cssi/SciSciGPT-SciSciNet huggingface dataset:
Logistic Regression Regret: What’s the Catch?

We address the problem of the achievable regret rates with online logistic regression. We derive lower bounds with logarithmic regret under $L_1$, $L_2$, and $L_\infty$ constraints on the parameter values. The bounds are dominated by $d/2 \log T$, where $T$ is the horizon and $d$ is the dimensionality of the parameter space. We show their achievability for $d=o(T^{1/3})$ in all these cases with Bayesian methods, that achieve them up to a $d/2 \log d$ term. Interesting different behaviors are shown for larger dimensionality. Specifically, on the negative side, if $d = \Omega(\sqrt{T})$, any algorithm is guaranteed regret of $\Omega(d \log T)$ (greater than $\Theta(\sqrt{T})$) under $L_\infty$ constraints on the parameters (and the example features). On the positive side, under $L_1$ constraints on the parameters, there exist Bayesian algorithms that can achieve regret that is sub-linear in $d$ for the asymptotically larger values of $d$. For $L_2$ constraints, it is shown that for large enough $d$, the regret remains linear in $d$ but no longer logarithmic in $T$. Adapting the \emph{redundancy-capacity\/} theorem from information theory, we demonstrate a principled methodology based on grids of parameters to derive lower bounds. Grids are also utilized to derive some upper bounds. Our results strengthen results by Kakade and Ng (2005) and Foster et al. (2018) for upper bounds for this problem, introduce novel lower bounds, and adapt a methodology that can be used to obtain such bounds for other related problems. They also give a novel characterization of the asymptotic behavior when the dimension of the parameter space is allowed to grow with $T$. They additionally strengthen connections to the information theory literature, demonstrating that the actual regret for logistic regression depends on the richness of the parameter class, where even within this problem, richer classes lead to greater regret.
An Algebraic Approach for High-level Text Analytics

Text analytical tasks like word embedding, phrase mining and topic modeling, are placing increasing demands as well as challenges to existing database management systems. In this paper, we provide a novel algebraic approach based on associative arrays. Our data model and algebra can bring together relational operators and text operators, which enables interesting optimization opportunities for hybrid data sources that have both relational and textual data. We demonstrate its expressive power in text analytics using several real-world tasks.
Motion Guided LiDAR-Camera Self-calibration and Accelerated Depth Upsampling for Autonomous Vehicles

This work proposes a novel motion guided method for targetless self-calibration of a LiDAR and camera and use the re-projection of LiDAR points onto the image reference frame for real-time depth upsampling. The calibration parameters are estimated by optimizing an objective function that penalizes distances between 2D and re-projected 3D motion vectors obtained from time-synchronized image and point cloud sequences. For upsampling, a simple, yet effective and time efficient formulation that minimizes depth gradients subject to an equality constraint involving the LiDAR measurements is proposed. Validation is performed on recorded real data from urban environments and demonstrations that our two methods are effective and suitable to mobile robotics and autonomous vehicle applications imposing real-time requirements is shown.
Entropy in a Closed Manifold and Partial Regularity of Mean Curvature Flow Limit of Surfaces

Inspired by the idea of Colding and Minicozzi (Ann Math 182:755–833, 2015), we define (mean curvature flow) entropy for submanifolds in a general ambient Riemannian manifold. In particular, this entropy is equivalent to area growth of a closed submanifold in a closed ambient manifold with non-negative Ricci curvature. Moreover, this entropy is monotone along the mean curvature flow in a closed Riemannian manifold with non-negative sectional curvatures and parallel Ricci curvature. As an application, we show the partial regularity of the limit of mean curvature flow of surfaces in a three dimensional Riemannian manifold with non-negative sectional curvatures and parallel Ricci curvature.
Tidal Currents Detected in Kraken Mare Straits from Cassini VIMS Sun Glitter Observations

We present Cassini VIMS observations of sun glitter -- wave-induced reflections from a liquid surface offset from a specular point -- on Kraken Mare. Sun glitter reveals rough sea surfaces around Kraken Mare, namely the coasts and narrow straits. The sun glitter observations indicate wave activity driven by the winds and tidal currents in Kraken Mare during northern summer. T104 Cassini VIMS observations show three sun glitter features in Bayta Fretum indicative of variegated wave fields. We cannot uniquely determine one source for the coastal Bayta waves, but we lean toward the interpretation of surface winds, because tidal currents should be too weak to generate capillary-gravity waves in Bayta Fretum. T105 and T110 observations reveal wave fields in the straits of Seldon Fretum, Lulworth Sinus, and Tunu Sinus that likely originate from the constriction of tidal currents. Coastlines of Bermoothes and Hufaidh Insulae adjoin rough sea surfaces, suggesting a complex interplay of wind-roughened seas and localized tidal currents. Bermoothes and Hufaidh Insulae may share characteristics of either the Torres Strait off Australia or the Aland region of Finland, summarized as an island-dense strait with shallow bathymetry that hosts complex surface circulation patterns. Hufaidh Insulae could host seafloor bedforms formed by tidal currents with an abundant sediment supply, similar to the Torres Strait. The coastlines of Hufaidh and Bermoothes Insulae likely host ria or flooded coastal inlets, suggesting the Insulae may be local peaks of primordial crust isolated by an episode of sea-level rise or tectonic uplift.
Wolf phase tomography (WPT) of transparent structures using partially coherent illumination

