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2018-03-06
On Simple Back-Off in Unreliable Radio Networks
In this paper, we study local and global broadcast in the dual graph model, which describes communication in a radio network with both reliable and unreliable links. Existing work proved that efficient solutions to these problems are impossible in the dual graph model under standard assumptions. In real networks, however, simple back-off strategies tend to perform well for solving these basic communication tasks. We address this apparent paradox by introducing a new set of constraints to the dual graph model that better generalize the slow/fast fading behavior common in real networks. We prove that in the context of these new constraints, simple back-off strategies now provide efficient solutions to local and global broadcast in the dual graph model. We also precisely characterize how this efficiency degrades as the new constraints are reduced down to non-existent, and prove new lower bounds that establish this degradation as near optimal for a large class of natural algorithms. We conclude with a preliminary investigation of the performance of these strategies when we include additional generality to the model. These results provide theoretical foundations for the practical observation that simple back-off algorithms tend to work well even amid the complicated link dynamics of real radio networks.
1803.02216v3
2018-04-12
Connectivity in Random Annulus Graphs and the Geometric Block Model
We provide new connectivity results for {\em vertex-random graphs} or {\em random annulus graphs} which are significant generalizations of random geometric graphs. Random geometric graphs (RGG) are one of the most basic models of random graphs for spatial networks proposed by Gilbert in 1961, shortly after the introduction of the Erd\H{o}s-R\'{en}yi random graphs. They resemble social networks in many ways (e.g. by spontaneously creating cluster of nodes with high modularity). The connectivity properties of RGG have been studied since its introduction, and analyzing them has been significantly harder than their Erd\H{o}s-R\'{en}yi counterparts due to correlated edge formation. Our next contribution is in using the connectivity of random annulus graphs to provide necessary and sufficient conditions for efficient recovery of communities for {\em the geometric block model} (GBM). The GBM is a probabilistic model for community detection defined over an RGG in a similar spirit as the popular {\em stochastic block model}, which is defined over an Erd\H{o}s-R\'{en}yi random graph. The geometric block model inherits the transitivity properties of RGGs and thus models communities better than a stochastic block model. However, analyzing them requires fresh perspectives as all prior tools fail due to correlation in edge formation. We provide a simple and efficient algorithm that can recover communities in GBM exactly with high probability in the regime of connectivity.
1804.05013v3
2018-04-19
Equilibrium magnetization of a quasispherical cluster of single-domain particles
Equilibrium magnetization curve of a rigid finite-size spherical cluster of single-domain particles is investigated both numerically and analytically. The spatial distribution of particles within the cluster is random. Dipole-dipole interactions between particles are taken into account. The particles are monodisperse. It is shown, using the stochastic Landau-Lifshitz-Gilbert equation that the magnetization of such clusters is generally lower than predicted by the classical Langevin model. In a broad range of dipolar coupling parameters and particle volume fractions, the cluster magnetization in the weak field limit can be successfully described by the modified mean-field theory, which was originally proposed for the description of concentrated ferrofluids. In moderate and strong fields, the theory overestimates the cluster magnetization. However, predictions of the theory can be improved by adjusting the corresponding mean-field parameter. If magnetic anisotropy of particles is additionally taken into account and if the distribution of the particles' easy axes is random and uniform, then the cluster equilibrium response is even weaker. The decrease of the magnetization with increasing anisotropy constant is more pronounced at large applied fields. The phenomenological generalization of the modified mean-field theory, that correctly describes this effect for small coupling parameters, is proposed.
1804.07196v2
2018-05-28
Starbug fibre positioning robots: performance and reliability enhancements
Starbugs are miniature piezoelectric walking robots that can be operated in parallel to position many payloads like optical fibers across a telescopes focal plane. They consist of two concentric piezoelectric ceramic tubes that walk with micron step size. In addition to individual optical fibers, Starbugs have moved a payload of 0.75kg at several millimeters per second. The Australian Astronomical Observatory previously developed prototype devices and tested them in the laboratory. Now we are optimizing the Starbug design for production and deployment in the TAIPAN instrument, which will be capable of configuring 300 optical fibers over a six degree field-of-view on the UK Schmidt Telescope within a few minutes. The TAIPAN instrument will demonstrate the technology and capability for MANIFEST (Many Instrument Fiber-System) proposed for the Giant Magellan Telescope. Design is addressing: connector density and voltage limitations, mechanical reliability and construction repeatability, field plate residues and scratching, metrology stability, and facilitation of improved motion in all aspects of the design for later evaluation. Here we present the new design features of the AAO TAIPAN Starbug.
1805.10761v1
2018-06-14
Resolving interfacial charge transfer in titanate superlattices using resonant X-ray reflectometry
Charge transfer in oxide heterostructures can be tuned to promote emergent interfacial states, and accordingly, has been the subject of intense study in recent years. However, accessing the physics at these interfaces, which are often buried deep below the sample surface, remains difficult. Addressing this challenge requires techniques capable of measuring the local electronic structure with high-resolution depth dependence. Here, we have used linearly-polarized resonant X-ray reflectometry (RXR) as a means to visualize charge transfer in oxide superlattices with atomic layer precision. From our RXR measurements, we extract valence depth profiles of SmTiO$_3$ (SmTO)/SrTiO$_3$ (STO) heterostructures with STO quantum wells varying in thickness from 5 SrO planes down to a single, atomically thin SrO plane. At the polar-nonpolar SmTO/STO interface, an electrostatic discontinuity leads to approximately half an electron per areal unit cell transferred from the interfacial SmO layer into the neighboring STO quantum well. We observe this charge transfer as a suppression of the t$_{2g}$ absorption peaks that minimizes contrast with the neighboring SmTO layers at those energies and leads to a pronounced absence of superlattice peaks in the reflectivity data. Our results demonstrate the sensitivity of RXR to electronic reconstruction at the atomic scale, and establish RXR as a powerful means of characterizing charge transfer at buried oxide interfaces.
1806.05733v1
2018-06-18
Formation Timescales for High-Mass X-ray Binaries in M33
We have identified 55 candidate high-mass X-ray binaries (HMXBs) in M33 using available archival {\it HST} and {\it Chandra} imaging to find blue stars associated with X-ray positions. We use the {\it HST} photometric data to model the color-magnitude diagrams in the vicinity of each candidate HMXB to measure a resolved recent star formation history (SFH), and thus a formation timescale, or age for the source. Taken together, the SFHs for all candidate HMXBs in M33 yield an age distribution that suggests preferred formation timescales for HMXBs in M33 of $<$ 5 Myr and $\sim$ 40 Myr after the initial star formation episode. The population at 40 Myr is seen in other Local Group galaxies, and can be attributed to a peak in formation efficiency of HMXBs with neutron stars as compact objects and B star secondary companions. This timescale is preferred as neutron stars should form in abundance from $\sim$ 8 M$_{\odot}$ core-collapse progenitors on these timescales, and B stars are shown observationally to be most actively losing mass around this time. The young population at $<$ 5 Myr has not be observed in other Local Group HMXB population studies, but may be attributed to a population of very massive progenitors forming black holes very early on. We discuss these results in the context of massive binary evolution, and the implications for compact object binaries and gravitational wave sources.
1806.06863v1
2018-06-24
Nanoscopic time crystal obtained by nonergodic spin dynamics
We study the far-from-equilibrium properties of quenched magnetic nanoscopic classical spin systems. In particular, we focus on the interplay between lattice vibrations and magnetic frustrations induced by surface effects typical of an antiferromagnet. We use a combination of Monte Carlo simulations and explore the dynamical behaviours by solving the stochastic Landau-Lifshitz-Gilbert equation at finite temperature. The Monte Carlo approach treats both the ionic degrees of freedom and spin variables on the same footing, via an extended Lennard-Jones Hamiltonian with a spin-lattice coupling. The zero temperature phase diagram of the finite size nanoscopic systems with respect to the range of the Heisenberg interaction and the Lennard-Jones coupling constant shows two main structures with non-trivial magnetisation triggered by antiferromagnetism: a simple cubic and a body-centred cubic. At non zero temperature, the competition between spins and the ionic vibrations considerably affects the magnetization of the system. Exploring the dynamics reveals a non-trivial structural induced behaviour in the spin relaxation with a concomitant memory of the initially applied ferromagnetic quench. We report the observation of a non-trivial dynamical scenario, obtained after a ferromagnetic magnetic quench at low temperature. Furthermore, we observe long-lived non-thermal states which could open new avenues for nano-technology.
1806.09130v4
2018-06-29
The warm Neptunes around HD 106315 have low stellar obliquities
We present the obliquity of the warm Neptune HD 106315c measured via a series of spectroscopic transit observations. HD 106315c is a 4.4 REarth warm Neptune orbiting a moderately rotating late F-star with a period of 21.05 days. HD 106315 also hosts a 2.5 REarth super-Earth on a 9.55 day orbit. Our Doppler tomographic analyses of four transits observed by the Magellan/MIKE, HARPS, and TRES facilities find HD 106315c to be in a low stellar obliquity orbit, consistent with being well aligned with the spin axis of the host star at lambda = -10 +3.6/-3.8 deg. We suggest, via dynamical N-body simulations, that the two planets in the system must be co-planar, and thus are both well aligned with the host star. HD 106315 is only the fourth warm Neptune system with obliquities measured. All warm Neptune systems have been found in well aligned geometries, consistent with the interpretation that these systems are formed in-situ in the inner protoplanetary disk, and also consistent with the majority of Kepler multi-planet systems that are in low obliquity orbits. With a transit depth of 1.02 mmag, HD 106315c is among the smallest planets to have been detected in transit spectroscopy, and we discuss its detection in the context of TESS and the next generations of spectrographs.
1807.00024v1
2018-07-13
BFORE: A CMB Balloon Payload to Measure Reionization, Neutrino Mass, and Cosmic Inflation
BFORE is a high-altitude ultra-long-duration balloon mission to map the cosmic microwave background (CMB). During a 28-day mid-latitude flight launched from Wanaka, New Zealand, the instrument will map half the sky to improve measurements of the optical depth to reionization tau. This will break parameter degeneracies needed to detect neutrino mass. BFORE will also hunt for the gravitational wave B-mode signal, and map Galactic dust foregrounds. The mission will be the first near-space use of TES/mSQUID multichroic detectors (150/217 GHz and 280/353 GHz bands) with low-power readout electronics.
1807.05215v1
2018-07-19
Unsupervised Metric Learning in Presence of Missing Data
For many machine learning tasks, the input data lie on a low-dimensional manifold embedded in a high dimensional space and, because of this high-dimensional structure, most algorithms are inefficient. The typical solution is to reduce the dimension of the input data using standard dimension reduction algorithms such as ISOMAP, LAPLACIAN EIGENMAPS or LLES. This approach, however, does not always work in practice as these algorithms require that we have somewhat ideal data. Unfortunately, most data sets either have missing entries or unacceptably noisy values. That is, real data are far from ideal and we cannot use these algorithms directly. In this paper, we focus on the case when we have missing data. Some techniques, such as matrix completion, can be used to fill in missing data but these methods do not capture the non-linear structure of the manifold. Here, we present a new algorithm MR-MISSING that extends these previous algorithms and can be used to compute low dimensional representation on data sets with missing entries. We demonstrate the effectiveness of our algorithm by running three different experiments. We visually verify the effectiveness of our algorithm on synthetic manifolds, we numerically compare our projections against those computed by first filling in data using nlPCA and mDRUR on the MNIST data set, and we also show that we can do classification on MNIST with missing data. We also provide a theoretical guarantee for MR-MISSING under some simplifying assumptions.
1807.07610v3
2018-08-09
Four new eclipsing mid M-dwarf systems from the New Luyten Two Tenths catalog
Using data from the MEarth-North and MEarth-South transit surveys, we present the detection of eclipses in four mid M-dwarf systems: LP 107-25, LP 261-75, LP 796-24, and LP 991-15. Combining the MEarth photometry with spectroscopic follow-up observations, we show that LP 107-25 and LP 796-24 are short-period (1.388 and 0.523 day, respectively) eclipsing binaries in triple-lined systems with substantial third light contamination from distant companions. LP 261-75 is a short-period (1.882 day) single-lined system consisting of a mid M-dwarf eclipsed by a probable brown dwarf secondary, with another distant visual brown dwarf companion. LP 991-15 is a long-period (29.3 day) double-lined eclipsing binary on an eccentric orbit with a geometry which produces only primary eclipses. A spectroscopic orbit is given for LP 991-15, and initial orbits for LP 107-25 and LP 261-75.
1808.03243v1
2018-08-14
Addressing Johnson graphs, complete multipartite graphs, odd cycles and other graphs
Graham and Pollak showed that the vertices of any graph $G$ can be addressed with $N$-tuples of three symbols, such that the distance between any two vertices may be easily determined from their addresses. An addressing is optimal if its length $N$ is minimum possible. In this paper, we determine an addressing of length $k(n-k)$ for the Johnson graphs $J(n,k)$ and we show that our addressing is optimal when $k=1$ or when $k=2, n=4,5,6$, but not when $n=6$ and $k=3$. We study the addressing problem as well as a variation of it in which the alphabet used has more than three symbols, for other graphs such as complete multipartite graphs and odd cycles. We also present computations describing the distribution of the minimum length of addressings for connected graphs with up to $10$ vertices. Motivated by these computations we settle a problem of Graham, showing that most graphs on $n$ vertices have an addressing of length at most $n-(2-o(1))\log_2 n$.
1808.04757v2
2018-09-26
On Bioelectric Algorithms: A Novel Application of Theoretical Computer Science to Core Problems in Developmental Biology
Cellular bioelectricity describes the biological phenomenon in which cells in living tissue generate and maintain patterns of voltage gradients induced by differing concentrations of charged ions. A growing body of research suggests that bioelectric patterns represent an ancient system that plays a key role in guiding many important developmental processes including tissue regeneration, tumor suppression, and embryogenesis. Understanding the relationship between high-level bioelectric patterns and low-level biochemical processes might also enable powerful new forms of synthetic biology. A key open question in this area is understanding how a collection of cells, interacting with each other and the extracellular environment only through simple ligand bindings and ion fluxes, can compute non-trivial patterns and perform non-trivial information processing tasks. The standard approach to this question is to model a given bioelectrical network as a system of differential equations and then explore its behavior using simulation techniques. In this paper, we propose applying a computational approach. In more detail, we present the cellular bioelectric model (CBM), a new computational model that captures the primary capabilities and constraints of bioelectric interactions between cells and their environment. We use this model to investigate several important topics in cellular bioelectricity, including symmetry breaking and information processing. Among other results, we describe and analyze a basic bioelectric strategy the efficiently stabilizes arbitrary cell networks into maximal independent sets (a structure known to play a role in the nervous system development of flys), and prove cells in our model are Turing complete in their ability to process information encoded in their initial voltage potential.
