Evolution of shocks and turbulence in major cluster mergers

We performed a set of cosmological simulations of major mergers in galaxy clusters to study the evolution of merger shocks and the subsequent injection of turbulence in the post-shock region and in the intra-cluster medium (ICM). The computations were done with the grid-based, adaptive mesh refinement hydro code Enzo, using an especially designed refinement criteria for refining turbulent flows in the vicinity of shocks. A substantial amount of turbulence energy is injected in the ICM due to major merger. Our simulations show that the shock launched after a major merger develops an ellipsoidal shape and gets broken by the interaction with the filamentary cosmic web around the merging cluster. The size of the post-shock region along the direction of shock propagation is about 300 kpc h^-1, and the turbulent velocity dispersion in this region is larger than 100 km s^-1. Scaling analysis of the turbulence energy with the cluster mass within our cluster sample is consistent with M^(5/3), i.e. the scaling law for the thermal energy in the self-similar cluster model. This clearly indicates the close relation between virialization and injection of turbulence in the cluster evolution. We found that the ratio of the turbulent to total pressure in the cluster core within 2 Gyr after the major merger is larger than 10%, and it takes about 4 Gyr to get relaxed, which is substantially longer than typically assumed in the turbulent re-acceleration models, invoked to explain the statistics of observed radio halos. Striking similarities in the morphology and other physical parameters between our simulations and the "symmetrical radio relics" found at the periphery of the merging cluster A3376 are finally discussed. In particular, the interaction between the merger shock and the filaments surrounding the cluster could explain the presence of "notch-like" features at the edges of the double relics.Comment: 16 pages, 19 figures, Published in Astrophysical Journal (online) and printed version will be published on 1st January, 201

Computational structure‐based drug design: Predicting target flexibility

The role of molecular modeling in drug design has experienced a significant revamp in the last decade. The increase in computational resources and molecular models, along with software developments, is finally introducing a competitive advantage in early phases of drug discovery. Medium and small companies with strong focus on computational chemistry are being created, some of them having introduced important leads in drug design pipelines. An important source for this success is the extraordinary development of faster and more efficient techniques for describing flexibility in three‐dimensional structural molecular modeling. At different levels, from docking techniques to atomistic molecular dynamics, conformational sampling between receptor and drug results in improved predictions, such as screening enrichment, discovery of transient cavities, etc. In this review article we perform an extensive analysis of these modeling techniques, dividing them into high and low throughput, and emphasizing in their application to drug design studies. We finalize the review with a section describing our Monte Carlo method, PELE, recently highlighted as an outstanding advance in an international blind competition and industrial benchmarks.We acknowledge the BSC-CRG-IRB Joint Research Program in Computational Biology. This work was supported by a grant from the Spanish Government CTQ2016-79138-R.J.I. acknowledges support from SVP-2014-068797, awarded by the Spanish Government.Peer ReviewedPostprint (author's final draft

Real-space analysis of branch point motion in architecturally complex polymers

By means of large-scale molecular dynamics simulations, we investigate branch point motion in pure branched polymers and in mixtures of stars and linear chains. We perform a purely geometrical density-based cluster analysis of the branch point trajectories and identify regions of strong localization (traps). Our results demonstrate that the branch point motion can be described as the motion over a network of traps at the time scales corresponding to the reptation regime. Residence times within the traps are broadly distributed, even extending to times much longer than the side-arm relaxation time. The distributions of distances between consecutively visited traps are very similar for all the investigated branched polymers, even though tube dilation is much stronger in the star/linear mixtures than in the pure branched systems. Our analysis suggests that the diffusivity of the branch point introduced by hierarchical models must be understood as a parameter to account for the effective friction associated with the relaxed side arm, more than the description of a hopping process with a precise time scale.We acknowledge support from projects FP7-PEOPLE-2007-1-1-ITN (DYNACOP, EU), MAT2012-31088 (Spain), and IT654-13 (GV, Spain). We acknowledge the programs PRACE, HPC-Europa2 and ESMI (EU), and ICTS (Spain) for generous allocation of CPU time at GENCI (France), HLRS and FZJ-JSC (Germany), and CESGA (Spain).Peer Reviewe

LIDT-DD: A new self-consistent debris disc model including radiation pressure and coupling collisional and dynamical evolution

In most current debris disc models, the dynamical and the collisional evolutions are studied separately, with N-body and statistical codes, respectively, because of stringent computational constraints. We present here LIDT-DD, the first code able to mix both approaches in a fully self-consistent way. Our aim is for it to be generic enough so as to be applied to any astrophysical cases where we expect dynamics and collisions to be deeply interlocked with one another: planets in discs, violent massive breakups, destabilized planetesimal belts, exozodiacal discs, etc. The code takes its basic architecture from the LIDT3D algorithm developed by Charnoz et al.(2012) for protoplanetary discs, but has been strongly modified and updated in order to handle the very constraining specificities of debris discs physics: high-velocity fragmenting collisions, radiation-pressure affected orbits, absence of gas, etc. In LIDT-DD, grains of a given size at a given location in a disc are grouped into "super-particles", whose orbits are evolved with an N-body code and whose mutual collisions are individually tracked and treated using a particle-in-a-box prescription. To cope with the wide range of possible dynamics, tracers are sorted and regrouped into dynamical families depending on their orbits. The code retrieves the classical features known for debris discs, such as the particle size distributions in unperturbed discs, the outer radial density profiles (slope in -1.5) outside narrow collisionally active rings, and the depletion of small grains in "dynamically cold" discs. The potential of the new code is illustrated with the test case of the violent breakup of a massive planetesimal within a debris disc. The main potential future applications of the code are planet/disc interactions, and more generally any configurations where dynamics and collisions are expected to be intricately connected.Comment: Accepted for publication in A&A. 20 pages, 17 figures. Abstract shortened for astro-p