In 1969, Emil Wolf proposed diffraction tomography using coherent holographic imaging to extract 3D information from transparent, inhomogeneous objects. In the same era, the Wolf equations were first used to describe the propagation correlations associated with partially coherent fields. Combining these two concepts, we present Wolf phase tomography (WPT), which is a method for performing diffraction tomography using partially coherent fields. WPT reconstruction works directly in the space-time domain, without the need for Fourier transformation, and decouples the refractive index (RI) distribution from the thickness of the sample. We demonstrate the WPT principle using the data acquired by a quantitative-phase-imaging method that upgrades an existing phase-contrast microscope by introducing controlled phase shifts between the incident and scattered fields. The illumination field in WPT is partially spatially coherent (emerging from a ring-shaped pupil function) and of low temporal coherence (white light), and as such, it is well suited for the Wolf equations. From three intensity measurements corresponding to different phase-contrast frames, the 3D RI distribution is obtained immediately by computing the Laplacian and second time derivative of the measured complex correlation function. We validate WPT with measurements of standard samples (microbeads), spermatozoa, and live neural cultures. The high throughput and simplicity of this method enables the study of 3D, dynamic events in living cells across the entire multiwell plate, with an RI sensitivity on the order of 10-5.
Stable and non-symmetric pitchfork bifurcations

In this paper, we present a criterion for pitchfork bifurcations of smooth vector fields based on a topological argument. Our result expands Rajapakse and Smale℉s result [15] significantly. Based on our criterion, we present a class of families of non-symmetric vector fields undergoing a pitchfork bifurcation.
Mycobacterium tuberculosis Rv0991c Is a Redox-Regulated Molecular Chaperone.

ABSTRACT The bacterial pathogen Mycobacterium tuberculosis is the leading cause of death by an infectious disease among humans. Here, we describe a previously uncharacterized M. tuberculosis protein, Rv0991c, as a molecular chaperone that is activated by oxidation. Rv0991c has homologs in most bacterial lineages and appears to function analogously to the well-characterized Escherichia coli redox-regulated chaperone Hsp33, despite a dissimilar protein sequence. Rv0991c is transcriptionally coregulated with hsp60 and hsp70 chaperone genes in M. tuberculosis, suggesting that Rv0991c functions with these chaperones in maintaining protein quality control. Supporting this hypothesis, we found that, like oxidized Hsp33, oxidized Rv0991c prevents the aggregation of a model unfolded protein in vitro and promotes its refolding by the M. tuberculosis Hsp70 chaperone system. Furthermore, Rv0991c interacts with DnaK and can associate with many other M. tuberculosis proteins. We therefore propose that Rv0991c, which we named “Ruc” (redox-regulated protein with unstructured C terminus), represents a founding member of a new chaperone family that protects M. tuberculosis and other species from proteotoxicity during oxidative stress. IMPORTANCEM. tuberculosis infections are responsible for more than 1 million deaths per year. Developing effective strategies to combat this disease requires a greater understanding of M. tuberculosis biology. As in all cells, protein quality control is essential for the viability of M. tuberculosis, which likely faces proteotoxic stress within a host. Here, we identify an M. tuberculosis protein, Ruc, that gains chaperone activity upon oxidation. Ruc represents a previously unrecognized family of redox-regulated chaperones found throughout the bacterial superkingdom. Additionally, we found that oxidized Ruc promotes the protein-folding activity of the essential M. tuberculosis Hsp70 chaperone system. This work contributes to a growing body of evidence that oxidative stress provides a particular strain on cellular protein stability.
Automated Screening of Sickle Cells using a Smartphone-Based Microscope and Deep Learning

We present a deep learning-based framework for performing automatic screening of sickle cells using a smartphone-based microscope. We achieved 98% accuracy when blindly testing 96 human blood smear slides, including 32 with sickle cell disease.
Assessing practitioner beliefs about software defect prediction

Just because software developers say they believe in “X”, that does not necessarily mean that “X” is true. As shown here, there exist numerous beliefs listed in the recent Software Engineering literature which are only supported by small portions of the available data. Hence we ask what is the source of this disconnect between beliefs and evidence?. To answer this question we look for evidence for ten beliefs within 300,000+ changes seen in dozens of open-source projects. Some of those beliefs had strong support across all the projects; specifically, A commit that involves more added and removed lines is more bug-prone” and “Files with fewer lines contributed by their owners (who contribute most changes) are bug-prone”. Most of the widely-held beliefs studied are only sporadically supported in the data; i.e. large effects can appear in project data and then disappear in subsequent releases. Such sporadic support explains why developers believe things that were relevant to their prior work, but not necessarily their current work. Our conclusion will be that we need to change the nature of the debate with Software Engineering. Specifically, while it is important to report the effects that hold right now, it is also important to report on what effects change over time.CCS CONCEPTS• Software and its engineering → Maintaining software.
Unstable population dynamics in obligate co-operators.