1809.10046v1
2018-10-02
Floquet engineering of classical systems
We develop the Floquet-Magnus expansion for a classical equation of motion under a periodic drive that is applicable to both isolated and open systems. For classical systems, known approaches based on the Floquet theorem fail due to the nonlinearity and the stochasticity of their equations of motion (EOMs) in contrast to quantum ones. Here, employing their master equation, we successfully extend the Floquet methodology to classical EOMs to obtain their Floquet-Magnus expansions, thereby overcoming this difficulty. Our method has a wide range of application from classical to quantum as long as they are described by differential equations including the Langevin equation, the Gross-Pitaevskii equation, and the time-dependent Ginzburg-Landau equation. By analytically evaluating the higher-order terms of the Floquet-Magnus expansion, we find that it is, at least asymptotically, convergent and well approximates the relaxation to their prethermal or non-equilibrium steady states. To support these analytical findings, we numerically analyze two examples: (i) the Kapitza pendulum with friction and (ii) laser-driven magnets described by the stochastic Landau-Lifshitz-Gilbert equation. In both cases, the effective EOMs obtained from their Floquet-Magnus expansions correctly reproduce their exact time evolution for a long time up to their non-equilibrium steady states. In the example of driven magnets, we demonstrate the controlled generations of a macroscopic magnetization and a spin chirality by laser and discuss possible applications to spintronics.
1810.01103v2
2018-10-02
Geodesic motion on the groups of diffeomorphisms with $H^1$ metric as geometric generalised Lagrangian mean theory
Generalized Lagrangian mean theories are used to analyze the interactions between mean flows and fluctuations, where the decomposition is based on a Lagrangian description of the flow. A systematic geometric framework was recently developed by Gilbert and Vanneste (J. Fluid Mech., 2018) who cast the decomposition in terms of intrinsic operations on the group of volume preserving diffeomorphism or on the full diffeomorphism group. In this setting, the mean of an ensemble of maps can be defined as the Riemannian center of mass on either of these groups. We apply this decomposition in the context of Lagrangian averaging where equations of motion for the mean flow arise via a variational principle from a mean Lagrangian, obtained from the kinetic energy Lagrangian of ideal fluid flow via a small amplitude expansion for the fluctuations. We show that the Euler-$\alpha$ equations arise as Lagrangian averaged Euler equations when using the $L^2$-geodesic mean on the volume preserving diffeomorphism group of a manifold without boundaries, imposing a `Taylor hypothesis', which states that first order fluctuations are transported as a vector field by the mean flow, and assuming that fluctuations are statistically isotropic. Similarly, the EPDiff equations arise as the Lagrangian averaged Burgers' equations using the same argument on the full diffeomorphism group. These results generalize an earlier observation by Oliver (Proc. R. Soc. A, 2017) to manifolds in geometrically fully intrinsic terms.
1810.01377v1
2018-10-07
Training Convolutional Neural Networks and Compressed Sensing End-to-End for Microscopy Cell Detection
Automated cell detection and localization from microscopy images are significant tasks in biomedical research and clinical practice. In this paper, we design a new cell detection and localization algorithm that combines deep convolutional neural network (CNN) and compressed sensing (CS) or sparse coding (SC) for end-to-end training. We also derive, for the first time, a backpropagation rule, which is applicable to train any algorithm that implements a sparse code recovery layer. The key observation behind our algorithm is that cell detection task is a point object detection task in computer vision, where the cell centers (i.e., point objects) occupy only a tiny fraction of the total number of pixels in an image. Thus, we can apply compressed sensing (or, equivalently sparse coding) to compactly represent a variable number of cells in a projected space. Then, CNN regresses this compressed vector from the input microscopy image. Thanks to the SC/CS recovery algorithm (L1 optimization) that can recover sparse cell locations from the output of CNN. We train this entire processing pipeline end-to-end and demonstrate that end-to-end training provides accuracy improvements over a training paradigm that treats CNN and CS-recovery layers separately. Our algorithm design also takes into account a form of ensemble average of trained models naturally to further boost accuracy of cell detection. We have validated our algorithm on benchmark datasets and achieved excellent performances.
1810.03075v1
2018-11-16
Asymmetric Drift in the Andromeda Galaxy (M31) as a Function of Stellar Age
We analyze the kinematics of Andromeda's disk as a function of stellar age by using photometry from the Panchromatic Hubble Andromeda Treasury (PHAT) survey and spectroscopy from the Spectroscopic and Photometric Landscape of Andromeda's Stellar Halo (SPLASH) survey. We use HI 21-cm and CO ($\rm J=1 \rightarrow 0$) data to examine the difference between the deprojected rotation velocity of the gas and that of the stars. We divide the stars into four stellar age bins, from shortest lived to longest lived: massive main sequence stars (0.03 Gyr), more luminous intermediate mass asymptotic giant branch (AGB) stars (0.4 Gyr), less luminous intermediate mass AGB stars (2 Gyr), and low mass red giant branch stars (4 Gyr). There is a clear correlation between the offset of the stellar and the gas rotation velocity, or the asymmetric drift: the longer lived populations lag farther behind the gas than short lived populations. We also examine possible causes of the substructure in the rotation curves and find that the most significant cause of scatter in the rotation curves comes from the tilted ring model being an imperfect way to account for the multiple warps in Andromeda's disk.
1811.07037v2
2018-11-21
Exploring interfacial exchange coupling and sublattice effect in heavy metal/ferrimagnetic insulator heterostructures using Hall measurements, x-ray magnetic circular dichroism, and neutron reflectometry
We use temperature-dependent Hall measurements to identify contributions of spin Hall, magnetic proximity, and sublattice effects to the anomalous Hall signal in heavy metal/ferrimagnetic insulator heterostructures with perpendicular magnetic anisotropy. This approach enables detection of both the magnetic proximity effect onset temperature and the magnetization compensation temperature and provides essential information regarding the interfacial exchange coupling. Onset of a magnetic proximity effect yields a local extremum in the temperature-dependent anomalous Hall signal, which occurs at higher temperature as magnetic insulator thickness increases. This magnetic proximity effect onset occurs at much higher temperature in Pt than W. The magnetization compensation point is identified by a sharp anomalous Hall sign change and divergent coercive field. We directly probe the magnetic proximity effect using x-ray magnetic circular dichroism and polarized neutron reflectometry, which reveal an antiferromagnetic coupling between W and the magnetic insulator. Finally, we summarize the exchange-coupling configurations and the anomalous Hall-effect sign of the magnetized heavy metal in various heavy metal/magnetic insulator heterostructures.
1811.08574v2
2018-12-13
Qatar Exoplanet Survey: Qatar-7b -- A Very Hot Jupiter Orbiting a Metal Rich F-Star
We present the discovery of Qatar-7b --- a very hot and inflated giant gas planet orbiting close its parent star. The host star is a relatively massive main sequence F-star with mass and radius Mstar = 1.41 +/- 0.03 Msun and Rstar = 1.56 +/- 0.02 Rsun, respectively, at a distance d = 726 +/- 26 pc, and an estimated age ~1 Gyr. With its orbital period of P = 2.032 days the planet is located less than 5 stellar radii from its host star and is heated to a high temperature Teq ~ 2100 K. From a global solution to the available photometric and radial velocity observations, we calculate the mass and radius of the planet to be Mpl = 1.88 +/- 0.25 Mjup and Rpl = 1.70 +/- 0.03 Rjup, respectively. The planet radius and equilibrium temperature put Qatar-7b in the top 6% of the hottest and largest known exoplanets. With its large radius and high temperature Qatar-7b is a valuable addition to the short list of targets that offer the best opportunity for studying their atmospheres through transmission spectroscopy.
1812.05601v1
2019-01-02
Leader Election in Well-Connected Graphs
In this paper, we look at the problem of randomized leader election in synchronous distributed networks with a special focus on the message complexity. We provide an algorithm that solves the implicit version of leader election (where non-leader nodes need not be aware of the identity of the leader) in any general network with $O(\sqrt{n} \log^{7/2} n \cdot t_{mix})$ messages and in $O(t_{mix}\log^2 n)$ time, where $n$ is the number of nodes and $t_{mix}$ refers to the mixing time of a random walk in the network graph $G$. For several classes of well-connected networks (that have a large conductance or alternatively small mixing times e.g. expanders, hypercubes, etc), the above result implies extremely efficient (sublinear running time and messages) leader election algorithms. Correspondingly, we show that any substantial improvement is not possible over our algorithm, by presenting an almost matching lower bound for randomized leader election. We show that $\Omega(\sqrt{n}/\phi^{3/4})$ messages are needed for any leader election algorithm that succeeds with probability at least $1-o(1)$, where $\phi$ refers to the conductance of a graph. To the best of our knowledge, this is the first work that shows a dependence between the time and message complexity to solve leader election and the connectivity of the graph $G$, which is often characterized by the graph's conductance $\phi$. Apart from the $\Omega(m)$ bound in [Kutten et al., J.ACM 2015] (where $m$ denotes the number of edges of the graph), this work also provides one of the first non-trivial lower bounds for leader election in general networks.
1901.00342v1
2019-01-23
Cooperation Speeds Surfing: Use Co-Bandit!
In this paper, we explore the benefit of cooperation in adversarial bandit settings. As a motivating example, we consider the problem of wireless network selection. Mobile devices are often required to choose the right network to associate with for optimal performance, which is non-trivial. The excellent theoretical properties of EXP3, a leading multi-armed bandit algorithm, suggest that it should work well for this type of problem. Yet, it performs poorly in practice. A major limitation is its slow rate of stabilization. Bandit-style algorithms perform better when global knowledge is available, i.e., when devices receive feedback about all networks after each selection. But, unfortunately, communicating full information to all devices is expensive. Therefore, we address the question of how much information is adequate to achieve better performance. We propose Co-Bandit, a novel cooperative bandit approach, that allows devices to occasionally share their observations and forward feedback received from neighbors; hence, feedback may be received with a delay. Devices perform network selection based on their own observation and feedback from neighbors. As such, they speed up each other's rate of learning. We prove that Co-Bandit is regret-minimizing and retains the convergence property of multiplicative weight update algorithms with full information. Through simulation, we show that a very small amount of information, even with a delay, is adequate to nudge each other to select the right network and yield significantly faster stabilization at the optimal state (about 630x faster than EXP3).
1901.07768v1
2019-01-31
Still out there: Modeling and Identifying Russian Troll Accounts on Twitter
There is evidence that Russia's Internet Research Agency attempted to interfere with the 2016 U.S. election by running fake accounts on Twitter - often referred to as "Russian trolls". In this work, we: 1) develop machine learning models that predict whether a Twitter account is a Russian troll within a set of 170K control accounts; and, 2) demonstrate that it is possible to use this model to find active accounts on Twitter still likely acting on behalf of the Russian state. Using both behavioral and linguistic features, we show that it is possible to distinguish between a troll and a non-troll with a precision of 78.5% and an AUC of 98.9%, under cross-validation. Applying the model to out-of-sample accounts still active today, we find that up to 2.6% of top journalists' mentions are occupied by Russian trolls. These findings imply that the Russian trolls are very likely still active today. Additional analysis shows that they are not merely software-controlled bots, and manage their online identities in various complex ways. Finally, we argue that if it is possible to discover these accounts using externally - accessible data, then the platforms - with access to a variety of private internal signals - should succeed at similar or better rates.
1901.11162v1
2019-02-11
Efficient Randomized Test-And-Set Implementations
We study randomized test-and-set (TAS) implementations from registers in the asynchronous shared memory model with n processes. We introduce the problem of group election, a natural variant of leader election, and propose a framework for the implementation of TAS objects from group election objects. We then present two group election algorithms, each yielding an efficient TAS implementation. The first implementation has expected max-step complexity $O(\log^\ast k)$ in the location-oblivious adversary model, and the second has expected max-step complexity $O(\log\log k)$ against any read/write-oblivious adversary, where $k\leq n$ is the contention. These algorithms improve the previous upper bound by Alistarh and Aspnes [2] of $O(\log\log n)$ expected max-step complexity in the oblivious adversary model. We also propose a modification to a TAS algorithm by Alistarh, Attiya, Gilbert, Giurgiu, and Guerraoui [5] for the strong adaptive adversary, which improves its space complexity from super-linear to linear, while maintaining its $O(\log n)$ expected max-step complexity. We then describe how this algorithm can be combined with any randomized TAS algorithm that has expected max-step complexity $T(n)$ in a weaker adversary model, so that the resulting algorithm has $O(\log n)$ expected max-step complexity against any strong adaptive adversary and $O(T(n))$ in the weaker adversary model. Finally, we prove that for any randomized 2-process TAS algorithm, there exists a schedule determined by an oblivious adversary such that with probability at least $(1/4)^t$ one of the processes needs at least t steps to finish its TAS operation. This complements a lower bound by Attiya and Censor-Hillel [7] on a similar problem for $n\geq 3$ processes.
1902.04002v1
2019-03-11
Evidence for the formation of nanoprecipitates with magnetically disordered regions in bulk $\mathrm{Ni}_{50}\mathrm{Mn}_{45}\mathrm{In}_{5}$ Heusler alloys
Shell ferromagnetism is a new functional property of certain Heusler alloys which has been recently observed in $\mathrm{Ni}_{50}\mathrm{Mn}_{45}\mathrm{In}_{5}$. We report the results of a comparative study of the magnetic microstructure of bulk $\mathrm{Ni}_{50}\mathrm{Mn}_{45}\mathrm{In}_{5}$ Heusler alloys using magnetometry, synchrotron x-ray diffraction, and magnetic small-angle neutron scattering (SANS). By combining unpolarized and spin-polarized SANS (POLARIS) we demonstrate that a number of important conclusions regarding the mesoscopic spin structure can be made. In particular, the analysis of the magnetic neutron data suggests that nanoprecipitates with an effective ferromagnetic component form in an antiferromagnetic matrix on field annealing at $700 \, \mathrm{K}$. These particles represent sources of perturbation, which seem to give rise to magnetically disordered regions in the vicinity of the particle-matrix interface. Analysis of the spin-flip SANS cross section via the computation of the correlation function yields a value of $\sim 55 \, \mathrm{nm}$ for the particle size and $\sim 20 \, \mathrm{nm}$ for the size of the spin-canted region.
1903.04183v1
2019-03-14
Low Field-size, Rate-Optimal Streaming Codes for Channels With Burst and Random Erasures
In this paper, we design erasure-correcting codes for channels with burst and random erasures, when a strict decoding delay constraint is in place. We consider the sliding-window-based packet erasure model proposed by Badr et al., where any time-window of width $w$ contains either up to $a$ random erasures or an erasure burst of length at most $b$. One needs to recover any erased packet, where erasures are as per the channel model, with a strict decoding delay deadline of $\tau$ time slots. Presently existing rate-optimal constructions in the literature require, in general, a field-size which grows exponential in $\tau$, for a constant $\frac{a}{\tau}$. In this work, we present a new rate-optimal code construction covering all channel and delay parameters, which requires an $O(\tau^2)$ field-size. As a special case, when $(b-a)=1$, we have a field-size linear in $\tau$. We also present three other constructions having linear field-size, under certain constraints on channel and decoding delay parameters. As a corollary, we obtain low field-size, rate-optimal convolutional codes for any given column distance and column span. Simulations indicate that the newly proposed streaming code constructions offer lower packet-loss probabilities compared to existing schemes, for selected instances of Gilbert-Elliott and Fritchman channels.
