Dark-matter dynamical friction versus gravitational-wave emission in the evolution of compact-star binaries

The measured orbital period decay of compact-star binaries, with characteristic orbital periods $\sim 0.1$~days, is explained with very high precision by the gravitational wave (GW) emission of an inspiraling binary in vacuum. However, the binary gravitational binding energy is also affected by an usually neglected phenomenon, namely the dark matter dynamical friction (DMDF) produced by the interaction of the binary components with their respective DM gravitational wakes. The entity of this effect depends on the orbital period and on the local value of the DM density, hence on the position of the binary in the Galaxy. We evaluate the DMDF produced by three different DM profiles: the Navarro-Frenk-White (NFW), the non-singular-isothermal-sphere (NSIS) and the Ruffini-Arg\"uelles-Rueda (RAR) profile based on self-gravitating keV fermions. We first show that indeed, due to their Galactic position, the GW emission dominates over the DMDF in the NS-NS, NS-WD and WD-WD binaries for which measurements of the orbital decay exist. Then, we evaluate the conditions under which the effect of DMDF on the binary evolution becomes comparable to, or overcomes, the one of the GW emission. We find that, for instance for $1.3$--$0.2$ $M_\odot$ NS-WD, $1.3$--$1.3$~$M_\odot$ NS-NS, and $0.25$--$0.50$~$M_\odot$ WD-WD, located at 0.1~kpc, this occurs at orbital periods around 20--30 days in a NFW profile while, in a RAR profile, it occurs at about 100 days. For closer distances to the Galactic center, the DMDF effect increases and the above critical orbital periods become interestingly shorter. Finally, we also analyze the system parameters for which DMDF leads to an orbital widening instead of orbital decay. All the above imply that a direct/indirect observational verification of this effect in compact-star binaries might put strong constraints on the nature of DM and its Galactic distribution.Comment: 15 pages, 12 figures, 2 tables, accepted for publication in Phys. Rev. D, 201

Deep Semantic Classification for 3D LiDAR Data

Robots are expected to operate autonomously in dynamic environments. Understanding the underlying dynamic characteristics of objects is a key enabler for achieving this goal. In this paper, we propose a method for pointwise semantic classification of 3D LiDAR data into three classes: non-movable, movable and dynamic. We concentrate on understanding these specific semantics because they characterize important information required for an autonomous system. Non-movable points in the scene belong to unchanging segments of the environment, whereas the remaining classes corresponds to the changing parts of the scene. The difference between the movable and dynamic class is their motion state. The dynamic points can be perceived as moving, whereas movable objects can move, but are perceived as static. To learn the distinction between movable and non-movable points in the environment, we introduce an approach based on deep neural network and for detecting the dynamic points, we estimate pointwise motion. We propose a Bayes filter framework for combining the learned semantic cues with the motion cues to infer the required semantic classification. In extensive experiments, we compare our approach with other methods on a standard benchmark dataset and report competitive results in comparison to the existing state-of-the-art. Furthermore, we show an improvement in the classification of points by combining the semantic cues retrieved from the neural network with the motion cues.Comment: 8 pages to be published in IROS 201

Statistical Behavior Of Domain Systems

We study the statistical behavior of two out of equilibrium systems. The first one is a quasi one-dimensional gas with two species of particles under the action of an external field which drives each species in opposite directions. The second one is a one-dimensional spin system with nearest neighbor interactions also under the influence of an external driving force. Both systems show a dynamical scaling with domain formation. The statistical behavior of these domains is compared with models based on the coalescing random walk and the interacting random walk. We find that the scaling domain size distribution of the gas and the spin systems is well fitted by the Wigner surmise, which lead us to explore a possible connection between these systems and the circular orthogonal ensemble of random matrices. However, the study of the correlation function of the domain edges, show that the statistical behavior of the domains in both gas and spin systems, is not completely well described by circular orthogonal ensemble, nor it is by other models proposed such as the coalescing random walk and the interacting random walk. Nevertheless, we find that a simple model of independent intervals describe more closely the statistical behavior of the domains formed in these systems.Comment: v2: minor change

Certification aspects of airplanes which may operate with significant natural laminar flow

Recent research by NASA indicates that extensive natural laminar flow (NLF) is attainable on modern high performance airplanes currently under development. Modern airframe construction methods and materials, such as milled aluminum skins, bonded aluminum skins, and composite materials, offer the potential for production of aerodynamic surfaces having waviness and roughness below the values which are critical for boundary layer transition. Areas of concern with the certification aspects of Natural Laminar Flow (NLF) are identified to stimulate thought and discussion of the possible problems. During its development, consideration has been given to the recent research information available on several small business and experimental airplanes and the certification and operating rules for general aviation airplanes. The certification considerations discussed are generally applicable to both large and small airplanes. However, from the information available at this time, researchers expect more extensive NLF on small airplanes because of their lower operating Reynolds numbers and cleaner leading edges (due to lack of leading-edge high lift devices). Further, the use of composite materials for aerodynamic surfaces, which will permit incorporation of NLF technology, is currently beginning to appear in small airplanes

Dependence of the electronic structure of self-assembled InGaAs/GaAs quantum dots on height and composition

While electronic and spectroscopic properties of self-assembled In_{1-x}Ga_{x}As/GaAs dots depend on their shape, height and alloy compositions, these characteristics are often not known accurately from experiment. This creates a difficulty in comparing measured electronic and spectroscopic properties with calculated ones. Since simplified theoretical models (effective mass, k.p, parabolic models) do not fully convey the effects of shape, size and composition on the electronic and spectroscopic properties, we offer to bridge the gap by providing accurately calculated results as a function of the dot height and composition. Prominent results are the following. (i) Regardless of height and composition, the electron levels form shells of nearly degenerate states. In contrast, the hole levels form shells only in flat dots and near the highest hole level (HOMO). (ii) In alloy dots, the electrons' ``s-p'' splitting depends weakly on height, while the ``p-p'' splitting depends non-monotonically. In non-alloyed InAs/GaAs dots, both these splittings depend weakly on height. For holes in alloy dots, the ``s-p'' splitting decreases with increasing height, whereas the ``p-p'' splitting remains nearly unchaged. Shallow, non-alloyed dots have a ``s-p'' splitting of nearly the same magnitude, whereas the ``p-p'' splitting is larger. (iii) As height increases, the ``s'' and ``p'' character of the wavefunction of the HOMO becomes mixed, and so does the heavy- and light-hole character. (iv) In alloy dots, low-lying hole states are localized inside the dot. Remarkably, in non-alloyed InAs/GaAs dots these states become localized at the interface as height increases. This localization is driven by the biaxial strain present in the nanostructure.Comment: 14 pages, 12 figure

Arrow's theorem for weak orders

We characterize binary decision rules which are independent and strongly paretian,or independent and almost strongly paretian when the individual preferences and the collective preference are weak orders.Binary decision rule, lexicographic dictatorship