Abstract Cooperation significantly impacts a species’ population dynamics as individuals choose others to associate with based upon fitness opportunities. Models of these dynamics typically assume that individuals can freely move between groups. Such an assumption works well for facultative co-operators (e.g. flocking birds, schooling fish, and swarming locusts) but less so for obligate co-operators (e.g. canids, cetaceans, and primates). With obligate co-operators, the fitness consequences from associations are stronger compared to facultative co-operators. Consequently, individuals within a group should be more discerning and selective over their associations, rejecting new members and even removing current members. Incorporating such aspects into population models may better reflect obligately cooperative species. In this paper, we create and analyze a model of the population dynamics of obligate co-operators. In our model, a behavioral game determines within-group population dynamics that then spill over into between-group dynamics. Our analysis shows that group number increases when population dynamics are stable, but additional groups lead to unstable population dynamics and an eventual collapse of group numbers. Using a more general analysis, we identify a fundamental mismatch between the stability of the behavioral dynamics and the stability of the population dynamics. When one is stable, the other is not. Our results suggest that group turnover may be inherent to the population dynamics of obligate co-operators. The instability arises from a non-chaotic deterministic process, and such dynamics should be predictable and testable.
Gender Slopes: Counterfactual Fairness for Computer Vision Models by Attribute Manipulation

Automated computer vision systems have been applied in many domains including security, law enforcement, and personal devices, but recent reports suggest that these systems may produce biased results, discriminating against people in certain demographic groups. Diagnosing and understanding the underlying true causes of model biases, however, are challenging tasks because modern computer vision systems rely on complex black-box models whose behaviors are hard to decode. We propose to use an encoder-decoder network developed for image attribute manipulation to synthesize facial images varying in the dimensions of gender and race while keeping other signals intact. We use these synthesized images to measure counterfactual fairness of commercial computer vision classifiers by examining the degree to which these classifiers are affected by gender and racial cues controlled in the images, e.g., feminine faces may elicit higher scores for the concept of nurse and lower scores for STEM-related concepts.
Clot Permeability, Agonist Transport, and Platelet Binding Kinetics in Arterial Thrombosis.

Abstract The formation of wall-adherent platelet aggregates is a critical process in arterial thrombosis. A growing aggregate experiences frictional drag forces exerted on it by fluid moving over or through the aggregate. The magnitude of these forces is strongly influenced by the permeability of the developing aggregate; the permeability depends on the aggregate’s porosity. Aggregation is mediated by formation of ensembles of molecular bonds; each bond involves a plasma protein bridging the gap between specific receptors on the surfaces of two different platelets. The ability of the bonds existing at any time to sustain the drag forces on the aggregate determines whether it remains intact or sheds individual platelets or larger fragments (emboli). We investigate platelet aggregation in coronary-sized arteries using both computational simulations and in vitro experiments. The computational model tracks the formation and breaking of bonds between platelets and treats the thrombus as an evolving porous, viscoelastic material, which moves differently from the background fluid. This relative motion generates drag forces which the fluid and thrombus exert on one another. These forces are computed from a permeability-porosity relation parameterized from experimental measurements. Basing this relation on measurements from occlusive thrombi formed in our flow chamber experiments, along with other physiological parameter values, the model produced stable dense thrombi on a similar timescale to the experiments. When we parameterized the permeability-porosity relation using lower permeabilities reported by others, bond formation was insufficient to balance drag forces on an early thrombus and keep it intact. Under high shear flow, soluble agonist released by platelets was limited to the thrombus and a boundary layer downstream, thus restricting thrombus growth into the vessel lumen. Adding to the model binding and activation of unactivated platelets through von Willebrand-factor-mediated processes allowed greater growth and made agonist-induced activation more effective.
An extension in the Adams spectral sequence in dimension 54

We establish a hidden extension in the Adams spectral sequence converging to the stable homotopy groups of spheres at the prime 2 in the 54-stem. This extension is exceptional in that the only proof we know proceeds via Pstragowski's category of synthetic spectra. This was the final unresolved hidden 2-extension in the Adams spectral sequence through dimension 80. We hope this provides a concise demonstration of the computational leverage provided by $\mathbb{F}_2$-synthetic spectra.
On the optimization landscape of tensor decompositions

