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Screened modified gravity theories evade the solar system tests that have proved prohibitive for classical alternative gravity theories. In many cases, they do not fit into the PPN formalism. The environmental dependence of the screening has motivated a concerted effort to find new and novel probes of gravity using objects that are well-studied but have hitherto not been used to test gravity. Astrophysical objects---stars, galaxies, clusters---have proved competitive tools for this purpose since they occupy the partially-screened regime between solar system and the Hubble flow. In this article we review the current astrophysical tests of screened modified gravity theories. | astrophysics |
Accurately forecasting county level COVID-19 confirmed cases is crucial to optimizing medical resources. Forecasting emerging outbreaks pose a particular challenge because many existing forecasting techniques learn from historical seasons trends. Recurrent neural networks (RNNs) with LSTM-based cells are a logical choice of model due to their ability to learn temporal dynamics. In this paper, we adapt the state and county level influenza model, TDEFSI-LONLY, proposed in Wang et a. [l2020] to national and county level COVID-19 data. We show that this model poorly forecasts the current pandemic. We analyze the two week ahead forecasting capabilities of the TDEFSI-LONLY model with combinations of regularization techniques. Effective training of the TDEFSI-LONLY model requires data augmentation, to overcome this challenge we utilize an SEIR model and present an inter-county mixing extension to this model to simulate sufficient training data. Further, we propose an alternate forecast model, {\it County Level Epidemiological Inference Recurrent Network} (\alg{}) that trains an LSTM backbone on national confirmed cases to learn a low dimensional time pattern and utilizes a time distributed dense layer to learn individual county confirmed case changes each day for a two weeks forecast. We show that the best, worst, and median state forecasts made using CLEIR-Net model are respectively New York, South Carolina, and Montana. | statistics |
Two dimensional conformal field theories, can be described by their pseudo Goldstone bosons when the conformal symmetry is spontaneously and anomalously broken. We show that the Schwarzian action of these bosons leads to the Cardy formula without using modular invariance. As a result, the Cardy formula applies to conformal field theories on a cylinder and chiral theories in one dimension. This also explains why the Cardy--Verlinde formula for theories on $S^1 \times S^{d-2}$ can be written in the form of the Cardy formula of an effective two dimensional theory. | high energy physics theory |
We consider an open-string realisation of $\mathcal{N}=2\to \mathcal{N}=0$ spontaneous breaking of supersymmetry in four-dimensional Minkowski spacetime. It is based on type IIB orientifold theory compactified on $T^2\times T^4/\mathbb{Z}_2$, with Scherk--Schwarz supersymmetry breaking implemented along $T^2$. We show that in the regions of moduli space where the supersymmetry breaking scale is lower than the other scales, there exist configurations with minima that have massless Bose-Fermi degeneracy and hence vanishing one-loop effective potential, up to exponentially suppressed corrections. These backgrounds describe non-Abelian gauge theories, with all open-string moduli and blowing up modes of $T^4/\mathbb{Z}_2$ stabilized, while all untwisted closed-string moduli remain flat directions. Other backgrounds with strictly positive effective potentials exist, where the only instabilities arising at one loop are associated with the supersymmetry breaking scale, which runs away. All of these backgrounds are consistent non-perturbatively. | high energy physics theory |
We uncover an aspect of the Kibble--Zurek phenomenology, according to which the spectrum of critical exponents of a classical or quantum phase transition is revealed, by driving the system slowly in directions parallel to the phase boundary. This result is obtained in a renormalization group formulation of the Kibble--Zurek scenario, and based on a connection between the breaking of adiabaticity and the exiting of the critical domain via new relevant directions induced by the slow drive. The mechanism does not require fine tuning, in the sense that scaling originating from irrelevant operators is observable in an extensive regime of drive parameters. Therefore, it should be observable in quantum simulators or dynamically tunable condensed-matter platforms. | condensed matter |
Deep learning based methods have penetrated many image processing problems and become dominant solutions to these problems. A natural question raised here is "Is there any space for conventional methods on these problems?" In this paper, exposure interpolation is taken as an example to answer this question and the answer is "Yes". A framework on fusing conventional and deep learning method is introduced to generate an medium exposure image for two large-exposureratio images. Experimental results indicate that the quality of the medium exposure image is increased significantly through using the deep learning method to refine the interpolated image via the conventional method. The conventional method can be adopted to improve the convergence speed of the deep learning method and to reduce the number of samples which is required by the deep learning method. | electrical engineering and systems science |
As part of a quality control process in manufacturing it is often necessary to test whether all parts of a product satisfy a required property, with as few inspections as possible. When multiple inspection apparatuses with different costs and precision exist, it is desirable that testing can be carried out cost-effectively by properly controlling the trade-off between the costs and the precision. In this paper, we formulate this as a level set estimation (LSE) problem under cost-dependent input uncertainty - LSE being a type of active learning for estimating the level set, i.e., the subset of the input space in which an unknown function value is greater or smaller than a pre-determined threshold. Then, we propose a new algorithm for LSE under cost-dependent input uncertainty with theoretical convergence guarantee. We demonstrate the effectiveness of the proposed algorithm by applying it to synthetic and real datasets. | statistics |
To study the elastic properties of rod-like DNA nanostructures, we perform long simulations of these structure using the oxDNA coarse-grained model. By analysing the fluctuations in these trajectories we obtain estimates of the bend and twist persistence lengths, and the underlying bend and twist elastic moduli and couplings between them. Only on length scales beyond those associated with the spacings between the interhelix crossovers do the bending fluctuations behave like those of a worm-like chain. The obtained bending persistence lengths are much larger than that for double-stranded DNA and increase non-linearly with the number of helices, whereas the twist moduli increase approximately linearly. To within the numerical error in our data, the twist-bend coupling constants are of order zero. That the bending persistence lengths we obtain are generally somewhat higher than in experiment probably reflects both that the simulated origami have no assembly defects and that the oxDNA extensional modulus for double-stranded DNA is too large. | condensed matter |
White dwarfs are the remnants of low and intermediate mass stars. Because of electron degeneracy, their evolution is just a simple gravothermal process of cooling. Recently, thanks to Gaia data, it has been possible to construct the luminosity function of massive (0.9 < M/Msun < 1.1) white dwarfs in the solar neighborhood (d < 100 pc). Since the lifetime of their progenitors is very short, the birth times of both, parents and daughters, are very close and allow to reconstruct the (effective) star formation rate. This rate started growing from zero during the early Galaxy and reached a maximum 6-7 Gyr ago. It declined and ~5 Gyr ago started to climb once more reaching a maximum 2 - 3 Gyr in the past and decreased since then. There are some traces of a recent star formation burst, but the method used here is not appropriate for recently born white dwarfs. | astrophysics |
Observations with the Wisconsin H-alpha Mapper (WHAM) reveal a large, diffuse ionized halo that surrounds the Small Magellanic Cloud (SMC). We present the first kinematic H-alpha survey of an extended region around the galaxy, from (l,b) = (289.5,-35.0) to (315.1,-5.3) and covering +90 <= vLSR <= +210 km s-1. The ionized gas emission extends far beyond the central stellar component of the galaxy, reaching similar distances to that of the diffuse neutral halo traced by 21 cm observations. H-alpha emission extends several degrees beyond the sensitivity of current H I surveys toward smaller Galactic longitudes and more negative Galactic latitudes. The velocity field of the ionized gas near the SMC appears similar to to the neutral halo of the galaxy. Using the observed emission measure as a guide, we estimate the mass of this newly revealed ionized component to be roughly (0.8 - 1.0) x 10^9 M_sun, which is comparable to the total neutral mass in the same region of (0.9 - 1.1) x 10^9 M_sun. We find ratios of the total ionized gas mass divided by the total neutral plus ionized gas mass in three distinct subregions to be: (1) 46%-54% throughout the SMC and its extended halo, (2) 12%-32% in the SMC Tail that extends toward the Magellanic Bridge, and (3) 65%-79% in a filament that extends away from the SMC toward the Magellanic Stream. This newly discovered, coherent H-alpha filament does not appear to have a well-structured neutral component and is also not coincident with two previously identified filaments traced by 21 cm emission within the Stream. | astrophysics |
We introduce a very early universe model based on the thermodynamics of a gas of closed strings in a background which is non-perturbative in $\alpha'$. Upon considering the fully $\alpha'$-corrected equations extended to include certain anisotropic cosmological backgrounds, we describe the evolution of the system in three different stages parametrized by the gas' equation of state. Using standard string thermodynamical arguments, we start with an isotropic 10-dimensional universe inside the string scale and evolve it towards a universe with four large spacetime dimensions and six stabilized internal dimensions in the Einstein frame. | high energy physics theory |
Inspired by the easily scalable solution of peer evaluation in various domains that need an ever-growing body of material to be evaluated, e.g., in journal submissions, or in evaluating proposals for public funding, peer-grading has found widespread use in Massive Open Online Coursewares (MOOCs). Current peer-grading practices often rely on the goodwill of the peer evaluators for accuracy and fairness in the evaluation, while evaluators can be competitive or energy-saver. In this paper, we consider strategic graders and introduce a mechanism, TRUPEQA, that (a) uses a constant number of instructor-graded answer-scripts to quantitatively measure the accuracies of the peer graders and adjusts the finally assigned scores accordingly, and (b) penalizes deliberate under-performing. We show that this mechanism is unique in its class in satisfying certain properties desirable of a peer-grading mechanism. When the cost of evaluation is factored in, a modification of TRUPEQA implements the social optima in an equilibrium. We also run a peer-grading experiment in a classroom environment and find evidence that the final assigned grades are closer to the true grades under TRUPEQA than under the peer-grading mechanism currently used in popular MOOCs. | computer science |
A key challenge for reinforcement learning is solving long-horizon planning and control problems. Recent work has proposed leveraging programs to help guide the learning algorithm in these settings. However, these approaches impose a high manual burden on the user since they must provide a guiding program for every new task they seek to achieve. We propose an approach that leverages program synthesis to automatically generate the guiding program. A key challenge is how to handle partially observable environments. We propose model predictive program synthesis, which trains a generative model to predict the unobserved portions of the world, and then synthesizes a program based on samples from this model in a way that is robust to its uncertainty. We evaluate our approach on a set of challenging benchmarks, including a 2D Minecraft-inspired ``craft'' environment where the agent must perform a complex sequence of subtasks to achieve its goal, a box-world environment that requires abstract reasoning, and a variant of the craft environment where the agent is a MuJoCo Ant. Our approach significantly outperforms several baselines, and performs essentially as well as an oracle that is given an effective program. | computer science |
