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Kagome metals have established a new arena for correlated electron physics. To date, the predominant experimental evidence centers around unconventional charge order, nematicity, and superconductivity, while magnetic fluctuations due to electronic interactions, i.e., beyond local atomic magnetism, have largely been elusive. From ab initio design and many-body analysis, we develop a model framework of Cu-based kagome materials the simulations of which reveal unconventional magnetic order in a kagome metal. We find the challenge of locating the appropriate parameter regime for such exotic order to center around two aspects. First, the correlations implied by low-energy orbitals have to be sufficiently large to yield a dominance of magnetic fluctuations and weak to retain an itinerant parent state. Second, the kinematic kagome profile at the Fermi level demands an efficient mitigation of sublattice interference causing the suppression of magnetic fluctuations descending from electronic onsite repulsion. We elucidate our methodology by analyzing the proposed compound CsCu$_3$Cl$_5$, assessing its feasibility for future material synthesis., Comment: 5 pages, 3 figures

We argue that kagome metals can feature an excitonic condensate of unconventional nature. Studying the recently discovered variant ScV$_6$Sn$_6$, we identify electron and hole pockets due to a pair of van Hove singularities (vHS) close to the Fermi level, with an approximate spectral particle-hole symmetry at low energies. A significant fraction of the Fermi level density of states away from the vHS is removed by the onset of high temperature charge density wave order, and makes the bands more two dimensional, setting the stage for the formation of excitons. We develop a two-orbital minimal model which captures these features, along with the sublattice support of the wavefunctions, and find $s$-wave or $d$-wave excitons depending on the microscopic interaction parameters -- the latter of which exhibits either a charge nematic or time-reversal symmetry breaking flux order depending on strain, offering an explanation of recent STM and transport experiments. The appearance of particle-type and hole-type vHS, and the excitonic resonance associated with it, may be a common thread to understanding nematicity and time-reversal symmetry breaking in kagome metals., Comment: 4.5 + 3 pages, 5 + 4 figures

Materials hosting flat bands at the vicinity of the Fermi level promote exotic symmetry broken states. Common to many of these are van Hove singularities at saddle points of the dispersion or even higher-order van Hove singularities where the dispersion is flattened further. The band structure of kagome metals hosts both a flat band and two regular saddle points flanking a Dirac node. We investigate the kagome ferromagnetic metal Co$_3$Sn$_2$S$_2$ using scanning tunneling spectroscopy. We identify a new mechanism by which a triangular distortion on its kagome Co$_3$Sn surface termination considerably flattens the saddle point dispersion, and induces an isolated higher-order van Hove singularity (HOvHS) with algebraically divergent density of states pinned to the Fermi energy. The distortion-induced HOvHS precipitates a Pomeranchuk instability of the Fermi surface, resulting in the formation of a series of nematic electronic states. We visualize the nematic order across an energy shell of about 100 meV in both real-, reciprocal-, and momentum-spaces, as a cascade of wavefunction distributions which spontaneously break the remaining rotational symmetry of the underlying distorted kagome lattice, without generating any additional translational symmetry breaking. It signifies the spontaneous removal of a subset of saddle points from the Fermi energy to lower energies. By tracking the electronic wavefunction structure across the deformed Fermi surface we further identify a charge pumping-like evolution of the wavefunction center of mass. The mechanism we find for the generation of higher-order saddle points under a kagome distortion may be common to other kagome materials, and potentially other lattice structures, suggesting a generic new avenue for inducing unconventional electronic instabilities towards exotic states of matter.

The recent observation of superconductivity in twisted bilayer WSe$_2$ raises intriguing questions concerning the origin and the properties of superconducting states realized in bands with non-trivial topological properties and repulsive electron-electron interactions. Using a continuum band structure model, we analyze a mechanism for Coulomb interaction-driven superconductivity in twisted bilayers of WSe$_2$. We discuss the symmetries and the phenomenological properties of the resulting superconducting phases and their evolution with interlayer potential difference, tunable via an out of plane electric field. The pairing strength is a non-monotonic function of interlayer potential, being larger at intermediate values due to mixing of singlet and triplet pairing. In contrast, at larger interlayer potential, the pairing tendency is suppressed due to enhanced Coulomb repulsion. The superconducting state is chiral in a large regime of parameters and undergoes a transition to a nodal nematic superconductor at a critical potential difference. The chiral state, characterized by an intervalley-symmetric superposition of triplet and singlet pairs, is classified as a topological superconductor within the Altland-Zirnbauer class C. At zero interlayer potential difference, the superconducting state is instead of class D, which hosts Majorana zero modes, making it a promising candidate for applications in quantum computation., Comment: 9+11 pages, 4+9 figures

