Accumulation of Particles and Formation of a Dissipative Structure in a Nonequilibrium Bath

The standard textbooks contain good explanations of how and why equilibrium thermodynamics emerges in a reservoir with particles that are subjected to Gaussian noise. However, in systems that convert or transport energy, the noise is often not Gaussian. Instead, displacements exhibit an α-stable distribution. Such noise is commonly called Lévy noise. With such noise, we see a thermodynamics that deviates from what traditional equilibrium theory stipulates. In addition, with particles that can propel themselves, so-called active particles, we find that the rules of equilibrium thermodynamics no longer apply. No general nonequilibrium thermodynamic theory is available and understanding is often ad hoc. We study a system with overdamped particles that are subjected to Lévy noise. We pick a system with a geometry that leads to concise formulae to describe the accumulation of particles in a cavity. The nonhomogeneous distribution of particles can be seen as a dissipative structure, i.e., a lower-entropy steady state that allows for throughput of energy and concurrent production of entropy. After the mechanism that maintains nonequilibrium is switched off, the relaxation back to homogeneity represents an increase in entropy and a decrease of free energy. For our setup we can analytically connect the nonequilibrium noise and active particle behavior to entropy decrease and energy buildup with simple and intuitive formulae.     

The Odyssey of Entropy: Cryptography

After being introduced by Shannon as a measure of disorder and unavailable information, the notion of entropy has found its applications in a broad range of scientific disciplines. In this paper, we present a systematic review on the applications of entropy and related information-theoretical concepts in the design, implementation and evaluation of cryptographic schemes, algorithms, devices and systems. Moreover, we study existing trends, and establish a roadmap for future research in these areas.     

Exploring the Origin of Maximum Entropy States Relevant to Resonant Modes in Modern Chladni Plates

The resonant modes generated from the modern Chladni experiment are systematically confirmed to intimately correspond to the maximum entropy states obtained from the inhomogeneous Helmholtz equation for the square and equilateral triangle plates. To investigate the origin of maximum entropy states, the inhomogeneous Helmholtz equation is modified to consider the point interaction coming from the driving oscillator. The coupling strength associated with the point interaction is characterized by a dimensionless factor α. The δ potential of the point interaction is numerically modelled by a truncated basis with an upper index N. The asymptotic behavior for the upper index N is thoroughly explored to verify that the coupling strength of α = 1.0 can make the theoretical resonant modes agree excellently with the maximum entropy states as N→∞. It is further authenticated that nearly the same resonant modes can be obtained by using a larger coupling strength α when a smaller upper index N is exploited in the calculation.     

Estimating Non-Gaussianity of a Quantum State by Measuring Orthogonal Quadratures

We derive the lower bounds for a non-Gaussianity measure based on quantum relative entropy (QRE). Our approach draws on the observation that the QRE-based non-Gaussianity measure of a single-mode quantum state is lower bounded by a function of the negentropies for quadrature distributions with maximum and minimum variances. We demonstrate that the lower bound can outperform the previously proposed bound by the negentropy of a quadrature distribution. Furthermore, we extend our method to establish lower bounds for the QRE-based non-Gaussianity measure of a multimode quantum state that can be measured by homodyne detection, with or without leveraging a Gaussian unitary operation. Finally, we explore how our lower bound finds application in non-Gaussian entanglement detection.     

The Use of the Statistical Entropy in Some New Approaches for the Description of Biosystems

Some problems of describing biological systems with the use of entropy as a measure of the complexity of these systems are considered. Entropy is studied both for the organism as a whole and for its parts down to the molecular level. Correlation of actions of various parts of the whole organism, intercellular interactions and control, as well as cooperativity on the microlevel lead to a more complex structure and lower statistical entropy. For a multicellular organism, entropy is much lower than entropy for the same mass of a colony of unicellular organisms. Cooperativity always reduces the entropy of the system; a simple example of ligand binding to a macromolecule carrying two reaction centers shows how entropy is consistent with the ambiguity of the result in the Bernoulli test scheme. Particular attention is paid to the qualitative and quantitative relationship between the entropy of the system and the cooperativity of ligand binding to macromolecules. A kinetic model of metabolism. corresponding to Schrödinger’s concept of the maintenance biosystems by “negentropy feeding”, is proposed. This model allows calculating the nonequilibrium local entropy and comparing it with the local equilibrium entropy inherent in non-living matter.     

高斯型耦合Tavis-Cummings模型中原子的熵压缩

利用全量子理论研究了高斯型耦合Tavis-Cummings模型中一个原子的熵压缩,运用数值计算方法讨论了原子垂直于腔轴的运动速度、光场强度以及两原子的初态对单个原子熵压缩的影响.结果表明,原子的熵压缩时间由原子的运动速度决定,压缩程度由光场强度决定,压缩时间和压缩程度还决定于原子的初始状态.     

氯化锌修饰蓝光量子点发光二极管EI北大核心CSCD

采用氯化锌(ZnCl_(2))修饰镉基CdSe/ZnS蓝光量子点(B-QD)薄膜,发现与量子点表面结合力更强的ZnCl_(2)能够部分取代量子点长链配体油酸,有效钝化量子点表面缺陷,提高薄膜的荧光量子效率(PLQY)。此外,由于ZnCl_(2)具有偶极作用,使量子点真空能级提高0.2 eV,一方面可改善电子和空穴载流子注入平衡,另一方面可有效降低发光器件的启亮电压,提高器件的发光寿命。这种无机配体修饰量子点薄膜的方法可能为解决蓝光量子点发光二极管(B-QLEDs)因空穴注入困难和量子点表面缺陷导致器件性能不高的问题提供一个有效思路。     

原子系统中偶极-偶极相互作用对量子存储支撑熵不确定度的调控研究

本文研究了Markovian过程和non-Markovian过程两种情况下,原子系统中偶极-偶极(D-D)相互作用和失谐量对两原子系统量子存储支撑(QMA)熵不确定度的调控作用.与Markovian过程相比,在non-Markovian过程中,由于库环境的记忆效应使得具有D-D相互作用的两原子系统QMA熵不确定度的演化行为呈现出振荡上升现象,且熵不确定度的上升趋势得到减缓,从而抑制了由系统量子噪声引起的退相干效应.此外,D-D相互作用对两原子系统QMA熵不确定度具有显著的调控能力,且D-D相互作用比失谐量的调控能力更强.     

Predicting the Standard Enthalpy (ΔHo f) and Entropy (So) of Alkanes by Artificial Neural Networks

Abstract

Artificial Neural Networks (ANNs) with Extended Delta-Bar-Delta (EDBD) back propagation learning algorithm have been developed to predict the standard enthalpy and entropy of 87 acyclic alkanes. Molecular weight, boiling point and density of the compounds were used as input parameters. The network's architecture and parameters were optimized to give maximum performances. The best network was a 3-6-2 ANN, and the optimum learning epoch was about 1320. The results show that the maximum relative errors of enthalpy and entropy are less than 3%. They reveal that the performances of ANNs for predicting the enthalpy and entropy of alkanes are satisfying.