1903.06210v1
2019-03-21
Emergent topology and symmetry-breaking order in correlated quench dynamics
Quenching a quantum system involves three basic ingredients: the initial phase, the post-quench target phase, and the non-equilibrium dynamics which carries the information of the former two. Here we propose a dynamical theory to characterize both the topology and symmetry-breaking order in correlated quantum system, through quenching the Haldane-Hubbard model from an initial magnetic phase to topologically nontrivial regime. The equation of motion for the complex pseudospin dynamics is obtained with the flow equation method, with the pseudospin evolution shown to obey a microscopic Landau-Lifshitz-Gilbert-Bloch equation. We find that the correlated quench dynamics exhibit robust universal behaviors on the so-called band-inversion surfaces (BISs), from which the nontrivial topology and magnetic order can be extracted. In particular, the topology of the post-quench regime can be characterized by an emergent dynamical topological pattern of quench dynamics on BISs, which is robust against dephasing and heating induced by interactions; the pre-quench symmetry-breaking orders is read out from a universal scaling behavior of the quench dynamics emerging on the BIS, which is valid beyond the mean-field regime. This work opens a way to characterize both the topology and symmetry-breaking orders by correlated quench dynamics.
1903.09144v3
2019-03-22
Advanced Non-Destructive in Situ Characterization of Metals with the French Collaborating Research Group D2AM/BM02 Beamline at the European Synchrotron Radiation Facility
The ability to non-destructively measure the structural properties of devices, either in situ or operando, are now possible using an intense X-ray synchrotron source combined with specialized equipment. This tool attracted researchers, in particular metallurgists, to attempt more complex and ambitious experiments aimed at answering unresolved questions in formation mechanisms, phase transitions, and magnetism complex alloys for industrial applications. In this paper, we introduce the diffraction diffusion anomale multi-longueur d'onde (D2AM) beamline, a French collaborating research group (CRG) beamline at the European Synchrotron Radiation Facility (ESRF), partially dedicated to in situ X-ray scattering experiments. The design of the beamline combined with the available equipment (two-dimensional fast photon counting detectors, sophisticated high precision kappa diffractometer, a variety of sample environments, continuous scanning for X-ray imaging, and specific software for data analysis) has made the D2AM beamline a highly efficient tool for advanced, in situ synchrotron characterization in materials science, e.g., single crystal or polycrystalline materials, powders, liquids, thin films, or epitaxial nanostructures. This paper gathers the main elements and equipment available at the beamline and shows its potential and flexibility in performing a wide variety of temporally, spatially, and energetically resolved X-ray synchrotron scattering measurements in situ.
1903.09390v1
2019-03-31
Relaxation to equilibrium in models of classical spins with long-range interactions
For a model long-range interacting system of classical Heisenberg spins, we study how fluctuations, such as those arising from having a finite system size or through interaction with the environment, affect the dynamical process of relaxation to Boltzmann-Gibbs equilibrium. Under deterministic spin precessional dynamics, we unveil the full range of quasistationary behavior observed during relaxation to equilibrium, whereby the system is trapped in nonequilibrium states for times that diverge with the system size. The corresponding stochastic dynamics, modeling interaction with the environment and constructed in the spirit of the stochastic Landau-Lifshitz-Gilbert equation, however shows a fast relaxation to equilibrium on a size-independent timescale and no signature of quasistationarity, provided the noise is strong enough. Similar fast relaxation is also seen in Glauber Monte Carlo dynamics of the model, thus establishing the ubiquity of what has been reported earlier in particle dynamics (hence distinct from the spin dynamics considered here) of long-range interacting systems, that quasistationarity observed in deterministic dynamics is washed away by fluctuations induced through contact with the environment.
1904.00432v2
2019-04-27
Blue-Light-Emitting Color Centers in High-Quality Hexagonal Boron Nitride
Light emitters in wide band gap semiconductors are of great fundamental interest and have potential as optically addressable qubits. Here we describe the discovery of a new color center in high-quality hexagonal boron nitride (h-BN) with a sharp emission line at 435 nm. The emitters are activated and deactivated by electron beam irradiation and have spectral and temporal characteristics consistent with atomic color centers weakly coupled to lattice vibrations. The emitters are conspicuously absent from commercially available h-BN and are only present in ultra-high-quality h-BN grown using a high-pressure, high-temperature Ba-B-N flux/solvent, suggesting that these emitters originate from impurities or related defects specific to this unique synthetic route. Our results imply that the light emission is activated and deactivated by electron beam manipulation of the charge state of an impurity-defect complex.
1904.12107v6
2019-04-30
Realization of Ordered Magnetic Skyrmions in Thin Films at Ambient Conditions
Magnetic skyrmions present interesting physics due to their topological nature and hold significant promise for future information technologies. A key barrier to realizing skyrmion devices has been stabilizing these spin structures under ambient conditions. In this manuscript, we exploit the tunable magnetic properties of amorphous Fe/Gd mulitlayers to realize skyrmion lattices which are stable over a large temperature and magnetic field parameter space, including room temperature and zero magnetic field. These hybrid skyrmions have both Bloch-type and N\'eel-type character and are stabilized by dipolar interactions rather than Dzyaloshinskii-Moriya interactions, which are typically considered required for the generation of skyrmions. Small angle neutron scattering (SANS) was used in combination with soft X-ray microscopy to provide a unique, multi-scale probe of the local and long-range order of these structures. These results identify a pathway to engineer controllable skyrmion phases in thin film geometries which are stable at ambient conditions.
1904.13274v1
2019-05-16
Ultralow-loss domain wall motion driven by magnetocrystalline anisotropy gradient in antiferromagnetic nanowire
Searching for new methods controlling antiferromagnetic (AFM) domain wall is one of the most important issues for AFM spintronic device operation. In this work, we study theoretically the domain wall motion of an AFM nanowire, driven by the axial anisotropy gradient generated by external electric field, allowing the electro control of AFM domain wall motion in the merit of ultra-low energy loss. The domain wall velocity depending on the anisotropy gradient magnitude and intrinsic material properties is simulated based on the Landau-Lifshitz-Gilbert equation and also deduced using the energy dissipation theorem. It is found that the domain wall moves at a nearly constant velocity for small gradient, and accelerates for large gradient due to the enlarged domain wall width. The domain wall mobility is independent of lattice dimension and types of domain wall, while it is enhanced by the Dzyaloshinskii-Moriya interaction. In addition, the physical mechanism for much faster AFM wall dynamics than ferromagnetic wall dynamics is qualitatively explained. This work unveils a promising strategy for controlling the AFM domain walls, benefiting to future AFM spintronic applications.
1905.06695v2
2019-05-22
Constraining level densities using spectral data
Several models of level densities exist and they often make simplified assumptions regarding the overall behavior of the total level densities (LD) and the intrinsic spin and parity distributions of the excited states. Normally, such LD models are constrained only by the measured $D_0$, i.e. the density of levels at the neutron separation energy of the compound nucleus (target plus neutron), and the sometimes subjective extrapolation of discrete levels. In this work we use microscopic Hartree-Fock-Bogoliubov (HFB) level densities, which intrinsically provide more realistic spin and parity distributions, and associate variations predicted by the HFB model with the observed double-differential cross sections at low outgoing neutron energy, region that is dominated by the LD input. With this approach we are able to perform fits of the LD based on actual experimental data, constraining the model and ensuring its consistency. This approach can be particularly useful in extrapolating the LD to nuclei for which high-excited discrete levels and/or values of $D_0$ are unknown. It also predicts inelastic gamma (n,n$^{\prime}\gamma$) cross sections that in some cases can differ significantly from more standard LD models such as Gilbert-Cameron.
1905.09194v1
2019-05-23
The Kepler Smear Campaign: Light curves for 102 Very Bright Stars
We present the first data release of the Kepler Smear Campaign, using collateral 'smear' data obtained in the Kepler four-year mission to reconstruct light curves of 102 stars too bright to have been otherwise targeted. We describe the pipeline developed to extract and calibrate these light curves, and show that we attain photometric precision comparable to stars analyzed by the standard pipeline in the nominal Kepler mission. In this paper, aside from publishing the light curves of these stars, we focus on 66 red giants for which we detect solar-like oscillations, characterizing 33 of these in detail with spectroscopic chemical abundances and asteroseismic masses as benchmark stars. We also classify the whole sample, finding nearly all to be variable, with classical pulsations and binary effects. All source code, light curves, TRES spectra, and asteroseismic and stellar parameters are publicly available as a Kepler legacy sample.
1905.09831v1
2019-06-06
A Hot Saturn Near (but unassociated with) the Open Cluster NGC 1817
We report on the discovery of a hot Saturn-sized planet (9.916 +/- 0.985 R_earth) around a late F star, EPIC 246865365, observed in Campaign 13 of the K2 mission. We began studying this planet candidate because prior to the release of Gaia DR2, the host star was thought to have been a member (> 90% membership probability) of the approximately 1 Gyr open cluster NGC 1817 based on its kinematics and photometric distance. We identify the host star (among three stars within the K2 photometric aperture) using seeing-limited photometry and rule out false positive scenarios using adaptive optics imaging and radial velocity observations. We statistically validate EPIC 246865365b by calculating a false positive probability rate of 0.01%. However, we also show using new kinematic measurements provided by Gaia DR2 and our measured radial velocity of the system that EPIC 246865365 is unassociated with the cluster NGC 1817. Therefore, the long-running search for a giant transiting planet in an open cluster remains fruitless. Finally, we note that our use of seeing-limited photometry is a good demonstration of similar techniques that are already being used to follow up TESS planet candidates, especially in crowded regions.
1906.02395v1
2019-06-12
Towards the nucleon hadronic tensor from lattice QCD
We present the first calculation of the hadronic tensor on the lattice for the nucleon. The hadronic tensor can be used to extract the structure functions in deep inelastic scatterings and also provide information for the neutrino-nucleon scattering which is crucial to the neutrino-nucleus scattering experiments at low energies. The most challenging part in the calculation is to solve an inverse problem. We have implemented and tested three algorithms using mock data, showing that the Bayesian Reconstruction method has the best resolution in extracting peak structures while the Backus-Gilbert and Maximum Entropy methods are somewhat more stable for the flat spectral function. Numerical results are presented for both the elastic case (clover fermions on domain wall configuration with $m_\pi\sim$ 370 MeV and $a\sim$ 0.06 fm) and a case (anisotropic clover lattice with $m_\pi\sim$ 380 MeV and $a_t\sim$ 0.035 fm) with large momentum transfer. For the former case, the reconstructed Minkowski hadronic tensor gives precisely the vector charge which proves the feasibility of the approach. While for the latter case, the nucleon resonances and possibly shallow inelastic scattering contributions around $\nu=1$ GeV are clearly observed but no information is obtained for higher excited states with $\nu>2$ GeV. A check of the effective masses of $\rho$ meson with different lattice setups indicates that, in order to reach higher energy transfers, using lattices with smaller lattice spacings is essential.
1906.05312v1
2019-06-17
Non-equilibrium Green's Function and First Principle Approach to Modeling of Multiferroic Tunnel Junctions
Recently, multiferroic tunnel junctions (MFTJs) have gained significant spotlight in the literature due to its high tunneling electro-resistance together with its non-volatility. In order to analyze such devices and to have insightful understanding of its characteristics, there is a need for developing a multi-physics modeling and simulation framework. The simulation framework discussed in this paper is motivated by the scarcity of such multi-physics studies in the literature. In this study, a theoretical analysis of MFTJs is demonstrated using self-consistent analysis of spin-based non-equilibrium Green's function (NEGF) method to estimate the tunneling current, Landau-Khalatnikov (LK) equation to model the ferroelectric polarization dynamics, together with landau-Lifshitz-Gilbert's (LLG) equations to capture the magnetization dynamics. The spin-based NEGF method is equipped with a magnetization dependent Hamiltonian that eases the modeling of the tunneling electro-resistance (TER), tunneling magneto-resistance (TMR), and the magnetoelectric effect (ME) in MFTJs. Moreover, we apply the first principle calculations to estimate the screening lengths of the MFTJ electrodes that are necessary for estimation of tunneling current. The simulation results of the proposed framework are in good agreement with the experimental results. Finally, a comprehensive analysis of TER and TMR of MFTJs and their dependence on various device parameters is illustrated.
1906.06986v1
2019-06-27
Indications for Dzyaloshinskii-Moriya Interaction at the Pd/Fe Interface Studied by \textit{In Situ} Polarized Neutron Reflectometry
Using \textit{in situ} polarized neutron reflectometry, the depth resolved evolution of the magnetism and structure in a Pd/Fe/Pd trilayer thin-film is measured during growth. The initial film structure of Pd/Fe shows a small proximity induced magnetism in the underlayer and a magnetization in the Fe layer of $\approx1.6$\,$\mu_{\text{B}}$ per Fe atom, less than the expected bulk value of $2.2$\,$\mu_{\text{B}}$. Deposition of the Pd capping layer initially follows an island-like growth mode with subsequent coalescence. With increasing Pd deposition the Fe moment and the proximity-induced magnetism in the Pd capping layer decrease. After final deposition of the Pd capping layer, the magnetic profile is structurally and magnetically symmetric across the Fe layer, with magnetism induced in Pd up to 0.92 \,nm from the interface. Throughout the Pd deposition the Pd/Fe/Pd trilayer structure is becoming increasingly symmetric, a fact which points to a Dzyaloshinskii-Moriya interaction as a likely cause of the observed magnetic behavior.
1906.11532v1
2019-07-01
Robust Formation of Ultrasmall Room-Temperature Neél Skyrmions in Amorphous Ferrimagnets from Atomistic Simulations
Ne\'el skyrmions originate from interfacial Dzyaloshinskii Moriya interaction (DMI). Recent studies have explored using thin-film ferromagnets and ferrimagnets to host Ne\'el skyrmions for spintronic applications. However, it is unclear if ultrasmall (10 nm or less) skyrmions can ever be stabilized at room temperature for practical use in high density parallel racetrack memories. While thicker films can improve stability, DMI decays rapidly away from the interface. As such, spins far away from the interface would experience near-zero DMI, raising question on whether or not unrealistically large DMI is needed to stabilize skyrmions, and whether skyrmions will also collapse away from the interface. To address these questions, we have employed atomistic stochastic Landau-Lifshitz-Gilbert simulations to investigate skyrmions in amorphous ferrimagnetic GdCo. It is revealed that a significant reduction in DMI below that of Pt is sufficient to stabilize ultrasmall skyrmions even in films as thick as 15 nm. Moreover, skyrmions are found to retain a uniform columnar shape across the film thickness despite the decaying DMI. Our results show that increasing thickness and reducing DMI in GdCo can further reduce the size of skyrmions at room temperature, which is crucial to improve the density and energy efficiency in skyrmion based devices.