It is shown how the characteristic thermal effects that observers experience in space-times possessing an event horizon can manifest already in a simple quantum system with affine symmetry living on the real line. The derivation presented is essentially group theoretic in nature: a thermal state emerges naturally when comparing different representations of the group of affine transformations of the real line. The freedom in the choice of different notions of translation generators is the key to the Unruh effect "on a line" we describe. | high energy physics theory |
This paper is concerned with the classical two-species Lotka-Volterra diffusion system with strong competition. The sharp dynamical behavior of the solution is established in two different situations: either one species is an invasive one and the other is a native one or both are invasive species. Our results seem to be the first that provide a precise spreading speed and profile for such a strong competition system. Among other things, our analysis relies on the construction of new types of supersolution and subsolution, which are optimal in certain sense. | mathematics |
The spatiotemporal evolution of the field and plasma in the optical breakdown induced in the volume of transparent dielectric (fused silica) by the focused fs laser pulse is studied under condition of the so-called plasma-resonance-induced ionization instability that results in the deep small-scale periodic modulation of the breakdown plasma parameters in the direction of the laser polarization. In the framework of the model used, the optical electric field was calculated with allowance for the effects influencing both its long-scale structure (the beam focusing accounted for in the given-ray-tube approximation, phase and group delays, and back reflection) and the small-scale one (quasi-static enhancement in the plasma resonance regions). The plasma density evolution is described by the rate equation taking into account the photoionization, avalanche ionization, and ambipolar diffusion. Based on the fulfilled numerical calculations, we have described the main types of the breakdown wave originating in the focal region and have found the laser pulse intensity range where the instability evolving from very small seed perturbations leads to the formation of the contrast subwavelength periodic structure containing the number of the narrow zones with overcritical plasma density and enhanced energy deposition. The latter allows us to consider this structure as underlying the nanograting formation observed experimentally in the fused silica irradiated by series of repeated fs pulses. | physics |
We investigate the chiral electronic modes at the interface between two regions of a threefold topological semimetal, which is illuminated by left and right handed elliptically polarized waves. The radiation effects on the band structure of semimetal is analyzed by using Floquet theory. Two distinct solutions of the interface modes are found with the chirality depending on the phase of the irradiation. We also consider the anomalous Hall response which is attributed to the transition between dispersionless flat band and conic bands. | condensed matter |
We prove the generalized Franchetta conjecture for the locally complete family of hyper-K\"ahler eightfolds constructed by Lehn-Lehn-Sorger-van Straten. As a corollary, we establish the Beauville-Voisin conjecture for very general LLSS eightfolds. The strategy consists in reducing to the Franchetta property for relative fourth powers of cubic fourfolds, by using the recent description of LLSS eightfolds as moduli spaces of semistable objects in the Kuznetsov component of the derived category of cubic fourfolds, together with its generalization to the relative setting due to Bayer-Lahoz-Macr\`i-Nuer-Perry-Stellari. As a by-product, we compute the Chow motive of the Fano variety of lines on a smooth cubic hypersurface in terms of the Chow motive of the cubic hypersurface. | mathematics |
Is there oceanic superrotation on exoplanets? Atmospheric superrotation, characterized by west-to-east winds over the equator, is a common phenomenon in the atmospheres of Venus, Titan, Saturn, Jupiter, and tidally locked exoplanets. The stratospheric atmosphere of Earth is also superrotating during the westerly phase of the quasi-biennial oscillation (QBO). However, whether the same phenomenon can occur in ocean is poorly known. Through numerical simulations, here we show that oceanic superrotation does occur on tidally locked terrestrial planets around low-mass stars. Its formation (spun-up from rest) is associated with surface winds, the equatorward momentum convergence by Rossby waves, and the eastward propagation of Kelvin waves in the ocean. Its maintenance is driven by equatorward momentum transports of coupled Rossby-Kelvin waves in the ocean excited from the uneven stellar radiation distribution. The width of the superrotation is mainly constrained by the Rossby deformation radius in the ocean, while its strength is more complex. Many factors can influence the strength, including planetary rotation rate, stellar flux, greenhouse gas concentration, seawater salinity, bottom drag, and a scaling theory is lack. This work confirms that superrotation can occur on tidally locked terrestrial planets with seawater oceans and suggests that it may also occur on tidally locked hot planets with magma oceans that will possibly be observed in the near future. | astrophysics |
Considerable progress in experimental studies of atomic gases in a toroidal geometry has opened up novel prospects for the investigation of fundamental properties of superfluid states and creation of new configurations for atomtronic circuits. In particular, atomic Bose-Einstein condensates loaded in a dual-ring trap suggest a possibility to consider the tunneling dynamics between coupled condensates with different angular momenta. Accordingly, we address the tunneling in a pair of coaxial ring-shaped condensates separated by a horizontal potential barrier. A weak-coupling truncated (finite-mode) Galerkin model and direct numerical simulations of the underlying three-dimensional Gross-Pitaevskii equation are used for the analysis of tunneling superflows driven by an initial imbalance in atomic populations of the rings. The superflows through the Bose-Josephson junction are strongly affected by persistent currents which are present in the rings. Josephson oscillations of the population imbalance and angular momenta in the coupled rings are obtained for co-rotating states and non-rotating ones. On the other hand, the azimuthal structure of the tunneling flow implies formation of Josephson vortices (fluxons) with zero net current through the junction for hybrid states, built of counter-rotating persistent currents in the coupled rings. | condensed matter |
The goal of this paper is to obtain quantitative results on the number and on the size of maximal independent sets and maximal matchings in several block-stable graph classes that satisfy a proper sub-criticality condition. In particular we cover trees, cacti graphs and series-parallel graphs. The proof methods are based on a generating function approach and a proper singularity analysis of solutions of implicit systems of functional equations in several variables. As a byproduct, this method extends previous results of Meir and Moon for trees [Meir, Moon: On maximal independent sets of nodes in trees, Journal of Graph Theory 1988]. | mathematics |
Let $X$ be a right Hilbert module over a $C^*$-algebra $A$ equipped with the canonical operator space structure. We define an elementary operator on $X$ as a map $\phi : X \to X$ for which there exists a finite number of elements $u_i$ in the $C^*$-algebra $\mathbb{B}(X)$ of adjointable operators on $X$ and $v_i$ in the multiplier algebra $M(A)$ of $A$ such that $\phi(x)=\sum_i u_i xv_i$ for $x \in X$. If $X=A$ this notion agrees with the standard notion of an elementary operator on $A$. In this paper we extend Mathieu's theorem for elementary operators on prime $C^*$-algebras by showing that the completely bounded norm of each elementary operator on a non-zero Hilbert $A$-module $X$ agrees with the Haagerup norm of its corresponding tensor in $\mathbb{B}(X)\otimes M(A)$ if and only if $A$ is a prime $C^*$-algebra. | mathematics |
We provide a necessary and sufficient condition for a type D Temperley-Lieb algebra ${\rm TLD}_n(\delta)$ being semi-simple by studying branching rule for cell modules. As a byproduct, our result is used to study the so-called forked Temperley-Lieb algebra, which is a quotient algebra of ${\rm TLD}_n(\delta)$. | mathematics |
For active-sterile mixing to be responsible for the full relic abundance of dark matter additional new physics is needed beyond the keV-scale sterile neutrino itself. The extra ingredient we consider here is the presence of self-interactions among the sterile neutrinos. We examine whether active-to-sterile conversion is amplified enough in this scenario that the observed abundance of dark matter can be obtained with a subconstraint mixing angle. This turns out never to be the case in the region we explore: either self-interactions have too small an impact and cannot escape bounds on the mass and mixing angle, or they have too great an impact and cause dark matter to be overproduced. The sharp transition from marginal to excessive effectiveness occurs because a resonance criterion is met in the effective in-medium mixing angle. Once the system goes resonant the game is as good as over, as nonlinearity in the Boltzmann equation leads to runaway production of sterile neutrinos, beginning at a plasma temperature of a few hundred MeV and typically ending at a few tens of MeV. The scenario is therefore ruled out largely by its own dynamics. In this study we focus exclusively on mediators heavier than $\sim 1$ GeV; future work will extend the analysis to lighter mediators, allowing for contact to be made with the kinds of scenarios motivated by issues of small-scale structure. | high energy physics phenomenology |
Generative Adversarial Networks (GANs) have been used to model the underlying probability distribution of sample based datasets. GANs are notoriuos for training difficulties and their dependence on arbitrary hyperparameters. One recent improvement in GAN literature is to use the Wasserstein distance as loss function leading to Wasserstein Generative Adversarial Networks (WGANs). Using this as a basis, we show various ways in which the Wasserstein distance is estimated for the task of generative modelling. Additionally, the secrets in training such models are shown and summarized at the end of this work. Where applicable, we extend current works to different algorithms, different cost functions, and different regularization schemes to improve generative models. | computer science |
We study the implicit bias of AdaGrad on separable linear classification problems. We show that AdaGrad converges to a direction that can be characterized as the solution of a quadratic optimization problem with the same feasible set as the hard SVM problem. We also give a discussion about how different choices of the hyperparameters of AdaGrad might impact this direction. This provides a deeper understanding of why adaptive methods do not seem to have the generalization ability as good as gradient descent does in practice. | statistics |
Multi-scale convolutional neural networks (CNNs) achieve significant success in single image super-resolution (SISR), which considers the comprehensive information from different receptive fields. However, recent multi-scale networks usually aim to build the hierarchical exploration with different sizes of filters, which lead to high computation complexity costs, and seldom focus on the inherent correlations among different scales. This paper converts the multi-scale exploration into a sequential manner, and proposes a progressive multi-scale residual network (PMRN) for SISR problem. Specifically, we devise a progressive multi-scale residual block (PMRB) to substitute the larger filters with small filter combinations, and gradually explore the hierarchical information. Furthermore, channel- and pixel-wise attention mechanism (CPA) is designed for finding the inherent correlations among image features with weighting and bias factors, which concentrates more on high-frequency information. Experimental results show that the proposed PMRN recovers structural textures more effectively with superior PSNR/SSIM results than other small networks. The extension model PMRN$^+$ with self-ensemble achieves competitive or better results than large networks with much fewer parameters and lower computation complexity. | electrical engineering and systems science |
