An equal area law for holographic entanglement entropy of the AdS-RN black hole

The Anti-de Sitter-Reissner-Nordstrom (AdS-RN) black hole in the canonical ensemble undergoes a phase transition similar to the liquid-gas phase transition, i.e. the isocharges on the entropy-temperature plane develop an unstable branch when the charge is smaller than a critical value. It was later discovered that the isocharges on the entanglement entropy-temperature plane also exhibit the same van der Waals-like structure, for spherical entangling regions. In this paper, we present numerical results which sharpen this similarity between entanglement entropy and black hole entropy, by showing that both of these entropies obey Maxwell's equal area law to an accuracy of around 1 %. Moreover, we checked this for a wide range of size of the spherical entangling region, and the equal area law holds independently of the size. We also checked the equal area law for AdS-RN in 4 and 5 dimensions, so the conclusion is not specific to a particular dimension. Finally, we repeated the same procedure for a similar, van der Waals-like transition of the dyonic black hole in AdS in a mixed ensemble (fixed electric potential and fixed magnetic charge), and showed that the equal area law is not valid in this case. Thus the equal area law for entanglement entropy seems to be specific to the AdS-RN background.Comment: 17 pages, multiple figures. v4: matches published versio

Fluctuation and dissipation in de Sitter space

In this paper we study some thermal properties of quantum field theories in de Sitter space by means of holographic techniques. We focus on the static patch of de Sitter and assume that the quantum fields are in the standard Bunch-Davies vacuum. More specifically, we follow the stochastic motion of a massive charged particle due to its interaction with Hawking radiation. The process is described in terms of the theory of Brownian motion in inhomogeneous media and its associated Langevin dynamics. At late times, we find that the particle undergoes a regime of slow diffusion and never reaches the horizon, in stark contrast to the usual random walk behavior at finite temperature. Nevertheless, the fluctuation-dissipation theorem is found to hold at all times.Comment: 1+45 pages, 5 figures. v4: matches published versio

Modeling and Analyzing Academic Researcher Behavior

. This paper suggests a theoretical framework for analyzing the mechanism of the behavior of academic researchers whose interests are tangled and vary widely in academic factors (the intrinsic satisfaction in conducting research, the improvement in individual research ability, etc.) or non-academic factors (career rewards, financial rewards, etc.). Furthermore, each researcher also has his/her different academic stances in their preferences about academic freedom and academic entrepreneurship. Understanding the behavior of academic researchers will contribute to nurture young researchers, to improve the standard of research and education as well as to boost collaboration in academia-industry. In particular, as open innovation is increasingly in need of the involvement of university researchers, to establish a successful approach to entice researchers into enterprises' research, companies must comprehend the behavior of university researchers who have multiple complex motivations. The paper explores academic researchers' behaviors through optimizing their utility functions, i.e. the satisfaction obtained by their research outputs. This paper characterizes these outputs as the results of researchers' 3C: Competence (the ability to implement the research), Commitment (the effort to do the research), and Contribution (finding meaning in the research). Most of the previous research utilized the empirical methods to study researcher's motivation. Without adopting economic theory into the analysis, the past literature could not offer a deeper understanding of researcher's behavior. Our contribution is important both conceptually and practically because it provides the first theoretical framework to study the mechanism of researcher's behavior

Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach

International audienceRecent years have witnessed the rapid development of human activity recognition (HAR) based on werable sensor data. One can find many practical applications in this area, especially in the field of health care. Many machine learning algorithms such as Decision Trees, Support Vector Machine, Naive Bayes, K-Nearest Neighbor and Multilayer Perceptron are successfully used in HAR. Although these methods are fast and easy for implementation, they still have some limitations due to poor performance in a number of situations. In this paper, we propose a novel method based on the ensemble learning to boost the performance of these machine learning methods for HAR

Design Space Exploration of the Violacein Pathway in Escherichia coli Based Transcription Translation Cell-Free System (TX-TL)

In this study, an Escherichia coli (E. coli) based transcription translation cell-free system (TX-TL) was employed to sample various enzyme expression levels of the violacein pathway. The pathway was successfully reconstructed in TX-TL. Its variation produced different metabolites as evident from the extracts assorted colors. Analysis of the violacein product via UV-Vis absorption and liquid chromatography-mass spectrometry (LC-MS) detected 68 nanograms of violacein per 10 microliters reaction volume. Significant buildup of prodeoxyviolacein intermediate was also detected in the equimolar TX-TL reaction. Finally, design space exploration experiments suggested an improvement in violacein production at high VioC and VioD DNA concentrations