Nowadays, the ubiquitous nature of information invokes the rapid development of new interdisciplinary sciences integrated with computing. One manifestation of this trend is the dynamism of information expressed in the different sciences with regards to information quality, amount, type, form of expression, and nature.

The dynamism of information in classical systems refers to the behavior of information processed by a physical system that can be described by classical (non-quantum) mechanics. As a principle it involves studying how information is transmitted and stored in the system, as well as how it affects the system’s overall behavior. This can include analyzing the information flow through networks, the impact of noise or disturbances on information transmission, and the emergence of complex patterns and structures within the system. Information dynamics can be applied in fields such as signal processing, communication theory, and complex systems science.

Nevertheless, when it comes to quantum systems, information dynamics refers to the study of how information is transmitted, processed, and stored in a system that can only be described by quantum mechanics. It involves analyzing how quantum information is encoded, transferred, and processed by quantum states, such as qubits, and how it interacts with the system’s environment. One of the key features of quantum information dynamics is quantum entanglement, which allows for the transmission of information across long distances without the need for physical connections.

Information dynamics in quantum systems also involves studying the interaction between quantum information and classical information, as well as the development of quantum technologies such as quantum computing and quantum communication. The study of information dynamics in quantum systems plays a critical role in advancing our understanding of the fundamental workings of the quantum world and has important applications in fields ranging from cryptography and computing to quantum sensing and simulation.

The book aims to present all aspects of the field as it consists of two parts: natural systems as information processors, and computers as natural systems. Part 1 contains eight chapters, each of which is divided into many subchapters. It covers the concept of the information; various application areas like logic or genetic code; epistemological aspects like causality, prediction, and learning; randomized information, followed by classical Hamiltonian dynamics and dissipative dynamics; fluctuations, noise and microscopic degrees of freedom; and ending with a large chapter on quantum mechanics. Part 2 contains only two chapters: “Physical Aspects of Computing” and “Quantum Computation.” The book ends with a chapter called “Epilogue.”

Personally, though the title itself didn’t impress me much, once I started reading it I found the book comprehensive to such an extent that I became fascinated with how the author addresses the target audience, which includes graduate and postgraduate students in physics, as this book is the compendium of a lecture series on “Theoretical Solid-State Physics,” “Quantum Optics,” and “Experimental High-Energy Physics.”

What captured my attention the most is a graph of neighboring sciences such as philosophy, biology, physics, and mathematics, with the particular information dynamics of each included. Then I got emotional to see a photo of the Jacquard weaving loom of 1805, as “the first man-made tool generating patterns from a digital memory medium.” Subchapter 1.2 discusses information in 3D vision called semiotics, including its semantics, syntax, and pragmatics. Morse code is also quite impressive as it assigns letters to a combination of dots and dashes, let alone the Boltzmann original numeric entropy definition. Based on a comparison of two Venn diagrams, a bipartite system exponential expansion is determined by the number of information terms. For those willing to understand deoxyribonucleic acid (DNA) sequencing to all types of ribonucleic acid (RNA), including mRNA, I strongly recommend the colorful graph of a DNA polymer with binary information coding of its chemical structure.

It is clear that the author is an immensely experienced academic with special skills appropriate to student audiences and all those unfamiliar with the area.