The discovery of van der Waals superconductors in recent years has generated a lot of excitement for their potentially novel pairing mechanisms. However, their typical atomic-scale thickness and micrometer-scale lateral dimensions impose severe challenges to investigations of pairing symmetry by conventional methods. In this report we demonstrate a new technique that employs high-quality-factor superconducting resonators to measure the kinetic inductance -- up to a part per million -- and loss of a van der Waals superconductor. We analyze the equivalent circuit model to extract the kinetic inductance, superfluid stiffness, penetration depth, and ratio of imaginary and real parts of the complex conductivity. We validate the technique by measuring aluminum and finding excellent agreement in both the zero-temperature superconducting gap as well as the complex conductivity data when compared with BCS theory. We then demonstrate the utility of the technique by measuring the kinetic inductance of multi-layered niobium diselenide and discuss the limits to the accuracy of our technique when the transition temperature of the sample, NbSe$_2$ at 7.06 K, approaches our Nb probe resonator at 8.59 K. Our method will be useful for practitioners in the growing fields of superconducting physics, materials science, and quantum sensing, as a means of characterizing superconducting circuit components and studying pairing mechanisms of the novel superconducting states which arise in layered 2D materials and heterostructures., Comment: 17 pages, 4 tables, 17 figures

Novel states of matter arise in quantum materials due to strong interactions among electrons. A nematic phase breaks the point group symmetry of the crystal lattice and is known to emerge in correlated materials. Here we report the observation of an intra-unit-cell nematic order and signatures of Pomeranchuk instability in the Kagome metal ScV6Sn6. Using scanning tunneling microscopy and spectroscopy, we reveal a stripe-like nematic order breaking the crystal rotational symmetry within the Kagome lattice itself. Moreover, we identify a set of van Hove singularities adhering to the Kagome layer electrons, which appear along one direction of the Brillouin zone while being annihilated along other high-symmetry directions, revealing a rotational symmetry breaking. Via detailed spectroscopic maps, we further observe an elliptical deformation of Fermi surface, which provides direct evidence for an electronically mediated nematic order. Our work not only bridges the gap between electronic nematicity and Kagome physics, but also sheds light on the potential mechanism for realizing symmetry-broken phases in correlated electron systems., Comment: 19 pages, 5 figures

Vagus Nerve Stimulation (VNS) is an established palliative treatment for drug resistant epilepsy. While effective for many patients, its mechanism of action is incompletely understood. Predicting individuals' response, or optimum stimulation parameters, is challenging. Computational modelling has informed other problems in epilepsy but, to our knowledge, has not been applied to VNS. We started with an established, four-population neural mass model (NMM), capable of reproducing the seizure-like dynamics of a thalamocortical circuit. We extended this to include 18 further neural populations, representing nine other brain regions relevant to VNS, with connectivity based on existing literature. We modelled stimulated afferent vagal fibres as projecting to the nucleus tractus solitarius (NTS), which receives input from the vagus nerve in vivo. Bifurcation analysis of a deterministic version of the model showed higher background NTS input made the model monostable at a fixed point (FP), representing normal activity, while lower inputs produce bistability between the FP and a limit cycle (LC), representing the seizure state. Adding noise produced transitions between seizure and normal states. This stochastic model spent decreasing time in the seizure state with increasing background NTS input, until seizures were abolished, consistent with the deterministic model. Simulated VNS stimulation, modelled as a 30 Hz square wave, was summed with the background input to the NTS and was found to reduce total seizure duration in a dose-dependent manner, similar to expectations in vivo. We have successfully produced an in silico model of VNS in epilepsy, capturing behaviour seen in vivo. This may aid understanding therapeutic mechanisms of VNS in epilepsy and provides a starting point to (i) determine which patients might respond best to VNS, and (ii) optimise individuals' treatments.