Scalable Analysis, Verification and Design of IC Power Delivery

Due to recent aggressive process scaling into the nanometer regime, power delivery network design faces many challenges that set more stringent and specific requirements to the EDA tools. For example, from the perspective of analysis, simulation efficiency for large grids must be improved and the entire network with off-chip models and nonlinear devices should be able to be analyzed. Gated power delivery networks have multiple on/off operating conditions that need to be fully verified against the design requirements. Good power delivery network designs not only have to save the wiring resources for signal routing, but also need to have the optimal parameters assigned to various system components such as decaps, voltage regulators and converters. This dissertation presents new methodologies to address these challenging problems. At first, a novel parallel partitioning-based approach which provides a flexible network partitioning scheme using locality is proposed for power grid static analysis. In addition, a fast CPU-GPU combined analysis engine that adopts a boundary-relaxation method to encompass several simulation strategies is developed to simulate power delivery networks with off-chip models and active circuits. These two proposed analysis approaches can achieve scalable simulation runtime. Then, for gated power delivery networks, the challenge brought by the large verification space is addressed by developing a strategy that efficiently identifies a number of candidates for the worst-case operating condition. The computation complexity is reduced from O(2^N) to O(N). At last, motivated by a proposed two-level hierarchical optimization, this dissertation presents a novel locality-driven partitioning scheme to facilitate divide-and-conquer-based scalable wire sizing for large power delivery networks. Simultaneous sizing of multiple partitions is allowed which leads to substantial runtime improvement. Moreover, the electric interactions between active regulators/converters and passive networks and their influences on key system design specifications are analyzed comprehensively. With the derived design insights, the system-level co-design of a complete power delivery network is facilitated by an automatic optimization flow. Results show significant performance enhancement brought by the co-design

Nonparametric Transient Classification using Adaptive Wavelets

Classifying transients based on multi band light curves is a challenging but crucial problem in the era of GAIA and LSST since the sheer volume of transients will make spectroscopic classification unfeasible. Here we present a nonparametric classifier that uses the transient's light curve measurements to predict its class given training data. It implements two novel components: the first is the use of the BAGIDIS wavelet methodology - a characterization of functional data using hierarchical wavelet coefficients. The second novelty is the introduction of a ranked probability classifier on the wavelet coefficients that handles both the heteroscedasticity of the data in addition to the potential non-representativity of the training set. The ranked classifier is simple and quick to implement while a major advantage of the BAGIDIS wavelets is that they are translation invariant, hence they do not need the light curves to be aligned to extract features. Further, BAGIDIS is nonparametric so it can be used for blind searches for new objects. We demonstrate the effectiveness of our ranked wavelet classifier against the well-tested Supernova Photometric Classification Challenge dataset in which the challenge is to correctly classify light curves as Type Ia or non-Ia supernovae. We train our ranked probability classifier on the spectroscopically-confirmed subsample (which is not representative) and show that it gives good results for all supernova with observed light curve timespans greater than 100 days (roughly 55% of the dataset). For such data, we obtain a Ia efficiency of 80.5% and a purity of 82.4% yielding a highly competitive score of 0.49 whilst implementing a truly "model-blind" approach to supernova classification. Consequently this approach may be particularly suitable for the classification of astronomical transients in the era of large synoptic sky surveys.Comment: 14 pages, 8 figures. Published in MNRA

Mass transfer in eccentric binaries: the new Oil-on-Water SPH technique

To measure the onset of mass transfer in eccentric binaries we have developed a two-phase SPH technique. Mass transfer is important in the evolution of close binaries, and a key issue is to determine the separation at which mass transfer begins. The circular case is well understood and can be treated through the use of the Roche formalism. To treat the eccentric case we use a newly-developed two phase system. The body of the donor star is made up from high-mass "water" particles, whilst the atmosphere is modelled with low-mass "oil" particles. Both sets of particles take part fully in SPH interactions. To test the technique we model circular mass-transfer binaries containing a 0.6 Msun donor star and a 1 Msun white dwarf; such binaries are thought to form cataclysmic variable (CV) systems. We find that we can reproduce a reasonable CV mass-transfer rate, and that our extended atmosphere gives a separation that is too large by aproximately 16%, although its pressure scale height is considerably exaggerated. We use the technique to measure the semi-major axis required for the onset of mass transfer in binaries with a mass ratio of q=0.6 and a range of eccentricities. Comparing to the value obtained by considering the instantaneous Roche lobe at pericentre we find that the radius of the star required for mass transfer to begin decreases systematically with increasing eccentricity.Comment: 9 pages, 8 figures, accepted by MNRA