Terrestrial Planet Formation I. The Transition from Oligarchic Growth to Chaotic Growth

We use a hybrid, multiannulus, n-body-coagulation code to investigate the growth of km-sized planetesimals at 0.4-2 AU around a solar-type star. After a short runaway growth phase, protoplanets with masses of roughly 10^26 g and larger form throughout the grid. When (i) the mass in these `oligarchs' is roughly comparable to the mass in planetesimals and (ii) the surface density in oligarchs exceeds 2-3 g/sq cm at 1 AU, strong dynamical interactions among oligarchs produce a high merger rate which leads to the formation of several terrestrial planets. In disks with lower surface density, milder interactions produce several lower mass planets. In all disks, the planet formation timescale is roughly 10-100 Myr, similar to estimates derived from the cratering record and radiometric data.Comment: Astronomical Journal, accepted; 22 pages + 15 figures in ps format; eps figures at http://cfa-www.harvard.edu/~kenyon/dl/ revised version clarifies evolution and justifies choice of promotion masse

Quantum data hiding in the presence of noise

When classical or quantum information is broadcast to separate receivers, there exist codes that encrypt the encoded data such that the receivers cannot recover it when performing local operations and classical communication, but they can decode reliably if they bring their systems together and perform a collective measurement. This phenomenon is known as quantum data hiding and hitherto has been studied under the assumption that noise does not affect the encoded systems. With the aim of applying the quantum data hiding effect in practical scenarios, here we define the data-hiding capacity for hiding classical information using a quantum channel. Using this notion, we establish a regularized upper bound on the data hiding capacity of any quantum broadcast channel, and we prove that coherent-state encodings have a strong limitation on their data hiding rates. We then prove a lower bound on the data hiding capacity of channels that map the maximally mixed state to the maximally mixed state (we call these channels "mictodiactic"---they can be seen as a generalization of unital channels when the input and output spaces are not necessarily isomorphic) and argue how to extend this bound to generic channels and to more than two receivers.Comment: 12 pages, accepted for publication in IEEE Transactions on Information Theor

Fractional-order susceptible-infected model: definition and applications to the study of COVID-19 main protease

We propose a model for the transmission of perturbations across the amino acids of a protein represented as an interaction network. The dynamics consists of a Susceptible-Infected (SI) model based on the Caputo fractional-order derivative. We find an upper bound to the analytical solution of this model which represents the worse-case scenario on the propagation of perturbations across a protein residue network. This upper bound is expressed in terms of Mittag-Leffler functions of the adjacency matrix of the network of inter-amino acids interactions. We then apply this model to the analysis of the propagation of perturbations produced by inhibitors of the main protease of SARS CoV-2. We find that the perturbations produced by strong inhibitors of the protease are propagated far away from the binding site, confirming the long-range nature of intra-protein communication. On the contrary, the weakest inhibitors only transmit their perturbations across a close environment around the binding site. These findings may help to the design of drug candidates against this new coronavirus.Comment: 21 pages, 2 figure

Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates

Computational drug design based on artificial intelligence is an emerging research area. At the time of writing this paper, the world suffers from an outbreak of the coronavirus SARS-CoV-2. A promising way to stop the virus replication is via protease inhibition. We propose an evolutionary multi-objective algorithm (EMOA) to design potential protease inhibitors for SARS-CoV-2's main protease. Based on the SELFIES representation the EMOA maximizes the binding of candidate ligands to the protein using the docking tool QuickVina 2, while at the same time taking into account further objectives like drug-likeliness or the fulfillment of filter constraints. The experimental part analyzes the evolutionary process and discusses the inhibitor candidates.Comment: 15 pages, 7 figures, submitted to PPSN 202

Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy

Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities. The task involves taking a user query as input and returning a list of people sorted by their level of expertise regarding the user query. This paper introduces a novel approach for combining multiple estimators of expertise based on a multisensor data fusion framework together with the Dempster-Shafer theory of evidence and Shannon's entropy. More specifically, we defined three sensors which detect heterogeneous information derived from the textual contents, from the graph structure of the citation patterns for the community of experts, and from profile information about the academic experts. Given the evidences collected, each sensor may define different candidates as experts and consequently do not agree in a final ranking decision. To deal with these conflicts, we applied the Dempster-Shafer theory of evidence combined with Shannon's Entropy formula to fuse this information and come up with a more accurate and reliable final ranking list. Experiments made over two datasets of academic publications from the Computer Science domain attest for the adequacy of the proposed approach over the traditional state of the art approaches. We also made experiments against representative supervised state of the art algorithms. Results revealed that the proposed method achieved a similar performance when compared to these supervised techniques, confirming the capabilities of the proposed framework