The text in the profile of those offering their properties in England in English and in Germany in German, are compared to explore whether trust is built, and privacy concerns are reduced in the same way. Six methods of building trust are used by the landlords: (1) the level of formality, (2) distance and proximity, (3) emotiveness and humor, (4) being assertive and passive aggressive, (5) conformity to the platform language style and terminology and (6) setting boundaries. Privacy concerns are not usually reduced directly as this is left to the platform. The findings indicate that language has a limited influence and the platform norms and habits are the biggest influence.

Ultraclean graphene at charge neutrality hosts a quantum critical Dirac fluid of interacting electrons and holes. Interactions profoundly affect the charge dynamics of graphene, which is encoded in the properties of its electron-photon collective modes: surface plasmon polaritons (SPPs). Here we show that polaritonic interference patterns are particularly well suited to unveil the interactions in Dirac fluids by tracking polaritonic interference in time at temporal scales commensurate with the electronic scattering. Spacetime SPP interference patterns recorded in tera-hertz (THz) frequency range provided unobstructed readouts of the group velocity and lifetime of polariton that can be directly mapped onto the electronic spectral weight and the relaxation rate. Our data uncovered prominent departures of the electron dynamics from the predictions of the conventional Fermi-liquid theory. The deviations are particularly strong when the densities of electrons and holes are approximately equal. The proposed spacetime imaging methodology can be broadly applied to probe the electrodynamics of quantum materials.

Magic-angle twisted bilayer graphene (TBG) exhibits a captivating phase diagram as a function of doping, featuring superconductivity and a variety of insulating and magnetic states. The bands host Dirac fermions with a reduced Fermi velocity; experiments have shown that the Dirac dispersion reappears near integer fillings of the moir\'e unit cell -- referred to as the $\textit{Dirac revival}$ phenomenon. The reduced velocity of these Dirac states leads us to propose a scenario in which the Dirac fermions possess an approximately quadratic dispersion. The quadratic momentum dependence and particle-hole degeneracy at the Dirac point results in a logarithmic enhancement of interaction effects, which does not appear for a linear dispersion. The resulting non-trivial renormalisation group (RG) flow naturally produces the qualitative phase diagram as a function of doping -- with nematic and insulating states near integer fillings, which give way to superconducting states past a critical relative doping. The RG method further produces different results to strong-coupling Hartree-Fock treatments: producing T-IVC insulating states for repulsive interactions, explaining the results of very recent STM experiments, alongside nodal $A_2$ superconductivity near half-filling, whose properties explain puzzles in tunnelling studies of the superconducting state. The model explains a diverse range of additional experimental observations, unifying many aspects of the phase diagram of TBG.

Existing image/video datasets for cattle behavior recognition are mostly small, lack well-defined labels, or are collected in unrealistic controlled environments. This limits the utility of machine learning (ML) models learned from them. Therefore, we introduce a new dataset, called Cattle Visual Behaviors (CVB), that consists of 502 video clips, each fifteen seconds long, captured in natural lighting conditions, and annotated with eleven visually perceptible behaviors of grazing cattle. We use the Computer Vision Annotation Tool (CVAT) to collect our annotations. To make the procedure more efficient, we perform an initial detection and tracking of cattle in the videos using appropriate pre-trained models. The results are corrected by domain experts along with cattle behavior labeling in CVAT. The pre-hoc detection and tracking step significantly reduces the manual annotation time and effort. Moreover, we convert CVB to the atomic visual action (AVA) format and train and evaluate the popular SlowFast action recognition model on it. The associated preliminary results confirm that we can localize the cattle and recognize their frequently occurring behaviors with confidence. By creating and sharing CVB, our aim is to develop improved models capable of recognizing all important behaviors accurately and to assist other researchers and practitioners in developing and evaluating new ML models for cattle behavior classification using video data.

