differences among models. If model parameters are averaged across all sites ~80% of the variance among models reflects clade; for models that consider protein structure ~50% of the variance reflected relative solvent accessibility and ~25% reflected clade. Relaxed purifying selection in taxa with smaller long-term effective population sizes appears to explain much of the among clade variance. Relaxed selection on solvent-exposed sites was correlated with the degree of change in amino acid side-chain volume for substitutions; other differences among models were more complex. Beyond the information they reveal about protein evolution, our clade-specific models also represent tools for phylogenomic inference. Availability: model files are available from htps://github.com/ebraun68/clade_specific_prot_models.
Thermal properties of graphene: Fundamentals and applications

Graphene is a two-dimensional (2D) material with over 100-fold anisotropy of heat flow between the in-plane and out-of-plane directions. High in-plane thermal conductivity is due to covalent sp2 bonding between carbon atoms, whereas out-of-plane heat flow is limited by weak van der Waals coupling. Herein, we review the thermal properties of graphene, including its specific heat and thermal conductivity (from diffusive to ballistic limits) and the influence of substrates, defects, and other atomic modifications. We also highlight practical applications in which the thermal properties of graphene play a role. For instance, graphene transistors and interconnects benefit from the high in-plane thermal conductivity, up to a certain channel length. However, weak thermal coupling with substrates implies that interfaces and contacts remain significant dissipation bottlenecks. Heat flow in graphene or graphene composites could also be tunable through a variety of means, including phonon scattering by substrates, edges, or interfaces. Ultimately, the unusual thermal properties of graphene stem from its 2D nature, forming a rich playground for new discoveries of heat-flow physics and potentially leading to novel thermal management applications.
Exceptional point engineered glass slide for microscopic thermal mapping

Thermal sensing with fine spatial resolution is important to the study of many scientific areas. While modern microscopy systems allow optical detection at high spatial resolution, their intrinsic functions are mainly focused on imaging but limited in detecting other physical parameters, for example, mapping thermal variations. Here, with a coating of an optical exceptional point structure, we demonstrate a low-cost but efficient multifunctional microscope slide, supporting real-time monitoring and mapping of temperature distribution and heat transport in addition to conventional microscopic imaging. The square-root dependency associated with an exceptional point leads to enhanced thermal sensitivity for precise temperature measurement. With a microscale resolution, real-time thermal mapping is conducted, showing dynamic temperature variation in a spatially defined area. Our strategy of integrating low-cost and efficient optical sensing technologies on a conventional glass slide enables simultaneous detection of multiple environmental parameters, producing improved experimental control at the microscale in various scientific disciplines.
Size Dependence of the Multiple Exciton Generation Rate in CdSe Quantum Dots

The multiplication rates of hot carriers in CdSe quantum dots are quantified using an atomistic pseudopotential approach and first-order perturbation theory. We consider both the case of an individual carrier (electron or hole) decaying into a trion and the case of an electron−hole pair decaying into a biexciton. The dependence on quantum dot volume of multiplication rate, density of final states, and effective Coulomb interaction are determined. We show that the multiplication rate of a photogenerated electron−hole pair decreases with dot size for a given absolute photon energy. However, if the photon energy is rescaled by the volume-dependent optical gap, then smaller dots exhibit an enhancement in carrier multiplication rate for a given relative photon energy. We find that holes have much higher multiplication rates than electrons of the same excess energy due to the larger density of final states (positive trions). When electron−hole pairs are generated by photon absorption, however, the net carrier m...
AUTOMATED CLASSIFICATION OF PERIODIC VARIABLE STARS DETECTED BY THE WIDE-FIELD INFRARED SURVEY EXPLORER

We describe a methodology to classify periodic variable stars identified using photometric time-series measurements constructed from the Wide-field Infrared Survey Explorer (WISE) full-mission single-exposure Source Databases. This will assist in the future construction of a WISE Variable Source Database that assigns variables to specific science classes as constrained by the WISE observing cadence with statistically meaningful classification probabilities. We have analyzed the WISE light curves of 8273 variable stars identified in previous optical variability surveys (MACHO, GCVS, and ASAS) and show that Fourier decomposition techniques can be extended into the mid-IR to assist with their classification. Combined with other periodic light-curve features, this sample is then used to train a machine-learned classifier based on the random forest (RF) method. Consistent with previous classification studies of variable stars in general, the RF machine-learned classifier is superior to other methods in terms of accuracy, robustness against outliers, and relative immunity to features that carry little or redundant class information. For the three most common classes identified by WISE: Algols, RR Lyrae, and W Ursae Majoris type variables, we obtain classification efficiencies of 80.7%, 82.7%, and 84.5% respectively using cross-validation analyses, with 95% confidence intervals of approximately ±2%. These accuracies are achieved at purity (or reliability) levels of 88.5%, 96.2%, and 87.8% respectively, similar to that achieved in previous automated classification studies of periodic variable stars.
A low-steering piezo-driven mirror