Non-convex optimization with local search heuristics has been widely used in machine learning, achieving many state-of-art results. It becomes increasingly important to understand why they can work for these NP-hard problems on typical data. The landscape of many objective functions in learning has been conjectured to have the geometric property that “all local optima are (approximately) global optima”, and thus they can be solved efficiently by local search algorithms. However, establishing such property can be very difficult. In this paper, we analyze the optimization landscape of the random over-complete tensor decomposition problem, which has many applications in unsupervised learning, especially in learning latent variable models. In practice, it can be efficiently solved by gradient ascent on a non-convex objective. We show that for any small constant $$\varepsilon > 0$$ , among the set of points with function values $$(1+\varepsilon )$$ -factor larger than the expectation of the function, all the local maxima are approximate global maxima. Previously, the best-known result only characterizes the geometry in small neighborhoods around the true components. Our result implies that even with an initialization that is barely better than the random guess, the gradient ascent algorithm is guaranteed to solve this problem. However, achieving such a initialization with random guess would still require super-polynomial number of attempts. Our main technique uses Kac–Rice formula and random matrix theory. To our best knowledge, this is the first time when Kac–Rice formula is successfully applied to counting the number of local optima of a highly-structured random polynomial with dependent coefficients.
What the Tevatron Found

The CDF collaboration has reported a 4.1σ excess in their lepton, missing energy, and dijets channel. This excess, which takes the form of an approximately Gaussian peak centered at a dijet invariant mass of 147 GeV, has provoked a great deal of experimental and theoretical interest. Although the DO collaboration has reported that they do not observe a signal consistent with CDF, there is currently no widely accepted explanation for the discrepancy between these two experiments. A resolution of this issue is of great importance — not least because it may teach us lessons relevant for future searches at the LHC — and it will clearly require additional information. In this paper, we consider the ability of the Tevatron and LHC detectors to observe evidence associated with the CDF excess in a variety of channels. We also discuss the ability of selected kinematic distributions to distinguish between Standard Model explanations of the observed excess and various new physics scenarios.
Constraints on the parameter space in an inert doublet model with two active doublets

We study a three Higgs doublet model where one doublet is inert and the other two doublets are active. Flavor changing neutral currents are avoided at tree-level by imposing a softly broken $$ {Z}_2^{\prime } $$ symmetry and we consider type I and type II Yukawa structures. The lightest inert scalar is a viable Dark Matter (DM) candidate. A numerical scan of the free parameters is performed taking into account theoretical constraints such as positivity of the scalar potential and unitarity of 2 → 2 scattering amplitudes. The model is further constrained by experimental results such as B physics lower limits on charged Higgs masses, Electroweak Precision Observables, LEP II, LHC Higgs measurements, Planck measurement of the DM relic abundance and WIMP direct searches by the LUX and XENON1T experiments. The model predictions for mono-jet, mono Z and mono Higgs final states are studied and tested against current LHC data and we find the model to be allowed. We also discuss the effects of abandoning the “dark democracy” assumption common in studies of inert models. Projected sensitivities of direct detection experiments will leave only a tiny window in the DM mass versus coupling plane that is compliant with relic density bounds.
Oscillation and the mean ergodic theorem for uniformly convex Banach spaces

Let B be a p-uniformly convex Banach space, with p ≥ 2. Let T be a linear operator on B, and let Anx denote the ergodic average 1 n P i<n T n x. We prove the following variational inequality in the case where T is power bounded from above and below: for any increasing sequence (tk)k2N of natural numbers we have P k kAtk+1x − Atkxk p ≤ Ckxk p , where the constant C depends only on p and the modulus of uniform convexity. For T a nonexpansive operator, we obtain a weaker bound on the number of "-fluctuations in the sequence. We clarify the relationship between bounds on the number of "- fluctuations in a sequence and bounds on the rate of metastability, and provide lower bounds on the rate of metastability that show that our main result is sharp.
Universal Entanglement Dynamics following a Local Quench

We study the time dependence of the entanglement between two quantum wires after suddenly connecting them via tunneling through an impurity. The result at large times is given by the well known formula $S(t) \approx {1\over 3}\ln {t}$. We show that the intermediate time regime can be described by a universal cross-over formula $S=F(tT_K)$, where $T_K$ is the crossover (Kondo) temperature: the function $F$ describes the dynamical "healing" of the system at large times. We discuss how to obtain analytic information about $F$ in the case of an integrable quantum impurity problem using the massless Form-Factors formalism for twist and boundary condition changing operators. Our results are confirmed by density matrix renormalization group calculations and exact free fermion numerics.
Hedging in games: Faster convergence of external and swap regrets