Interstellar objects (ISOs) represent a compelling and under-explored category of celestial bodies, providing physical laboratories to understand the formation of our solar system and probe the composition and properties of material formed in exoplanetary systems. In this work, we investigate existing approaches to designing successful flyby missions to ISOs, including a deep learning-driven guidance and control algorithm for ISOs traveling at velocities over 60 km/s. We have generated spacecraft trajectories to a series of synthetic representative ISOs, simulating a ground campaign to observe the target and resolve its state, thereby determining the cruise and close approach delta-Vs required for the encounter. We discuss the accessibility of and mission design to ISOs with varying characteristics, with special focuses on 1) state covariance estimation throughout the cruise, 2) handoffs from traditional navigation approaches to novel autonomous navigation for fast flyby regimes, and 3) overall recommendations about preparing for the future in situ exploration of these targets. The lessons learned also apply to the fast flyby of other small bodies, e.g., long-period comets and potentially hazardous asteroids, which also require tactical responses with similar characteristics., Comment: IEEE Aerospace Conference, Preprint Version, Accepted: November 2022

Interstellar objects (ISOs) are likely representatives of primitive materials invaluable in understanding exoplanetary star systems. Due to their poorly constrained orbits with generally high inclinations and relative velocities, however, exploring ISOs with conventional human-in-the-loop approaches is significantly challenging. This paper presents Neural-Rendezvous -- a deep learning-based guidance and control framework for encountering fast-moving objects, including ISOs, robustly, accurately, and autonomously in real time. It uses pointwise minimum norm tracking control on top of a guidance policy modeled by a spectrally-normalized deep neural network, where its hyperparameters are tuned with a loss function directly penalizing the MPC state trajectory tracking error. We show that Neural-Rendezvous provides a high probability exponential bound on the expected spacecraft delivery error, the proof of which leverages stochastic incremental stability analysis. In particular, it is used to construct a non-negative function with a supermartingale property, explicitly accounting for the ISO state uncertainty and the local nature of nonlinear state estimation guarantees. In numerical simulations, Neural-Rendezvous is demonstrated to satisfy the expected error bound for 100 ISO candidates. This performance is also empirically validated using our spacecraft simulator and in high-conflict and distributed UAV swarm reconfiguration with up to 20 UAVs., Comment: Preprint Version, Accepted: October, 2024 (One-minute YouTube summary: https://youtu.be/q3e0LYS2IYQ, DOI: https://doi.org/10.2514/1.G007671)

Recent experiments on kagome metals AV$_3$Sb$_5$ (A=K,Rb,Cs) [M. Kang et al., Nat. Phys. 18, 301-308 (2022)] identify twofold van Hove singularities (TvHS) with opposite concavity near the Fermi energy, generating two approximately hexagonal Fermi surfaces -- one electron-like and the other hole-like. Here we propose that a TvHS generates a novel time-reversal symmetry breaking excitonic order -- arising due to bound pairs of electrons and holes located at opposite concavity van Hove singularities. We introduce a minimal model for the TvHS and investigate interaction induced many-body instabilities via the perturbative renormalisation group technique and a free energy analysis. Specialising to parameters appropriate for the kagome metals AV$_3$Sb$_5$, we construct a phase diagram comprising chiral excitons, charge density wave and a region of coexistence. We propose this as an explanation of a diverse range of experimental observations in AV$_3$Sb$_5$. Notably, the chiral excitonic state gives rise to a quantum anomalous Hall conductance, providing an appealing interpretation of the observed anomalous Hall effect in kagome metals. Possible alternative realisations of the TvHS mechanism in bilayer materials are also discussed. We suggest that TvHS open up interesting possibilities for correlated phases, enriching the set of competing ground states to include excitonic order.

Onboard autonomy technologies such as planning and scheduling, identification of scientific targets, and content-based data summarization, will lead to exciting new space science missions. However, the challenge of operating missions with such onboard autonomous capabilities has not been studied to a level of detail sufficient for consideration in mission concepts. These autonomy capabilities will require changes to current operations processes, practices, and tools. We have developed a case study to assess the changes needed to enable operators and scientists to operate an autonomous spacecraft by facilitating a common model between the ground personnel and the onboard algorithms. We assess the new operations tools and workflows necessary to enable operators and scientists to convey their desired intent to the spacecraft, and to be able to reconstruct and explain the decisions made onboard and the state of the spacecraft. Mock-ups of these tools were used in a user study to understand the effectiveness of the processes and tools in enabling a shared framework of understanding, and in the ability of the operators and scientists to effectively achieve mission science objectives., Comment: 16 pages, 18 Figures, 1 Table, to be published in IEEE Aerospace 2022 (AeroConf 2022)