We present a piezo-driven translatable mirror with excellent pointing stability, capable of driving at frequencies up to tens of kilohertz. Our system uses a tripod of piezo actuators with independently controllable drive voltages, where the ratios of the individual drive voltages are tuned to minimize residual tilting. Attached to a standard ∅ = 12.7 mm mirror, the system has a resonance-free mechanical bandwidth up to 51 kHz, with displacements up to 2 μm at 8 kHz. The maximum static steering error is 5.5 μrad/μm displaced, and the dynamic steering error is lower than 0.6 μrad μm−1. This simple design should be useful for a large set of optical applications where tilt-free displacements are required, and we demonstrate its application in an ensemble of cold atoms trapped in periodically driven optical lattices.
ObjSim: lightweight automatic patch prioritization via object similarity

In the context of test case based automatic program repair (APR), patches that pass all the test cases but fail to fix the bug are called overfitted patches. Currently, patches generated by APR tools get inspected manually by the users to find and adopt genuine fixes. Being a laborious activity hindering widespread adoption of APR, automatic identification of overfitted patches has lately been the topic of active research. This paper presents engineering details of ObjSim: a fully automatic, lightweight similarity-based patch prioritization tool for JVM-based languages. The tool works by comparing the system state at the exit point(s) of patched method before and after patching and prioritizing patches that result in state that is more similar to that of original, unpatched version on passing tests while less similar on failing ones. Our experiments with patches generated by the recent APR tool PraPR for fixable bugs from Defects4J v1.4.0 show that ObjSim prioritizes 16.67% more genuine fixes in top-1 place. A demo video of the tool is located at https://bit.ly/2K8gnYV.
THE 2-GENERALIZED KNOT GROUP DETERMINES THE KNOT

Generalized knot groups Gn(K) were introduced independently by Kelly [5] and Wada [10]. We prove that G2(K) determines the unoriented knot type and sketch a proof of the same for Gn(K) for n > 2.
Probability models of chance fluctuations in spectra of astronomical sources with applications to X-ray absorption lines

The search for faint emission or absorption lines in astronomical spectra has received considerable attention in recent years, especially in the X-ray wavelength range. These features usually appea...
Cloud-scale VM-deflation for Running Interactive Applications On Transient Servers

Transient computing has become popular in public cloud environments for running delay-insensitive batch and data processing applications at low cost. Since transient cloud servers can be revoked at any time by the cloud provider, they are considered unsuitable for running interactive application such as web services. In this paper, we present VM deflation as an alternative mechanism to server preemption for reclaiming resources from transient cloud servers under resource pressure. Using real traces from top-tier cloud providers, we show the feasibility of using VM deflation as a resource reclamation mechanism for interactive applications in public clouds. We show how current hypervisor mechanisms can be used to implement VM deflation and present cluster deflation policies for resource management of transient and on-demand cloud VMs. Experimental evaluation of our deflation system on a Linux cluster shows that microservice-based applications can be deflated by up to 50% with negligible performance overhead. Our cluster-level deflation policies allow overcommitment levels as high as 50%, with less than a 1% decrease in application throughput, and can enable cloud platforms to increase revenue by 30%.
MAXIMIZING THE ExoEarth CANDIDATE YIELD FROM A FUTURE DIRECT IMAGING MISSION

ExoEarth yield is a critical science metric for future exoplanet imaging missions. Here we estimate exoEarth candidate yield using single visit completeness for a variety of mission design and astrophysical parameters. We review the methods used in previous yield calculations and show that the method choice can significantly impact yield estimates as well as how the yield responds to mission parameters. We introduce a method, called Altruistic Yield Optimization, that optimizes the target list and exposure times to maximize mission yield, adapts maximally to changes in mission parameters, and increases exoEarth candidate yield by up to 100% compared to previous methods. We use Altruistic Yield Optimization to estimate exoEarth candidate yield for a large suite of mission and astrophysical parameters using single visit completeness. We find that exoEarth candidate yield is most sensitive to telescope diameter, followed by coronagraph inner working angle, followed by coronagraph contrast, and finally coronagraph contrast noise floor. We find a surprisingly weak dependence of exoEarth candidate yield on exozodi level. Additionally, we provide a quantitative approach to defining a yield goal for future exoEarth-imaging missions.
Chaotic spin dynamics of a long nanomagnet driven by a current

We study the spin dynamics of a long nanomagnet driven by an electrical current. In the case of only dc current, the spin dynamics has a sophisticated bifurcation diagram of attractors. One type of attractors is a weak chaos. On the other hand, in the case of only ac current, the spin dynamics has a rather simple bifurcation diagram of attractors. That is, for small Gilbert damping, when the ac current is below a critical value, the attractor is a limit cycle; above the critical value, the attractor is chaotic (turbulent). For normal Gilbert damping, the attractor is always a limit cycle in the physically interesting range of the ac current. We also developed a Melnikov integral theory for a theoretical prediction on the occurrence of chaos. Our Melnikov prediction seems to be performing quite well in the dc case. In the ac case, our Melnikov prediction seems to be predicting transient chaos. The sustained chaotic attractor seems to have extra support from parametric resonance leading to a turbulent state.