1907.00647v1
2019-07-03
Effect of Zeeman coupling on the Majorana vortex modes in iron-based topological superconductors
In the superconducting regime of FeTe$_{(1-x)}$Se$_x$, there exist two types of vortices which are distinct by the presence or absence of zero energy states in their core. To understand their origin, we examine the interplay of Zeeman coupling and superconducting pairings in three-dimensional metals with band inversion. Weak Zeeman fields are found to suppress the intra-orbital spin-singlet pairing, known to localize the states at the ends of the vortices on the surface. On the other hand, an orbital-triplet pairing is shown to be stable against Zeeman interactions, but leads to delocalized zero-energy Majorana modes which extend through the vortex. In contrast, the finite-energy vortex modes remain localized at the vortex ends even when the pairing is of orbital-triplet form. Phenomenologically, this manifests as an observed disappearance of zero-bias peaks within the cores of topological vortices upon increase of the applied magnetic field. The presence of magnetic impurities in FeTe$_{(1-x)}$Se$_x$, which are attracted to the vortices, would lead to such Zeeman-induced delocalization of Majorana modes in a fraction of vortices that capture a large enough number of magnetic impurities. Our results provide an explanation to the dichotomy between topological and non-topological vortices recently observed in FeTe$_{(1-x)}$Se$_x$.
1907.02077v2
2019-07-10
Increasing Gender Diversity and Inclusion in Scientific Committees and Related Activities at STScI
We present a new initiative by the Women in Astronomy Forum at Space Telescope Science Institute (STScI) to increase gender diversity and inclusion in STScI's scientific committees and the activities they generate. This initiative offers new and uniform guidelines on binary gender representation goals for each committee and recommendations on how to achieve them in a homogeneous way, as well as metrics and tools to track progress towards defined goals. While the new guidelines presented in the paper focus on binary gender representation, they can be adapted and implemented to support all minority groups. By creating diverse committees and making them aware of, and trained on implicit bias, we expect to create a diverse outcome in the activities they generate, which, in turn, will advance science further and faster.
1907.04880v1
2019-07-19
Sparse Recovery for Orthogonal Polynomial Transforms
In this paper we consider the following sparse recovery problem. We have query access to a vector $\vx \in \R^N$ such that $\vhx = \vF \vx$ is $k$-sparse (or nearly $k$-sparse) for some orthogonal transform $\vF$. The goal is to output an approximation (in an $\ell_2$ sense) to $\vhx$ in sublinear time. This problem has been well-studied in the special case that $\vF$ is the Discrete Fourier Transform (DFT), and a long line of work has resulted in sparse Fast Fourier Transforms that run in time $O(k \cdot \mathrm{polylog} N)$. However, for transforms $\vF$ other than the DFT (or closely related transforms like the Discrete Cosine Transform), the question is much less settled. In this paper we give sublinear-time algorithms---running in time $\poly(k \log(N))$---for solving the sparse recovery problem for orthogonal transforms $\vF$ that arise from orthogonal polynomials. More precisely, our algorithm works for any $\vF$ that is an orthogonal polynomial transform derived from Jacobi polynomials. The Jacobi polynomials are a large class of classical orthogonal polynomials (and include Chebyshev and Legendre polynomials as special cases), and show up extensively in applications like numerical analysis and signal processing. One caveat of our work is that we require an assumption on the sparsity structure of the sparse vector, although we note that vectors with random support have this property with high probability. Our approach is to give a very general reduction from the $k$-sparse sparse recovery problem to the $1$-sparse sparse recovery problem that holds for any flat orthogonal polynomial transform; then we solve this one-sparse recovery problem for transforms derived from Jacobi polynomials.
1907.08362v1
2019-08-28
Interplay of spin and mass superfluidity in antiferromagnetic spin-1 BEC and bicirculation vortices
The paper investigates the coexistence and interplay of spin and mass superfluidity in the antiferromagnetic spin-1 BEC. The hydrodynamical theory describes the spin degree of freedom by the equations similar to the Landau--Lifshitz--Gilbert theory for bipartite antiferromagnetic insulator. The variables in the spin space are two subspins with absolute value $\hbar/2$, which play the role of two sublattice spins in the antiferromagnetic insulators. As well as in bipartite antiferromagnetic insulators, in the antiferromagnetic spin-1 BEC there are two spin-wave modes, one is a gapless Goldstone mode, another is gapped. The Landau criterion shows that in limit of small total spin (two subspins are nearly antiparallel) instability of supercurrents starts from the gapped mode. In the opposite limit of large total spin (two subspins are nearly parallel) the gapless modes become unstable earlier than the gapped one. Mass and spin supercurrents decay via phase slips, when vortices cross streamlines of supercurrent. The vortices participating in phase slips are nonsingular bicirculation vortices. They are characterized by two topological charges, which are winding numbers describing circulations of two angles around the vortex axis. The winding numbers can be half-integer. A particular example of a half-integer vortex is a half-quantum vortex with the superfluid velocity circulation $h/2m$. But the superfluid velocity circulation is not a topological charge, and in general the quantum of this circulation can be continuously tuned from 0 to $h/2m$.
1908.10633v2
2019-09-23
The NASA Probe space mission concept, Cosmic Evolution Through UV Surveys (CETUS)
The mission concept, Cosmic Origins Through UV Surveys (CETUS) is an all-UV space mission concept that was selected and funded by NASA for study in 2017. The main capabilities of CETUS that even Hubble doesn't have are: (1) wide-field (17.4'x17.4') imaging and spectroscopy of astronomical sources with <0.5'' resolution; (2) spectral sensitivity to UV radiation at wavelengths as short as 1000 {\AA}; (3) near-UV multi-object slit spectroscopy; and (4) rapid-response UV spectroscopy and deep imaging of transients like GW 170817; and (5) 23 times higher sensitivity to extended sources. The main purposes of this CETUS Final Report are to describe the CETUS scientific program and to demonstrate the maturity of its instrumentation, which forms the basis of its estimated cost. While there are similarities of this Final Report to that submitted to NASA in March 2019 by the Goddard Space Flight Center, there are important differences including the following. * Science. The science case has been refreshed, deepened, and expanded as a result of ideas and recommendations expressed in the Astro2020 science white papers. * Instrumentation. Detailed investigations including a high-level error budget for focus with implications for thermal management, target acquisition in the MOS micro-shutter array, contamination control have been carried out. * Mission Design. The spacecraft and mission operations concepts as developed by NGIS Gilbert (formerly Orbital ATK) rather than the output of Goddard's Mission Design Lab have been adopted.. * Technology. Technology maturation plans have been updated.
1909.10437v1
2019-09-25
Towards an improved understanding of molecular evolution: the relative roles of selection, drift, and everything in between
A major goal of molecular evolutionary biology is to identify loci or regions of the genome under selection versus those evolving in a neutral manner. Correct identification allows accurate inference of the evolutionary process and thus comprehension of historical and contemporary processes driving phenotypic change and adaptation. A fundamental difficulty lies in distinguishing sites targeted by selection from both sites linked to these targets and sites fully independent of selection. These three categories of sites necessitate attention in light of the debate over the relative importance of selection versus neutrality and the neutral theory. Modern genomic insights have proved that complex processes such as linkage, demography, and biased gene conversion complicate our understanding of the role of neutral versus selective processes in evolution. In this perspective, we first highlight the importance of the genomic and (a)biotic context of new mutations to identify the targets of natural selection. We then present mechanisms that may constrain the evolution of genomes and bias the inference of selection. We discuss these mechanisms within the two critical levels that they occur: the population level and the molecular level. We highlight that they should be taken into account to correctly distinguish sites across the genome subject to selective or non-selective forces and stress that a major current field-wide goal is to quantify the absolute importance of these mechanisms.
1909.11490v4
2019-10-08
Correlated fluctuations in spin orbit torque-coupled perpendicular nanomagnets
Low barrier nanomagnets have attracted a lot of research interest for their use as sources of high quality true random number generation. More recently, low barrier nanomagnets with tunable output have been shown to be a natural hardware platform for unconventional computing paradigms such as probabilistic spin logic. Efficient generation and tunability of high quality random bits is critical for these novel applications. However, current spintronic random number generators are based on superparamagnetic tunnel junctions (SMTJs) with tunability obtained through spin transfer torque (STT), which unavoidably leads to challenges in designing concatenated networks using these two terminal devices. The more recent development of utilizing spin orbit torque (SOT) allows for a three terminal device design, but can only tune in-plane magnetization freely, which is not very energy efficient due to the needs of overcoming a large demagnetization field. In this work, we experimentally demonstrate for the first time, a stochastic device with perpendicular magnetic anisotropy (PMA) that is completely tunable by SOT without the aid of any external magnetic field. Our measurements lead us to hypothesize that a tilted anisotropy might be responsible for the observed tunability. We carry out stochastic Landau-Lifshitz-Gilbert (sLLG) simulations to confirm our experimental observation. Finally, we build an electrically coupled network of two such stochastic nanomagnet based devices and demonstrate that finite correlation or anti-correlation can be established between their output fluctuations by a weak interconnection, despite having a large difference in their natural fluctuation time scale. Simulations based on a newly developed dynamical model for autonomous circuits composed of low barrier nanomagnets show close agreement with the experimental results.
1910.03184v1
2019-10-09
Prophets, Secretaries, and Maximizing the Probability of Choosing the Best
Suppose a customer is faced with a sequence of fluctuating prices, such as for airfare or a product sold by a large online retailer. Given distributional information about what price they might face each day, how should they choose when to purchase in order to maximize the likelihood of getting the best price in retrospect? This is related to the classical secretary problem, but with values drawn from known distributions. In their pioneering work, Gilbert and Mosteller [\textit{J. Amer. Statist. Assoc. 1966}] showed that when the values are drawn i.i.d., there is a thresholding algorithm that selects the best value with probability approximately $0.5801$. However, the more general problem with non-identical distributions has remained unsolved. In this paper we provide an algorithm for the case of non-identical distributions that selects the maximum element with probability $1/e$, and we show that this is tight. We further show that if the observations arrive in a random order, this barrier of $1/e$ can be broken using a static threshold algorithm, and we show that our success probability is the best possible for any single-threshold algorithm under random observation order. Moreover, we prove that one can achieve a strictly better success probability using more general multi-threshold algorithms, unlike the non-random-order case. Along the way, we show that the best achievable success probability for the random-order case matches that of the i.i.d.\ case, which is approximately $0.5801$, under a "no-superstars" condition that no single distribution is very likely ex ante to generate the maximum value. We also extend our results to the problem of selecting one of the $k$ best values.
1910.03798v1
2019-10-24
Order and Information in the Patterns of Spinning Magnetic Micro-disks at the Air-water Interface
The application of the Shannon entropy to study the relationship between information and structures has yielded insights into molecular and material systems. However, the difficulty in directly observing and manipulating atoms and molecules hampers the ability of these systems to serve as model systems for further exploring the links between information and structures. Here, we use, as a model experimental system, hundreds of spinning magnetic micro-disks self-organizing at the air-water interface to generate various spatiotemporal patterns with varying degrees of orders. Using the neighbor distance as the information-bearing variable, we demonstrate the links among information, structure, and interactions. Most importantly, we establish a direct link between information and structure without using explicit knowledge of interactions. Finally, we show that the Shannon entropy by neighbor distances is a powerful observable in characterizing structural changes. Our findings are relevant for analyzing natural self-organizing systems and for designing collective robots.
1910.11226v3
2019-11-17
Interfacial-Redox-Induced Tuning of Superconductivity in YBa$_{2}$Cu$_{3}$O$_{7-δ}$
Solid state ionic approaches for modifying ion distributions in getter/oxide heterostructures offer exciting potentials to control material properties. Here we report a simple, scalable approach allowing for total control of the superconducting transition in optimally doped YBa$_{2}$Cu$_{3}$O$_{7-{\delta}}$ (YBCO) films via a chemically-driven ionic migration mechanism. Using a thin Gd capping layer of up to 20 nm deposited onto 100 nm thick epitaxial YBCO films, oxygen is found to leach from deep within the YBCO. Progressive reduction of the superconducting transition is observed, with complete suppression possible for a sufficiently thick Gd layer. These effects arise from the combined impact of redox-driven electron doping and modification of the YBCO microstructure due to oxygen migration and depletion. This work demonstrates an effective ionic control of superconductivity in oxides, an interface induced effect that goes well into the quasi-bulk regime, opening up possibilities for electric field manipulation.
1911.07275v1
2019-12-10
Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery
Symbolic regression is a powerful technique that can discover analytical equations that describe data, which can lead to explainable models and generalizability outside of the training data set. In contrast, neural networks have achieved amazing levels of accuracy on image recognition and natural language processing tasks, but are often seen as black-box models that are difficult to interpret and typically extrapolate poorly. Here we use a neural network-based architecture for symbolic regression called the Equation Learner (EQL) network and integrate it with other deep learning architectures such that the whole system can be trained end-to-end through backpropagation. To demonstrate the power of such systems, we study their performance on several substantially different tasks. First, we show that the neural network can perform symbolic regression and learn the form of several functions. Next, we present an MNIST arithmetic task where a separate part of the neural network extracts the digits. Finally, we demonstrate prediction of dynamical systems where an unknown parameter is extracted through an encoder. We find that the EQL-based architecture can extrapolate quite well outside of the training data set compared to a standard neural network-based architecture, paving the way for deep learning to be applied in scientific exploration and discovery.
1912.04825v2
2019-12-17
New search for mirror neutron regeneration
The possibility of relatively fast neutron oscillations into a mirror neutron state is not excluded experimentally when a mirror magnetic field is considered. Direct searches for the disappearance of neutrons into mirror neutrons in a controlled magnetic field have previously been performed using ultracold neutrons, with some anomalous results reported. We describe a technique using cold neutrons to perform a disappearance and regeneration search, which would allow us to unambiguously identify a possible oscillation signal. An experiment using the existing General Purpose-Small Angle Neutron Scattering instrument at the High Flux Isotope Reactor at Oak Ridge National Laboratory will have the sensitivity to fully explore the parameter space of prior ultracold neutron searches and confirm or refute previous claims of observation. This instrument can also conclusively test the validity of recently suggested oscillation-based explanations for the neutron lifetime anomaly.
