Search results for " ENTROPY"
showing 10 items of 236 documents
Entanglement entropy in a periodically driven quantum Ising chain
2016
We numerically study the dynamics of entanglement entropy, induced by an oscillating time periodic driving of the transverse field, h(t), of a one-dimensional quantum Ising chain. We consider several realizations of h(t), and we find a number of results in analogy with entanglement entropy dynamics induced by a sudden quantum quench. After short-time relaxation, the dynamics of entanglement entropy synchronises with h(t), displaying an oscillatory behaviour at the frequency of the driving. Synchronisation in the dynamics of entanglement entropy, is spoiled by the appearance of quasi-revivals which fade out in the thermodynamic limit, and which we interpret using a quasi-particle picture ada…
The Grain Boundary Wetting Phenomena in the Ti-Containing High-Entropy Alloys: A Review
2021
In this review, the phenomenon of grain boundary (GB) wetting by melt is analyzed for multicomponent alloys without principal components (also called high-entropy alloys or HEAs) containing titanium. GB wetting can be complete or partial. In the former case, the liquid phase forms the continuous layers between solid grains and completely separates them. In the latter case of partial GB wetting, the melt forms the chain of droplets in GBs, with certain non-zero contact angles. The GB wetting phenomenon can be observed in HEAs produced by all solidification-based technologies. GB leads to the appearance of novel GB tie lines Twmin and Twmax in the multicomponent HEA phase diagrams. The so-cal…
Application of entropic approach to estimate the mean flow velocity and Manning roughness coefficient in a high-curvature flume
2016
The entropy-based approach allows the estimation of the mean flow velocity in open channel flow by using the maximum flow velocity. The linear relationship between the mean velocity, umax, and the mean flow velocity, um, through the dimensionless parameter Φ(M), has been verified both in natural rivers and in laboratory channels. Recently, the authors of this study investigated the reliability of the entropy-based formula in a straight channel and under different bed and side-walls' roughness conditions. The present study aims to further validate the entropy-based approach and to explore the effectiveness of entropy-based formula in high curvature channels. Results show that as the effect o…
A validity and reliability study of Conditional Entropy Measures of Pulse Rate Variability
2019
In this work, we present the feasibility to use a simpler methodological approach for the assessment of the short-term complexity of Heart Rate Variability (HRV). Specifically, we propose to exploit Pulse Rate Variability (PRV) recorded through photoplethysmography in place of HRV measured from the ECG, and to compute complexity via a linear Gaussian approximation in place of the standard model-free methods (e.g., nearest neighbor entropy estimates) usually applied to HRV. Linear PRV-based and model-free HRV-based complexity measures were compared via statistical tests, correlation analysis and Bland-Altman plots, demonstrating an overall good agreement. These results support the applicabil…
Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations
2020
Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in the learned value function has unpredictable consequences in the space of the policies it represents…
Efficient Algorithms for Sequence Analysis with Entropic Profiles
2017
Entropy, being closely related to repetitiveness and compressibility, is a widely used information-related measure to assess the degree of predictability of a sequence. Entropic profiles are based on information theory principles, and can be used to study the under-/over-representation of subwords, by also providing information about the scale of conserved DNA regions. Here, we focus on the algorithmic aspects related to entropic profiles. In particular, we propose linear time algorithms for their computation that rely on suffix-based data structures, more specifically on the truncated suffix tree (TST) and on the enhanced suffix array (ESA). We performed an extensive experimental campaign …
Spectral entropy based neuronal network synchronization analysis based on microelectrode array measurements
2016
Synchrony and asynchrony are essential aspects of the functioning of interconnected neuronal cells and networks. New information on neuronal synchronization can be expected to aid in understanding these systems. Synchronization provides insight in the functional connectivity and the spatial distribution of the information processing in the networks. Synchronization is generally studied with time domain analysis of neuronal events, or using direct frequency spectrum analysis, e.g., in specific frequency bands. However, these methods have their pitfalls. Thus, we have previously proposed a method to analyze temporal changes in the complexity of the frequency of signals originating from differ…
Measuring spectrally-resolved information transfer.
2020
Information transfer, measured by transfer entropy, is a key component of distributed computation. It is therefore important to understand the pattern of information transfer in order to unravel the distributed computational algorithms of a system. Since in many natural systems distributed computation is thought to rely on rhythmic processes a frequency resolved measure of information transfer is highly desirable. Here, we present a novel algorithm, and its efficient implementation, to identify separately frequencies sending and receiving information in a network. Our approach relies on the invertible maximum overlap discrete wavelet transform (MODWT) for the creation of surrogate data in t…
Analyzing the feasibility of time correlated spectral entropy for the assessment of neuronal synchrony
2016
In this paper, we study neuronal network analysis based on microelectrode measurements. We search for potential relations between time correlated changes in spectral distributions and synchrony for neuronal network activity. Spectral distribution is quantified by spectral entropy as a measure of uniformity/complexity and this measure is calculated as a function of time for the recorded neuronal signals, i.e., time variant spectral entropy. Time variant correlations in the spectral distributions between different parts of a neuronal network, i.e., of concurrent measurements via different microelectrodes, are calculated to express the relation with a single scalar. We demonstrate these relati…
Study of Selective Adsorption of Gases by Calorimetry
2013
This chapter is devoted to the study of coadsorption of gases in nanoporous solids by using the differential calorimetry. In the first part, the thermodynamic principles of adsorption of gases are recalled. Some of them have already presented in chapter one. However a special attention has been paid here to the determination of the adsorption enthalpies and entropies and we focused on the selective adsorption of binary mixtures. Then the specific experimental technique based on the combination of differential calorimetry with manometry and gas phase chromatography or mass spectrometry is shown in details. In the last part, the thermodynamic concepts on coadsorption are illustrated with expe…