Optimal quantum reservoir computing for the noisy intermediate-scale quantum era

Universal fault-tolerant quantum computers require millions of qubits with low error rates. Since this technology is years ahead, noisy intermediate-scale quantum (NISQ) computation is receiving tremendous interest. In this setup, quantum reservoir computing is a relevant machine learning algorithm. Its simplicity of training and implementation allows to perform challenging computations on today's available machines. In this Letter, we provide a criterion to select optimal quantum reservoirs, requiring few and simple gates. Our findings demonstrate that they render better results than other commonly used models with significantly less gates and also provide insight on the theoretical gap between quantum reservoir computing and the theory of quantum states' complexit

Advanced Multiphysics Modeling of Solar Tower Receivers Using Object-oriented Software and High Performance Computing Platforms

AbstractThis paper presents an advanced methodology for the detailed modeling of the heat transfer and fluid dynamics phenomena in solar tower receivers. It has been carried out in the framework of a more ambitious enterprise which aims at modeling all the complex heat transfer and fluid dynamics phenomena present in central solar receivers. The global model is composed of 4 sub-models (heat conduction, two-phase flow, solar and thermal radiation and natural convection) which are described. Results of the numerical model obtained so far are also presented and discusse

Membrane Computing as a Modelling Tool: Looking Back and Forward from Sevilla

This paper is a tribute to Prof. Mario de Jesús Pérez- Jiménez. An overview of modelling applications in membrane computing has been compiled, trying to narrate it from a historical perspective and including numerous bibliographical references. Since being exhaustive was obviously out of scope, this quick tour on almost two decades of applications is biased, paying special attention to the contributions in which Prof. Pérez-Jiménez and members of his research group were involved.Ministerio de Economía y Competitividad TIN2017-89842-

Voluntary suppression of associated activity decreases force steadiness in the active hand

Unilateral muscle contractions are often accompanied by the activation of the ipsilateral hemisphere, producing associated activity (AA) in the contralateral homologous muscles. However, the functional role of AA is not fully understood. We determined the effects of voluntary suppression of AA in the first dorsal interosseous (FDI), on force steadiness during a constant force isometric contraction of the contralateral FDI. Participants (n = 17, 25.5 years) performed two trials of isometric FDI contractions as steadily as possible. In Trial 1, they did not receive feedback or explicit instructions for suppressing the AA in the contralateral homologous FDI. In Trial 2, participants received feedback and were asked to voluntarily suppress the AA in the contralateral nontarget FDI. During both trials, corticospinal excitability and motor cortical inhibition were measured. The results show that participants effectively suppressed the AA in the nontarget contralateral FDI (-71%), which correlated with reductions in corticospinal excitability (-57%), and the suppression was also accompanied by increases in inhibition (27%) in the ipsilateral motor cortex. The suppression of AA impaired force steadiness, but the decrease in force steadiness did not correlate with the magnitude of suppression. The results show that voluntary suppression of AA decreases force steadiness in the active hand. However, due to the lack of association between suppression and decreased steadiness, we interpret these data to mean that specific elements of the ipsilateral brain activation producing AA in younger adults are neither contributing nor detrimental to unilateral motor control during a steady isometric contraction

3DHIP-Calculator A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models

The assessment of the deep geothermal potential is an essential task during the early phases of any geothermal project. The well-known 'Heat-In-Place' volumetric method is the most widely used technique to estimate the available stored heat and the recoverable heat fraction of deep geothermal reservoirs at the regional scale. Different commercial and open-source software packages have been used to date to estimate these parameters. However, these tools are either not freely available, can only consider the entire reservoir volume or a specific part as a single-voxel model, or are restricted to certain geographical areas. The 3DHIP-Calculator tool presented in this contribution is an open-source software designed for the assessment of the deep geothermal potential at the regional scale using the volumetric method based on a stochastic approach. The tool estimates the Heat-In-Place and recoverable thermal energy using 3D geological and 3D thermal voxel models as input data. The 3DHIP-Calculator includes an easy-to-use graphical user interface (GUI) for visualizing and exporting the results to files for further postprocessing, including GIS-based map generation. The use and functionalities of the 3DHIP-Calculator are demonstrated through a case study of the Reus-Valls sedimentary basin (NE, Spain)

Unexpected residual habitats raise hope for the survival of the fan mussel Pinna nobilis along the Occitan coast (Northwest Mediterranean Sea)

In 2019, the status of the Mediterranean fan mussel Pinna nobilis was elevated to ‘Critically Endangered’ on the IUCN Red List, in response to the pandemic caused by the parasite Haplosporidium pinnae. Identifying refuge habitats, free from parasites, is critical to the survival of the mussel. The distribution of P. nobilis was investigated along the Occitan coast (Northwest Mediterranean Sea) because of the presence of a unique lagoonal system that may provide potential refuges. Interviews with users and managers were conducted to identify target zones where the species was sighted. In situ surveys were carried out to define the main aggregations of fan mussels and characterize the habitat. Line transects were deployed to count and measure individuals to estimate density, abundance, and size distribution. Population densities were variable, ranging from 0.6 ± 0.2 (SE) to 70.8 ± 7.6 ind. 100 m−2, representing one of the highest densities re - ported in the Mediterranean Sea. The total abundance of individuals across the coast was extra - polated to 163 000, with 87% located in Thau and Salses-Leucate, highlighting these lagoons as essential for the survival of the species. This study also revealed the diversity of habitats colonized by P. nobilis. In the context of the pandemic, only the lagoon populations remain unaffected and provide natural refuges that have disappeared from all open-water coastal areas. However, the conditions in these lagoons could become unfavorable, leading to the collapse of the last P. nobilis populations. We therefore propose that Thau and Salses-Leucate lagoons, which harbor the largest remaining populations of P. nobilis, should be declared as conservation priorities.En prens

An introduction to schoenberg's approximation

AbstractFor a given function B and a non-zero real number h, Schoenberg's approximation defines from some data (jh, yj)jϵZd the function ΣjϵZd yj B(•h − j). For people not used to this kind of approximation, this paper intends to do a summary of the main definitions, properties and utilizations of Schoenberg's approximation: we show that the main tool to handle Schoenberg's approximation is the Fourier transform of B and even more its modified version, the transfer function of B; we give conditions for convergence of ΣjϵZd f(jh) B(•h − j) when h tends to zero, and we give various ways to define various B as combinations of translates of some function ϕ (usually ϕ is either some radial function, or obtained by a tensor product of some radial function), depending on the properties we want for the associated Schoenberg's approximation. Last, we show how multi-resolution analysis, subdivision techniques, and wavelets techniques, are nicely connected to Schoenberg's approximation