1912.08264v1
2020-01-06
Highly efficient spin orbit torque in Pt/Co/Ir multilayers with antiferromagnetic interlayer exchange coupling
We have studied the spin orbit torque (SOT) in Pt/Co/Ir multilayers with 3 repeats of the unit structure. As the system exhibits oscillatory interlayer exchange coupling (IEC) with varying Ir layer thickness, we compare the SOT of films when the Co layers are coupled ferromagnetically and antiferromagnetically. SOT is evaluated using current induced shift of the anomalous Hall resistance hysteresis loops. A relatively thick Pt layer, serving as a seed layer to the multilayer, is used to generate spin current via the spin Hall effect. In the absence of antiferromagnetic coupling, the SOT is constant against the applied current density and the corresponding spin torque efficiency (i.e. the effective spin Hall angle) is $\sim$0.09, in agreement with previous reports. In contrast, for films with antiferromagnetic coupling, the SOT increases with the applied current density and eventually saturates. The SOT at saturation is a factor of $\sim$15 larger than that without the antiferromagnetic coupling. The spin torque efficiency is $\sim$5 times larger if we assume the net total magnetization is reduced by a factor of 3 due to the antiferromagnetic coupling. Model calculations based on the Landau Lifshitz Gilbert equation show that the presence of antiferromagnetic coupling can increase the SOT but the degree of enhancement is limited, in this case, to a factor of 1.2-1.4. We thus consider there are other sources of SOT, possibly at the interfaces, which may account for the highly efficient SOT in the uncompensated synthetic anti-ferromagnet (SAF) multilayers.
2001.01454v1
2019-11-24
Cybernetical Concepts for Cellular Automaton and Artificial Neural Network Modelling and Implementation
As a discipline cybernetics has a long and rich history. In its first generation it not only had a worldwide span, in the area of computer modelling, for example, its proponents such as John von Neumann, Stanislaw Ulam, Warren McCulloch and Walter Pitts, also came up with models and methods such as cellular automata and artificial neural networks, which are still the foundation of most modern modelling approaches. At the same time, cybernetics also got the attention of philosophers, such as the Frenchman Gilbert Simondon, who made use of cybernetical concepts in order to establish a metaphysics and a natural philosophy of individuation, giving cybernetics thereby a philosophical interpretation, which he baptised allagmatic. In this paper, we emphasise this allagmatic theory by showing how Simondon's philosophical concepts can be used to formulate a generic computer model or metamodel for complex systems modelling and its implementation in program code, according to generic programming. We also present how the developed allagmatic metamodel is capable of building simple cellular automata and artificial neural networks.
2001.02037v3
2020-02-12
Competition between magnetic order and charge localization in Na$_2$IrO$_3$ thin crystal devices
Spin orbit assisted Mott insulators such as sodium iridate (Na$_2$IrO$_3$) have been an important subject of study in the recent years. In these materials, the interplay of electronic correlations, spin-orbit coupling, crystal field effects and a honeycomb arrangement of ions bring exciting ground states, predicted in the frame of the Kitaev model. The insulating character of Na$_2$IrO$_3$ has hampered its integration to an electronic device, desirable for applications, such as the manipulation of quasiparticles interesting for topological quantum computing. Here we show through electronic transport measurements supported by Angle Resolved Photoemission Spectroscopy (ARPES) experiments, that electronic transport in Na$_2$IrO$_3$ is ruled by variable range hopping and it is strongly dependent on the magnetic ordering transition known for bulk Na$_2$IrO$_3$, as well as on external electric fields. Electronic transport measurements allow us to deduce a value for the localization length and the density of states in our Na$_2$IrO$_3$ thin crystals devices, offering an alternative approach to study insulating layered materials.
2002.04785v1
2020-02-13
Electron Beam-Induced Nanopores in Bernal-Stacked Hexagonal Boron Nitride
Controlling the size and shape of nanopores in two-dimensional materials is a key challenge in applications such as DNA sequencing, sieving, and quantum emission in artificial atoms. We here investigate experimentally and theoretically triangular vacancies in (unconventional) Bernal-stacked AB-h-BN formed using a high-energy electron beam. Due to the geometric configuration of AB-h-BN, triangular pores in different layers are aligned, and their sizes are controlled by the duration of the electron irradiation. Interlayer covalent bonding at the vacancy edge is not favored, as opposed to what occurs in the more common AA'-stacked BN. A variety of monolayer, concentric and bilayer pores in bilayer AB-h-BN are observed in high-resolution transmission electron microscopy and characterized using ab initio simulations. Bilayer pores in AB-h-BN are commonly formed, and grow without breaking the bilayer character. Nanopores in AB-h-BN exhibit a wide range of electronic properties, ranging from half-metallic to non-magnetic and magnetic semiconducting. Therefore, because of the controllability of the pore size, the electronic structure is also highly controllable in these systems, and can potentially be tuned for particular applications.
2002.05795v3
2020-02-26
Effect of chemical substitution on the skyrmion phase in Cu$_2$OSeO$_3$
Magnetic skyrmions have been the focus of intense research due to their unique qualities which result from their topological protections. Previous work on Cu$_2$OSeO$_3$, the only known insulating multiferroic skyrmion material, has shown that chemical substitution alters the skyrmion phase. We chemically substitute Zn, Ag, and S into powdered Cu$_2$OSeO$_3$ to study the effect on the magnetic phase diagram. In both the Ag and the S substitutions, we find that the skyrmion phase is stabilized over a larger temperature range, as determined via magnetometry and small-angle neutron scattering (SANS). Meanwhile, while previous magnetometry characterization suggests two high temperature skyrmion phases in the Zn-substituted sample, SANS reveals the high temperature phase to be skyrmionic while we are unable to distinguish the other from helical order. Overall, chemical substitution weakens helical and skyrmion order as inferred from neutron scattering of the $|$q$| \approx$ 0.01 $\r{A}^{-1}$ magnetic peak.
2002.11827v1
2020-03-10
Smart City IoT Services Creation through Large Scale Collaboration
Smart cities solutions are often monolithically implemented, from sensors data handling through to the provided services. The same challenges are regularly faced by different developers, for every new solution in a new city. Expertise and know-how can be re-used and the effort shared. In this article we present the methodologies to minimize the efforts of implementing new smart city solutions and maximizing the sharing of components. The final target is to have a live technical community of smart city application developers. The results of this activity comes from the implementation of 35 city services in 27 cities between Europe and South Korea. To share efforts, we encourage developers to devise applications using a modular approach. Single-function components that are re-usable by other city services are packaged and published as standalone components, named Atomic Services. We identify 15 atomic services addressing smart city challenges in data analytics, data evaluation, data integration, data validation, and visualization. 38 instances of the atomic services are already operational in several smart city services. We detail in this article, as atomic service examples, some data predictor components. Furthermore, we describe real-world atomic services usage in the scenarios of Santander and three Danish cities. The resulting atomic services also generate a side market for smart city solutions, allowing expertise and know-how to be re-used by different stakeholders.
2003.04843v1
2020-03-23
Low Power Unsupervised Anomaly Detection by Non-Parametric Modeling of Sensor Statistics
This work presents AEGIS, a novel mixed-signal framework for real-time anomaly detection by examining sensor stream statistics. AEGIS utilizes Kernel Density Estimation (KDE)-based non-parametric density estimation to generate a real-time statistical model of the sensor data stream. The likelihood estimate of the sensor data point can be obtained based on the generated statistical model to detect outliers. We present CMOS Gilbert Gaussian cell-based design to realize Gaussian kernels for KDE. For outlier detection, the decision boundary is defined in terms of kernel standard deviation ($\sigma_{Kernel}$) and likelihood threshold ($P_{Thres}$). We adopt a sliding window to update the detection model in real-time. We use time-series dataset provided from Yahoo to benchmark the performance of AEGIS. A f1-score higher than 0.87 is achieved by optimizing parameters such as length of the sliding window and decision thresholds which are programmable in AEGIS. Discussed architecture is designed using 45nm technology node and our approach on average consumes $\sim$75 $\mu$W power at a sampling rate of 2 MHz while using ten recent inlier samples for density estimation. \textcolor{red}{Full-version of this research has been published at IEEE TVLSI}
2003.10088v1
2020-03-30
Efficient nonparametric inference on the effects of stochastic interventions under two-phase sampling, with applications to vaccine efficacy trials
The advent and subsequent widespread availability of preventive vaccines has altered the course of public health over the past century. Despite this success, effective vaccines to prevent many high-burden diseases, including HIV, have been slow to develop. Vaccine development can be aided by the identification of immune response markers that serve as effective surrogates for clinically significant infection or disease endpoints. However, measuring immune response marker activity is often costly, which has motivated the usage of two-phase sampling for immune response evaluation in clinical trials of preventive vaccines. In such trials, the measurement of immunological markers is performed on a subset of trial participants, where enrollment in this second phase is potentially contingent on the observed study outcome and other participant-level information. We propose nonparametric methodology for efficiently estimating a counterfactual parameter that quantifies the impact of a given immune response marker on the subsequent probability of infection. Along the way, we fill in theoretical gaps pertaining to the asymptotic behavior of nonparametric efficient estimators in the context of two-phase sampling, including a multiple robustness property enjoyed by our estimators. Techniques for constructing confidence intervals and hypothesis tests are presented, and an open source software implementation of the methodology, the txshift R package, is introduced. We illustrate the proposed techniques using data from a recent preventive HIV vaccine efficacy trial.
2003.13771v2
2020-04-05
Effects of the Affordable Care Act Dependent Coverage Mandate on Health Insurance Coverage for Individuals in Same-Sex Couples
A large body of research documents that the 2010 dependent coverage mandate of the Affordable Care Act was responsible for significantly increasing health insurance coverage among young adults. No prior research has examined whether sexual minority young adults also benefitted from the dependent coverage mandate, despite previous studies showing lower health insurance coverage among sexual minorities and the fact that their higher likelihood of strained relationships with their parents might predict a lower ability to use parental coverage. Our estimates from the American Community Surveys using difference-in-differences and event study models show that men in same-sex couples age 21-25 were significantly more likely to have any health insurance after 2010 compared to the associated change for slightly older 27 to 31-year-old men in same-sex couples. This increase is concentrated among employer-sponsored insurance, and it is robust to permutations of time periods and age groups. Effects for women in same-sex couples and men in different-sex couples are smaller than the associated effects for men in same-sex couples. These findings confirm the broad effects of expanded dependent coverage and suggest that eliminating the federal dependent mandate could reduce health insurance coverage among young adult sexual minorities in same-sex couples.
2004.02296v1
2020-04-07
A general framework for inference on algorithm-agnostic variable importance
In many applications, it is of interest to assess the relative contribution of features (or subsets of features) toward the goal of predicting a response -- in other words, to gauge the variable importance of features. Most recent work on variable importance assessment has focused on describing the importance of features within the confines of a given prediction algorithm. However, such assessment does not necessarily characterize the prediction potential of features, and may provide a misleading reflection of the intrinsic value of these features. To address this limitation, we propose a general framework for nonparametric inference on interpretable algorithm-agnostic variable importance. We define variable importance as a population-level contrast between the oracle predictiveness of all available features versus all features except those under consideration. We propose a nonparametric efficient estimation procedure that allows the construction of valid confidence intervals, even when machine learning techniques are used. We also outline a valid strategy for testing the null importance hypothesis. Through simulations, we show that our proposal has good operating characteristics, and we illustrate its use with data from a study of an antibody against HIV-1 infection.
2004.03683v2
2020-04-15
Magic DIAMOND: Multi-Fascicle Diffusion Compartment Imaging with Tensor Distribution Modeling and Tensor-Valued Diffusion Encoding
Diffusion tensor imaging provides increased sensitivity to microstructural tissue changes compared to conventional anatomical imaging but also presents limited specificity. To tackle this problem, the DIAMOND model subdivides the voxel content into diffusion compartments and draws from diffusion-weighted data to estimate compartmental non-central matrix-variate Gamma distribution of diffusion tensors, thereby resolving crossing fascicles while accounting for their respective heterogeneity. Alternatively, tensor-valued diffusion encoding defines new acquisition schemes tagging specific features of the intra-voxel diffusion tensor distribution directly from the outcome of the measurement. However, the impact of such schemes on estimating brain microstructural features has only been studied in a handful of parametric single-fascicle models. In this work, we derive a general Laplace transform for the non-central matrix-variate Gamma distribution, which enables the extension of DIAMOND to tensor-valued encoded data. We then evaluate this "Magic DIAMOND" model in silico and in vivo on various combinations of tensor-valued encoded data. Assessing uncertainty on parameter estimation via stratified bootstrap, we investigate both voxel-based and fixel-based metrics by carrying out multi-peak tractography. We show that our estimated metrics can be mapped along tracks robustly across regions of fiber crossing, which opens new perspectives for tractometry and microstructure mapping along specific white-matter tracts.
2004.07340v2
2020-04-16
Measuring Human and Economic Activity from Satellite Imagery to Support City-Scale Decision-Making during COVID-19 Pandemic
The COVID-19 outbreak forced governments worldwide to impose lockdowns and quarantines to prevent virus transmission. As a consequence, there are disruptions in human and economic activities all over the globe. The recovery process is also expected to be rough. Economic activities impact social behaviors, which leave signatures in satellite images that can be automatically detected and classified. Satellite imagery can support the decision-making of analysts and policymakers by providing a different kind of visibility into the unfolding economic changes. In this work, we use a deep learning approach that combines strategic location sampling and an ensemble of lightweight convolutional neural networks (CNNs) to recognize specific elements in satellite images that could be used to compute economic indicators based on it, automatically. This CNN ensemble framework ranked third place in the US Department of Defense xView challenge, the most advanced benchmark for object detection in satellite images. We show the potential of our framework for temporal analysis using the US IARPA Function Map of the World (fMoW) dataset. We also show results on real examples of different sites before and after the COVID-19 outbreak to illustrate different measurable indicators. Our code and annotated high-resolution aerial scenes before and after the outbreak are available on GitHub (https://github.com/maups/covid19-satellite-analysis).
2004.07438v4
2020-04-16
Subjectifying Objectivity: Delineating Tastes in Theoretical Quantum Gravity Research
Research in Theoretical Quantum Gravity has continued expansively even as it has become detached from classic arbiters of research such as direct empirical falsification. This makes it an interesting test case for social-scientific theories of what motivates and mediates contemporary scientific research and the nature of scientific objectivity. For our empirical investigation, we conducted 50 semi-structured interviews with researchers in the rival camps of String Theory and Loop Quantum Gravity, coded a subset for reoccurring themes, and subjected the resulting data to statistical analysis. Theoretically, we mobilize aspects of Daston and Galison's depiction of the scientific self and its relation to epistemic virtues, Pierre Bourdieu's field-centered account of social space, and Kantian notions of aesthetics in order to delineate the subjective tastes and the related process of collective consensus-making in contemporary quantum gravity research. We make two key contributions. First, our analysis sheds light on the inner workings of the field by connecting its internal epistemic struggles with relevant social-scientific theories. For example, we are able to suggest an explanation for how one approach, String Theory, has become so dominant. Second, our application of theories of social reproduction to the substance of scientific inquiry merits some substantive generalizations to Daston and Galison's framework. Most significantly, we propose as an addendum to their progression the notion of objectivity through intersubjectivity: objectivity obtained not through the suppression of the self but by its (regulated) pluralistic expression and performance.