We explore higher order topological superconductivity in an artificial Dirac material with intrinsic spin-orbit coupling, which is a doped $\mathbb{Z}_2$ topological insulator in the normal state. A mechanism for superconductivity due to repulsive interactions -- $\mathit{pseudospin}$ $\mathit{pairing}$ -- has recently been shown to naturally result in higher-order topology in Dirac systems past a minimum chemical potential \cite{Li2021}. Here we apply this theory through microscopic modeling of a superlattice potential imposed on an inversion symmetric hole-doped semiconductor heterostructure, known as hole-based semiconductor artificial graphene, and extend previous work to include the effects of spin-orbit coupling. We find that spin-orbit coupling enhances interaction effects, providing an experimental handle to increase the efficiency of the superconducting mechanism. We show that the phase diagram of these systems, as a function of chemical potential and interaction strength, contains three superconducting states -- a first-order topological $p+ip$ state, a second-order topological spatially modulated $p+i\tau p$ state, and a second-order topological extended $s$-wave state, $s_\tau$. We calculate the symmetry-based indicators for the $p+i\tau p$ and $s_\tau$ states, which prove these states possess second-order topology. Exact diagonalisation results are presented which illustrate the interplay between the boundary physics and spin orbit interaction. We argue that this class of systems offer an experimental platform to engineer and explore first and higher-order topological superconducting states.

We demonstrate the existence of novel interaction effects in hole-doped semiconductor quantum wells which are connected to dramatic changes in the Fermi surface geometry occurring upon variation of the doping. We present band structure calculations showing that quantum wells formed in $p$-type cubic semiconductors develop nested Fermi surfaces at a critical hole density set by the width $d$ of the quantum well $k_F\sim \pi/d$. Nesting gives rise to competing superconducting and charge or spin density wave order, which we analyze using the perturbative renormalization group method. The correlated phases may be created or destroyed by tuning the hole density towards or away from the critical density. Our results establish $p$-type semiconductor quantum wells as a platform for novel correlated phases, which may be precisely controlled using electrostatic gating and external magnetic fields.

A large class of decision making under uncertainty problems can be described via Markov decision processes (MDPs) or partially observable MDPs (POMDPs), with application to artificial intelligence and operations research, among others. Traditionally, policy synthesis techniques are proposed such that a total expected cost or reward is minimized or maximized. However, optimality in the total expected cost sense is only reasonable if system behavior in the large number of runs is of interest, which has limited the use of such policies in practical mission-critical scenarios, wherein large deviations from the expected behavior may lead to mission failure. In this paper, we consider the problem of designing policies for MDPs and POMDPs with objectives and constraints in terms of dynamic coherent risk measures, which we refer to as the constrained risk-averse problem. For MDPs, we reformulate the problem into a infsup problem via the Lagrangian framework and propose an optimization-based method to synthesize Markovian policies. For MDPs, we demonstrate that the formulated optimization problems are in the form of difference convex programs (DCPs) and can be solved by the disciplined convex-concave programming (DCCP) framework. We show that these results generalize linear programs for constrained MDPs with total discounted expected costs and constraints. For POMDPs, we show that, if the coherent risk measures can be defined as a Markov risk transition mapping, an infinite-dimensional optimization can be used to design Markovian belief-based policies. For stochastic finite-state controllers (FSCs), we show that the latter optimization simplifies to a (finite-dimensional) DCP and can be solved by the DCCP framework. We incorporate these DCPs in a policy iteration algorithm to design risk-averse FSCs for POMDPs., Comment: arXiv admin note: substantial text overlap with arXiv:2012.02423

We discuss a pairing mechanism in interacting two-dimensional multipartite lattices that intrinsically leads to a second order topological superconducting state with a spatially modulated gap. When the chemical potential is close to Dirac points, oppositely moving electrons on the Fermi surface undergo an interference phenomenon in which the Berry phase converts a repulsive electron-electron interaction into an effective attraction. The topology of the superconducting phase manifests as gapped edge modes in the quasiparticle spectrum and Majorana Kramers pairs at the corners. We present symmetry arguments which constrain the possible form of the electron-electron interactions in these systems and classify the possible superconducting phases which result. Exact diagonalization of the Bogoliubov-de Gennes Hamiltonian confirms the existence of gapped edge states and Majorana corner states, which strongly depend on the spatial structure of the gap. Possible applications to vanadium-based superconducting kagome metals AV$_3$Sb$_3$ (A=K,Rb,Cs) are discussed.