We consider the setting where players run the Hedge algorithm or its optimistic variant to play an $n$-action game repeatedly for $T$ rounds. 1) For two-player games, we show that the regret of optimistic Hedge decays at $\tilde{O}( 1/T ^{5/6} )$, improving the previous bound $O(1/T^{3/4})$ by Syrgkanis, Agarwal, Luo and Schapire (NIPS'15) 2) In contrast, we show that the convergence rate of vanilla Hedge is no better than $\tilde{\Omega}(1/ \sqrt{T})$, addressing an open question posted in Syrgkanis, Agarwal, Luo and Schapire (NIPS'15). For general m-player games, we show that the swap regret of each player decays at rate $\tilde{O}(m^{1/2} (n/T)^{3/4})$ when they combine optimistic Hedge with the classical external-to-internal reduction of Blum and Mansour (JMLR'07). The algorithm can also be modified to achieve the same rate against itself and a rate of $\tilde{O}(\sqrt{n/T})$ against adversaries. Via standard connections, our upper bounds also imply faster convergence to coarse correlated equilibria in two-player games and to correlated equilibria in multiplayer games.
The Evolution of Soft Collinear Effective Theory

Soft Collinear Effective Theory (SCET) is an effective field theory of Quantum Chromodynamics (QCD) for processes where there are energetic, nearly lightlike degrees of freedom interacting with one another via soft radiation. SCET has found many applications in high-energy and nuclear physics, especially in recent years the physics of hadronic jets in e+e-, lepton-hadron, hadron-hadron, and heavy-ion collisions. SCET can be used to factorize multi-scale cross sections in these processes into single-scale hard, collinear, and soft functions, and to evolve these through the renormalization group to resum large logarithms of ratios of the scales that appear in the QCD perturbative expansion, as well as to study properties of nonperturbative effects. We overview the elementary concepts of SCET and describe how they can be applied in high-energy and nuclear physics.
Automatic Extraction of Rules Governing Morphological Agreement

Creating a descriptive grammar of a language is an indispensable step for language documentation and preservation. However, at the same time it is a tedious, time-consuming task. In this paper, we take steps towards automating this process by devising an automated framework for extracting a first-pass grammatical specification from raw text in a concise, human- and machine-readable format. We focus on extracting rules describing agreement, a morphosyntactic phenomenon at the core of the grammars of many of the world’s languages. We apply our framework to all languages included in the Universal Dependencies project, with promising results. Using cross-lingual transfer, even with no expert annotations in the language of interest, our framework extracts a grammatical specification which is nearly equivalent to those created with large amounts of gold-standard annotated data. We confirm this finding with human expert evaluations of the rules that our framework produces, which have an average accuracy of 78%. We release an interface demonstrating the extracted rules at https://neulab.github.io/lase/
Counting exceptional instantons

We show how to obtain the instanton partition function of N = 2 SYM with exceptional gauge group EFG using blow-up recursion relations derived by Nakajima and Yoshioka. We compute the two instanton contribution and match it with the recent proposal for the superconformal index of rank 2 SCFTs with E_(6,7) global symmetry.
Relation between exponential behavior and energy denominators - Weak coupling limit

We show some interesting properties of tridiagonal and pentadiagonal matrices in the weak coupling limits. In the former case of this limit, the ground state wave function amplitudes are identical ...
Parametric Fokker-Planck equation

We derive the Fokker-Planck equation on the parametric space. It is the Wasserstein gradient flow of relative entropy on the statistical manifold. We pull back the PDE to a finite dimensional ODE on parameter space. Some analytical examples and numerical examples are presented.
Extending smooth cyclic group actions on the Poincaré homology sphere

Let $X_0$ denote a compact, simply-connected smooth $4$-manifold with boundary the Poincar\'e homology $3$-sphere $\Sigma(2,3,5)$ and with even negative definite intersection form $Q_{X_0}=E_8$. We show that free $\mathbb{Z}/p$ actions on $\Sigma(2,3,5)$ do not extend to smooth actions on $X_0$ with isolated fixed points for any prime $p>7$. The approach is to study the equivariant version of the Yang-Mills instanton-one moduli space for $4$-manifolds with cylindrical ends. As an application we show that for $p>7$ a smooth $\mathbb{Z}/p$ action on $\#^8 S^2 \times S^2$ with isolated fixed points does not split along a free action on $\Sigma(2,3,5)$. The results hold for $p=7$ if the action is homologically trivial.
An Active Galactic Nucleus Caught in the Act of Turning Off and On