2004.07450v2
2020-04-22
Excitation of high-frequency magnon modes in magnetoelastic films by short strain pulses
Development of energy efficient techniques for generation of spin waves (magnons) is important for implementation of low-dissipation spin-wave-based logic circuits and memory elements. A promising approach to achieve this goal is based on the injection of short strain pulses into ferromagnetic films with a strong magnetoelastic coupling between spins and strains. Here we report micromagnetoelastic simulations of the magnetization and strain dynamics excited in Fe$_{81}$Ga$_{19}$ films by picosecond and nanosecond acoustic pulses created in a GaAs substrate by a transducer subjected to an optical or electrical impulse. The simulations performed via the numerical solution of the coupled Landau-Lifshitz-Gilbert and elastodynamic equations show that the injected strain pulse induces an inhomogeneous magnetization precession in the ferromagnetic film. The precession lasts up to 1 ns and can be treated as a superposition of magnon modes having the form of standing spin waves. For Fe$_{81}$Ga$_{19}$ films with nanoscale thickness, up to seven (six) distinct modes have been revealed under free-surface (pinning) magnetic boundary conditions. Remarkably, magnon modes with frequencies over 1 THz can be excited by acoustic pulses with an appropriate shape and duration in the films subjected to a moderate external magnetic field. This finding shows that short strain pulses represent a promising tool for the generation of THz spin waves necessary for the implementation of high-speed magnonic devices.
2004.10838v1
2020-04-23
Correlation-driven eightfold magnetic anisotropy in a two-dimensional oxide monolayer
Engineering magnetic anisotropy in two-dimensional systems has enormous scientific and technological implications. The uniaxial anisotropy universally exhibited by two-dimensional magnets has only two stable spin directions, demanding 180 degrees spin switching between states. We demonstrate a novel eightfold anisotropy in magnetic SrRuO3 monolayers by inducing a spin reorientation in (SrRuO3)1/(SrTiO3)N superlattices, in which the magnetic easy axis of Ru spins is transformed from uniaxial <001> direction (N = 1 and 2) to eightfold <111> directions (N = 3, 4 and 5). This eightfold anisotropy enables 71 and 109 degrees spin switching in SrRuO3 monolayers, analogous to 71 and 109 degrees polarization switching in ferroelectric BiFeO3. First-principle calculations reveal that increasing the SrTiO3 layer thickness induces an emergent correlation-driven orbital ordering, tuning spin-orbit interactions and reorienting the SrRuO3 monolayer easy axis. Our work demonstrates that correlation effects can be exploited to substantially change spin-orbit interactions, stabilizing unprecedented properties in two-dimensional magnets and opening rich opportunities for low-power, multi-state device applications.
2004.10939v1
2020-04-27
Dynamic Predictions of Postoperative Complications from Explainable, Uncertainty-Aware, and Multi-Task Deep Neural Networks
Accurate prediction of postoperative complications can inform shared decisions regarding prognosis, preoperative risk-reduction, and postoperative resource use. We hypothesized that multi-task deep learning models would outperform random forest models in predicting postoperative complications, and that integrating high-resolution intraoperative physiological time series would result in more granular and personalized health representations that would improve prognostication compared to preoperative predictions. In a longitudinal cohort study of 56,242 patients undergoing 67,481 inpatient surgical procedures at a university medical center, we compared deep learning models with random forests for predicting nine common postoperative complications using preoperative, intraoperative, and perioperative patient data. Our study indicated several significant results across experimental settings that suggest the utility of deep learning for capturing more precise representations of patient health for augmented surgical decision support. Multi-task learning improved efficiency by reducing computational resources without compromising predictive performance. Integrated gradients interpretability mechanisms identified potentially modifiable risk factors for each complication. Monte Carlo dropout methods provided a quantitative measure of prediction uncertainty that has the potential to enhance clinical trust. Multi-task learning, interpretability mechanisms, and uncertainty metrics demonstrated potential to facilitate effective clinical implementation.
2004.12551v2
2020-05-08
Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding
Given data, finding a faithful low-dimensional hyperbolic embedding of the data is a key method by which we can extract hierarchical information or learn representative geometric features of the data. In this paper, we explore a new method for learning hyperbolic representations by taking a metric-first approach. Rather than determining the low-dimensional hyperbolic embedding directly, we learn a tree structure on the data. This tree structure can then be used directly to extract hierarchical information, embedded into a hyperbolic manifold using Sarkar's construction \cite{sarkar}, or used as a tree approximation of the original metric. To this end, we present a novel fast algorithm \textsc{TreeRep} such that, given a $\delta$-hyperbolic metric (for any $\delta \geq 0$), the algorithm learns a tree structure that approximates the original metric. In the case when $\delta = 0$, we show analytically that \textsc{TreeRep} exactly recovers the original tree structure. We show empirically that \textsc{TreeRep} is not only many orders of magnitude faster than previously known algorithms, but also produces metrics with lower average distortion and higher mean average precision than most previous algorithms for learning hyperbolic embeddings, extracting hierarchical information, and approximating metrics via tree metrics.
2005.03847v4
2020-07-08
On the production of He$^+$ of solar origin in the solar wind
Solar wind measurements in the heliosphere are predominantly comprised of protons, alphas, and minor elements in a highly ionized state. The majority of low charge states, such as He$^{+}$, measured in situ are often attributed to pick up ions of non-solar origin. However, through inspection of the velocity distribution functions of near Earth measurements, we find a small but significant population of He$^+$ ions in the normal solar wind whose properties indicate that it originated from the Sun and has evolved as part of the normal solar wind. Current ionization models, largely governed by electron impact and radiative ionization and recombination processes, underestimate this population by several orders of magnitude. Therefore, to reconcile the singly ionized He observed, we investigate recombination of solar He$^{2+}$ through charge exchange with neutrals from circumsolar dust as a possible formation mechanism of solar He$^{+}$. We present an empirical profile of neutrals necessary for charge exchange to become an effective vehicle to recombine He$^{2+}$ to He$^{+}$ such that it meets observational He$^{+}$ values. We find the formation of He$^{+}$ is not only sensitive to the density of neutrals but also to the inner boundary of the neutral distribution encountered along the solar wind path. However, further observational constraints are necessary to confirm that the interaction between solar $\alpha$ particles and dust neutrals is the primary source of the He$^{+}$ observations.
2007.04402v2
2020-07-28
Towers and the first-order theory of hyperbolic groups
This paper is devoted to the first-order theory of torsion-free hyperbolic groups. One of its purposes is to review some results and to provide precise and correct statements and definitions, as well as some proofs and new results. A key concept is that of a tower (Sela) or NTQ system (Kharlampovich-Myasnikov). We discuss them thoroughly. We state and prove a new general theorem which unifies several results in the literature: elementarily equivalent torsion-free hyperbolic groups have isomorphic cores (Sela); if $H$ is elementarily embedded in a torsion-free hyperbolic group $G$, then $G$ is a tower over $H$ relative to $H$ (Perin); free groups (Perin-Sklinos, Ould-Houcine), and more generally free products of prototypes and free groups, are homogeneous. The converse to Sela and Perin's results just mentioned is true. This follows from the solution to Tarski's problem on elementary equivalence of free groups, due independently to Sela and Kharlampovich-Myasnikov, which we treat as a black box throughout the paper. We present many examples and counterexamples, and we prove some new model-theoretic results. We characterize prime models among torsion-free hyperbolic groups, and minimal models among elementarily free groups. Using Fra\"iss\'e's method, we associate to every torsion-free hyperbolic group $H$ a unique homogeneous countable group $\mathcal{M}$ in which any hyperbolic group $H'$ elementarily equivalent to $H$ has an elementary embedding. In an appendix we give a complete proof of the fact, due to Sela, that towers over a torsion-free hyperbolic group $H$ are $H$-limit groups.
2007.14148v1
2020-08-13
Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method
We establish a machine learning model for the prediction of the magnetization dynamics as function of the external field described by the Landau-Lifschitz-Gilbert equation, the partial differential equation of motion in micromagnetism. The model allows for fast and accurate determination of the response to an external field which is illustrated by a thin-film standard problem. The data-driven method internally reduces the dimensionality of the problem by means of nonlinear model reduction for unsupervised learning. This not only makes accurate prediction of the time steps possible, but also decisively reduces complexity in the learning process where magnetization states from simulated micromagnetic dynamics associated with different external fields are used as input data. We use a truncated representation of kernel principal components to describe the states between time predictions. The method is capable of handling large training sample sets owing to a low-rank approximation of the kernel matrix and an associated low-rank extension of kernel principal component analysis and kernel ridge regression. The approach entirely shifts computations into a reduced dimensional setting breaking down the problem dimension from the thousands to the tens.
2008.05986v3
2020-07-20
Artificial Intelligence is stupid and causal reasoning won't fix it
Artificial Neural Networks have reached Grandmaster and even super-human performance across a variety of games: from those involving perfect-information (such as Go) to those involving imperfect-information (such as Starcraft). Such technological developments from AI-labs have ushered concomitant applications across the world of business - where an AI brand tag is fast becoming ubiquitous. A corollary of such widespread commercial deployment is that when AI gets things wrong - an autonomous vehicle crashes; a chatbot exhibits racist behaviour; automated credit scoring processes discriminate on gender etc. - there are often significant financial, legal and brand consequences and the incident becomes major news. As Judea Pearl sees it, the underlying reason for such mistakes is that, 'all the impressive achievements of deep learning amount to just curve fitting'. The key, Judea Pearl suggests, is to replace reasoning by association with causal-reasoning - the ability to infer causes from observed phenomena. It is a point that was echoed by Gary Marcus and Ernest Davis in a recent piece for the New York Times: 'we need to stop building computer systems that merely get better and better at detecting statistical patterns in data sets - often using an approach known as Deep Learning - and start building computer systems that from the moment of their assembly innately grasp three basic concepts: time, space and causality'. In this paper, foregrounding what in 1949 Gilbert Ryle termed a category mistake, I will offer an alternative explanation for AI errors: it is not so much that AI machinery cannot grasp causality, but that AI machinery - qua computation - cannot understand anything at all.
2008.07371v1
2020-08-19
Dynamical decoupling in interacting systems: applications to signal-enhanced hyperpolarized readout
Methods that preserve coherence broadly impact all quantum information processing and metrology applications. Dynamical decoupling methods accomplish this by protecting qubits in noisy environments but are typically constrained to the limit where the qubits themselves are non-interacting. Here we consider the alternate regime wherein the inter-qubit couplings are of the same order as dephasing interactions with the environment. We propose and demonstrate a multi-pulse protocol that protects transverse spin states by suitably Hamiltonian engineering the inter-spin coupling while simultaneously suppressing dephasing noise on the qubits. We benchmark the method on 13C nuclear spin qubits in diamond, dipolar coupled to each other and embedded in a noisy electronic spin bath, and hyperpolarized via optically pumped NV centers. We observe effective state lifetimes of 13C nuclei $T_2^{\prime}\approx$2.5s at room temperature, an extension of over 4700-fold over the conventional $T_2^{\ast}$ free induction decay. The spins are continuously interrogated during the applied quantum control, resulting in 13C NMR line narrowing and an $>$500-fold boost in SNR due to the lifetime extension. Together with hyperpolarization spin interrogation is accelerated by $>10^{11}$ over conventional 7T NMR. This work suggests strategies for the dynamical decoupling of coupled qubit systems with applications in a variety of experimental platforms.
2008.08323v1
2020-08-30
Microwave and spin transfer torque driven coherent control in ferromagnets
Coherent control is a method used to manipulate the state of matter using oscillatory electromagnetic radiation which relies on the non-adiabatic interaction. It is commonly applied in quantum processing applications. This technique is interesting in the context of ferromagnetic materials because of the ability to combine it with spintronics for the purpose of fundamental spin transport research, low-power information processing, and potentially future quantum bit (Qubit) applications. In this work we address the theoretical grounds of coherent manipulation in practical ferromagnetic systems. We study electromagnetic radiation driven interaction that is enhanced in the presence of spin polarized currents and map the conditions that allow coherent manipulation for which Rabi oscillations take place. The role of the magnetic anisotropy field is shown to act as an additional oscillatory driving field. We discuss the Gilbert losses in the context of effective coherence decay rates and show that it is possible to control these rates by application of a static spin current. The case of coherent manipulation using oscillatory spin currents that is free of radiation is discussed as well. Our work paves the way towards spin current amplification as well as radiation-free coherent control schemes that may potentially lead to novel Qubits that are robust and scalable.
2008.13139v3
2020-08-31
Philosophy-Guided Modelling and Implementation of Adaptation and Control in Complex Systems
Control was from its very beginning an important concept in cybernetics. Later on, with the works of W. Ross Ashby, for example, biological concepts such as adaptation were interpreted in the light of cybernetic systems theory. Adaptation is the process by which a system is capable of regulating or controlling itself in order to adapt to changes of its inner and outer environment maintaining a homeostatic state. In earlier works we have developed a system metamodel that on the one hand refers to cybernetic concepts such as structure, operation, and system, and on the other to the philosophy of individuation of Gilbert Simondon. The result is the so-called allagmatic method that is capable of creating concrete models of systems such as artificial neural networks and cellular automata starting from abstract building blocks. In this paper, we add to our already existing method the cybernetic concepts of control and especially adaptation. In regard to the system metamodel, we rely again on philosophical theories, this time the philosophy of organism of Alfred N. Whitehead. We show how these new meta-theoretical concepts are described formally and how they are implemented in program code. We also show what role they play in simple experiments. We conclude that philosophical abstract concepts help to better understand the process of creating computer models and their control and adaptation. In the outlook we discuss how the allagmatic method needs to be extended in order to cover the field of complex systems and Norbert Wiener's ideas on control.
2009.00110v4
2020-09-02
X-ray linear dichroic ptychography
Biominerals such as seashells, corals skeletons, bone, and enamel are optically anisotropic crystalline materials with unique nano- and micro-scale organization that translates into exceptional macroscopic mechanical properties, providing inspiration for engineering new and superior biomimetic structures. Here we use particles of Seriatopora aculeata coral skeleton as a model and demonstrate, for the first time, x-ray linear dichroic ptychography. We map the aragonite (CaCO3) crystal c-axis orientations in coral skeleton with 35 nm spatial resolution. Linear dichroic phase imaging at the O K-edge energy shows strong polarization-dependent contrast and reveals the presence of both narrow (< 35{\deg}) and wide (> 35{\deg}) c-axis angular spread in sub-micrometer coral particles. These x-ray ptychography results were corroborated using 4D scanning transmission electron nano-diffraction on the same particles. Evidence of co-oriented but disconnected corallite sub-domains indicates jagged crystal boundaries consistent with formation by amorphous nanoparticle attachment. Looking forward, we anticipate that x-ray linear dichroic ptychography can be applied to study nano-crystallites, interfaces, nucleation and mineral growth of optically anisotropic materials with sub-ten nanometers spatial resolution in three dimensions.