The standard nonperturbative approaches of renormalization group for tensor models are generally focused on a purely local potential approximation (i.e. involving only generalized traces and product of them) and are showed to strongly violate the modified Ward identities. This paper as a continuation of our recent contribution [Physical Review D 101, 106015 (2020)], intended to investigate the approximation schemes compatibles with Ward identities and constraints between $2n$-points observables in the large $N$-limit. We consider separately two different approximations: In the first one, we try to construct a local potential approximation from a slight modification of the Litim regulator, so that it remains optimal in the usual sense, and preserves the boundary conditions in deep UV and deep IR limits. In the second one, we introduce derivative couplings in the truncations and show that the compatibility with Ward identities implies strong relations between $\beta$-functions, allowing to close the infinite hierarchy of flow equations in the non-branching sector, up to a given order in the derivative expansion. Finally, using exact relation between correlations functions in large $N$-limit, we show that strictly local truncations are insufficient to reach the exact value for the critical exponent, highlighting the role played by these strong relations between observables taking into account the behavior of the flow; and the role played by the multi-trace operators, discussed in the two different approximation schemes. In both cases, we compare our conclusions to the results obtained in the literature and conclude that, at a given order, taking into account the exact functional relations between observables like Ward identities in a systematic way we can strongly improve the physical relevance of the approximation for exact RG equation. | high energy physics theory |
In expanding universes, the entanglement entropy must be time-dependent because the background geometry changes with time. For understanding time evolution of quantum correlations, we take into account two distinct holographic models, the dS boundary model and the braneworld model. In this work, we focus on two-dimensional expanding universes for analytic calculation and comparison. Although two holographic models realize expanding universes in totally different ways, we show that they result in the qualitatively same time-dependence for eternal inflation. We further investigate the time-dependent correlations in the radiation-dominated era of the braneworld model. Intriguingly, the holographic result reveals that a thermal system in the expanding universe is {\it dethermalized} after a critical time characterized by the subsystem size. | high energy physics theory |
Assessing population-level effects of vaccines and other infectious disease prevention measures is important to the field of public health. In infectious disease studies, one person's treatment may affect another individual's outcome, i.e., there may be interference between units. For example, use of bed nets to prevent malaria by one individual may have an indirect or spillover effect to other individuals living in close proximity. In some settings, individuals may form groups or clusters where interference only occurs within groups, i.e., there is partial interference. Inverse probability weighted estimators have previously been developed for observational studies with partial interference. Unfortunately, these estimators are not well suited for studies with large clusters. Therefore, in this paper, the parametric g-formula is extended to allow for partial interference. G-formula estimators are proposed of overall effects, spillover effects when treated, and spillover effects when untreated. The proposed estimators can accommodate large clusters and do not suffer from the g-null paradox that may occur in the absence of interference. The large sample properties of the proposed estimators are derived, and simulation studies are presented demonstrating the finite-sample performance of the proposed estimators. The Demographic and Health Survey from the Democratic Republic of the Congo is then analyzed using the proposed g-formula estimators to assess the overall and spillover effects of bed net use on malaria. | statistics |
With the largest dish Five-hundred-meter Aperture Spherical radio Telescope (FAST), both the mean and single pulses of PSR B2016$+$28, especially including the single-pulse structure, are investigated in detail in this study. The mean pulse profiles at different frequencies can be well fitted in a conal model, and the peak separation of intensity-dependent pulse profiles increases with intensity. The integrated pulses are obviously frequency dependent (pulse width decreases by $\sim\,20\%$ as frequency increases from 300 MHz to 750 MHz), but the structure of single pulses changes slightly (the corresponding correlation scale decreases by only $\sim\,1\%$). This disparity between mean and single pulses provides independent evidence for the existence of the RS-type vacuum inner gap, indicating a strong bond between particles on the pulsar surface. Diffused drifting sub-pulses are analyzed. The results show that the modulation period along pulse series ($P_3$) is positively correlated to the separation between two adjacent sub-pulses ($P_2$). This correlation may hint a rough surface on the pulsar, eventually resulting in the irregular drift of sparks. All the observational results may have significant implications in the dynamics of pulsar magnetosphere and are discussed extensively in this paper. | astrophysics |
Ensembles of decision trees perform well on many problems, but are not interpretable. In contrast to existing approaches in interpretability that focus on explaining relationships between features and predictions, we propose an alternative approach to interpret tree ensemble classifiers by surfacing representative points for each class -- prototypes. We introduce a new distance for Gradient Boosted Tree models, and propose new, adaptive prototype selection methods with theoretical guarantees, with the flexibility to choose a different number of prototypes in each class. We demonstrate our methods on random forests and gradient boosted trees, showing that the prototypes can perform as well as or even better than the original tree ensemble when used as a nearest-prototype classifier. In a user study, humans were better at predicting the output of a tree ensemble classifier when using prototypes than when using Shapley values, a popular feature attribution method. Hence, prototypes present a viable alternative to feature-based explanations for tree ensembles. | statistics |
Understanding the intricate properties of one-dimensional quantum systems coupled to multiple reservoirs poses a challenge to both analytical approaches and simulation techniques. Fortunately, density matrix renormalization group-based tools, which have been widely used in the study of closed systems, have also been recently extended to the treatment of open systems. We present an implementation of such method based on state-of-the-art matrix product state (MPS) and tensor network methods, that produces accurate results for a variety of combinations of parameters. Unlike most approaches, which use the time-evolution to reach the steady-state, we focus on an algorithm that is time-independent and focuses on recasting the problem in exactly the same language as the standard Density Matrix Renormalization Group (DMRG) algorithm, initially put forward by M. C. Ba\~nuls et al. in Phys. Rev. Lett. 114, 220601 (2015). Hence, it can be readily exported to any of the available DMRG platforms. We show that this implementation is suited for studying thermal transport in one-dimensional systems. As a case study, we focus on the XXZ quantum spin chain and benchmark our results by comparing the spin current and magnetization profiles with analytical results. We then explore beyond what can be computed analytically. Our code is freely available on github at https://www.github.com/heitorc7/oDMRG. | quantum physics |
We deal with a set of autonomous robots moving on an infinite grid. Those robots are opaque, have limited visibility capabilities, and run using synchronous Look-Compute-Move cycles. They all agree on a common chirality, but have no global compass. Finally, they may use lights of different colors, but except from that, robots have neither persistent memories, nor communication mean. We consider the infinite grid exploration (IGE) problem. For this problem we give two impossibility results and three algorithms, including one which is optimal in terms of number of robots. In more detail, we first show that two robots are not sufficient in our settings to solve the problem, even when robots have a common coordinate system. We then show that if the robots' coordinate systems are not self-consistent, three or four robots are not sufficient to solve the problem. Finally, we present three algorithms that solve the IGE problem in various settings. The first algorithm uses six robots with constant colors and a visibility range of one. The second one uses the minimum number of robots, i.e., five, as well as five modifiable colors, still under visibility one. The last algorithm requires seven oblivious anonymous robots, yet assuming visibility two. Notice that the two last algorithms also satisfy achieve exclusiveness. | computer science |
The paper considers the problem of multi-agent consensus in the presence of adversarial agents which may try to prevent and introduce undesired influence on the coordination among the regular agents. To our setting, we extend the so-called mean subsequence reduced algorithms with the aim to reduce the amount of communication via two measures: The agents exchange information in the form of ternary data at each transmission and moreover keep the frequency of data exchange low by employing self- and event-triggered communication. We will observe that in hostile environments with adversaries, the self-triggered approach can bring certain advantages over the event-triggered counterpart. | electrical engineering and systems science |
Quantum control of atoms at ultrashort distances from surfaces would open a new paradigm in quantum optics and offer a novel tool for the investigation of near-surface physics. Here, we investigate the motional states of atoms that are bound weakly to the surface of a hot optical nanofiber. We theoretically demonstrate that with optimized mechanical properties of the nanofiber these states are quantized despite phonon-induced decoherence. We further show that it is possible to influence their properties with additional nanofiber-guided light fields and suggest heterodyne fluorescence spectroscopy to probe the spectrum of the quantized atomic motion. Extending the optical control of atoms to smaller atom-surface separations could create opportunities for quantum communication and instigate the convergence of surface physics, quantum optics, and the physics of cold atoms. | quantum physics |
We consider linear magneto-quasistatic field equations which arise in simulation of low-frequency electromagnetic devices coupled to electrical circuits. A finite element discretization of such equations on 3D domains leads to a singular system of differential-algebraic equations. First, we study the structural properties of such a system and present a new regularization approach based on projecting out the singular state components. Furthermore, we present a Lyapunov-based balanced truncation model reduction method which preserves stability and passivity. By making use of the underlying structure of the problem, we develop an efficient model reduction algorithm. Numerical experiments demonstrate its performance on a test example. | mathematics |
