Pulsed Laser Interactions with Space Debris: Target Shape Effects

Among the approaches to the proposed mitigation and remediation of the space debris problem is the de-orbiting of objects in low Earth orbit through irradiation by ground-based high-intensity pulsed lasers. Laser ablation of a thin surface layer causes target recoil, resulting in the depletion of orbital angular momentum and accelerated atmospheric re-entry. However, both the magnitude and direction of the recoil are shape dependent, a feature of the laser-based remediation concept that has received little attention. Since the development of a predictive capability is desirable, we have investigated the dynamical response to ablation of objects comprising a variety of shapes. We derive and demonstrate a simple analytical technique for calculating the ablation-driven transfer of linear momentum, emphasizing cases for which the recoil is not exclusively parallel to the incident beam. For the purposes of comparison and contrast, we examine one case of momentum transfer in the low-intensity regime, where photon pressure is the dominant momentum transfer mechanism, showing that shape and orientation effects influence the target response in a similar, but not identical, manner. We address the related problem of target spin and, by way of a few simple examples, show how ablation can alter the spin state of a target, which often has a pronounced effect on the recoil dynamics.Comment: 51 pages, 14 figures, to appear in Advances in Space Researc

Solving multi-target haptic problems in menu interaction

While haptic feedback has been shown to enhance user performance and satisfaction in single target interactions in desktop user interfaces, it is not clear whether this will hold for more realistic, multi-target interactions. Here we present an experimental study of haptically enhanced menus. We evaluate a visual condition, a haptic condition and an adjusted haptic condition designed to support menu interactions. We conclude that thoughtful design can create multi-target haptic augmentations that provide performance benefits

Acceleration by Strong Interactions

Beyond the attractive strong potential needed for hadronic bound states, strong interactions are predicted to provide repulsive forces depending on the color charges involved. The repulsive interactions could in principle serve for particle acceleration with highest gradients in the order of GeV/fm. Indirect evidence for repulsive interactions have been reported in the context of heavy meson production at colliders. In this contribution, we sketch a thought experiment to directly investigate repulsive strong interactions. For this we prepare two quarks using two simultaneous deep inelastic scattering processes off an iron target. We discuss the principle setup of the experiment and estimate the number of electrons on target required to observe a repulsive effect between the quarks.Comment: 6 pages, 7 figure

Protein Functional Families to characterise drug-target interactions.

The quest for “magic bullets” has been the driving force in drug discovery during the last two decades. However, the increasing rate of drug failure over this period has occurred concurrently with the assumption that a drug is a selective ligand for a single target. It now seems likely that polypharmacology is the rule rather than the exception [1]. Our previous research shows that protein domains are a good proxy for drug targets, and that drug polypharmacology emerges as a consequence of the multi-domain composition of proteins [2]. In this study, we investigate further the idea that the domain is the druggable entity within a protein target. We have identified a specific class of domains (CATH Functional Families) as the best currently available for identifying drug-target interactions. We show how this opens a new direction in target identification with potential application in drug repurposing.1. Hopkins, AL. (2008) Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol; 4: 682 2. Moya-García AA & Ranea JAG (2013) Insights into polypharmacology from drug-domain associations. Bioinformatics 29: 1934–1937)Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Universidad de Granad

Final-state interactions in deep-inelastic scattering from a tensor polarized deuteron target

Deep-inelastic scattering (DIS) from a tensor polarized deuteron is sensitive to possible non-nucleonic components of the deuteron wave function. To accurately estimate the size of the nucleonic contribution, final-state interactions (FSIs) need to be accounted for in calculations. We outline a model that, based on the diffractive nature of the effective hadron-nucleon interaction, uses the generalized eikonal approximation to model the FSIs in the resonance region, taking into account the proton-neutron component of the deuteron. The calculation uses a factorized model with a basis of three resonances with mass $W<2$ GeV as the relevant set of effective hadron states entering the final-state interaction amplitude for inclusive DIS. We present results for the tensor asymmetry observable $A_{zz}$ for kinematics accessible in experiments at Jefferson Lab and Hermes. For inclusive DIS, sizeable effects are found when including FSIs for Bjorken $x>0.2$, but the overall size of $A_{zz}$ remains small. For tagged spectator DIS, FSIs effects are largest at spectator momenta around 300 MeV and for forward spectator angles.Comment: 7 pages, 3 figures, proceedings of the Tensor Polarized Solid Target Workshop March 10-12, 2014 (Jefferson Lab, Newport News, USA

