Interplay between bending and stretching in carbon nanoribbons

We investigate the bending properties of carbon nanoribbons by combining continuum elasticity theory and tight-binding atomistic simulations. First, we develop a complete analysis of a given bended configuration through continuum mechanics. Then, we provide by tight-binding calculations the value of the bending rigidity in good agreement with recent literature. We discuss the emergence of a stretching field induced by the full atomic-scale relaxation of the nanoribbon architecture. We further prove that such an in-plane strain field can be decomposed into a first contribution due to the actual bending of the sheet and a second one due to edge effects.Comment: 5 pages, 6 figure

Impact hazard protection efficiency by a small kinetic impactor

In this paper the ability of a small kinetic impactor spacecraft to mitigate an Earth-threatening asteroid is assessed by means of a novel measure of efficiency. This measure estimates the probability of a space system to deflect a single randomly-generated Earth-impacting object to a safe distance from the Earth. This represents a measure of efficiency that is not biased by the orbital parameters of a test-case object. A vast number of virtual Earth-impacting scenarios are investigated by homogenously distributing in orbital space a grid of 17,518 Earth impacting trajectories. The relative frequency of each trajectory is estimated by means Opik’s theory and Bottke’s near Earth objects model. A design of the entire mitigation mission is performed and the largest deflected asteroid computed for each impacting trajectory. The minimum detectable asteroid can also be estimated by an asteroid survey model. The results show that current technology would likely suffice against discovered airburst and local damage threats, whereas larger space systems would be necessary to reliably tackle impact hazard from larger threats. For example, it is shown that only 1,000 kg kinetic impactor would suffice to mitigate the impact threat of 27.1% of objects posing similar threat than that posed by Apophis

Semi-autonomous Intersection Collision Avoidance through Job-shop Scheduling

In this paper, we design a supervisor to prevent vehicle collisions at intersections. An intersection is modeled as an area containing multiple conflict points where vehicle paths cross in the future. At every time step, the supervisor determines whether there will be more than one vehicle in the vicinity of a conflict point at the same time. If there is, then an impending collision is detected, and the supervisor overrides the drivers to avoid collision. A major challenge in the design of a supervisor as opposed to an autonomous vehicle controller is to verify whether future collisions will occur based on the current drivers choices. This verification problem is particularly hard due to the large number of vehicles often involved in intersection collision, to the multitude of conflict points, and to the vehicles dynamics. In order to solve the verification problem, we translate the problem to a job-shop scheduling problem that yields equivalent answers. The job-shop scheduling problem can, in turn, be transformed into a mixed-integer linear program when the vehicle dynamics are first-order dynamics, and can thus be solved by using a commercial solver.Comment: Submitted to Hybrid Systems: Computation and Control (HSCC) 201

Optical Spectroscopy of X-Mega targets in the Carina Nebula - VI. FO 15: a new O-Type double-lined eclipsing binary

We report the discovery of a new O-type double-lined spectroscopic binary with a short orbital period of 1.4 days. We find the primary component of this binary, FO 15, to have an approximate spectral type O5.5Vz, i.e. a Zero-Age-Main-Sequence star. The secondary appears to be of spectral type O9.5V. We have performed a numerical model fit to the public ASAS photometry, which shows that FO 15 is also an eclipsing binary. We find an orbital inclination of ~ 80 deg. From a simultaneous light-curve and radial velocity solution we find the masses and radii of the two components to be 30 +/- 1 and 16 +/- 1 solar masses and 7.5 +/- 0.5 and 5.3 +/- 0.5 solar radii. These radii, and hence also the luminosities, are smaller than those of normal O-type stars, but similar to recently born ZAMS O-type stars. The absolute magnitudes derived from our analysis locate FO 15 at the same distance as Eta Carinae. From Chandra and XMM X-ray images we also find that there are two close X-ray sources, one coincident with FO 15 and another one without optical counterpart. This latter seems to be a highly variable source, presumably due to a pre-main-sequence stellar neighbour of FO 15.Comment: 11 pages, 9 figures, 3 tables. Accepted for publication in MNRAS. Higher resolution version available at http://lilen.fcaglp.unlp.edu.ar/papers2006.htm

Orbital dynamics of "smart dust" devices with solar radiation pressure and drag

This paper investigates how perturbations due to asymmetric solar radiation pressure, in the presence of Earth shadow, and atmospheric drag can be balanced to obtain long-lived Earth centred orbits for swarms of micro-scale 'smart dust' devices, without the use of active control. The secular variation of Keplerian elements is expressed analytically through an averaging technique. Families of solutions are then identified where Sun-synchronous apse-line precession is achieved passively to maintain asymmetric solar radiation pressure. The long-term orbit evolution is characterized by librational motion, progressively decaying due to the non-conservative effect of atmospheric drag. Long-lived orbits can then be designed through the interaction of energy gain from asymmetric solar radiation pressure and energy dissipation due to drag. In this way, the usual short drag lifetime of such high area-to-mass spacecraft can be greatly extended (and indeed selected). In addition, the effect of atmospheric drag can be exploited to ensure the rapid end-of-life decay of such devices, thus preventing long-lived orbit debris