We consider the design of two-pass voice trigger detection systems. We focus on the networks in the second pass that are used to re-score candidate segments obtained from the first-pass. Our baseline is an acoustic model(AM), with BiLSTM layers, trained by minimizing the CTC loss. We replace the BiLSTM layers with self-attention layers. Results on internal evaluation sets show that self-attention networks yield better accuracy while requiring fewer parameters. We add an auto-regressive decoder network on top of the self-attention layers and jointly minimize the CTC loss on the encoder and the cross-entropy loss on the decoder. This design yields further improvements over the baseline. We retrain all the models above in a multi-task learning(MTL) setting, where one branch of a shared network is trained as an AM, while the second branch classifies the whole sequence to be true-trigger or not. Results demonstrate that networks with self-attention layers yield $\sim$60% relative reduction in false reject rates for a given false-alarm rate, while requiring 10% fewer parameters. When trained in the MTL setup, self-attention networks yield further accuracy improvements. On-device measurements show that we observe 70% relative reduction in inference time. Additionally, the proposed network architectures are $\sim$5X faster to train. | electrical engineering and systems science |
The rise of IoT devices has led to the proliferation of smart buildings, offices, and homes worldwide. Although commodity IoT devices are employed by ordinary end-users, complex environments such as smart buildings, smart offices, conference rooms, or hospitality require customized and highly reliable solutions. Those systems called Enterprise Internet of Things (EIoT) connect such environments to the Internet and are professionally managed solutions usually offered by dedicated vendors. As EIoT systems require specialized training, software, and equipment to deploy, this has led to very little research investigating the security of EIoT systems and their components. In effect, EIoT systems in smart settings such as smart buildings present an unprecedented and unexplored threat vector for an attacker. In this work, we explore EIoT system vulnerabilities and insecure development practices. Specifically, focus on the usage of drivers as an attack mechanism, and introduce PoisonIvy, a number of novel attacks that demonstrate an attacker can easily compromise EIoT system controllers using malicious drivers. Specifically, we show how drivers used to integrate third-party devices to EIoT systems can be misused in a systematic fashion. To demonstrate the capabilities of attackers, we implement and evaluate PoisonIvy using a testbed of real EIoT devices. We show that an attacker can perform DoS attacks, gain remote control, and maliciously abuse system resources of EIoT systems. To the best of our knowledge, this is the first work to analyze the (in)securities of EIoT deployment practices and demonstrate the associated vulnerabilities in this ecosystem. With this work, we raise awareness on the (in)secure development practices used for EIoT systems, the consequences of which can largely impact the security, privacy, reliability, and performance of millions of EIoT systems worldwide. | computer science |
The paper is devoted to the consequences of blind random selection of items from different item populations that might be based on completely uncorrelated factors for item inter-correlations and corresponding factor loadings. Based on the model of essentially parallel measurements, we explore the consequences of presenting items from different populations across individuals and items from identical populations within each individual for the factor model and item inter-correlations in the total population of individuals. Moreover, we explore the consequences of presenting items from different as well as identical item populations across and within individuals. We show that correlations can be substantial in the total population of individuals even when -- in subpopulations of individuals -- items are drawn from populations with uncorrelated factors. In order to address this challenge for the validity of a scale, we propose a method that helps to detect whether item inter-correlations result from different item populations in different subpopulations of individuals and evaluate the method by means of a simulation study. Based on the analytical results and on results from a simulation study, we provide recommendations for the detection of subpopulations of individuals responding to items from different item populations. | statistics |
Time it takes to travel from one position to another, devoid of any quantum mechanical description, has been modeled variously, especially for quantum tunneling. The model time, if universally valid, must be subluminal, must hold everywhere (inside and outside the tunneling region), must comprise interference effects, and must have a sensible classical limit. Here we show that the quantum travel time, hypothesized to emerge with the state vector, is a function of the probability density and probability current such that all the criteria above are fulfilled. We compute it inside and outside a rectangular potential barrier and find physically sensible results. Moreover, we contrast it with recent ionization time measurements of the $\rm He$ as well as the $\rm Ar$ and $\rm Kr$ atoms, and find good agreement with data. The quantum travel time holds good for stationary systems, and can have applications in numerous tunneling-driven phenomena. | quantum physics |
Thanks to their continuous cooling and relative simplicity, white dwarf stars are routinely used to measure the ages of stellar populations. The usefulness of white dwarfs as cosmochronometers depends on the availability of accurate cooling models. A key ingredient of those models are the conductive opacities, which largely govern the cooling rate. In this work, we present improved conductive opacities for the regime of moderate coupling and moderate degeneracy that characterizes an important portion of the envelopes of DA and DB white dwarfs. We find differences of up to a factor 3 between our calculations and the commonly used opacities of Cassisi et al. (2007), which we attribute to an improved account of electron-electron scattering. The cooling models are strongly affected by those changes in the conductive opacities: the age of a 4000 K white dwarf can be reduced by as much as 2 Gyr. We provide analytical fits to our new opacities to facilitate the implementation of this important effect in white dwarf evolution codes. | astrophysics |
Using the Keck Cosmic Web Imager we obtain spectra of several globular clusters (GCs), ultra compact dwarfs (UCDs) and the inner halo starlight of M87, at a similar projected galactocentric radius of $\sim$5 kpc. This enables us, for the first time, to apply the same stellar population analysis to the GCs, UCDs and starlight consistently to derive ages, metallicities and alpha-element abundances in M87. We find evidence for a dual stellar population in the M87 halo light, i.e an $\sim$80\% component by mass which is old and metal-rich and a $\sim$20\% component which is old but metal-poor. Two red GCs share similar stellar populations to the halo light suggesting they may have formed contemporaneously with the dominant halo component. Three UCDs, and one blue GC, have similar stellar populations, with younger mean ages, lower metallicities and near solar alpha-element abundances. Combined with literature data, our findings are consistent with the scenario that UCDs are the remnant nucleus of a stripped galaxy. We further investigate the discrepancy in the literature for M87's kinematics at large radii, favouring a declining velocity dispersion profile. This work has highlighted the need for more self-consistent studies of galaxy halos. | astrophysics |
We investigated the influence of oxygen over-stoichiometry on apical oxygen disorder and magnetic correlations in Nd2NiO4+d (d~0.11) in the temperature range of 2-300 K by means of synchrotron x-ray powder diffraction, neutron single crystal and powder diffraction studies, combined with macroscopic magnetic measurements. In the investigated temperature range, the compound crystalizes in a tetragonal commensurate structure with the P42/ncm space group with excess oxygen atoms occupy the 4b (3/4 1/4 1/4) interstitial sites, coordinated by four apical oxygen atoms. Large and anisotropic thermal displacement parameters are found for equatorial and apical oxygen atoms, which are strongly reduced on an absolute scale compared to the Nd2NiO4.23 phase. Maximum Entropy analysis of the neutron single crystal diffraction data uncovered anharmonic contributions to the displacement parameters of the apical oxygen atoms, toward the nearest vacant 4b interstitial site, related to the phonon assisted oxygen diffusion mechanism. Macroscopic magnetization measurements and neutron powder diffraction studies reveal long-range antiferromagnetic ordering of the Ni-sublattice at TN ~ 53 K with a weak ferromagnetic component along the c-axis, while the long-range magnetic ordering of the Nd-sublattice occurs below 10 K. Temperature dependent neutron diffraction patterns show the appearance of a commensurate magnetic order at TN with the propagation vector k = (100) and the emergence of an additional incommensurate phase below 30 K, while both phases coexist at 2 K. The commensurate magnetic structure is best described by the P42/nc`m` Shubnikov space group. Refined magnetic moments of the Ni and Nd-sites at 2 K are 1.144(76) muB and 1.632(52) muB respectively. A possible origin of the incommensurate phase is discussed and a tentative magnetic phase diagram is proposed. | condensed matter |
To understand typical dynamics of an open quantum system in continuous time, we introduce an ensemble of random Lindblad operators, which generate Markovian completely positive evolution in the space of density matrices. Spectral properties of these operators, including the shape of the spectrum in the complex plane, are evaluated by using methods of free probabilities and explained with non-Hermitian random matrix models. We also demonstrate universality of the spectral features. The notion of ensemble of random generators of Markovian qauntum evolution constitutes a step towards categorization of dissipative quantum chaos. | quantum physics |
We explore the orbital dynamics of systems consisting of three planets, each as massive as the Earth, on coplanar, initially circular, orbits about a star of one solar mass. The initial semimajor axes of the planets are equally spaced in terms of their mutual Hill radius, which is equivalent to a geometric progression of orbital periods for small planets of equal mass. Our simulations explore a wide range of spacings of the planets, and were integrated for virtual times of up to 10 billion years or until the orbits of any pair of planets crossed. We find the same general trend of system lifetimes increasing exponentially with separation between orbits seen by previous studies of systems of three or more planets. One focus of this paper is to go beyond the rough trends found by previous numerical studies and quantitatively explore the nature of the scatter in lifetimes and the destabilizing effects of mean motion resonances. In contrast to previous results for five-planet systems, a nontrivial fraction of three-planet systems survive at least several orders of magnitude longer than most other systems with similar initial separation between orbits, with some surviving $10^{10}$ years at much smaller orbital separations than any found for five-planet systems. Substantial shifts in the initial planetary longitudes cause a scatter of roughly a factor of two in system lifetime, whereas the shift of one planet's initial position by 100 meters along its orbit results in smaller changes in the logarithm of the time to orbit crossing, especially for systems with short lifetimes. | astrophysics |
We study dynamical supersymmetry breaking in supersymmetric QCD theories for $N_f<N_c$. We consider a model with a singlet chiral superfield coupled to the infrared meson chiral superfield through a classical superpotential. We examine the vacuum structure of this model and show that in a particular limit of the parameter space with the large $N_c$ limit, it has a vacuum that dynamically breaks supersymmetry. The supersymmetric vacuum, in this limit, is being pushed to infinity. | high energy physics theory |
We study a multi-armed bandit problem with covariates in a setting where there is a possible delay in observing the rewards. Under some mild assumptions on the probability distributions for the delays and using an appropriate randomization to select the arms, the proposed strategy is shown to be strongly consistent. | statistics |