We present the discovery of an active galactic nucleus (AGN) that is turning off and then on again in the z = 0.06 galaxy SDSS J1354+1327. This episodic nuclear activity is the result of discrete accretion events that could have been triggered by a past interaction with the companion galaxy that is currently located 12.5 kpc away. We originally targeted SDSS J1354+1327 because its Sloan Digital Sky Survey spectrum has narrow AGN emission lines that exhibit a velocity offset of 69 km s−1relative to systemic. To determine the nature of the galaxy and its velocity-offset emission lines, we observed SDSS J1354+1327 with Chandra/ACIS, Hubble Space Telescope/Wide Field Camera 3, Apache Point Observatory optical longslit spectroscopy, and Keck/OSIRIS integral-field spectroscopy. We find a ~10 kpc cone of photoionized gas south of the galaxy center and a ~1 kpc semi-spherical front of shocked gas, which is responsible for the velocity offset in the emission lines, north of the galaxy center. We interpret these two outflows as the result of two separate AGN accretion events: the first AGN outburst created the southern outflow, and then <10^5 years later, the second AGN outburst launched the northern shock front. SDSS J1354+1327 is the galaxy with the strongest evidence for an AGN that has turned off and then on again, and it fits into the broader context of AGN flickering that includes observations of AGN light echoes.
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits

This paper proposes near-optimal algorithms for the pure-exploration linear bandit problem in the fixed confidence and fixed budget settings. Leveraging ideas from the theory of suprema of empirical processes, we provide an algorithm whose sample complexity scales with the geometry of the instance and avoids an explicit union bound over the number of arms. Unlike previous approaches which sample based on minimizing a worst-case variance (e.g. G-optimal design), we define an experimental design objective based on the Gaussian-width of the underlying arm set. We provide a novel lower bound in terms of this objective that highlights its fundamental role in the sample complexity. The sample complexity of our fixed confidence algorithm matches this lower bound, and in addition is computationally efficient for combinatorial classes, e.g. shortest-path, matchings and matroids, where the arm sets can be exponentially large in the dimension. Finally, we propose the first algorithm for linear bandits in the the fixed budget setting. Its guarantee matches our lower bound up to logarithmic factors.
Complex structure of the carbon arc discharge for synthesis of nanotubes

Comprehensive non-invasive spectroscopic techniques and electrical measurements of the carbon arc revealed two distinguishable plasma synthesis regions in the radial direction normal to the arc axis. These regions, which are defined as the arc core and the arc periphery, are shown to have very different compositions of carbon species with different densities and temperatures. The colder arc periphery is dominated by carbon diatomic molecules (C2), which are in the minority in the composition of the hot arc core. These differences are due to a highly non-uniform distribution of the arc current, which is mainly conducted through the arc core populated with carbon atoms and ions. Therefore, the ablation of the graphite anode is governed by the arc core, while the formation of carbon molecules occurs in the colder arc periphery. This result is consistent with previous predictions that the plasma environment in the arc periphery is suitable for synthesis of carbon nanotubes.
Heart beat characterization from ballistocardiogram signals using extended functions of multiple instances

A multiple instance learning (MIL) method, extended Function of Multiple Instances (eFUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The goal of this approach is to learn a personalized heartbeat “concept” for an individual. This heartbeat concept is a prototype (or “signature”) that characterizes the heartbeat pattern for an individual in ballistocardiogram data. The eFUMI method models the problem of learning a heartbeat concept from a BCG signal as a MIL problem. This approach elegantly addresses the uncertainty inherent in a BCG signal (e. g., misalignment between training data and ground truth, mis-collection of heartbeat by some transducers, etc.). Given a BCG training signal coupled with a ground truth signal (e.g., a pulse finger sensor), training “bags” labeled with only binary labels denoting if a training bag contains a heartbeat signal or not can be generated. Then, using these bags, eFUMI learns a personalized concept of heartbeat for a subject as well as several non-heartbeat background concepts. After learning the heartbeat concept, heartbeat detection and heart rate estimation can be applied to test data. Experimental results show that the estimated heartbeat concept found by eFUMI is more representative and a more discriminative prototype of the heartbeat signals than those found by comparison MIL methods in the literature.
Stochastic scattering theory for excitation-induced dephasing: Comparison to the Anderson-Kubo lineshape.

In this paper, we present a quantum stochastic model for spectroscopic lineshapes in the presence of a co-evolving and non-stationary background population of excitations. Starting from a field theory description for interacting bosonic excitons, we derive a reduced model whereby optical excitons are coupled to an incoherent background via scattering as mediated by their screened Coulomb coupling. The Heisenberg equations of motion for the optical excitons are then driven by an auxiliary stochastic population variable, which we take to be the solution of an Ornstein–Uhlenbeck process. Ito’s lemma then allows us to easily construct and evaluate correlation functions and response functions. Focusing on the linear response, we compare our model to the classic Anderson–Kubo model. While similar in motivation, there are differences in the predicted lineshapes, notably in terms of asymmetry, and variation with the increasing background population.
High-fidelity simulation of a standing-wave thermoacoustic–piezoelectric engine