2009.01093v1
2020-09-18
The effect of the surface magnetic anisotropy of the neodymium atoms on the coercivity in the neodymium permanent magnet
The Nd permanent magnet (Nd$_{2}$Fe$_{14}$B) is an indispensable material used in modern energy conversion devices. The realization of high coercivity at finite temperatures is a burning issue. One of the important ingredients for controlling the coercive force is the surface property of magnetic grains. It has been reported by first-principles studies that the Nd atoms in the first (001) surface layer facing the vacuum have in-plane anisotropy perpendicular to the $c$ axis, which may decrease the coercivity. Focusing on the surface anisotropy effect on the coercivity, we examine the coercivity at zero and finite temperatures by using an atomistic model reflecting the lattice structure of the Nd magnet with a stochastic Landau-Lifshitz-Gilbert equation method. We study general three cases, in which the Nd atoms in surface layers have (1) no anisotropy, (2) in-plane anisotropy, and (3) reinforced anisotropy for two types of surfaces, (001) and (100) surfaces. We find that in contrast to the zero-temperature case, due to the thermal fluctuation effect, the modification of only the first surface layer has little effect on the coercivity at finite temperatures. However, the modification of a few layers results in significant effects. We discuss the details of the dependence of the coercivity on temperature, type of surface, and modified layer depth, and also the features of domain growth in magnetization reversal.
2009.08572v1
2020-09-28
Precise control of $J_\mathrm{eff}=1/2$ magnetic properties in Sr$_2$IrO$_4$ epitaxial thin films by variation of strain and thin film thickness
We report on a comprehensive investigation of the effects of strain and film thickness on the structural and magnetic properties of epitaxial thin films of the prototypal $J_\mathrm{eff}=1/2$ compound Sr$_2$IrO$_4$ by advanced X-ray scattering. We find that the Sr$_2$IrO$_4$ thin films can be grown fully strained up to a thickness of 108 nm. By using X-ray resonant scattering, we show that the out-of-plane magnetic correlation length is strongly dependent on the thin film thickness, but independent of the strain state of the thin films. This can be used as a finely tuned dial to adjust the out-of-plane magnetic correlation length and transform the magnetic anisotropy from two-dimensional (2D) to three-dimensional (3D) behavior by incrementing film thickness. These results provide a clearer picture for the systematic control of the magnetic degrees of freedom in epitaxial thin films of Sr$_2$IrO$_4$ and bring to light the potential for a rich playground to explore the physics of $5d$-transition metal compounds.
2009.13185v1
2020-10-03
WinterLab: Developing a low-cost, portable experiment platform to encourage engagement in the electronics lab
Encouraging student engagement is a key aim in any educational setting, and allowing students the freedom to pursue their own methods of solving problems through independent experimentation has been shown to markedly improve this. In many contexts, however, allowing students this flexibility in their learning is hampered by constraints of the material itself, such as in the electronics laboratory, where expensive and bulky equipment confines the learning environment to the laboratory room. Finding ourselves in the position of teaching one such laboratory course at the undergraduate level, we sought to encourage students to learn through independent investigation and the pursuit of personal projects, by providing a more flexible and inquiry-based learning environment and allowing them to take their measurement equipment -- and their learning -- beyond the laboratory itself. We present this project as a case of design both for and by students, with the lead designer undertaking the project after attending the course in question, and pursuing its development as a foundational step in their graduate career. We discuss the challenges and opportunities we encountered over the course of the design and development process, and the eventual key output of the project: a portable, low-cost, integrated electronics experimentation platform called the Winterlab board.
2010.01426v2
2020-10-16
Hyperspectral interference tomography of nacre
Structural characterization of biologically formed materials is essential for understanding biological phenomena and their environment, and generating new bio-inspired engineering concepts. For example, nacre -- formed by mollusks in the ocean -- encodes local environmental conditions throughout its formation and has exceptional strength due to its nanoscale brick-and-mortar structure. This layered structure, comprising transparent aragonite tablets bonded with an ultra-thin organic polymer, also results in stunning interference colors. Existing methods of structural characterization of nacre rely on some form of cross-sectional analysis, such as scanning electron microscopy or polarization-dependent imaging contrast (PIC) mapping. However, these techniques are destructive and too time- and resource-intensive to analyze large sample areas. Here we present an all-optical, rapid, and non-destructive imaging technique -- hyperspectral interference tomography (HIT) -- to spatially map the structural parameters of nacre and other disordered layered materials. We combined hyperspectral imaging with optical-interference modeling to infer the mean tablet thickness and disordering of nacre layers across entire mollusk shells at various stages of development, observing a previously unknown relationship between the growth of the mollusk and tablet thickness. Our rapid, inexpensive, and nondestructive method can be readily applied to in-field studies.
2010.08170v1
2020-11-03
Recent results for the Landau-Lifshitz equation
We give a survey on some recent results concerning the Landau-Lifshitz equation, a fundamental nonlinear PDE with a strong geometric content, describing the dynamics of the magnetization in ferromagnetic materials. We revisit the Cauchy problem for the anisotropic Landau-Lifshitz equation, without dissipation, for smooth solutions, and also in the energy space in dimension one. We also examine two approximations of the Landau-Lifshitz equation given by of the Sine-Gordon equation and cubic Schr\"odinger equations, arising in certain singular limits of strong easy-plane and easy-axis anisotropy, respectively. Concerning localized solutions, we review the orbital and asymptotic stability problems for a sum of solitons in dimension one, exploiting the variational nature of the solitons in the hydrodynamical framework. Finally, we survey results concerning the existence, uniqueness and stability of self-similar solutions (expanders and shrinkers) for the isotropic Landau-Lifshitz equation with Gilbert term. Since expanders are associated with a singular initial condition with a jump discontinuity, we also review their well-posedness in spaces linked to the BMO space.
2011.01692v3
2020-11-10
The Virtual Goniometer: A new method for measuring angles on 3D models of fragmentary bone and lithics
The contact goniometer is a commonly used tool in lithic and zooarchaeological analysis, despite suffering from a number of shortcomings due to the physical interaction between the measuring implement, the object being measured, and the individual taking the measurements. However, lacking a simple and efficient alternative, researchers in a variety of fields continue to use the contact goniometer to this day. In this paper, we present a new goniometric method that we call the virtual goniometer, which takes angle measurements virtually on a 3D model of an object. The virtual goniometer allows for rapid data collection, and for the measurement of many angles that cannot be physically accessed by a manual goniometer. We compare the intra-observer variability of the manual and virtual goniometers, and find that the virtual goniometer is far more consistent and reliable. Furthermore, the virtual goniometer allows for precise replication of angle measurements, even among multiple users, which is important for reproducibility of goniometric-based research. The virtual goniometer is available as a plug-in in the open source mesh processing packages Meshlab and Blender, making it easily accessible to researchers exploring the potential for goniometry to improve archaeological methods and address anthropological questions.
2011.04898v2
2020-11-17
Competing energy scales in topological superconducting heterostructures
Artificially engineered topological superconductivity has emerged as a viable route to create Majorana modes, exotic quasiparticles which have raised great expectations for storing and manipulating information in topological quantum computational schemes. The essential ingredients for their realization are spin non-degenerate metallic states proximitized to an s-wave superconductor. In this context, proximity-induced superconductivity in materials with a sizable spin-orbit coupling has been heavily investigated in recent years. Although there is convincing evidence that superconductivity may indeed be induced, it has been difficult to elucidate its topological nature. In this work, we systematically engineer an artificial topological superconductor by progressively introducing superconductivity (Nb) into metals with strong spin-orbital coupling (Pt) and 3D topological surface states (Bi2Te3). Through a longitudinal study of the character of superconducting vortices within s-wave superconducting Nb and proximity-coupled Nb/Pt and Nb/Bi2Te3, we detect the emergence of a zero-bias peak that is directly linked to the presence of topological surface states. Supported by a detailed theoretical model, our results are rationalized in terms of competing energy trends which are found to impose an upper limit to the size of the minigap separating Majorana and trivial modes, its size being ultimately linked to fundamental materials properties.
2011.08812v1
2020-12-01
Phase-field modeling of biomineralization in mollusks and corals: Microstructure vs. formation mechanism
While biological crystallization processes have been studied on the microscale extensively, models addressing the mesoscale aspects of such phenomena are rare. In this work, we investigate whether the phase-field theory developed in materials science for describing complex polycrystalline structures on the mesoscale can be meaningfully adapted to model crystallization in biological systems. We demonstrate the abilities of the phase-field technique by modeling a range of microstructures observed in mollusk shells and coral skeletons, including granular, prismatic, sheet/columnar nacre, and sprinkled spherulitic structures. We also compare two possible micromechanisms of calcification: the classical route via ion-by-ion addition from a fluid state and a non-classical route, crystallization of an amorphous precursor deposited at the solidification front. We show that with appropriate choice of the model parameters microstructures similar to those found in biomineralized systems can be obtained along both routes, though the timescale of the non-classical route appears to be more realistic. The resemblance of the simulated and natural biominerals suggests that, underneath the immense biological complexity observed in living organisms, the underlying design principles for biological structures may be understood with simple math, and simulated by phase-field theory.
2012.00666v1
2020-12-02
Symmetry of the Magnetoelastic Interaction of Rayleigh and Shear Horizontal Magnetoacoustic Waves in Nickel Thin Films on LiTaO$_3$
We study the interaction of Rayleigh and shear horizontal surface acoustic waves (SAWs) with spin waves in thin Ni films on a piezoelectric LiTaO$_3$ substrate, which supports both SAW modes simultaneously. Because Rayleigh and shear horizontal modes induce different strain components in the Ni thin films, the symmetries of the magnetoelastic driving fields, of the magnetoelastic response, and of the transmission nonreciprocity differ for both SAW modes. Our experimental findings are well explained by a theoretical model based on a modified Landau--Lifshitz--Gilbert approach. We show that the symmetries of the magnetoelastic response driven by Rayleigh- and shear horizontal SAWs complement each other, which makes it possible to excite spin waves for any relative orientation of magnetization and SAW propagation direction and, moreover, can be utilized to characterize surface strain components of unknown acoustic wave modes.
2012.01055v2
2020-12-03
Localization of Malaria Parasites and White Blood Cells in Thick Blood Smears
Effectively determining malaria parasitemia is a critical aspect in assisting clinicians to accurately determine the severity of the disease and provide quality treatment. Microscopy applied to thick smear blood smears is the de facto method for malaria parasitemia determination. However, manual quantification of parasitemia is time consuming, laborious and requires considerable trained expertise which is particularly inadequate in highly endemic and low resourced areas. This study presents an end-to-end approach for localisation and count of malaria parasites and white blood cells (WBCs) which aid in the effective determination of parasitemia; the quantitative content of parasites in the blood. On a dataset of slices of images of thick blood smears, we build models to analyse the obtained digital images. To improve model performance due to the limited size of the dataset, data augmentation was applied. Our preliminary results show that our deep learning approach reliably detects and returns a count of malaria parasites and WBCs with a high precision and recall. We also evaluate our system against human experts and results indicate a strong correlation between our deep learning model counts and the manual expert counts (p=0.998 for parasites, p=0.987 for WBCs). This approach could potentially be applied to support malaria parasitemia determination especially in settings that lack sufficient Microscopists.
2012.01994v1
2020-12-05
Age-Optimal Low-Power Status Update over Time-Correlated Fading Channel
In this paper, we consider transmission scheduling in a status update system, where updates are generated periodically and transmitted over a Gilbert-Elliott fading channel. The goal is to minimize the long-run average age of information (AoI) at the destination under an average energy constraint. We consider two practical cases to obtain channel state information (CSI): (i) \emph{without channel sensing} and (ii) \emph{with delayed channel sensing}. For case (i), the channel state is revealed when an ACK/NACK is received at the transmitter following a transmission, but when no transmission occurs, the channel state is not revealed. Thus, we have to design schemes that balance tradeoffs across energy, AoI, channel exploration, and channel exploitation. The problem is formulated as a constrained partially observable Markov decision process problem (POMDP). To reduce algorithm complexity, we show that the optimal policy is a randomized mixture of no more than two stationary deterministic policies each of which is of a threshold-type in the belief on the channel. For case (ii), (delayed) CSI is available at the transmitter via channel sensing. In this case, the tradeoff is only between the AoI and energy consumption and the problem is formulated as a constrained MDP. The optimal policy is shown to have a similar structure as in case (i) but with an AoI associated threshold. Finally, the performance of the proposed structure-aware algorithms is evaluated numerically and compared with a Greedy policy.
2012.02958v2
2020-11-30
Procode: the Swiss Multilingual Solution for Automatic Coding and Recoding of Occupations and Economic Activities
Objective. Epidemiological studies require data that are in alignment with the classifications established for occupations or economic activities. The classifications usually include hundreds of codes and titles. Manual coding of raw data may result in misclassification and be time consuming. The goal was to develop and test a web-tool, named Procode, for coding of free-texts against classifications and recoding between different classifications. Methods. Three text classifiers, i.e. Complement Naive Bayes (CNB), Support Vector Machine (SVM) and Random Forest Classifier (RFC), were investigated using a k-fold cross-validation. 30 000 free-texts with manually assigned classification codes of French classification of occupations (PCS) and French classification of activities (NAF) were available. For recoding, Procode integrated a workflow that converts codes of one classification to another according to existing crosswalks. Since this is a straightforward operation, only the recoding time was measured. Results. Among the three investigated text classifiers, CNB resulted in the best performance, where the classifier predicted accurately 57-81% and 63-83% classification codes for PCS and NAF, respectively. SVM lead to somewhat lower results (by 1-2%), while RFC coded accurately up to 30% of the data. The coding operation required one minute per 10 000 records, while the recoding was faster, i.e. 5-10 seconds. Conclusion. The algorithm integrated in Procode showed satisfactory performance, since the tool had to assign the right code by choosing between 500-700 different choices. Based on the results, the authors decided to implement CNB in Procode. In future, if another classifier shows a superior performance, an update will include the required modifications.