Gallai asked in 1984 if any $k$-critical graph on $n$ vertices contains at least $n$ distinct $(k-1)$-critical subgraphs. The answer is trivial for $k\leq 3$. Improving a result of Stiebitz, Abbott and Zhou proved in 1995 that for all $k\geq 4$, such graph contains $\Omega(n^{1/(k-1)})$ distinct $(k-1)$-critical subgraphs. Since then no progress had been made until very recently, Hare resolved the case $k=4$ by showing that any $4$-critical graph on $n$ vertices contains at least $(8n-29)/3$ odd cycles. In this paper, we mainly focus on 4-critical graphs and develop some novel tools for counting cycles of specified parity. Our main result shows that any $4$-critical graph on $n$ vertices contains $\Omega(n^2)$ odd cycles, which is tight up to a constant factor by infinite many graphs. As a crucial step, we prove the same bound for 3-connected non-bipartite graphs, which may be of independent interest. Using the tools, we also give a very short proof for the case $k=4$. Moreover, we improve the longstanding lower bound of Abbott and Zhou to $\Omega(n^{1/(k-2)})$ for the general case $k\geq 5$. We will also discuss some related problems on $k$-critical graphs in the final section. | mathematics |
A fiber withdrawn from a bath of a dilute particulate suspension exhibits different coating regimes depending on the physical properties of the fluid, the withdrawal speed, the particle sizes, and the radius of the fiber. Our experiments indicate that only the liquid without particles is entrained for thin coating films. Beyond a threshold capillary number, the fiber is coated by a liquid film with entrained particles. We systematically characterize the role of the capillary number, the particle size, and the fiber radius on the threshold speed for particle entrainment. We discuss the boundary between these two regimes and show that the thickness of the liquid film at the stagnation point controls the entrainment process. The radius of the fiber provides a new degree of control in capillary filtering, allowing greater control over the size of the particles entrained in the film. | physics |
We generalize the notion of an asymptotic weak coupling expansion about an exactly solvable model in quantum mechanics and quantum field theory to an all positive value coupling convergent expansion. This is done by rescaling the variables available in the theory by free parameters, then adding and subtracting the exactly solvable model. The rest (initial rescaled theory by free parameters + the subtracted exactly solvable model) is expanded about the added exactly solvable model. Evaluating finite orders of this expansion at its extremum points with respect to the free parameter(s) gives a sequence that converges to the result of the previous asymptotic expansion, with a good convergence rate, at relative strong coupling. We solve for the eigenenergies of the anharmonic, pure anharmonic and double well potential problems using this method by expanding about the symmetrical point of these potentials. Accurate results for the eigenenergies can be obtained for all positive values of the coupling for the anharmonic and pure anharmonic oscillators and at strong coupling for the double well potential. To provide confirmation for the convergent formalism developed for $\phi^4$ theory and QED we improve the electron g-factor calculation at the one loop level using the convergent formalism. Applications of this method are not limited to quantum mechanics or quantum field theory, for example it can also have applications in the context of differential equations. | high energy physics theory |
Multiple scattering and induced parton splitting lead to a medium modification of the QCD evolution for jet fragmentation functions and the final hadron spectra. Medium-induced parton splittings not only lead to energy loss of leading partons and suppression of leading hadron spectra, but also modify the flavor composition of a jet due to induced flavor conversion via gluon emission, quark pair production and annihilation. Through a numerical study of the medium-modified QCD evolution, leading $K^-$ strange meson spectra are found to be particularly sensitive to the induced flavor conversion in semi-inclusive deeply inelastic scatterings (SIDIS) off a large nucleus. The induced flavor conversion can lead to increased number of gluons and sea quarks in a jet and, as a consequence, enhance the leading $K^-$ spectra to counter the effect of parton energy loss in SIDIS with large momentum fractions $x_B$ where the struck quarks are mostly valence quarks of the nucleus. | high energy physics phenomenology |
This work considers the problem of control and resource scheduling in networked systems. We present DIRA, a Deep reinforcement learning based Iterative Resource Allocation algorithm, which is scalable and control-aware. Our algorithm is tailored towards large-scale problems where control and scheduling need to act jointly to optimize performance. DIRA can be used to schedule general time-domain optimization based controllers. In the present work, we focus on control designs based on suitably adapted linear quadratic regulators. We apply our algorithm to networked systems with correlated fading communication channels. Our simulations show that DIRA scales well to large scheduling problems. | computer science |
Automatic analysis of spatio-temporal microscopy images is inevitable for state-of-the-art research in the life sciences. Recent developments in deep learning provide powerful tools for automatic analyses of such image data, but heavily depend on the amount and quality of provided training data to perform well. To this end, we developed a new method for realistic generation of synthetic 2D+t microscopy image data of fluorescently labeled cellular nuclei. The method combines spatiotemporal statistical shape models of different cell cycle stages with a conditional GAN to generate time series of cell populations and provides instance-level control of cell cycle stage and the fluorescence intensity of generated cells. We show the effect of the GAN conditioning and create a set of synthetic images that can be readily used for training and benchmarking of cell segmentation and tracking approaches. | electrical engineering and systems science |
Semi-supervised learning via learning from limited quantities of labeled data has been investigated as an alternative to supervised counterparts. Maximizing knowledge gains from copious unlabeled data benefit semi-supervised learning settings. Moreover, learning multiple tasks within the same model further improves model generalizability. We propose a novel multitask learning model, namely MultiMix, which jointly learns disease classification and anatomical segmentation in a sparingly supervised manner, while preserving explainability through bridge saliency between the two tasks. Our extensive experimentation with varied quantities of labeled data in the training sets justify the effectiveness of our multitasking model for the classification of pneumonia and segmentation of lungs from chest X-ray images. Moreover, both in-domain and cross-domain evaluations across the tasks further showcase the potential of our model to adapt to challenging generalization scenarios. | computer science |
Bitcoin is a peer-to-peer electronic cash system invented by Nakamoto in 2008. While it has attracted much research interest, its exact latency and security properties remain open. Existing analyses provide security and latency (or confirmation time) guarantees that are too loose for practical use. In fact the best known upper bounds are several orders of magnitude larger than the well-known private-mining lower bounds. This paper describes a continuous-time model for blockchains and develops a rigorous analysis that yields very close upper and lower bounds for the latency--security trade-off. For example, when the adversary controls 10% of the total mining power and the block propagation delays are within 10 seconds, a Bitcoin block is secured with less than $10^{-3}$ error probability after 5 hours 20 minutes of confirmation time, or with less than $10^{-10}$ error probability after 12 hours 15 minutes. These confirmation times are merely a few hours away from their corresponding lower bounds. To establish the tight results, the mining of some special blocks are shown to be renewal processes. The moment generation functions of their inter-arrival times are derived in closed form. The general results are applied to study the latency--security trade-off of several well-known proof-of-work longest-chain cryptocurrencies. Guidance is also provided on how to set parameters for different purposes. | computer science |
Wildland fire smoke exposures present an increasingly severe threat to public health, and thus there is a growing need for studying the effects of protective behaviors on improving health. Emerging smartphone applications provide unprecedented opportunities to study this important problem, but also pose novel challenges. Smoke Sense, a citizen science project, provides an interactive platform for participants to engage with a smartphone app that records air quality, health symptoms, and behaviors taken to reduce smoke exposures. We propose a new, doubly robust estimator of the structural nested mean model that accounts for spatially- and time-varying effects via a local estimating equation approach with geographical kernel weighting. Moreover, our analytical framework is flexible enough to handle informative missingness by inverse probability weighting of estimating functions. We evaluate the new method using extensive simulation studies and apply it to Smoke Sense survey data collected from smartphones for a better understanding of the relationship between smoke preventive measures and health effects. Our results estimate how the protective behaviors' effects vary over space and time and find that protective behaviors have more significant effects on reducing health symptoms in the Southwest than the Northwest region of the USA. | statistics |
During a geosteering operation the well path is intentionally adjusted in response to the new data acquired while drilling. To achieve consistent high-quality decisions, especially when drilling in complex environments, decision support systems can help cope with high volumes of data and interpretation complexities. They can assimilate the real-time measurements into a probabilistic earth model and use the updated model for decision recommendations. Recently, machine learning (ML) techniques have enabled a wide range of methods that redistribute computational cost from on-line to off-line calculations. In this paper, we introduce two ML techniques into the geosteering decision support framework. Firstly, a complex earth model representation is generated using a Generative Adversarial Network (GAN). Secondly, a commercial extra-deep electromagnetic simulator is represented using a Forward Deep Neural Network (FDNN). The numerical experiments demonstrate that the combination of the GAN and the FDNN in an ensemble randomized maximum likelihood data assimilation scheme provides real-time estimates of complex geological uncertainty. This yields reduction of geological uncertainty ahead of the drill-bit from the measurements gathered behind and around the well bore. | statistics |
We report the structural and magnetic ground state properties of the monoclinic compound barium iridium oxide Ba$_4$Ir$_3$O$_{10}$ using a combination of resonant x-ray scattering, magnetometry, and thermodynamic techniques. Magnetic susceptibility exhibits a pronounced antiferromagnetic transition at $T_{\text{N}}$ $\approx$ 25K, a weaker anomaly at $T_{\text{S}}$ $\approx$ 142K, and strong magnetic anisotropy at all temperatures. Resonant elastic x-ray scattering experiments reveal a second order structural phase transition at $T_{\text{S}}$ and a magnetic transition at $T_{\text{N}}$. Both structural and magnetic superlattice peaks are observed at $L$ = half integer values. The magnetization anomaly at $T_{\text{S}}$ implies the presence of magneto-elastic coupling, which conceivably facilitates the symmetry lowering. Mean field critical scattering is observed above $T_{\text{S}}$. The magnetic structure of the antiferromagnetic ground state is discussed based on the measured magnetic superlattice peak intensity. Our study not only presents essential information for understanding the intertwined structural and magnetic properties in Ba$_4$Ir$_3$O$_{10}$, but also highlights the necessary ingredients for exploring novel ground states with octahedra trimers. | condensed matter |
Batch Normalization (BN) is a common technique used to speed-up and stabilize training. On the other hand, the learnable parameters of BN are commonly used in conditional Generative Adversarial Networks (cGANs) for representing class-specific information using conditional Batch Normalization (cBN). In this paper we propose to generalize both BN and cBN using a Whitening and Coloring based batch normalization. We show that our conditional Coloring can represent categorical conditioning information which largely helps the cGAN qualitative results. Moreover, we show that full-feature whitening is important in a general GAN scenario in which the training process is known to be highly unstable. We test our approach on different datasets and using different GAN networks and training protocols, showing a consistent improvement in all the tested frameworks. Our CIFAR-10 conditioned results are higher than all previous works on this dataset. | statistics |