We have carried out wall-resolved unstructured fully compressible Navier–Stokes simulations of a complete standing-wave thermoacoustic–piezoelectric engine model inspired by the experimental work of Smoker et al. (J. Appl. Phys., vol. 111 (10), 2012, 104901). The model is axisymmetric and comprises a 51 cm long resonator divided into two sections: a small-diameter section enclosing a thermoacoustic stack and a larger-diameter section capped by a piezoelectric diaphragm tuned to the thermoacoustically amplified mode (388 Hz). The diaphragm is modelled with multi-oscillator broadband time-domain impedance boundary conditions (TDIBCs), providing higher fidelity over single-oscillator approximations. Simulations are first carried out to the limit cycle without energy extraction. The observed growth rates are shown to be grid convergent and are verified against a numerical dynamical model based on Rott’s theory. The latter is based on a staggered grid approach and allows jump conditions in the derivatives of pressure and velocity in sections of abrupt area change and the inclusion of linearized minor losses. The stack geometry maximizing the growth rate is also found. At the limit cycle, thermoacoustic heat leakage and frequency shifts are observed, consistent with experiments. Upon activation of the piezoelectric diaphragm, steady acoustic energy extraction and a reduced pressure amplitude limit cycle are obtained. A heuristic closure of the limit cycle acoustic energy budget is presented, supported by the linear dynamical model and the nonlinear simulations. The developed high-fidelity simulation framework provides accurate predictions of thermal-to-acoustic and acoustic-to-mechanical energy conversion (via TDIBCs), enabling a new paradigm for the design and optimization of advanced thermoacoustic engines.
Unconditionally Energy Stable DG Schemes for the Swift–Hohenberg Equation

The Swift–Hohenberg equation as a central nonlinear model in modern physics has a gradient flow structure. Here we introduce fully discrete discontinuous Galerkin (DG) schemes for a class of fourth order gradient flow problems, including the nonlinear Swift–Hohenberg equation, to produce free-energy-decaying discrete solutions, irrespective of the time step and the mesh size. We exploit and extend the mixed DG method introduced in Liu and Yin (J Sci Comput 77:467–501, 2018) for the spatial discretization, and the “Invariant Energy Quadratization” method for the time discretization. The resulting IEQ-DG algorithms are linear, thus they can be efficiently solved without resorting to any iteration method. We actually prove that these schemes are unconditionally energy stable. We present several numerical examples that support our theoretical results and illustrate the efficiency, accuracy and energy stability of our new algorithm. The numerical results on two dimensional pattern formation problems indicate that the method is able to deliver comparable patterns of high accuracy.
Sequential phase transitions and transient structured fluctuations in two-dimensional systems with a high-density Kagome lattice phase.

We report studies of (i) the isothermal density dependent sequences of phases in two-dimensional systems of particles with repulsive pair potentials devised by Truskett [J. Chem. Phys. 145, 054901 (2016)] and Torquato [Phys. Rev. E 88, 042309 (2013)] to support a high-density Kagome lattice phase and (ii) transient structured fluctuations close to a transition to a Kagome lattice. The commonalities in the sequences of phases in these systems and other 2D systems suggest the existence of a universal mechanism driving all to favor similar packing arrangements as the density is increased, but the simulations also show that the only such general rule proposed, namely, the Suto theorem, is not a necessary condition for the support of multiple distinct lattice structures by a particular pair potential. The transient fluctuations in the liquid close to the liquid-to-Kagome phase transition have Kagome symmetry, whereas deeper in the liquid phase, the fluctuations have hexagonal symmetry. When the transition is string-to-Kagome phase, the transient structured fluctuations in the string phase have both six-fold and other than six-fold symmetries. The path of the string-to-Kagome transition in the Truskett system involves intermediate honeycomb configurations that subsequently buckle to form a Kagome lattice. The path of the string-to-Kagome transition in the Torquato system suggests that the Kagome phase is formed by coiled strings merging together; increasing density generates a Kagome phase with imperfections such as 8-particle rings.
RECONCILING MODELS OF LUMINOUS BLAZARS WITH MAGNETIC FLUXES DETERMINED BY RADIO CORE-SHIFT MEASUREMENTS

Estimates of magnetic field strength in relativistic jets of active galactic nuclei, obtained by measuring the frequency-dependent radio core location, imply that the total magnetic fluxes in those jets are consistent with the predictions of the magnetically arrested disk (MAD) scenario of jet formation. On the other hand, the magnetic field strength determines the luminosity of the synchrotron radiation, which forms the low-energy bump of the observed blazar spectral energy distribution (SED). The SEDs of the most powerful blazars are strongly dominated by the high-energy bump, which is most likely due to the external radiation Compton mechanism. This high Compton dominance may be difficult to reconcile with the MAD scenario, unless (1) the geometry of external radiation sources (broad-line region, hot-dust torus) is quasi-spherical rather than flat, or (2) most gamma-ray radiation is produced in jet regions of low magnetization, e.g., in magnetic reconnection layers or in fast jet spines.
The High-energy emission of jetted AGN

