There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

N G van Kampen 1981 Amsterdam: North-Holland xiv + 419 pp price Dfl 180 This is a book which, at a lower price, could be expected to become an essential part of the library of every physical scientist concerned with problems involving fluctuations and stochastic processes, as well as those who just enjoy a beautifully written book. It provides an extensive graduate-level introduction which is clear, cautious, interesting and readable.

https://iopscience.iop.org/article/10.1088/0031-9112/34/4/040/pdf

Stochastic Processes in Physics and Chemistry

Since the subject of traffic dynamics has captured the interest of physicists, many surprising effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by ``phantom traffic jams'' even though drivers all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction in the volume of traffic cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize into lanes, while similar systems ``freeze by heating''? All of these questions have been answered by applying and extending methods from statistical physics and nonlinear dynamics to self-driven many-particle systems. This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic. These include microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts, such as a general modeling framework for self-driven many-particle systems, including spin systems. While the primary focus is upon vehicle and pedestrian traffic, applications to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are touched upon as well.

Traffic and related self-driven many-particle systems

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The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

/pdf/towards-6g-wireless-communication-networks-vision-enabling-2tj7a36yux.pdf

Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

The hydrodynamic equations for a gas of hard spheres with dissipative dynamics are derived from the Boltzmann equation. The heat and momentum fluxes are calculated to Navier-Stokes order and the transport coefficients are determined as explicit functions of the coefficient of restitution. The dispersion relations for the corresponding linearized equations are obtained and the stability of this linear description is discussed. This requires consideration of the linear Burnett contributions to the energy balance equation from the energy sink term. Finally, it is shown how these results can be imbedded in simpler kinetic model equations with the potential for analysis of more complex states.

Hydrodynamics for granular flow at low density

Kinetic Theory of Gases in Shear Flows

The dynamics for a system of hard spheres with dissipative collisions is described at the levels of statistical mechanics, kinetic theory, and simulation. The Liouville operator(s) and associated binary scattering operators are defined as the generators for time evolution in phase space. The BBGKY hierarchy for reduced distribution functions is given, and an approximate kinetic equation is obtained that extends the revised Enskog theory to dissipative dynamics. A Monte Carlo simulation method to solve this equation is described, extending the Bird method to the dense, dissipative hard-sphere system. A practical kinetic model for theoretical analysis of this equation also is proposed. As an illustration of these results, the kinetic theory and the Monte Carlo simulations are applied to the homogeneous cooling state of rapid granular flow.

Dissipative dynamics for hard spheres

List of Figures. List of Tables. Preface. Acknowledgements. Introduction. Introduction Author. 1: Kinetic Theory of Dilute Gases. 1. Introduction. 2. Derivation of the Boltzmann equation. 3. Chapman-Enskog expansion. 4. The Boltzmann equation for gas mixtures. 5. Kinetic models. 2: Uniform Shear Flow in a Simple Gas. 1. Introduction. 2. The Boltzmann equation for uniform shear flow. 3. Moment equations for a gas of Maxwell molecules. 4. Third- and fourth-degree velocity movements. 5. Singular behavior of the velocity moments. 6. Perturbation expansion of the distribution function. 3: Kinetic Model for Uniform Shear Flow.1. Introduction. 2. The BKG equation for uniform shear flow. 3. Power-law repulsive potentials. Hard spheres. 4. The thermostatted state. 5. Small perturbations from the thermostatted uniform shear flow. 6. Heat transport under uniform shear flow. 7. Stability analysis of the thermostatted uniform shear flow. 5: Uniform Shear Flow in a Binary Mixture. 6: Planar Couette Flow in a Simple Gas. 7: Planar Couette Flow in a Binary Mixture. Appendix A: Collisional moments for Maxwell molecules.

Kinetic Theory of Gases in Shear Flows: Nonlinear Transport

Direct Monte Carlo simulations of the Enskog-Boltzmann equation for a spatially uniform system of smooth inelastic spheres are performed. In order to reach a steady state, the particles are assumed to be under the action of an external driving force which does work to compensate for the collisional loss of energy. Three different types of external driving are considered: (a) a stochastic force, (b) a deterministic force proportional to the particle velocity and (c) a deterministic force parallel to the particle velocity but constant in magnitude. The Enskog-Boltzmann equation in case (b) is fully equivalent to that of the homogeneous cooling state (where the thermal velocity monotonically decreases with time) when expressed in terms of the particle velocity relative to the thermal velocity. Comparison of the simulation results for the fourth cumulant and the high energy tail with theoretical predictions derived in cases (a) and (b) [T. P. C. van Noije and M. H. Ernst, Gran. Matt. 1, 57 (1998)] shows a good agreement. In contrast to these two cases, the deviation from the Maxwell-Boltzmann distribution is not well represented by Sonine polynomials in case (c), even for low dissipation. In addition, the high energy tail exhibits an underpopulation effect in this case.

Andrés Santos

Papers

Hydrodynamics for granular flow at low density

Kinetic Theory of Gases in Shear Flows

Dissipative dynamics for hard spheres

Kinetic Theory of Gases in Shear Flows: Nonlinear Transport

Computer simulation of uniformly heated granular fluids