We compute the real-radiation corrections to Higgs boson pair production at next-to-next-to-leading order in QCD, in an expansion for large top quark mass. We concentrate on the radiative corrections to the interference contribution from the next-to-leading order one-particle reducible and the leading order amplitudes. This is a well defined and gauge invariant subset of the full real-virtual corrections to the inclusive cross section. We obtain analytic results for all phase-space master integrals both as an expansion around the threshold and in an exact manner in terms of Goncharov polylogarithms. | high energy physics phenomenology |
For a given pre-cubical set ($\square$--set) $K$ with two distinguished vertices $\bO$, $\bI$, we prove that the space $\vP(K)_\bO^\bI$ of d-paths on the geometric realization of $K$ with source $\bO$ and target $\bI$ is homotopy equivalent to its subspace $\vP^t(K)_\bO^\bI$ of tame d-paths. When $K$ is the underlying $\square$--set of a Higher Dimensional Automaton $A$, tame d-paths on $K$ represent step executions of $A$. Then, we define the cube chain category of $K$ and prove that its nerve is weakly homotopy equivalent to $\vP(K)_\bO^\bI$. | mathematics |
Contributions: Prior studies on education have mostly followed the model of the cross sectional study, namely, examining the pretest and the posttest scores. This paper shows that students' knowledge throughout the intervention can be estimated by time series analysis using a hidden Markov model. Background: Analyzing time series and the interaction between the students and the game data can result in valuable information that cannot be gained by only cross sectional studies of the exams. Research Questions: Can a hidden Markov model be used to analyze the educational games? Can a hidden Markov model be used to make a prediction of the students' performance? Methodology: The study was conducted on (N=854) students who played the Save Patch game. Students were divided into class 1 and class 2. Class 1 students are those who scored lower in the test than class 2 students. The analysis is done by choosing various features of the game as the observations. Findings: The state trajectories can predict the students' performance accurately for both class 1 and class 2. | statistics |
Recent analyses of the diffuse TeV-PeV neutrino flux highlight a tension between different Ice-Cube data samples that strongly suggests a two-component scenario rather than a single steep power-law flux. Such a tension is further strengthened once the latest ANTARES data are also taken into account. Remarkably, both experiments show an excess in the same energy range (40-200 TeV), whose origin could intriguingly be related to dark matter. In this paper, I discuss the combined analysis of IceCube and ANTARES data, highlighting the presence of the low-energy excess. Moreover, I update the results of the angular analysis for potential dark matter signals, previously obtained with the 4-year High-Energy Starting Events data. In particular, I statistically compare the distribution of the arrival directions of 6-year IceCube events belonging to the low-energy excess with the angular distributions expected in case of different dark matter neutrino signals. | high energy physics phenomenology |
We consider the filtering problem of estimating a hidden random variable $X$ by noisy observations. The noisy observation process is constructed by a randomised Markov bridge (RMB) $(Z_t)_{t\in [0,T]}$ of which terminal value is set to $Z_T=X$. That is, at the terminal time $T$, the noise of the bridge process vanishes and the hidden random variable $X$ is revealed. We derive the explicit filtering formula, governing the dynamics of the conditional probability process, for a general RMB. It turns out that the conditional probability is given by a function of current time $t$, the current observation $Z_t$, the initial observation $Z_0$, and the a priori distribution $\nu$ of $X$ at $t=0$. As an example for an RMB we explicitly construct the skew-normal randomised diffusion bridge and show how it can be utilised to extend well-known commodity pricing models and how one may propose novel stochastic price models for financial instruments linked to greenhouse gas emissions. | mathematics |
Is there any entanglement in the simplest ubiquitous bound system? We study the solutions to the time-independent Schr\"odinger equation for a Hydrogenic system and devise two entanglement tests for free and localised states. For free Hydrogenic systems, we compute the Schmidt basis diagonalisation for general energy eigenstates, and for a Hydrogenic system localised to a three-dimensional Gaussian wavepacket, we demonstrate that measuring its second moments is sufficient for detecting entanglement. Our results apply to any system that exhibits Hydrogenic structure. | quantum physics |
From the entropy argument for the dS swampland conjecture which connects the Gibbons-Hawking entropy bound with the distance conjecture, we find the entropic quasi-dS instability time given by $1/(\sqrt{\epsilon_H}H)\log(m_{\rm Pl}/H)$ as the lifetime of quasi-dS spacetime. It depends on the slow-roll parameter, and contains the logarithmic factor $\log(m_{\rm Pl}/H)$ which can be found in the scrambling (or decoherence) time as well. Such a logarithmic factor enhances the geodesic distance of the modulus from the mere Planck scale, and also possibly relaxes the bound on $m_{\rm Pl}^2 \nabla^2 V/V$. | high energy physics theory |
We derive the covariant Poisson's equation of (d+1)-dimensional Newton-Cartan gravity with (twistless) torsion by applying the `non-relativistic conformal method' introduced in arXiv:1512.06277. We apply this method on-shell to a Schr\"odinger field theory on the curved Newton-Hooke background. The covariance of the field equation in the presence of the non-relativistic cosmological constant, entails fixing all coefficients in the covariant Poisson's equation for (twistless) torsional Newton-Cartan gravity. We further derive Ehlers conditions and an equation associated to the torsion in this method. | high energy physics theory |
Testing new, innovative technologies is a crucial task for safety and acceptance. But how can new systems be tested if no historical real-world data exist? Simulation provides an answer to this important question. Classical simulation tools such as event-based simulation are well accepted. But most of these established simulation models require the specification of many parameters. Furthermore, simulation runs, e.g., CFD simulations, are very time consuming. Generative Adversarial Networks (GANs) are powerful tools for generating new data for a variety of tasks. Currently, their most frequent application domain is image generation. This article investigates the applicability of GANs for imitating simulations. We are comparing the simulation output of a technical system with the output of a GAN. To exemplify this approach, a well-known multi-car elevator system simulator was chosen. Our study demonstrates the feasibility of this approach. It also discusses pitfalls and technical problems that occurred during the implementation. Although we were able to show that in principle, GANs can be used as substitutes for expensive simulation runs, we also show that they cannot be used "out of the box". Fine tuning is needed. We present a proof-of-concept, which can serve as a starting point for further research. | statistics |
We develop theory of (possibly large) cotilting objects of injective dimension at most one in general Grothendieck categories. We show that such cotilting objects are always pure-injective and that they characterize the situation where the Grothendieck category is tilted using a torsion pair to another Grothendieck category. We prove that for Noetherian schemes with an ample family of line bundles a cotilting class is closed under injective envelopes if and only if it is invariant under twists by line bundles, and that such cotilting classes are parametrized by specialization closed subsets disjoint from the associated points of the scheme. Finally, we compute the cotilting sheaves of the latter type explicitly for curves as products of direct images of indecomposable injective modules or completed canonical modules at stalks. | mathematics |
This review paper discusses the science of astrometric catalogs, their current applications and future prospects for making progress in fundamental astronomy, astrophysics and gravitational physics. We discuss the concept of fundamental catalogs, their practical realizations, and future prospects. Particular attention is paid to the astrophysical implementations of the catalogs such as the measurement of the Oort constants, the secular aberration and parallax, and asteroseismology. We also consider the use of the fundamental catalogs in gravitational physics for testing general theory of relativity and detection of ultra-long gravitational waves of cosmological origin. | astrophysics |
THz pulses are generated from femtosecond pulse-excited ferromagnetic/nonmagnetic spintronic heterostructures via inverse spin Hall effect. The contribution from ultrafast demagnetization/remagnetization is extremely weak, in the comparison. The highest possible THz signal strength from spintronic THz emitters is limited by the optical damage threshold of the corresponding heterostructures. The THz generation efficiency does not saturate with the excitation fluence even up till the damage threshold. Bilayer (Fe, CoFeB)/(Pt, Ta) based FM/NM spintronic heterostructures have been studied for an optimized performance for THz generation when pumped by sub-50 fs amplified laser pulses at 800 nm. Among them, CoFeB/Pt is the best combination for an efficient THz source. The optimized FM/NM spintronic heterostructure on a quartz substrate, having alpha-phase Ta as the nonmagnetic layer, show the highest damage threshold as compared to those with Pt, irrespective of their generation efficiency. The damage threshold of the Fe/Ta heterostructure on quartz substrate is ~85 GW/cm2. | physics |
Eight Majorana fermions in $d=1+1$ dimensions enjoy a triality that permutes the representation of the $SO(8)$ global symmetry in which the fermions transform. This triality plays an important role in the quantization of the superstring, and in the analysis of interacting topological insulators and the associated phenomenon of symmetric mass generation. The purpose of these notes is to provide an introduction to the triality and its applications, with careful attention paid to various ${\bf Z}_2$ global and gauge symmetries and their coupling to background spin structures. | high energy physics theory |
We examine the challenge of viewing all the fields in supergravity as arising from a Kaluza-Klein like dimensional reduction of some higher-dimensional theory. This gives rise to what is known as exceptional field theory or double field theory. A particular emphasis is placed on following the Kaluza-Klein intuition leading to the identification of charged states and a reinterpretation of the central charges. We further give a description of the novel extended geometry as a generalised phase space and the relationship to string and M-theory theory and the notion of quantization | high energy physics theory |
I develop a model of a randomized experiment with a binary intervention and a binary outcome. Potential outcomes in the intervention and control groups give rise to four types of participants. Fixing ideas such that the outcome is mortality, some participants would live regardless, others would be saved, others would be killed, and others would die regardless. These potential outcome types are not observable. However, I use the model to develop estimators of the number of participants of each type. The model relies on the randomization within the experiment and on deductive reasoning. I apply the model to an important clinical trial, the PROWESS trial, and I perform a Monte Carlo simulation calibrated to estimates from the trial. The reduced form from the trial shows a reduction in mortality, which provided a rationale for FDA approval. However, I find that the intervention killed two participants for every three it saved. | statistics |