Structure Functions are not Parton Probabilities

The common view that structure functions measured in deep inelastic lepton scattering are determined by the probability of finding quarks and gluons in the target is not correct in gauge theory. We show that gluon exchange between the fast, outgoing partons and target spectators, which is usually assumed to be an irrelevant gauge artifact, affects the leading twist structure functions in a profound way. This observation removes the apparent contradiction between the projectile (eikonal) and target (parton model) views of diffractive and small x_{Bjorken} phenomena. The diffractive scattering of the fast outgoing quarks on spectators in the target causes shadowing in the DIS cross section. Thus the depletion of the nuclear structure functions is not intrinsic to the wave function of the nucleus, but is a coherent effect arising from the destructive interference of diffractive channels induced by final state interactions. This is consistent with the Glauber-Gribov interpretation of shadowing as a rescattering effect.Comment: 35 pages, 8 figures. Discussion of physical consequences of final state interactions amplified. Material on light-cone gauge choices adde

Charged Particle Production in Proton-, Deuteron-, Oxygen- and Sulphur-Nucleus Collisions at 200 GeV per Nucleon

The transverse momentum and rapidity distributions of net protons and negatively charged hadrons have been measured for minimum bias proton-nucleus and deuteron-gold interactions, as well as central oxygen-gold and sulphur-nucleus collisions at 200 GeV per nucleon. The rapidity density of net protons at midrapidity in central nucleus-nucleus collisions increases both with target mass for sulphur projectiles and with the projectile mass for a gold target. The shape of the rapidity distributions of net protons forward of midrapidity for d+Au and central S+Au collisions is similar. The average rapidity loss is larger than 2 units of rapidity for reactions with the gold target. The transverse momentum spectra of net protons for all reactions can be described by a thermal distribution with `temperatures' between 145 +- 11 MeV (p+S interactions) and 244 +- 43 MeV (central S+Au collisions). The multiplicity of negatively charged hadrons increases with the mass of the colliding system. The shape of the transverse momentum spectra of negatively charged hadrons changes from minimum bias p+p and p+S interactions to p+Au and central nucleus-nucleus collisions. The mean transverse momentum is almost constant in the vicinity of midrapidity and shows little variation with the target and projectile masses. The average number of produced negatively charged hadrons per participant baryon increases slightly from p+p, p+A to central S+S,Ag collisions.Comment: 47 pages, submitted to Z. Phys.

Complementarity of dark matter detectors in light of the neutrino background

Direct detection dark matter experiments looking for WIMP-nucleus elastic scattering will soon be sensitive to an irreducible background from neutrinos which will drastically affect their discovery potential. Here we explore how the neutrino background will affect future ton-scale experiments considering both spin-dependent and spin-independent interactions. We show that combining data from experiments using different targets can improve the dark matter discovery potential due to target complementarity. We find that in the context of spin-dependent interactions, combining results from several targets can greatly enhance the subtraction of the neutrino background for WIMP masses below 10 GeV/c$^2$ and therefore probe dark matter models to lower cross-sections. In the context of target complementarity, we also explore how one can tune the relative exposures of different target materials to optimize the WIMP discovery potential.Comment: 13 pages, 12 figures, 3 table

Bilinear Graph Neural Network with Neighbor Interactions

Graph Neural Network (GNN) is a powerful model to learn representations and make predictions on graph data. Existing efforts on GNN have largely defined the graph convolution as a weighted sum of the features of the connected nodes to form the representation of the target node. Nevertheless, the operation of weighted sum assumes the neighbor nodes are independent of each other, and ignores the possible interactions between them. When such interactions exist, such as the co-occurrence of two neighbor nodes is a strong signal of the target node's characteristics, existing GNN models may fail to capture the signal. In this work, we argue the importance of modeling the interactions between neighbor nodes in GNN. We propose a new graph convolution operator, which augments the weighted sum with pairwise interactions of the representations of neighbor nodes. We term this framework as Bilinear Graph Neural Network (BGNN), which improves GNN representation ability with bilinear interactions between neighbor nodes. In particular, we specify two BGNN models named BGCN and BGAT, based on the well-known GCN and GAT, respectively. Empirical results on three public benchmarks of semi-supervised node classification verify the effectiveness of BGNN -- BGCN (BGAT) outperforms GCN (GAT) by 1.6% (1.5%) in classification accuracy.Codes are available at: https://github.com/zhuhm1996/bgnn.Comment: Accepted by IJCAI 2020. SOLE copyright holder is IJCAI (International Joint Conferences on Artificial Intelligence), all rights reserve