We consider the problem of designing policies for Markov decision processes (MDPs) with dynamic coherent risk objectives and constraints. We begin by formulating the problem in a Lagrangian framework. Under the assumption that the risk objectives and constraints can be represented by a Markov risk transition mapping, we propose an optimization-based method to synthesize Markovian policies that lower-bound the constrained risk-averse problem. We demonstrate that the formulated optimization problems are in the form of difference convex programs (DCPs) and can be solved by the disciplined convex-concave programming (DCCP) framework. We show that these results generalize linear programs for constrained MDPs with total discounted expected costs and constraints. Finally, we illustrate the effectiveness of the proposed method with numerical experiments on a rover navigation problem involving conditional-value-at-risk (CVaR) and entropic-value-at-risk (EVaR) coherent risk measures., Comment: Draft Accepted for Presentation at The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Feb. 2-9, 2021

A close partnership between people and partially autonomous machines has enabled decades of space exploration. But to further expand our horizons, our systems must become more capable. Increasing the nature and degree of autonomy - allowing our systems to make and act on their own decisions as directed by mission teams - enables new science capabilities and enhances science return. The 2011 Planetary Science Decadal Survey (PSDS) and on-going pre-Decadal mission studies have identified increased autonomy as a core technology required for future missions. However, even as scientific discovery has necessitated the development of autonomous systems and past flight demonstrations have been successful, institutional barriers have limited its maturation and infusion on existing planetary missions. Consequently, the authors and endorsers of this paper recommend that new programmatic pathways be developed to infuse autonomy, infrastructure for support autonomous systems be invested in, new practices be adopted, and the cost-saving value of autonomy for operations be studied., Comment: 10 pages (compared to 8 submitted to PSADS), 2 figures, submitted to National Academy of Sciences Planetary Science and Astrobiology Decadal Survey 2023-2032

Technology development efforts in autonomy and cyber-defense have been evolving independently of each other, over the past decade. In this paper, we report our ongoing effort to integrate these two presently distinct areas into a single framework. To this end, we propose the two-player partially observable stochastic game formalism to capture both high-level autonomous mission planning under uncertainty and adversarial decision making subject to imperfect information. We show that synthesizing sub-optimal strategies for such games is possible under finite-memory assumptions for both the autonomous decision maker and the cyber-adversary. We then describe an experimental testbed to evaluate the efficacy of the proposed framework.

We consider the problem of designing policies for partially observable Markov decision processes (POMDPs) with dynamic coherent risk objectives. Synthesizing risk-averse optimal policies for POMDPs requires infinite memory and thus undecidable. To overcome this difficulty, we propose a method based on bounded policy iteration for designing stochastic but finite state (memory) controllers, which takes advantage of standard convex optimization methods. Given a memory budget and optimality criterion, the proposed method modifies the stochastic finite state controller leading to sub-optimal solutions with lower coherent risk.

Artificial lattices have served as a platform to study the physics of unconventional superconductivity. We study semiconductor artificial graphene -- a honeycomb superlattice imposed on a semiconductor heterostructure -- which hosts the Dirac physics of graphene but with a tunable periodic potential strength and lattice spacing, allowing control of the strength of the electron-electron interactions. We demonstrate a new mechanism for superconductivity due to repulsive interactions which requires a strong lattice potential and a minimum doping away from the Dirac points. The mechanism relies on the Berry phase of the emergent Dirac fermions, which causes oppositely moving electron pairs near the Dirac points to interfere destructively, reducing the Coulomb repulsion and thereby giving rise to an effective attraction. The attractive component of the interaction is enhanced by a novel antiscreening effect which, in turn, increases with doping; as a result there is a minimum doping beyond which superconducting order generically ensues. The dominant superconducting state exhibits a spatially modulated gap with chiral $p$-wave symmetry. Microscopic calculations suggest that the possible critical temperatures are large relative to the low carrier densities, for a range of experimentally realistic parameters.