The UV photoreactivity of polycyclic aromatic hydrocarbons (PAHs) in porous amorphous solid water has long been known to form both oxygenated photoproducts and photofragments. The aim of this study was to examine the influence of the ice structure upon reactivity under soft UV irradiation conditions. Mixtures of PAHs with amorphous solid water (porous and compact) and crystalline (cubic and hexagonal) ices were prepared in a high vacuum chamber and irradiated using a mercury lamp for up to 2.5 hours. The results show that the production of oxygenated PAHs is efficient only in amorphous water ice, while fragmentation can occur in both amorphous and crystalline ices. We conclude that the reactivity is driven by PAH-water interactions in favourable geometries, notably where dangling bonds are available at the surface of pores. These results suggest that the formation of oxygenated PAH molecules is most likely to occur in interstellar environments with porous (or compact) amorphous solid water and that this reactivity could considerably influence the inventory of aromatics in meteorites. | astrophysics |
Based on the effective invariant amplitudes of the transitions $J/\psi\to\gamma X(J^P)$ and $X(J^P)\to\phi\phi$, the spin dependence of the $J/\psi\to\gamma X(J^P)\to\gamma\phi\phi$ decay amplitude is obtained in the case of the intermediate resonances $X$ with $J^P=0^\pm,1^\pm,2^\pm$. Angular distributions of photons with the definite linear polarizations relative to the plane spanned by the momentum of initial electron and the total momentum of the $\phi\phi$ pair in the reaction $e^+e^-\to J/\psi\to\gamma X(J^P)\to\gamma\phi\phi$ are calculated. It is shown that the sign of the asymmetry of the distributions of the photons polarized in the above plane and orthogonal to it correlates with the signature $P_X(-1)^{J_X}$ of the $X$ resonance with given spin-parity $J_X^{P_X}$ so it may help to establish this quantum number in a way which does not depend on the specific model of the $X(J^P)\to\phi\phi$ amplitude. | high energy physics phenomenology |
Many network applications are based on binary-state networks, where each component has one of two states: success or failure. Efficient algorithms to evaluate binary-state network reliability are continually being developed. Reliability estimates the probability of the success state and is an effective and popular evaluation technique for binary-state networks. Binary-addition tree (BAT) algorithms are frequently used to calculate the efficiency and reliability of binary-state networks. In this study, we propose a novel, bounded BAT algorithm that employs three novel concepts: the first connected vector, the last disconnected vector, and super vectors. These vectors and the calculations of their occurrent probabilities narrow the search space and simplify the probability calculations to reduce the run time of the algorithm. Moreover, we show that replacing each undirected arc with two directed arcs, which is required in traditional direct methods, is unnecessary in the proposed algorithm. We call this novel concept the undirected vectors. The performance of the proposed bounded BAT algorithm was verified experimentally by solving a benchmark set of problems. | computer science |
Rotating photon gas exhibits a chirality separation along the angular velocity which is manifested through a generation of helicity and zilch currents. In this paper we study this system using the corresponding Wigner function and construct elements of the covariant chiral kinetic theory for photons from first principles. The Wigner function is solved order-by-order in $\hbar$ and the unconstrained terms are fixed by matching with quantum field theory results. We further consider the zilch and helicity currents and show that both manifestations of the chirality transport originate in the Berry phase of photons similarly to other chiral effects. Constructing the kinetic description from the Wigner function we find that the frame vector needed to fix the definition of spin of a massless particle is, in fact, the vector of the residual gauge freedom for the free Maxwell theory. We also briefly comment on the possible relation between vortical responses in rotating systems of massless particles and the anomalies of underlying quantum field theory. | high energy physics theory |
Spin waves in magnetic microresonators are at the core of modern magnonics. Here we demonstrate a new method of tunable excitation of different spin wave modes in magnetic microdisks by using a train of laser pulses coming at a repetition rate higher than the decay rate of spin precession. The microdisks are etched in a transparent bismuth iron garnet film and the light pulses influence the spins nonthermally through the inverse Faraday effect. The high repetition rate of the laser stimulus of 10 GHz establishes an interplay between the spin wave resonances in the frequency and momentum domains. As a result, the excitation efficiency of different spin modes can be tuned by a small variation of the external magnetic field. An additional degree of freedom is provided by scanning the laser spot within the microdisk area. This makes the proposed method for spin wave excitation advantageous for the forthcoming application of magnonics for telecommunication and quantum technologies. | physics |
Recent studies have shown that Deep Leaning models are susceptible to adversarial examples, which are data, in general images, intentionally modified to fool a machine learning classifier. In this paper, we present a multi-objective nested evolutionary algorithm to generate universal unrestricted adversarial examples in a black-box scenario. The unrestricted attacks are performed through the application of well-known image filters that are available in several image processing libraries, modern cameras, and mobile applications. The multi-objective optimization takes into account not only the attack success rate but also the detection rate. Experimental results showed that this approach is able to create a sequence of filters capable of generating very effective and undetectable attacks. | computer science |
In this paper is proposed an evaluation of ten metaheuristic optimization algorithms applied on the inverse optimization of the Interfacial Heat Transfer Coefficient (IHTC) coupled on the solidification phenomenon. It was considered an upward directional solidification system for Al-7wt.% Si alloy and, for IHTC model, a exponential time function. All thermophysical properties of the alloy were considered constant. Scheil Rule was used as segregation model ahead phase-transformation interface. Optimization results from Markov Chain Monte Carlo method (MCMC) were considered as reference. Based on average, quantiles 95% and 5%, kurtosis, average iterations and absolute errors of the metaheuristic methods, in relation to MCMC results, the Flower Pollination Algorithm (FPA) and Moth-Flame Optimization (MFO) presented the most appropriate results, outperforming the other methods in this particular phenomenon, based on these metrics. The regions with the most probable values for parameters in IHTC time function were also determined. | electrical engineering and systems science |
Self-interacting dark matter may have striking astrophysical signatures, such as observable offsets between galaxies and dark matter in merging galaxy clusters. Numerical N-body simulations used to predict such observables typically treat the galaxies as collisionless test particles, a questionable assumption given that each galaxy is embedded in its own dark matter halo. To enable a more accurate treatment we develop an effective description of small dark matter haloes taking into account the two major effects due to dark matter self-scatterings: deceleration and evaporation. We point out that self-scatterings can have a sizeable impact on the trajectories of galaxies, diminishing the separation between galaxies and dark matter in merging clusters. This effect depends sensitively on the underlying particle physics, in particular the angular dependence of the self-scattering cross section, and cannot be predicted from the momentum transfer cross section alone. | astrophysics |
The use of objective prior in Bayesian applications has become a common practice to analyze data without subjective information. Formal rules usually obtain these priors distributions, and the data provide the dominant information in the posterior distribution. However, these priors are typically improper and may lead to improper posterior. Here, we show, for a general family of distributions, that the obtained objective priors for the parameters either follow a power-law distribution or has an asymptotic power-law behavior. As a result, we observed that the exponents of the model are between 0.5 and 1. Understand these behaviors allow us to easily verify if such priors lead to proper or improper posteriors directly from the exponent of the power-law. The general family considered in our study includes essential models such as Exponential, Gamma, Weibull, Nakagami-m, Haf-Normal, Rayleigh, Erlang, and Maxwell Boltzmann distributions, to list a few. In summary, we show that comprehending the mechanisms describing the shapes of the priors provides essential information that can be used in situations where additional complexity is presented. | mathematics |
The generation of ultrafast laser pulses and the reconstruction of their electric fields is essential for many applications in modern optics. Quantum optical fields can also be generated on ultrafast time scales, however, the tools and methods available for strong laser pulses are not appropriate for measuring the properties of weak, possibly entangled pulses. Here, we demonstrate a method to reconstruct the joint-spectral amplitude of a two-photon energy-time entangled state from joint measurements of the frequencies and arrival times of the photons, and the correlations between them. Our reconstruction method is based on a modified Gerchberg-Saxton algorithm. Such techniques are essential to measure and control the shape of ultrafast entangled photon pulses. | quantum physics |
An important issue when using Machine Learning algorithms in recent research is the lack of interpretability. Although these algorithms provide accurate point predictions for various learning problems, uncertainty estimates connected with point predictions are rather sparse. A contribution to this gap for the Random Forest Regression Learner is presented here. Based on its Out-of-Bag procedure, several parametric and non-parametric prediction intervals are provided for Random Forest point predictions and theoretical guarantees for its correct coverage probability is delivered. In a second part, a thorough investigation through Monte-Carlo simulation is conducted evaluating the performance of the proposed methods from three aspects: (i) Analyzing the correct coverage rate of the proposed prediction intervals, (ii) Inspecting interval width and (iii) Verifying the competitiveness of the proposed intervals with existing methods. The simulation yields that the proposed prediction intervals are robust towards non-normal residual distributions and are competitive by providing correct coverage rates and comparably narrow interval lengths, even for comparably small samples. | statistics |
We report on the realization of large-scale 3D multilayer configurations of planar arrays of individual neutral atoms with immediate applications in quantum science and technology: a microlens-generated Talbot optical lattice In this novel platform, the single-beam illumination of a microlens array constitutes a structurally robust and wavelength-universal method for the realization of 3D atom arrays with favourable scaling properties due to the inherent self-imaging of the focal structure. Thus, 3D scaling comes without the requirement of extra resources. We demonstrate the trapping and imaging of individual rubidium atoms and the in-plane assembly of defect-free single-atom arrays in several Talbot planes. We present interleaved lattices with dynamic position control and parallelized sub-lattice addressing of spin states. | quantum physics |
Over the last four years, we have developed a series of lectures, labs and project assignments aimed at introducing enough technology so that students from a mix of disciplines can design and build innovative interface devices. | computer science |