Shimura varieties in the Torelli locus via Galois coverings of elliptic curves

We study Shimura subvarieties of $\mathsf{A}_g$ obtained from families of Galois coverings $f: C \rightarrow C'$ where $C'$ is a smooth complex projective curve of genus $g' \geq 1$ and $g= g(C)$. We give the complete list of all such families that satisfy a simple sufficient condition that ensures that the closure of the image of the family via the Torelli map yields a Shimura subvariety of $\mathsf{A}_g$ for $g' =1,2$ and for all $g \geq 2,4$ and for $g' > 2$ and $g \leq 9$. In a previous work of the first and second author together with A. Ghigi [FGP] similar computations were done in the case $g'=0$. Here we find 6 families of Galois coverings, all with $g' = 1$ and $g=2,3,4$ and we show that these are the only families with $g'=1$ satisfying this sufficient condition. We show that among these examples two families yield new Shimura subvarieties of $\mathsf{A}_g$, while the other examples arise from certain Shimura subvarieties of $\mathsf{A}_g$ already obtained as families of Galois coverings of $\mathbb{P}^1$ in [FGP]. Finally we prove that if a family satisfies this sufficient condition with $g'\geq 1$, then $g \leq 6g'+1$.Comment: 18 pages, to appear in Geometriae Dedicat

Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks

The PC algorithm is a popular method for learning the structure of Gaussian Bayesian networks. It carries out statistical tests to determine absent edges in the network. It is hence governed by two parameters: (i) The type of test, and (ii) its significance level. These parameters are usually set to values recommended by an expert. Nevertheless, such an approach can suffer from human bias, leading to suboptimal reconstruction results. In this paper we consider a more principled approach for choosing these parameters in an automatic way. For this we optimize a reconstruction score evaluated on a set of different Gaussian Bayesian networks. This objective is expensive to evaluate and lacks a closed-form expression, which means that Bayesian optimization (BO) is a natural choice. BO methods use a model to guide the search and are hence able to exploit smoothness properties of the objective surface. We show that the parameters found by a BO method outperform those found by a random search strategy and the expert recommendation. Importantly, we have found that an often overlooked statistical test provides the best over-all reconstruction results

Sensitivity Analysis and Quantification of the Role of Governing Transport Mechanisms and Parameters in a Gas Flow Model for Low-Permeability Porous Media

Recent models represent gas (methane) migration in low-permeability media as a weighted sum of various contributions, each associated with a given flow regime. These models typically embed numerous chemical/physical parameters that cannot be easily and unambiguously evaluated via experimental investigations. In this context, modern sensitivity analysis techniques enable us to diagnose the behavior of a given model through the quantification of the importance and role of model input uncertainties with respect to a target model output. Here, we rely on two global sensitivity analysis approaches and metrics (i.e., variance-based Sobol’ indices and moment-based AMA indices) to assess the behavior of a recent interpretive model that conceptualizes gas migration as the sum of a surface diffusion mechanism and two weighted bulk flow components. We quantitatively investigate the impact of (i) each uncertain model parameter and (ii) the type of their associated probability distribution on the evaluation of methane flow. We then derive the structure of an effective diffusion coefficient embedding all complex mechanisms of the model considered and allowing quantification of the relative contribution of each flow mechanism to the overall gas flow

Optimized Large-Scale CMB Likelihood And Quadratic Maximum Likelihood Power Spectrum Estimation

We revisit the problem of exact CMB likelihood and power spectrum estimation with the goal of minimizing computational cost through linear compression. This idea was originally proposed for CMB purposes by Tegmark et al.\ (1997), and here we develop it into a fully working computational framework for large-scale polarization analysis, adopting \WMAP\ as a worked example. We compare five different linear bases (pixel space, harmonic space, noise covariance eigenvectors, signal-to-noise covariance eigenvectors and signal-plus-noise covariance eigenvectors) in terms of compression efficiency, and find that the computationally most efficient basis is the signal-to-noise eigenvector basis, which is closely related to the Karhunen-Loeve and Principal Component transforms, in agreement with previous suggestions. For this basis, the information in 6836 unmasked \WMAP\ sky map pixels can be compressed into a smaller set of 3102 modes, with a maximum error increase of any single multipole of 3.8\% at $\ell\le32$, and a maximum shift in the mean values of a joint distribution of an amplitude--tilt model of 0.006$\sigma$. This compression reduces the computational cost of a single likelihood evaluation by a factor of 5, from 38 to 7.5 CPU seconds, and it also results in a more robust likelihood by implicitly regularizing nearly degenerate modes. Finally, we use the same compression framework to formulate a numerically stable and computationally efficient variation of the Quadratic Maximum Likelihood implementation that requires less than 3 GB of memory and 2 CPU minutes per iteration for $\ell \le 32$, rendering low-$\ell$ QML CMB power spectrum analysis fully tractable on a standard laptop.Comment: 13 pages, 13 figures, accepted by ApJ