Post-Newtonian Dynamics in Dense Star Clusters: Highly-Eccentric, Highly-Spinning, and Repeated Binary Black Hole Mergers

We present models of realistic globular clusters with post-Newtonian dynamics for black holes. By modeling the relativistic accelerations and gravitational-wave emission in isolated binaries and during three- and four-body encounters, we find that nearly half of all binary black hole mergers occur inside the cluster, with about 10% of those mergers entering the LIGO/Virgo band with eccentricities greater than 0.1. In-cluster mergers lead to the birth of a second generation of black holes with larger masses and high spins, which, depending on the black hole natal spins, can sometimes be retained in the cluster and merge again. As a result, globular clusters can produce merging binaries with detectable spins regardless of the birth spins of black holes formed from massive stars. These second-generation black holes would also populate any upper mass gap created by pair-instability supernovae.Comment: 9 pages, 3 figures, 2 appendices. To appear in Physical Review Letter

Introducción

De nou, tenim l'oportunitat de presentar una sèrie d'articles que proposen aproximacions teòriques que reconfiguren o visibilitzen els vincles existents entre elements materials i les seves representacions simbòliques i que afirmen, així, els nexes i les xarxes que componen el nostre món i les nostres pràctiques socials, tecnològiques o artístiques. La multitud d'enfocaments i de temàtiques que articulen aquest segon volum d'«Art Matters» ens condueix a reprendre la crítica als fonaments del racionalisme modern i la seva ingerència, tant en els discursos com en les pràctiques, a través de reflexions metodològiques i anàlisis objectuals.Once again, we have the opportunity to present a series of articles that propose theoretical approaches that reconfigure or enhance the visibility of the links that exist between material elements and their symbolic representations, underlining the nexus and networks that make up our world and our social, technological and artistic practices. The broad range of approaches and topics that comprise this second volume of Art Matters leads us to resume our criticism of the foundations of modern rationalism and its interference both in discourses and practices, through methodological reflections and object analysis.De nuevo, tenemos la oportunidad de presentar una serie de artículos que proponen aproximaciones teóricas que reconfiguran o visibilizan los vínculos existentes entre elementos materiales y sus representaciones simbólicas, afirmando los nexos y las redes que componen nuestro mundo y nuestras prácticas sociales, tecnológicas o artísticas. La multitud de enfoques y temáticas que articulan este segundo volumen de Art Matters nos conducen a retomar la crítica a los fundamentos del racionalismo moderno y su injerencia, tanto en los discursos como en las prácticas, a través de reflexiones metodológicas y análisis objetuales

A Versatile Processing Chain for Experimental TanDEM-X Product Evaluation

TanDEM-X is a high-resolution interferometric mission with the main goal of providing a global digital elevation model (DEM) of the Earth surface by means of single-pass X-band SAR interferometry. It is, moreover, the first genuinely bistatic spaceborne SAR mission, and, independently of its usual quasi-monostatic configuration, includes many of the peculiarities of bistatic SAR. An experimental, versatile, and flexible interferometric chain has been developed at DLR Microwaves and Radar Institute for the scientific exploitation of TanDEM-X data acquired in non-standard configurations. The paper describes the structure of the processing chain and focusses on some essential aspects of its bistatic part

FigGen: Text to Scientific Figure Generation

The generative modeling landscape has experienced tremendous growth in recent years, particularly in generating natural images and art. Recent techniques have shown impressive potential in creating complex visual compositions while delivering impressive realism and quality. However, state-of-the-art methods have been focusing on the narrow domain of natural images, while other distributions remain unexplored. In this paper, we introduce the problem of text-to-figure generation, that is creating scientific figures of papers from text descriptions. We present FigGen, a diffusion-based approach for text-to-figure as well as the main challenges of the proposed task. Code and models are available at https://github.com/joanrod/figure-diffusionComment: Published at ICLR 2023 as a Tiny Pape

Evaluating directive-based programming models on Wave Propagation Kernels

HPC systems have become mandatory to tackle the ever-increasing challenges imposed by new exploration areas around the world. The requirement for more HPC resources depends on the complexity of the area under exploration, yet the larger the HPC system, the more the energy consumption involved. Reduction of overall power consumption in HPC facilities, lead technologies vendors to introduce many-core devices and heterogeneous computing to the supercomputers, thus, forcing exploration codes to be ported to such new architectures. As the Oil & Gas industry has more than 30 years of legacy code, the effort to adapt it could be huge. To this extent, several programming models emerged, e.g. high-level directive-based programming models, such as OpenMP, OpenACC, and OmpSs rely on specifying to the compiler the parallelism directives to release users from manually decomposing and processing the parallel regions. The results show that it is possible to obtain a parallel code for current heterogeneous HPC architectures investing a few hours or days. The obtained speedup is at least an order of magnitude w.r.t. a sequential code. However, we provide parallelism inside a single computational node, and a wider study for evaluating the costs of porting and parallelizing across computational nodes is pending.Authors thank Repsol for the permission to publish the present research, carried out at the Repsol-BSC Research Center. This work has received funding from the European Union’s Horizon 2020 Programme (2014-2020) and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (www.hpc4e.eu), grant agreement n.◦ 689772.Peer ReviewedPostprint (author's final draft

OC-NMN: Object-centric Compositional Neural Module Network for Generative Visual Analogical Reasoning

A key aspect of human intelligence is the ability to imagine -- composing learned concepts in novel ways -- to make sense of new scenarios. Such capacity is not yet attained for machine learning systems. In this work, in the context of visual reasoning, we show how modularity can be leveraged to derive a compositional data augmentation framework inspired by imagination. Our method, denoted Object-centric Compositional Neural Module Network (OC-NMN), decomposes visual generative reasoning tasks into a series of primitives applied to objects without using a domain-specific language. We show that our modular architectural choices can be used to generate new training tasks that lead to better out-of-distribution generalization. We compare our model to existing and new baselines in proposed visual reasoning benchmark that consists of applying arithmetic operations to MNIST digits

Language Decision Transformers with Exponential Tilt for Interactive Text Environments

Text-based game environments are challenging because agents must deal with long sequences of text, execute compositional actions using text and learn from sparse rewards. We address these challenges by proposing Language Decision Transformers (LDTs), a framework that is based on transformer language models and decision transformers (DTs). Our LDTs extend DTs with 3 components: (1) exponential tilt to guide the agent towards high obtainable goals, (2) novel goal conditioning methods yielding better results than the traditional return-to-go (sum of all future rewards), and (3) a model of future observations that improves agent performance. LDTs are the first to address offline RL with DTs on these challenging games. Our experiments show that LDTs achieve the highest scores among many different types of agents on some of the most challenging Jericho games, such as Enchanter.Comment: 19 pages, 6 figures, 5 table