2012.07521v1
2020-12-16
Dynamic clay microstructures emerge via ion complexation waves
Clays control carbon, water and nutrient transport in the lithosphere, promote cloud formation5 and lubricate fault slip through interactions among hydrated mineral interfaces. Clay mineral properties are difficult to model because their structures are disordered, curved and dynamic. Consequently, interactions at the clay mineral-aqueous interface have been approximated using electric double layer models based on single crystals of mica and atomistic simulations. We discover that waves of complexation dipoles at dynamically curving interfaces create an emergent long-range force that drives exfoliation and restacking over time- and length-scales that are not captured in existing models. Curvature delocalizes electrostatic interactions in ways that fundamentally differ from planar surfaces, altering the ratio of ions bound to the convex and concave sides of a layer. Multiple-scattering reconstruction of low-dose energy-filtered cryo electron tomography enabled direct imaging of ion complexes and electrolyte distributions at hydrated and curved mineral interfaces with {\aa}ngstrom resolution over micron length scales. Layers exfoliate and restack abruptly and repeatedly over timescales that depend strongly on the counterion identity, demonstrating that the strong coupling between elastic, electrostatic and hydration forces in clays promote collective reorganization previously thought to be a feature only of active matter.
2012.09295v1
2020-12-17
Age-optimal Scheduling over Hybrid Channels
We consider the problem of minimizing the age of information when a source can transmit status updates over two heterogeneous channels. Our work is motivated by recent developments in 5G mmWave technology, where transmissions may occur over an unreliable but fast (e.g., mmWave) channel or a slow reliable (e.g., sub-6GHz) channel. The unreliable channel is modeled as a time-correlated Gilbert-Elliot channel at a high rate when the channel is in the 'ON' state. The reliable channel provides a deterministic but lower data rate. The scheduling strategy determines the channel to be used for transmission in each time slot, aiming to minimize the time-average age of information (AoI). The optimal scheduling problem is formulated as a Markov Decision Process (MDP), which is challenging to solve because super-modularity does not hold in a part of the state space. We address this challenge and show that a multi-dimensional threshold-type scheduling policy is optimal for minimizing the age. By exploiting the structure of the MDP and analyzing the discrete-time Markov chains (DTMCs) of the threshold-type policy, we devise a low-complexity bisection algorithm to compute the optimal thresholds. We compare different scheduling policies using numerical simulations.
2012.09403v6
2020-12-21
Variations on the Maiani-Testa approach and the inverse problem
We discuss a method to construct hadronic scattering and decay amplitudes from Euclidean correlators, by combining the approach of a regulated inverse Laplace transform with the work of Maiani and Testa. Revisiting the original result, we observe that the key observation, i.e. that only threshold scattering information can be extracted at large separations, can be understood by interpreting the correlator as a spectral function, $\rho(\omega)$, convoluted with the Euclidean kernel, $e^{- \omega t}$, which is sharply peaked at threshold. We therefore consider a modification in which a smooth step function, equal to one above a target energy, is inserted in the spectral decomposition. This can be achieved either through Backus-Gilbert-like methods or more directly using the variational approach. The result is a shifted resolution function, such that the large $t$ limit projects onto scattering or decay amplitudes above threshold. The utility of this method is highlighted through large $t$ expansions of both three- and four-point functions that include leading terms proportional to the real and imaginary parts (separately) of the target observable. This work also presents new results relevant for the un-modified correlator at threshold, including expressions for extracting the $N \pi$ scattering length from four-point functions and a new strategy to organize the large $t$ expansion that exhibits better convergence than the expansion in powers of $1/t$.
2012.11488v1
2021-01-13
PID passivity-based droop control of power converters: Large-signal stability, robustness and performance
We present a full review of PID passivity-based controllers (PBC) applied to power electronic converters, discussing limitations, unprecedented merits and potential improvements in terms of large-signal stability, robustness and performance. We provide four main contributions. The nominal case is first considered and it is shown, under the assumption of perfect knowledge of the system parameters, that the PID-PBC is able to guarantee global exponential stability of a desired operating point for any positive gains. Second, we analyze robustness of the controller to parameters uncertainty for a specific class of power converters, by establishing precise stability margins. Third, we propose a modification of the controller by introducing a leakage, in order to overcome some of the intrinsic performance and robustness limitations. Interestingly, such controller can be interpreted at steady-state as a droop between the input and the passive output, similar to traditional primary controllers. Fourth, we robustify the design against saturation of the control input via an appropriate monotone transformation of the controller. The obtained results are thoroughly discussed and validated by simulations on two relevant power applications: a dc/dc boost converter and an HVDC grid-connected voltage source converter.
2101.05047v2
2021-02-15
Recent Developments in Blockchain Technology and their Impact on Energy Consumption
The enormous power consumption of Bitcoin has led to undifferentiated discussions in science and practice about the sustainability of blockchain and distributed ledger technology in general. However, blockchain technology is far from homogeneous - not only with regard to its applications, which now go far beyond cryptocurrencies and have reached businesses and the public sector, but also with regard to its technical characteristics and, in particular, its power consumption. This paper summarizes the status quo of the power consumption of various implementations of blockchain technology, with special emphasis on the recent 'Bitcoin Halving' and so-called 'zk-rollups'. We argue that although Bitcoin and other proof-of-work blockchains do indeed consume a lot of power, alternative blockchain solutions with significantly lower power consumption are already available today, and new promising concepts are being tested that could further reduce in particular the power consumption of large blockchain networks in the near future. From this we conclude that although the criticism of Bitcoin's power consumption is legitimate, it should not be used to derive an energy problem of blockchain technology in general. In many cases in which processes can be digitised or improved with the help of more energy-efficient blockchain variants, one can even expect net energy savings.
2102.07886v1
2021-03-11
Toward the Next Generation of News Recommender Systems
This paper proposes a vision and research agenda for the next generation of news recommender systems (RS), called the table d'hote approach. A table d'hote (translates as host's table) meal is a sequence of courses that create a balanced and enjoyable dining experience for a guest. Likewise, we believe news RS should strive to create a similar experience for the users by satisfying the news-diet needs of a user. While extant news RS considers criteria such as diversity and serendipity, and RS bundles have been studied for other contexts such as tourism, table d'hote goes further by ensuring the recommended articles satisfy a diverse set of user needs in the right proportions and in a specific order. In table d'hote, available articles need to be stratified based on the different ways that news can create value for the reader, building from theories and empirical research in journalism and user engagement. Using theories and empirical research from communication on the uses and gratifications (U&G) consumers derive from media, we define two main strata in a table d'hote news RS, each with its own substrata: 1) surveillance, which consists of information the user needs to know, and 2) serendipity, which are the articles offering unexpected surprises. The diversity of the articles according to the defined strata and the order of the articles within the list of recommendations are also two important aspects of the table d'hote in order to give the users the most effective reading experience. We propose our vision, link it to the existing concepts in the RS literature, and identify challenges for future research.
2103.06909v1
2021-03-16
Machine learning methods for the prediction of micromagnetic magnetization dynamics
Machine learning (ML) entered the field of computational micromagnetics only recently. The main objective of these new approaches is the automatization of solutions of parameter-dependent problems in micromagnetism such as fast response curve estimation modeled by the Landau-Lifschitz-Gilbert (LLG) equation. Data-driven models for the solution of time- and parameter-dependent partial differential equations require high dimensional training data-structures. ML in this case is by no means a straight-forward trivial task, it needs algorithmic and mathematical innovation. Our work introduces theoretical and computational conceptions of certain kernel and neural network based dimensionality reduction approaches for efficient prediction of solutions via the notion of low-dimensional feature space integration. We introduce efficient treatment of kernel ridge regression and kernel principal component analysis via low-rank approximation. A second line follows neural network (NN) autoencoders as nonlinear data-dependent dimensional reduction for the training data with focus on accurate latent space variable description suitable for a feature space integration scheme. We verify and compare numerically by means of a NIST standard problem. The low-rank kernel method approach is fast and surprisingly accurate, while the NN scheme can even exceed this level of accuracy at the expense of significantly higher costs.
2103.09079v2
2021-03-18
Bounding the detection efficiency threshold in Bell tests using multiple copies of the maximally entangled two-qubit state carried by a single pair of particles
In this paper, we investigate the critical efficiency of detectors to observe Bell nonlocality using multiple copies of the maximally entangled two-qubit state carried by a single pair of particles, such as hyperentangled states, and the product of Pauli measurements. It is known that in a Clauser-Horne-Shimony-Holt (CHSH) Bell test the symmetric detection efficiency of $82.84\%$ can be tolerated for the two-qubit maximally entangled state. We beat this enigmatic threshold by entangling two particles with multiple degrees of freedom. The obtained upper bounds of the symmetric detection efficiency thresholds are $80.86\%$, $73.99\%$ and $69.29\%$ for two, three and four copies of the two-qubit maximally entangled state, respectively. The number of measurements and outcomes in the respective cases are 4, 8 and 16. To find the improved thresholds, we use large-scale convex optimization tools, which allows us to significantly go beyond state-of-the-art results. The proof is exact up to three copies, while for four copies it is due to reliable numerical computations. Specifically, we used linear programming to obtain the two-copy threshold and the corresponding Bell inequality, and convex optimization based on Gilbert's algorithm for three and four copies of the two-qubit state. We show analytically that the symmetric detection efficiency threshold decays exponentially with the number of copies of the two-qubit state. Our techniques can also be applied to more general Bell nonlocality scenarios with more than two parties.
2103.10413v2
2021-04-05
When Can Liquid Democracy Unveil the Truth?
In this paper, we investigate the so-called ODP-problem that has been formulated by Caragiannis and Micha [10]. Here, we are in a setting with two election alternatives out of which one is assumed to be correct. In ODP, the goal is to organise the delegations in the social network in order to maximize the probability that the correct alternative, referred to as ground truth, is elected. While the problem is known to be computationally hard, we strengthen existing hardness results by providing a novel strong approximation hardness result: For any positive constant $C$, we prove that, unless $P=NP$, there is no polynomial-time algorithm for ODP that achieves an approximation guarantee of $\alpha \ge (\ln n)^{-C}$, where $n$ is the number of voters. The reduction designed for this result uses poorly connected social networks in which some voters suffer from misinformation. Interestingly, under some hypothesis on either the accuracies of voters or the connectivity of the network, we obtain a polynomial-time $1/2$-approximation algorithm. This observation proves formally that the connectivity of the social network is a key feature for the efficiency of the liquid democracy paradigm. Lastly, we run extensive simulations and observe that simple algorithms (working either in a centralized or decentralized way) outperform direct democracy on a large class of instances. Overall, our contributions yield new insights on the question in which situations liquid democracy can be beneficial.
2104.01828v1
2021-04-05
Floquet prethermalization with lifetime exceeding 90s in a bulk hyperpolarized solid
We report the observation of long-lived Floquet prethermal states in a bulk solid composed of dipolar-coupled $^{13}$C nuclei in diamond at room temperature. For precessing nuclear spins prepared in an initial transverse state, we demonstrate pulsed spin-lock Floquet control that prevents their decay over multiple-minute long periods. We observe Floquet prethermal lifetimes $T_2'\approx$90.9s, extended >60,000-fold over the nuclear free induction decay times. The spins themselves are continuously interrogated for $\sim$10min, corresponding to the application of $\approx$5.8M control pulses. The $^{13}$C nuclei are optically hyperpolarized by lattice Nitrogen Vacancy (NV) centers; the combination of hyperpolarization and continuous spin readout yields significant signal-to-noise in the measurements. This allows probing the Floquet thermalization dynamics with unprecedented clarity. We identify four characteristic regimes of the thermalization process, discerning short-time transient processes leading to the prethermal plateau, and long-time system heating towards infinite temperature. This work points to new opportunities possible via Floquet control in networks of dilute, randomly distributed, low-sensitivity nuclei. In particular, the combination of minutes-long prethermal lifetimes and continuous spin interrogation opens avenues for quantum sensors constructed from hyperpolarized Floquet prethermal nuclei.
2104.01988v2
2021-04-14
Generalized Simple Streaming Codes from MDS Codes
Streaming codes represent a packet-level FEC scheme for achieving reliable, low-latency communication. In the literature on streaming codes, the commonly-assumed Gilbert-Elliott channel model, is replaced by a more tractable, delay-constrained, sliding-window (DCSW) channel model that can introduce either random or burst erasures. The known streaming codes that are rate optimal over the DCSW channel model are constructed by diagonally embedding a scalar block code across successive packets. These code constructions have field size that is quadratic in the delay parameter $\tau$ and have a somewhat complex structure with an involved decoding procedure. This led to the introduction of simple streaming (SS) codes in which diagonal embedding is replaced by staggered-diagonal embedding (SDE). The SDE approach reduces the impact of a burst of erasures and makes it possible to construct near-rate-optimal streaming codes using Maximum Distance Separable (MDS) code having linear field size. The present paper takes this development one step further, by retaining the staggered-diagonal feature, but permitting the placement of more than one code symbol from a given scalar codeword within each packet. These generalized, simple streaming codes allow us to improve upon the rate of SS codes, while retaining the simplicity of working with MDS codes. We characterize the maximum code rate of streaming codes under a constraint on the number of contiguous packets over which symbols of the underlying scalar code are dispersed. Such a constraint leads to simplified code construction and reduced-complexity decoding.
2104.07005v1
2021-04-22
COVID-19 and Big Data: Multi-faceted Analysis for Spatio-temporal Understanding of the Pandemic with Social Media Conversations
COVID-19 has been devastating the world since the end of 2019 and has continued to play a significant role in major national and worldwide events, and consequently, the news. In its wake, it has left no life unaffected. Having earned the world's attention, social media platforms have served as a vehicle for the global conversation about COVID-19. In particular, many people have used these sites in order to express their feelings, experiences, and observations about the pandemic. We provide a multi-faceted analysis of critical properties exhibited by these conversations on social media regarding the novel coronavirus pandemic. We present a framework for analysis, mining, and tracking the critical content and characteristics of social media conversations around the pandemic. Focusing on Twitter and Reddit, we have gathered a large-scale dataset on COVID-19 social media conversations. Our analyses cover tracking potential reports on virus acquisition, symptoms, conversation topics, and language complexity measures through time and by region across the United States. We also present a BERT-based model for recognizing instances of hateful tweets in COVID-19 conversations, which achieves a lower error-rate than the state-of-the-art performance. Our results provide empirical validation for the effectiveness of our proposed framework and further demonstrate that social media data can be efficiently leveraged to provide public health experts with inexpensive but thorough insight over the course of an outbreak.
2104.10807v1
2021-05-05
exoplanet: Gradient-based probabilistic inference for exoplanet data & other astronomical time series
"exoplanet" is a toolkit for probabilistic modeling of astronomical time series data, with a focus on observations of exoplanets, using PyMC3 (Salvatier et al., 2016). PyMC3 is a flexible and high-performance model-building language and inference engine that scales well to problems with a large number of parameters. "exoplanet" extends PyMC3's modeling language to support many of the custom functions and probability distributions required when fitting exoplanet datasets or other astronomical time series. While it has been used for other applications, such as the study of stellar variability, the primary purpose of "exoplanet" is the characterization of exoplanets or multiple star systems using time-series photometry, astrometry, and/or radial velocity. In particular, the typical use case would be to use one or more of these datasets to place constraints on the physical and orbital parameters of the system, such as planet mass or orbital period, while simultaneously taking into account the effects of stellar variability.
2105.01994v2