Development and selection of operational management strategies to achieve policy objectives

Since the reform of the EU Common Fisheries Policy in 2002, effort has been devoted to addressing the governance, scientific, social and economic issues required to introduce an ecosystem approach to fisheries management (EAFM) in Europe. Fisheries management needs to support the three pillars of sustainability (ecological, social and economic) and Fisheries Ecosystem Plans (FEPs) have been developed as a tool to assist managers considering the ecological, social and economic implications of their decision. Building upon previous studies (e.g. the FP5-funded European Fisheries Ecosystem Plan project), the core concept of the Making the European Fisheries Ecosystem Plan Operational (MEFEPO) project is to deliver operational frameworks (FEPs) for three regional seas. The project focus is on how best to make current institutional frameworks responsive to an EAFM at regional and pan-European levels in accordance with the principles of good governance. The regional seas selected for the project are the North Sea (NS), North Western Waters (NWW) and South Western Waters (SWW) RAC regions. The aim of this work package (WP5) was to develop operational objectives to achieve the ecological objectives identified for the 3 regional seas in WP2. This report describes the development and implementation of a transparent and formal process that should lead to identification of the “best” operational management strategies for an EAFM, based on sound scientific information and stakeholder involvement (e.g. regional industry groups, citizen groups, managers and other interest groups)

The Formation of Pluto's Low Mass Satellites

Motivated by the New Horizons mission, we consider how Pluto's small satellites -- currently Styx, Nix, Kerberos, and Hydra -- grow in debris from the giant impact that forms the Pluto-Charon binary. After the impact, Pluto and Charon accrete some of the debris and eject the rest from the binary orbit. During the ejection, high velocity collisions among debris particles produce a collisional cascade, leading to the ejection of some debris from the system and enabling the remaining debris particles to find stable orbits around the binary. Our numerical simulations of coagulation and migration show that collisional evolution within a ring or a disk of debris leads to a few small satellites orbiting Pluto-Charon. These simulations are the first to demonstrate migration-induced mergers within a particle disk. The final satellite masses correlate with the initial disk mass. More massive disks tend to produce fewer satellites. For the current properties of the satellites, our results strongly favor initial debris masses of 3-10 x 10^{19} g and current satellite albedos of roughly 0.4-1. We also predict an ensemble of smaller satellites with radii less than roughly 1-3 km, and very small particles, with radii of roughly 1-100 cm and optical depth smaller than 10^-10. These objects should have semimajor axes outside the current orbit of Hydra.Comment: 35 pages, 9 figures, revised based on comments from referees and colleagues, AJ, in pres

Connecting planets around horizontal branch stars with known exoplanets

We study the distribution of exoplanets around main sequence (MS) stars and apply our results to the binary model for the formation of extreme horizontal branch (EHB; sdO; sdB; hot subdwarfs) stars. By Binary model we refer both to stellar and substellar companions that enhance the mass loss rate, where substellar companions stand for both massive planets and brown dwarfs. We conclude that sdB (EHB) stars are prime targets for planet searches. We reach this conclusion by noticing that the bimodal distribution of planets around stars with respect to the parameter M_p*a^2, is most prominent for stars in the mass range 1Mo < M < 1.5Mo; 'a' is the orbital separation, 'M' is the stellar mass and 'M_p' the planet mass. This is also the mass range of the progenitors of EHB stars that are formed through the interaction of their progenitors with planets (assuming the EHB formation mechanism is the binary model). In the binary model for the formation of EHB stars interaction with a binary companion or a substellar object (a planet or a brown dwarf), causes the progenitor to lose most of its envelope mass during its red giant branch (RGB) phase. As a result of that the descendant HB star is hot, i.e., an EHB (sdB) star. The bimodal distribution suggests that even if the close-in planet that formed the EHB star did not survive its RGB common envelope evolution, one planet or more might survive at a>1AU. Also, if a planet or more are observed at a>1AU, it is possible that a closer massive planet did survive the common envelope phase, and it is orbiting the EHB with an orbital period of hours to days.Comment: MNRAS, in pres