Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

Memristors

This Edited Volume Memristors - Circuits and Applications of Memristor Devices is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of Engineering. The book comprises single chapters authored by various researchers and edited by an expert active in the physical sciences, engineering, and technology research areas. All chapters are complete in itself but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on physical sciences, engineering, and technology,and open new possible research paths for further novel developments

The Fuzziness in Molecular, Supramolecular, and Systems Chemistry

Fuzzy Logic is a good model for the human ability to compute words. It is based on the theory of fuzzy set. A fuzzy set is different from a classical set because it breaks the Law of the Excluded Middle. In fact, an item may belong to a fuzzy set and its complement at the same time and with the same or different degree of membership. The degree of membership of an item in a fuzzy set can be any real number included between 0 and 1. This property enables us to deal with all those statements of which truths are a matter of degree. Fuzzy logic plays a relevant role in the field of Artificial Intelligence because it enables decision-making in complex situations, where there are many intertwined variables involved. Traditionally, fuzzy logic is implemented through software on a computer or, even better, through analog electronic circuits. Recently, the idea of using molecules and chemical reactions to process fuzzy logic has been promoted. In fact, the molecular word is fuzzy in its essence. The overlapping of quantum states, on the one hand, and the conformational heterogeneity of large molecules, on the other, enable context-specific functions to emerge in response to changing environmental conditions. Moreover, analog input–output relationships, involving not only electrical but also other physical and chemical variables can be exploited to build fuzzy logic systems. The development of “fuzzy chemical systems” is tracing a new path in the field of artificial intelligence. This new path shows that artificially intelligent systems can be implemented not only through software and electronic circuits but also through solutions of properly chosen chemical compounds. The design of chemical artificial intelligent systems and chemical robots promises to have a significant impact on science, medicine, economy, security, and wellbeing. Therefore, it is my great pleasure to announce a Special Issue of Molecules entitled “The Fuzziness in Molecular, Supramolecular, and Systems Chemistry.” All researchers who experience the Fuzziness of the molecular world or use Fuzzy logic to understand Chemical Complex Systems will be interested in this book

Development and application of semiclassical models for strong-field phenomena

Semiclassical models based on classical trajectories for the description of the electron motion in the continuum are a powerful tool of strong-field, ultrafast, and attosecond physics. The semiclassical models allow us to identify the specific mechanism of a phenomenon of interest and visualize it in terms of classical trajectories. Often these models are also computationally simple. In the present work we developed a range of new semiclassical models and applied them to various strong-field phenomena. Among these are: capture of electrons into Rydberg states, sequential multiple ionization, above-threshold ionization of the hydrogen molecule, multielectron effects due to the laser-induced polarization of the atomic ion, and strong-field holography with photoelectrons. We also used the semiclassical simulations to understand the results obtained using quantum optimal control theory, namely, optimization of the high-harmonic yield by shaping of the driving pulse. We developed a method capable of retrieving effective single-active electron potentials, which are required for semiclassical simulations. In this method the single-active electron potential is found as the result of an optimization procedure aimed at reproducing given photoelectron momentum distributions. Finally, we applied deep learning to retrieve the internuclear distance in a molecule ionized by a strong laser pulse from the photoelectron momentum distribution. The results of this thesis will serve as a basis for development of new generation of semiclassical models that are expected to combine accurate description of the ionization step, the ability to account for interference and multielectron effects, and numerical efficiency. The emergence of such models will open new perspectives in the theory of laser-matter interaction

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

Using Quantum Fluctuations to Regularize an Analytic Continuation Problem from Many-Body Physics

Extracting spectral information via inversion from Quantum Monte Carlo sampled data isa difficult task. There is a need to analytically continue noisy and often incomplete imaginary-time data into the full complex domain. A new approach is proposed that uses the quantum fluctuations of spin momenta to regularize the inversion. A one-dimensional Heisenberg chain in the presence of a transverse field is first encoded with synthetic data representing several classes of spectral functions and then run through a Density Matrix Renormalization Group algorithm to find its ground state. This solution corresponds to a probable, high quality solution to the inversion. Using optimization constraints and sampling techniques, forward model spectra are replicated by inversion that capture distinguishing characteristics that are often washed out in methods that favor smoothed out solutions

Computational and Numerical Simulations

Computational and Numerical Simulations is an edited book including 20 chapters. Book handles the recent research devoted to numerical simulations of physical and engineering systems. It presents both new theories and their applications, showing bridge between theoretical investigations and possibility to apply them by engineers of different branches of science. Numerical simulations play a key role in both theoretical and application oriented research