Research use of sensitive information -- personally identifiable information (PII), protected health information (PHI), commercial or proprietary data, and the like -- is increasing as researchers' skill with "big data" matures. Duke University's Protected Network is an environment with technical controls in place that provide research groups with essential pieces of security measures needed for studies using sensitive information. The environment uses virtualization and authorization groups extensively to isolate data, provide elasticity of resources, and flexibly meet a range of computational requirements within tightly controlled network boundaries. Since its beginning in 2011, the environment has supported about 200 research projects and groups and has served as a foundation for specialized and protected IT infrastructures in the social sciences, population studies, and medical research. This article lays out key features of the development of the Protected Network and outlines the IT infrastructure design and organizational features that Duke has used in establishing this resource for researchers. It consists of four sections: 1. Context, 2. Infrastructure, 3. Authentication and identity management, and 4. The infrastructure as a "platform.", Comment: 25 pp., 4 figs

The creation of particles by two colliding strong laser beams is considered. It is found that the electron-positron pairs created in the laser field via the Schwinger mechanism may recollide after one or several oscillations in the field. Their collision can take place at high energy, which the pair gains from the field. As a result, high energy gamma quanta can be created by inelastic scattering or annihilation of the pair. Moreover, heavy particles such as muon pairs may also be created via the annihilation $e^+ + e^-\rightarrow \mu^+ + \mu^- $. The probability of $e^-e^+$ collision is greatly enhanced due to a strong alignment of the electron and positron momenta with the electric field. The found muon creation rate exponentially exceeds the rate predicted by the direct Schwinger mechanism for muons, while the photon creation rate exponentially exceeds photon emission due to the fermion oscillation.

The collision of two intense, low-frequency laser beams is considered. The $e^-e^+$ pairs created in this field are shown to exhibit recollisions, which take place at high energy accumulated due to the wiggling of fermions. The resulting $e^-e^+$ annihilation produces high energy photons, or heavy particles. The coherent nature of the laser field provides strong enhancement of the probability of these events. Analytical and numerical results are outlined., Comment: 5 pages, 3 figures

We develop a curvilinear invariant set of the diffusion tensor which may be applied to Diffusion Tensor Imaging measurements on tissues and porous media. This new set is an alternative to the more common invariants such as fractional anisotropy and the diffusion mode. The alternative invariant set possesses a different structure to the other known invariant sets; the second and third members of the curvilinear set measure the degree of orthotropy and oblateness/prolateness, respectively. The proposed advantage of these invariants is that they may work well in situations of low diffusion anisotropy and isotropy, as is often observed in tissues such as cartilage. We also explore the other orthogonal invariant sets in terms of their geometry in relation to eigenvalue space; a cylindrical set, a spherical set (including fractional anisotropy and the mode), and a log-Euclidean set. These three sets have a common structure. The first invariant measures the magnitude of the diffusion, the second and third invariants capture aspects of the anisotropy; the magnitude of the anisotropy and the shape of the diffusion ellipsoid (the manner in which the anisotropy is realised). We also show a simple method to prove the orthogonality of the invariants within a set., Comment: 14 pages, 1 table. Published in PLoS ONE (open access) but reformatted here

SAXSFit is a computer analysis program that has been developed to assist in the fitting of small-angle x-ray and neutron scattering spectra primarily from nanoparticles (nanopores). The fitting procedure yields the pore or particle size distribution and eta parameter for one or two size distributions (which can be log-normal, Schulz, or Gaussian). A power-law and/or constant background can also be included. The program is written in Java so as to be stand-alone and platform-independent, and is designed to be easy for novices to use, with a user-friendly graphical interface., Comment: 5 pages

Structural analysis of a layered manganese tungstate diaminoalkane hybrid series suggests that this compound forms a spin-5/2 spin-ladder structure. We use X-ray diffraction, electron microscopy and x-ray absorption spectroscopy results to infer the structure. DC magnetization of the manganese compound and a possible copper analogue appear to show that the manganese system behaves like 1-dimensional antiferromagnetic Heisenberg chains (i.e. $J_{\parallel} \gg J_{\perp})$ while the copper system is fitted well by a $S = {1/2}$ spin ladder model, giving the parameters $g = 1.920 \pm 0.008$, $J_{\parallel}/k_B = -0.3 \pm 1.4$K; $J_{\perp}/k_B = 213.6 \pm 1.1$K. The ability to tune adjacent inorganic layers of the hybrid materials by altering the length of the organic `spacer' molecules gives enormous promise for the use of these materials, especially when doped, to provide a greater understanding of spin ladder systems., Comment: 7 pages, 9 figures