Generation of cosmic microwave background (CMB) elliptic polarization due to the Cotton-Mouton (CM) effect in a cosmic magnetic field is studied. We concentrate on the generation of CMB circular polarization and on the rotation angle of the CMB polarization plane from the decoupling time until at present. For the first time, a rather detailed analysis of the CM effect for an arbitrary direction of the cosmic magnetic field with respect to photon direction of propagation is done. Considering the CMB linearly polarized at the decoupling time, it is shown that the CM effect is one of the most substantial effects in generating circular polarization especially in the low part of the CMB spectrum. It is shown that in the frequency range $10^8$ Hz $\leq \nu_0\leq 10^9$ Hz, the degree of circular polarization of the CMB at present for perpendicular propagation with respect to the cosmic magnetic field is in the range $ 10^{-13}\lesssim P_C(t_0)\lesssim 7.65\times 10^{-7}$ or Stokes circular polarization parameter $2.7 \times 10^{-13}$ K $\lesssim |V(t_0)|\lesssim 2 \times 10^{-6}$ K for values of the cosmic magnetic field amplitude at present in the range $10^{-9}$ G $\lesssim B\lesssim 8\times 10^{-8}$ G. On the other hand, for not perpendicular propagation with respect to the cosmic magnetic field we find $10^{-15}\lesssim P_C(t_0)\lesssim 6\times 10^{-12}$ or $2.72 \times 10^{-15}$ K $\lesssim |V(t_0)| \lesssim 10^{-11}$ K, for the same values of the cosmic magnetic field amplitude and same frequency range. Estimates on the rotation angle of the CMB polarization plane $\delta\psi_0$ due to the CM effect and constraints on the cosmic magnetic field amplitude from current constraints on $\delta\psi_0$ due to a combination of the CM and Faraday effects are found. | astrophysics |
Collider searches for long-lived particles yield a promising avenue to probe the freeze-in production of Dark Matter via the decay of a parent particle. We analyze the prospects of probing the parameter space of Dark Matter freeze-in from the decay of neutral parent particles at the LHC and beyond, taking as a case study a freeze-in Dark Matter scenario via the Standard Model Higgs. We obtain the projected sensitivity of the proposed MATHUSLA surface detector (for MATHUSLA100 and MATHUSLA200 configurations) for long-lived particle searches to the freeze-in Dark Matter parameter space, and study its complementarity to searches by ATLAS and CMS at HL-LHC, as well as the interplay with constraints from Cosmology: Big-Bang Nucleosynthesis and Lyman-$\alpha$ forest observations. We then analyze the improvement in sensitivity that would come from a forward detector within a future 100 TeV $pp$-collider. In addition, we discuss several technical aspects of the present Dark Matter freeze-in scenario: the role of the electroweak phase transition; the inclusion of thermal masses, which have been previously disregarded in freeze-in from decay studies; the impact of $2\to 2$ scattering processes on the Dark Matter relic abundance; and the interplay between freeze-in and super-WIMP Dark Matter production mechanisms. | high energy physics phenomenology |
We present a systematic calculation of the charged current semi-inclusive deeply inelastic scattering process at leading order twist-3 level in the parton model. We consider the general form of the negatively charged beam scattering off the polarized target which has spin-1. The calculations are carried out by applying the collinear expansion where multiple gluon scattering is taken into account and gauge links are obtained automatically. We first present the general form of the differential cross section in terms of the structure functions by kinematic analysis and then present the structure functions in terms of the the gauge invariant parton distribution functions up to twist-3 level. Considering the angle modulations and polarizations of the cross section, we calculate the complete azimuthal asymmetries in the charged current semi-inclusive deeply inelastic scattering process. The charge asymmetries are also considered in this paper with the introduction of the definitions of the $plus$ and $minus$ cross sections. | high energy physics phenomenology |
Estimating dynamic treatment regimes (DTRs) from retrospective observational data is challenging as some degree of unmeasured confounding is often expected. In this work, we develop a framework of estimating properly defined "optimal" DTRs with a time-varying instrumental variable (IV) when unmeasured covariates confound the treatment and outcome, rendering the potential outcome distributions only partially identified. We derive a novel Bellman equation under partial identification, use it to define a generic class of estimands (termed IV-optimal DTRs), and study the associated estimation problem. We then extend the IV-optimality framework to tackle the policy improvement problem, delivering IV-improved DTRs that are guaranteed to perform no worse and potentially better than a pre-specified baseline DTR. Importantly, our IV-improvement framework opens up the possibility of strictly improving upon DTRs that are optimal under the no unmeasured confounding assumption (NUCA). We demonstrate via extensive simulations the superior performance of IV-optimal and IV-improved DTRs over the DTRs that are optimal only under the NUCA. In a real data example, we embed retrospective observational registry data into a natural, two-stage experiment with noncompliance using a time-varying IV and estimate useful IV-optimal DTRs that assign mothers to high-level or low-level neonatal intensive care units based on their prognostic variables. | statistics |
There are two kinds of new physics effects on non-resonant di-Higgs process from gluon fusion, non-SM Higgs trilinear self-coupling $\lambda_{hhh}$ or new colored particles running in the loop. With the aim of disentangling different new physics contributions, we study their characteristics in the kinematic distributions. Assuming that the total cross section is observed to be about three times as large as the SM expectation, we consider the cases of $\lambda_{hhh}/\lambda_{hhh}^{\rm SM} =-0.5, 5.5$ as well as a new physics model with heavy vectorlike quarks in a type-II two Higgs double model, called the VLQ-2HDM. A reasonable benchmark point is suggested in the exact wrong-sign limit, where the opposite sign between the up-type VLQ and down-type VLQ couplings to the Higgs boson causes the cancellation of their contributions to the single-Higgs production from gluon fusion. Because of the threshold effects from the heavy VLQs in the loop, the VLQ-2HDM accommodates the bumps in the distributions of the invariant mass of the Higgs boson pair ($M_{hh}$) and the transverse momentum of a Higgs boson ($p_T^h$). The positions of two bumps are closely related as $ M_{hh} \simeq 2 M_{\rm VLQ}$ and $p_T^h \simeq M_{\rm VLQ}$. In addition, the bumps located at the heavy VLQ mass naturally lift up the $M_{hh}$ and $p_T^h$ distributions into high-mass and high-$p_T^h$ regions. On the other hand, the non-SM Higgs trilinear coupling cases have the distributions shift into low $ M_{hh}$ and $p_T^h$ regions. Therefore, the kinematic region with high $M_{hh}$ and high $p_T^h$ will be a smoking-gun signal for the VLQ-2HDM. Full HL-LHC simulations for the di-Higgs signals are also performed, confirming that the $b \bar{b} b \bar{b}$ final state can distinguish the VLQ-2HDM. | high energy physics phenomenology |
Dynamic dispatching aims to smartly allocate the right resources to the right place at the right time. Dynamic dispatching is one of the core problems for operations optimization in the mining industry. Theoretically, deep reinforcement learning (RL) should be a natural fit to solve this problem. However, the industry relies on heuristics or even human intuitions, which are often short-sighted and sub-optimal solutions. In this paper, we review the main challenges in using deep RL to address the dynamic dispatching problem in the mining industry. | computer science |
Spectroscopy is a powerful tool for studying molecules and is commonly performed on large thermal molecular ensembles that are perturbed by motional shifts and interactions with the environment and one another, resulting in convoluted spectra and limited resolution. Here, we use generally applicable quantum-logic techniques to prepare a trapped molecular ion in a single quantum state, drive terahertz rotational transitions with an optical frequency comb, and read out the final state non-destructively, leaving the molecule ready for further manipulation. We resolve rotational transitions to 11 significant digits and derive the rotational constant of CaH+ to be B_R = 142501777.9(1.7) kHz. Our approach suits a wide range of molecular ions, including polyatomics and species relevant for tests of fundamental physics, chemistry, and astrophysics. | physics |
Analyzing the morphological attributes of blood vessels plays a critical role in the computer-aided diagnosis of many cardiovascular and ophthalmologic diseases. Although being extensively studied, segmentation of blood vessels, particularly thin vessels and capillaries, remains challenging mainly due to the lack of an effective interaction between local and global features. In this paper, we propose a novel deep learning model called PC-Net to segment retinal vessels and major arteries in 2D fundus image and 3D computed tomography angiography (CTA) scans, respectively. In PC-Net, the pyramid squeeze-and-excitation (PSE) module introduces spatial information to each convolutional block, boosting its ability to extract more effective multi-scale features, and the coarse-to-fine (CF) module replaces the conventional decoder to enhance the details of thin vessels and process hard-to-classify pixels again. We evaluated our PC-Net on the Digital Retinal Images for Vessel Extraction (DRIVE) database and an in-house 3D major artery (3MA) database against several recent methods. Our results not only demonstrate the effectiveness of the proposed PSE module and CF module, but also suggest that our proposed PC-Net sets new state of the art in the segmentation of retinal vessels (AUC: 98.31%) and major arteries (AUC: 98.35%) on both databases, respectively. | electrical engineering and systems science |
Survival analysis is one of the most important fields of statistics in medicine and the biological sciences. In addition, the computational advances in the last decades have favoured the use of Bayesian methods in this context, providing a flexible and powerful alternative to the traditional frequentist approach. The objective of this paper is to summarise some of the most popular Bayesian survival models, such as accelerated failure time, proportional hazards, mixture cure, competing risks, frailty, and joint models of longitudinal and survival data. Moreover, an implementation of each presented model is provided using a BUGS syntax that can be run with JAGS from the R programming language. Reference to other Bayesian R-packages are also discussed. | statistics |
We study coherent dynamics of two interacting Bose-Bose droplets by means of the extended Gross-Pitaevskii equation. The relative motion of the droplets couples to the phases of their components. The dynamics can be understood in terms of the evolution of zero-energy modes recovering symmetries spontaneously broken by the mean field solution. A phase-dependent interaction potential and Josephson-junction-like equations are introduced to explain the observed behaviour. We show that the evolution of the droplets is a macroscopic manifestation of the hidden dynamics of their phases. The ocurrence of non-dissipative drag between the two supercurrents (Andreev-Bashkin effect) is discussed. | condensed matter |
We discuss how to implement backjumping (or intelligent backtracking) in Prolog programs by means of exception handling. This seems impossible in a general case. We provide a solution, which works in certain cases, in particular for binary programs. We also provide an approximate solution, for arbitrary programs. | computer science |
In future autonomous systems, wireless multi-hop communication is key to enable collaboration among distributed agents at low cost and high flexibility. When many agents need to transmit information over the same wireless network, communication becomes a shared and contested resource. Event-triggered and self-triggered control account for this by transmitting data only when needed, enabling significant energy savings. However, a solution that brings those benefits to multi-hop networks and can reallocate freed up bandwidth to additional agents or data sources is still missing. To fill this gap, we propose control-guided communication, a novel co-design approach for distributed self-triggered control over wireless multi-hop networks. The control system informs the communication system of its transmission demands ahead of time, and the communication system allocates resources accordingly. Experiments on a cyber-physical testbed show that multiple cart-poles can be synchronized over wireless, while serving other traffic when resources are available, or saving energy. These experiments are the first to demonstrate and evaluate distributed self-triggered control over low-power multi-hop wireless networks at update rates of tens of milliseconds. | computer science |
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