886 research outputs found
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
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