Tungsten trioxide adopts a variety of structures which can be intercalated with charged species to alter the electronic properties, thus forming `tungsten bronzes'. Similar optical effects are observed upon removing oxygen from WO_3, although the electronic properties are slightly different. Here we present a computational study of cubic and hexagonal alkali bronzes and examine the effects on cell size and band structure as the size of the intercalated ion is increased. With the exception of hydrogen (which is predicted to be unstable as an intercalate), the behaviour of the bronzes are relatively consistent. NaWO_3 is the most stable of the cubic systems, although in the hexagonal system the larger ions are more stable. The band structures are identical, with the intercalated atom donating its single electron to the tungsten 5d valence band. Next, this was extended to a study of fractional doping in the Na_xWO_3 system (0 < x < 1). A linear variation in cell parameter, and a systematic change in the position of the Fermi level up into the valence band was observed with increasing x. In the underdoped WO_3-x system however, the Fermi level undergoes a sudden jump into the conduction band at around x = 0.2. Lastly, three compounds of a layered WO_4×a,wdiaminoalkane hybrid series were studied and found to be insulating, with features in the band structure similar to those of the parent WO_3 compound which relate well to experimental UV-visible spectroscopy results., Comment: 12 pages, 16 figures

Tungsten oxide-organic layered hybrid materials have been studied by infrared and Raman spectroscopy, and demonstrate a difference in bonding nature as the length of the interlayer organic `spacer' molecule is increased. Ethylenediamine-tungsten oxide clearly displays a lack of terminal -NH3+ ammonium groups which appear in hybrids with longer alkane molecules, thus indicating that the longer chains are bound by electrostatic interactions as well as or in place of the hydrogen bonding that must be present in the shorter chain ethylenediamine hybrids. The presence of organic molecules between the tungsten oxide layers, compared with the layered tungstic acid H2WO4, shows a decrease in the apical W=O bond strength, as might be expected from the aforementioned electrostatic interaction., Comment: 7 pages, 5 figures

Tropospheric ozone (O3) negatively impacts human health and is also a greenhouse gas. It is formed photochemically by reactions of nitrogen oxides (NOx) and volatile organic compounds (VOCs), of which wildfires are an important source. This study presents data from research flights sampling wildfires in West and Central African savannah regions, both close to the fires and after the emissions had been transported several days over the tropical North Atlantic Ocean. Emission factors (EFs) in g kg-1 for NOx (as NO), six VOCs and formaldehyde were calculated from enhancement to mole fractions in data taken close to the fires. For NOx, the emission factor was calculated as 2.05±0.43 g kg-1 for Senegal and 1.20±0.28 g kg-1 for Uganda, both higher than the average value of 1.13±0.6 g kg-1 for previous studies of African savannah regions. For most VOCs (except acetylene), EFs in Uganda were lower by factors of 20-50% compared to Senegal, with almost all the values below those in the literature. O3 enhancement in the fire plumes was investigated by examining the ΔO3/ΔCO enhancement ratio, with values ranging from 0.07 - 0.14 close to the fires up to 0.25 for measurements taken over the Atlantic Ocean up to 200 hours downwind. In addition, measurements of O3 and its precursors were compared to the output of a global chemistry transport model (GEOS-CF) for the flights over the Atlantic Ocean. Normalised mean bias (NMB) comparison between the measured and modelled data was good outside of the fire plumes, with CO showing a model under-prediction of 4.6% and O3 a slight over-prediction of 0.7% (both within the standard deviation of the data). For NOx the agreement was poorer, with an under-prediction of 9.9% across all flights. Inside the fire plumes the agreement between modelled and measured values is worse, with the model being biased significantly lower for all three species. In total across all flights, there was an under-prediction of 29.4%, 16.5% and 37.5% for CO, O3 and NOx respectively. Finally, the measured ΔO3/ΔCO enhancement ratios were compared those in the model for the equivalent flight data, with the model showing a lower value of 0.17±0.03 compared to an observed value of 0.29±0.05. The results detailed here show that the O3 burden to the North Atlantic Ocean from African wildfires may be underestimated and that further study is required to better study the O3 precursor emissions and chemistry.

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