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Monte Carlo simulations for the Pierre Auger Observatory using the VO auger grid resources
E. Santos, Andrej Filipčič, Jon Paul Lundquist, Samo Stanič, Serguei Vorobiov, Danilo Zavrtanik, Marko Zavrtanik, Lukas Zehrer, 2022, published scientific conference contribution

Abstract: The Pierre Auger Observatory, located near Malargüe, Argentina, is the world’s largest cosmic-ray detector. It comprises a 3000 km^2 surface detector and 27 fluorescence telescopes, which measure the lateral and longitudinal distributions of the many millions of air-shower particles produced in the interactions initiated by a cosmic ray in the Earth’s atmosphere. The determination of the nature of cosmic rays and studies of the detector performances rely on extensive Monte Carlo simulations describing the physics processes occurring in extensive air showers and the detector responses. The aim of the Monte Carlo simulations task is to produce and provide the Auger Collaboration with reference libraries used in a wide variety of analyses. All multipurpose detector simulations are currently produced in local clusters using Slurm and HTCondor. The bulk of the shower simulations are produced on the grid, via the Virtual Organization auger, using the DIRAC middleware. The job submission is made via python scripts using the DIRAC-API. The Auger site is undergoing a major upgrade, which includes the installation of new types of detectors, demanding increased simulation resources. The novel detection of the radio component of extensive air showers is the most challenging endeavor, requiring dedicated shower simulations with very long computation times, not optimized for the grid production. For data redundancy, the simulations are stored on the Lyon server and the grid Disk Pool Manager and are accessible to the Auger members via iRODS and DIRAC, respectively. The CERN VMFile System is used for software distribution where, soon, the Auger Offline software will also be made available.
Keywords: Pierre Auger Observatory, indirect detection, fluorescence detection, surface detection, radio detection, ultra-high energy, cosmic rays, Monte Carlo simulation, computing resources, compute clusters, high capacity storage
Published in RUNG: 04.10.2023; Views: 502; Downloads: 7
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Polymer Vesicles with a Colloidal Armor of Nanoparticles
Rong Chen, Daniel J. G. Pearce, Sara Fortuna, David L. Cheung, Stefan A. F. Bon, 2011, original scientific article

Abstract: The fabrication of polymer vesicles with a colloidal armor made from a variety of nanoparticles is demonstrated. In addition, it is shown that the armored supracolloidal structure can be postmodified through film-formation of soft polymer latex particles on the surface of the polymersome, hereby effectively wrapping the polymersome in a plastic bag, as well as through formation of a hydrogel by disintegrating an assembled polymer latex made from poly(ethyl acrylate-co-methacrylic acid) upon increasing the pH. Furthermore, ordering and packing patterns are briefly addressed with the aid of Monte Carlo simulations, including patterns observed when polymersomes are exposed to a binary mixture of colloids of different size.
Keywords: Pickering emultion, self-assemblt, Monte Carlo, simulation, nanoparticle, packing, pattern garnd canonical, colloids
Published in RUNG: 11.10.2016; Views: 4641; Downloads: 0
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Agent based modelling for the 2D molecular self-organization of realistic molecules
Sara Fortuna, Alessandro Troisi, 2010, original scientific article

Abstract: We extend our previously developed agent-based (AB) algorithm to the study of the self-assembly of a fully atomistic model of experimental interest. We study the 2D self-assembly of a rigid organic molecule (1,4-benzene-dicarboxylic acid or TPA), comparing the AB results with Monte Carlo (MC) and MC simulated annealing, a technique traditionally used to solve the global minimization problem. The AB algorithm gives a lower energy configuration in the same simulation time than both of the MC simulation techniques. We also show how the AB algorithm can be used as a part of the protocol to calculate the phase diagram with less computational effort than standard techniques.
Keywords: self-assembly, self-organisation, 1, 4-benzene-dicarboxylic acid, TPA, agent based, Monte Carlo, simulation, phase diagram
Published in RUNG: 11.10.2016; Views: 4700; Downloads: 0
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Hexagonal lattice model of the patterns formed by hydrogen-bonded molecules on the surface
Sara Fortuna, David L. Cheung, Alessandro Troisi, 2010, original scientific article

Abstract: We model the two-dimensional self-assembly of planar molecules capable of complementary interactions (like hydrogen bonding) as a set of hexagonal tiles on a hexagonal lattice. We use Monte Carlo simulations to study the phase diagrams of three model systems. The phases are characterized using a variety of order parameters, and they are studied as a function of the strength of the complementary interaction energy. This simplified model is proven to be capable of reproducing the phases encountered in real systems, unifying within the same framework most of the structures encountered experimentally.
Keywords: self-assembly, self-organisation, Monte Carlo, simulation, lattice model, dicarboxilic acid, hexagonal lattice
Published in RUNG: 10.10.2016; Views: 4681; Downloads: 0
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An artificial intelligence approach for modeling molecular self-assembly: Agent Based simulations of rigid molecules
Sara Fortuna, Alessandro Troisi, 2009, original scientific article

Abstract: Agent-based simulations are rule-based models traditionally used for the simulations of complex systems. In this paper, an algorithm based on the concept of agent-based simulations is developed to predict the lowest energy packing of a set of identical rigid molecules. The agents are identified with rigid portions of the system under investigation, and they evolve following a set of rules designed to drive the system toward the lowest energy minimum. The algorithm is compared with a conventional Metropolis Monte Carlo algorithm, and it is applied on a large set of representative models of molecules. For all the systems studied, the agent-based method consistently finds a significantly lower energy minima than the Monte Carlo algorithm because the system evolution includes elements of adaptation (new configurations induce new types of moves) and learning (past successful choices are repeated).
Keywords: Self-assembly, self-organisation, agent based, Monte Carlo, rigid molecules, simulation
Published in RUNG: 10.10.2016; Views: 4680; Downloads: 0
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Packing patterns of silica nanoparticles on surfaces of armored polystyrene latex particles
Sara Fortuna, Catheline A. L. Colard, Stefan A. F. Bon, Alessandro Troisi, 2009, original scientific article

Abstract: Fascinating packing patterns of identical spherical and discotic objects on curved surfaces occur readily in nature and science. Examples include C60 fullerenes,(1, 2)13-atom cuboctahedral metal clusters,(3) and S-layer proteins on outer cell membranes.(4) Numerous situations with surface-arranged objects of variable size also exist, such as the lenses on insect eyes, biomineralized shells on coccolithophorids,(5) and solid-stabilized emulsion droplets(6) and bubbles.(7) The influence of size variations on these packing patterns, however, is studied sparsely. Here we investigate the packing of nanosized silica particles on the surface of polystyrene latex particles fabricated by Pickering miniemulsion polymerization of submicrometer-sized armored monomer droplets. We are able to rationalize the experimental morphology and the nearest-neighbor distribution with the help of Monte Carlo simulations. We show that broadening of the nanoparticle size distribution has pronounced effects on the self-assembled equilibrium packing structures, with original 12-point dislocations or grain-boundary scars gradually fading out.
Keywords: packing patterns, silica, simulation, Monte Carlo, order, disorder, transition, armored particles, nanoparticles, Pickering emulsion
Published in RUNG: 10.10.2016; Views: 4517; Downloads: 0
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