Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

A Bayesian approach to the modelling of alpha Cen A

Determining the physical characteristics of a star is an inverse problem consisting in estimating the parameters of models for the stellar structure and evolution, knowing certain observable quantities. We use a Bayesian approach to solve this problem for alpha Cen A, which allows us to incorporate prior information on the parameters to be estimated, in order to better constrain the problem. Our strategy is based on the use of a Markov Chain Monte Carlo (MCMC) algorithm to estimate the posterior probability densities of the stellar parameters: mass, age, initial chemical composition,... We use the stellar evolutionary code ASTEC to model the star. To constrain this model both seismic and non-seismic observations were considered. Several different strategies were tested to fit these values, either using two or five free parameters in ASTEC. We are thus able to show evidence that MCMC methods become efficient with respect to more classical grid-based strategies when the number of parameters increases. The results of our MCMC algorithm allow us to derive estimates for the stellar parameters and robust uncertainties thanks to the statistical analysis of the posterior probability densities. We are also able to compute odds for the presence of a convective core in alpha Cen A. When using core-sensitive seismic observational constraints, these can raise above ~40%. The comparison of results to previous studies also indicates that these seismic constraints are of critical importance for our knowledge of the structure of this star.Comment: 21 pages, 6 figures, to be published in MNRA

Kinetic energy fluctuation-driven locomotor transitions on potential energy landscapes of beam obstacle traversal and self-righting

Despite contending with constraints imposed by the environment, morphology, and physiology, animals move well by physically interactingwith the environment to use and transition between modes such as running, climbing, and self-righting. By contrast, robots struggle to do so in real world. Understanding the principles of how locomotor transitions emerge from constrained physical interaction is necessary for robots to move robustly using similar strategies. Recent studies discovered that discoid cockroaches use and transition between diverse locomotor modes to traverse beams and self-right on ground. For both systems, animals probabilistically transitioned between modes via multiple pathways, while its self-propulsion created kinetic energy fluctuation. Here, we seek mechanistic explanations for these observations by adopting a physics-based approach that integrates biological and robotic studies. We discovered that animal and robot locomotor transitions during beam obstacle traversal and ground self-righting are barrier-crossing transitions on potential energy landscapes. Whereas animals and robot traversed stiff beams by rolling their body betweenbeam, they pushed across flimsy beams, suggesting a concept of terradynamic favorability where modes with easier physical interaction are more likely to occur. Robotic beam traversal revealed that, system state either remains in a favorable mode or transitions to one when energy fluctuation is comparable to the transition barrier. Robotic self-righting transitions occurred similarly and revealed that changing system parameters lowers barriers over which comparable fluctuation can induce transitions. Thetransitionsof animalsin both systems mostly occurred similarly, but sensory feedback may facilitate its beam traversal. Finally, we developed a method to measure animal movement across large spatiotemporal scales in a terrain treadmill.Comment: arXiv admin note: substantial text overlap with arXiv:2006.1271

Windblown Sand Modelling and Mitigation for Civil Structures

L'abstract è presente nell'allegato / the abstract is in the attachmen

Combined controls of sedimentology and diagenesis on seismic properties in lacustrine and palustrine carbonates (Upper Miocene, Samos Island, Greece)