Quasars with flat radio spectra and one-sided, arc-second scale, ≈ 100 mJy GHz radio jets are found to have similar scale X-ray jets in about 60% of such objects, even in short 5 to 10 ks Chandra observations. Jets emit in the GHz band via synchrotron radiation, as known from polarization measurements. The X-ray emission is explained most simply, i.e. with the fewest additional parameters, as inverse Compton (iC) scattering of cosmic microwave background (cmb) photons by the relativistic electrons in the jet. With physics based assumptions, one can estimate enthalpy fluxes upwards of 1046 erg s−1, sufficient to reverse cooling flows in clusters of galaxies, and play a significant role in the feedback process which correlates the masses of black holes and their host galaxy bulges. On a quasar-by-quasar basis, we can show that the total energy to power these jets can be supplied by the rotational energy of black holes with spin parameters as low as a = 0.3. For a few bright jets at redshifts less than 1, the Fermi gamma ray observatory shows upper limits at 10 Gev which fall below the fluxes predicted by the iC/cmb mechanism, proving the existence of multiple relativistic particle populations. At large redshifts, the cmb energy density is enhanced by a factor (1+z)4, so that iC/cmb must be the dominant mechanism for relativistic jets unless their rest frame magnetic field strength is hundreds of micro-Gauss.
Locality and nonlinear quantum mechanics

Nonlinear modifications of quantum mechanics generically lead to nonlocal effects which violate relativistic causality. We study these effects using the functional Schrodinger equation for quantum fields and identify a type of nonlocality which causes nearly instantaneous entanglement of spacelike separated systems. We describe a simple example involving widely separated wave packet (coherent) states, showing that nonlinearity in the Schrodinger evolution causes spacelike entanglement, even in free field theory.
Gauged supergravity from the Lunin-Maldacena background

We show how to expand the Lunin-Maldacena solution to the full bosonic sector of gauged $$ \mathcal{N} $$ = 2 supergravity. In particular, we construct a consistent truncation of IIB supergravity on a β-deformed AdS5 × S5 background retaining a dynamical metric and graviphoton in five dimensions. We comment on the relation between this solution and similar constructions on Sasaki-Einstein manifolds, as well as the possibility of further consistent truncations which generalize the Lunin-Maldacena solution.
TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction

Critical incident stages identification and reasonable prediction of traffic incident duration are essential in traffic incident management. In this paper, we propose a traffic incident duration prediction model that simultaneously predicts the impact of the traffic incidents and identifies the critical groups of temporal features via a multi-task learning framework. First, we formulate a sparsity optimization problem that extracts low-level temporal features based on traffic speed readings and then generalizes higher level features as phases of traffic incidents. Second, we propose novel constraints on feature similarity exploiting prior knowledge about the spatial connectivity of the road network to predict the incident duration. The proposed problem is challenging to solve due to the orthogonality constraints, non-convexity objective, and non-smoothness penalties. We develop an algorithm based on the alternating direction method of multipliers (ADMM) framework to solve the proposed formulation. Extensive experiments and comparisons to other models on real-world traffic data and traffic incident records justify the efficacy of our model.
Stability and dynamics of magnetocapillary interactions

Recent experiments have shown that floating ferromagnetic beads, under the influence of an oscillating background magnetic field, can move along a liquid–air interface in a sustained periodic locomotion [Lumay et al., Soft Matter, 2013, 9, 2420]. Dynamic activity arises from a periodically induced dipole–dipole repulsion between the beads acting in concert with capillary attraction. We investigate analytically and numerically the stability and dynamics of this magnetocapillary swimming, and explore other related topics including the steady and periodic equilibrium configurations of two and three beads, and bead collisions. The swimming speed and system stability depend on a dimensionless measure of the relative repulsive and attractive forces which we term the magnetocapillary number. An oscillatory magnetic field may stabilize an otherwise unstable collinear configuration, and striking behaviors are observed in fast transitions to and from locomotory states, offering insight into the behavior and self-assembly of interface-bound micro-particles.
Superconformal multi-black hole quantum mechanics

The quantum mechanics of N slowly-moving charged BPS black holes in five-dimensional = 1 supergravity is considered. The moduli space metric of the N black holes is derived and shown to admit 4 supersymmetries. A near-horizon limit is found in which the dynamics of widely separated black holes decouples from that of strongly-interacting, near-coincident black holes. This decoupling suggests that the quantum states supported in the near-horizon moduli space can be interpreted as internal states of a single composite black hole carrying all of the charge. The near-horizon theory is shown to have an enhanced D(2,1;0) superconformal symmetry. Eigenstates of the Hamiltonian H of the near-horizon theory are ill-defined due to noncompact regions of the moduli space corresponding to highly redshifted near-coincident black holes. It is argued that one should consider, instead of H eigenstates, eigenstates of 2L0 = H+K, where K is the generator of special conformal transformations. The result is a well defined Hilbert space with a discrete spectrum describing the N-black hole dynamics.