International audienceFor the subsurface characterization of carbonates, linking physical properties (e.g. porosity and seismic reflectors) with their geological significance (e.g. sedimentary facies and diage-nesis) is of primary importance. To address this issue, we study the lacustrine and palustrine carbonates on Samos Island through a geological and geophysical characterization of a sed-imentary succession. The microstructures of the samples are described, and the samples' physical properties are measured (porosity, P-wave velocity and density). The results show that the identification of only the primary (i.e. sedimentary) microstructure is not sufficient for explaining the huge variations in porosity and P-wave velocity. Hence, we highlight two early diagenetic processes that strongly impact the microstructures and control the physical properties: (i) neomorphism occludes porosity and increases the P-wave velocity of mud-and grain-supported microstructures, which implies a mineralogical stabilization of the grains; (ii) conversely, the dissolution process creates porosity and decreases the P-wave velocity of grain-supported microstructures if the mineralogical composition of the grains is not previously stabilized. These two diagenetic processes thus depend on the primary microstructures and mineralogy of the sediments. This work aims to explain the variations in porosity and P-wave velocity for each defined primary microstructure. A 1-D seismogram is then built to highlight seismic reflectors with a metre-scale resolution. These reflectors are associated with several geological contrasts. Hard kicks (positive amplitude reflectors) match well with exposure surfaces related to palaeosols. They correspond to contrasts between non-modified primary microstructures and highly neomorphosed microstructures. Conversely, soft kicks (negative amplitude reflectors) are linked with diagenetic contrasts (e.g. neomorphosed mi-crostructures versus non-modified primary microstructures) and sedimentary contrasts that can be overprinted by diagenesis (e.g. neomorphosed mud-supported microstructures versus dissolved grain-supported microstructures). This study highlights that high-resolution seismic reflectors of lacustrine and palustrine carbonates are strongly related to the spatial contrasts of primary microstructures overprinted by early diagenesis

Fully-automated μMRI morphometric phenotyping of the Tc1 mouse model of Down Syndrome

We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to the Tc1 mouse model of Down syndrome, to identify new morphological phenotypes in the brain of this first transchromosomic animal carrying human chromosome 21. We incorporate an accessible approach for simultaneously scanning multiple ex vivo brains, requiring only a 3D-printed brain holder, and novel image processing steps for their separation and orientation. We employ clinically established multi-atlas techniques-superior to single-atlas methods-together with publicly-available atlas databases for automatic skull-stripping and tissue segmentation, providing high-quality, subject-specific tissue maps. We follow these steps with group-wise registration, structural parcellation and both Voxel- and Tensor-Based Morphometry-advantageous for their ability to highlight morphological differences without the laborious delineation of regions of interest. We show the application of freely available open-source software developed for clinical MRI analysis to mouse brain data: NiftySeg for segmentation and NiftyReg for registration, and discuss atlases and parameters suitable for the preclinical paradigm. We used this pipeline to compare 29 Tc1 brains with 26 wild-type littermate controls, imaged ex vivo at 9.4T. We show an unexpected increase in Tc1 total intracranial volume and, controlling for this, local volume and grey matter density reductions in the Tc1 brain compared to the wild-types, most prominently in the cerebellum, in agreement with human DS and previous histological findings

A Probabilistic Approach in Failure Modelling of Aluminium High Pressure Die-Castings

Aluminium high pressure die-castings are essential elements of a modern car body, e.g. structural nodes are produced as die-castings. Numerical models are required to guarantee structural reliability. However, the ductility of die-castings is influenced by defects caused by the casting process. As a result, the ductility exhibits a global systematic variation and a local random variation. The main objective of the present work is the experimental and numerical analysis of these variations

Solid-state single-photon sources: recent advances for novel quantum materials

In this review, we describe the current landscape of emergent quantum materials for quantum photonic applications. We focus on three specific solid-state platforms: single emitters in monolayers of transition metal dichalcogenides, defects in hexagonal boron nitride, and colloidal quantum dots in perovskites. These platforms share a unique technological accessibility, enabling the rapid implementation of testbed quantum applications, all while being on the verge of becoming technologically mature enough for a first generation of real-world quantum applications. The review begins with a comprehensive overview of the current state-of-the-art for relevant single-photon sources in the solid-state, introducing the most important performance criteria and experimental characterization techniques along the way. We then benchmark progress for each of the three novel materials against more established (yet complex) platforms, highlighting performance, material-specific advantages, and giving an outlook on quantum applications. This review will thus provide the reader with a snapshot on latest developments in the fast-paced field of emergent single-photon sources in the solid-state, including all the required concepts and experiments relevant to this technology.Comment: 35 pages, 8 figures, review pape