The dynamics of transition from laminar to turbulent flow remains to this day a major challenge in theoretical and applied mechanics. A series of IUTAM symposia held over the last twenty five years at well-known Centres of research in the subject - Novosibirsk, Stuttgart, Toulouse, Sendai and Sedona (Arizona) - has proved to be a great catalyst which has given a boost to research and our understanding of the field. At this point of time, the field is changing significantly with several emerging directions. The sixth IUTAM meeting in the series, which was held at the Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore, India, focused on the progress after the fifth meeting held at Sedona in 1999. The s- posium, which adhered to the IUTAM format of a single session, included seven invited lectures, fifty oral presentations and eight posters. During the course of the symposium, the following became evident. The area of laminar-turbulent transition has progressed considerably since 1999. Better theoretical tools, for handling nonlinearities as well as transient behaviour are now available. This is accompanied by an en- mous increase in the level of sophistication of both experiments and direct numerical simulations. The result has been that our understanding of the early stages of the transition process is now on much firmer footing and we are now able to study many aspects of the later stages of the transition process.

The ninth Advanced Study Institute (AS!) on Techniques and Concepts of High Energy Physics was almost canceled before ifbegan! A certain visitor to the area (Hurricane Bertha) arrived unexpectedly early in 1996. It was the first hur ricane in memory to menace the Caribbean in early July! Fortunately, it passed St. Croix several days before our meeting, and left very little damage. (The Altar ellis survived the eye of the storm in the in the British West Islands!) The meeting was held once again at the hotel on the Cay, on that spec of land in the harbor ofChrirtiansted, St. Croix, U. S. Virgin Islands. After the first two days of, at times, outrageous downpour, the 71 participants from 26 coun tries began to relax and enjoy the lectures and the lovely surroundings of the In stitute. The primary support for the meeting was provided by the ~cientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was cosponsored by the U. S. department of Energy, by the Fermi National Accelera tor Laboratory (Fermi-lab), by the U. S. National Science Foundation, and by the University of Rochester. In addition, the International Science Foundation con tributed to the support of a participant from Russia. As in the case of the previous ASIs, the scientific program was designed for advanced graduate students and recent Ph. D. recipients in experimental parti cle physics.

In May 2002 a number of about 20 scientists from various disciplines were invited by the Berlin-Brandenburg Academy of Sciences and Humanities to participate in an interdisciplinary workshop on structures and structure generating processes. The site was the beautiful little castle of Blankensee, south of Berlin. The disciplines represented ranged from mathematics and information theory, over various ?elds of engineering, biochemistry and biology, to the economic and social sciences. All participants presented talks explaining the nature of structures considered in their ?elds and the associated procedures of analysis. It soon became evident that the study of structures is indeed a common c- cern of virtually all disciplines. The motivation as well as the methods of analysis, however, differ considerably. In engineering, the generation of artifacts, such as infrastructures or technological processes, are of primary interest. Frequently, the analysis aims there at de?ning a simpli?ed mathematical model for the optimization of the structures and the structure generating processes. Mathematical or heuristic methods are applied, the latter preferably of the type of biology based evolutionary algorithms. On the other hand, setting up complex technical structures is not pos- ble by such simpli?ed model calculations but requires a different and less model but rather knowledge-based type of approach, using empirical rules rather than formal equations. In biochemistry, interest is frequently focussed on the structures of molecules, such as proteins or ribonucleic acids. Again, optimal structures can usually be de?ned.

Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.

Monte Carlo computer simulations are now a standard tool in scientific fields such as condensed-matter physics, including surface-physics and applied-physics problems (metallurgy, diffusion, and segregation, etc. ), chemical physics, including studies of solutions, chemical reactions, polymer statistics, etc., and field theory. With the increasing ability of this method to deal with quantum-mechanical problems such as quantum spin systems or many-fermion problems, it will become useful for other questions in the fields of elementary-particle and nuclear physics as well. The large number of recent publications dealing either with applications or further development of some aspects of this method is a clear indication that the scientific community has realized the power and versatility of Monte Carlo simula tions, as well as of related simulation techniques such as "molecular dynamics" and "Langevin dynamics," which are only briefly mentioned in the present book. With the increasing availability of recent very-high-speed general-purpose computers, many problems become tractable which have so far escaped satisfactory treatment due to prac tical limitations (too small systems had to be chosen, or too short averaging times had to be used). While this approach is admittedly rather expensive, two cheaper alternatives have become available, too: (i) array or vector processors specifical ly suited for wide classes of simulation purposes; (ii) special purpose processors, which are built for a more specific class of problems or, in the extreme case, for the simulation of one single model system."

This work arises from our teaching this subject during many years. The vast majority of these exercises are the exams we gave to our students in this period. We carefully selected the subjects of the exercises to cover all the material which is most needed and which is treated in the most well known texts on these subjects. Each exercise is carefully solved in full details, explaining the theory behind the solution with particular care for those issues that, from our experience, are found most difficult from the average student. Indeed, several exercises are designed to throw light on aspects of the theory that, for one reason or another, are usually neglected with the result to make the students feel uneasy about them. In fact most students get acquainted just with the more common manipulations, which are illustrated by many examples in textbooks. Our exercises never require extensive calculations but tend to be somewhat unusual and force the solver to think about the problem starting from the principles, rather than by analogy with some previously solved exercise."

Thisvolumeexploresabductivecognition, animportantbut, atleastuntilthe third quarter of the last century, neglected topic in cognition. It integrates and further develops ideas already introduced in a previous book, which I published in 2001 (Abduction, Reason, and Science. Processes of Discovery and Explanation, Kluwer Academic/Plenum Publishers, New York). Thestatusofabductionisverycontroversial. Whendealingwithabductive reasoning misinterpretations and equivocations are common. What are the di?erences between abduction and induction? What are the di?erences - tween abduction and the well-known hypothetico-deductive method? What did Peircemeanwhen heconsideredabductionboth a kindofinferenceanda kind of instinct or when he considered perception a kind of abduction? Does abduction involve only the generation of hypotheses or their evaluation too? Are the criteria for the best explanation in abductive reasoning epistemic, or pragmatic, or both? Does abduction preserve ignorance or extend truth or both? How many kinds of abduction are there? Is abduction merely a kind of "explanatory" inference or does it involve other non-explanatory ways of guessing hypotheses? The book aims at increasing knowledge about creative and expert inf- ences. The study of these high-level methods of abductive reasoning is s- uated at the crossroads of philosophy, logic, epistemology, arti?cial intel- gence, neuroscience, cognitive psychology, animal cognition and evolutionary theories; that is, at the heart of cognitive science. Philosophers of science in thetwentiethcenturyhavetraditionallydistinguishedbetweentheinferential processesactiveinthelogicofdiscoveryandtheonesactiveinthelogicofj- ti?cation. Most have concluded that no logic of creative processes exists and, moreover, that a rational model of discovery is impossible. In short, scienti?c creative inferences are irrational and there is no "reasoning" to hypotheses.

Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deducible from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developed along the chapters, are able to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.

Adding one and one makes two, usually. But sometimes things add up to more than the sum of their parts. This observation, now frequently expressed in the maxim "more is different", is one of the characteristic features of complex systems and, in particular, complex networks. Along with their ubiquity in real world systems, the ability of networks to exhibit emergent dynamics, once they reach a certain size, has rendered them highly attractive targets for research. The resulting network hype has made the word "network" one of the most in uential buzzwords seen in almost every corner of science, from physics and biology to economy and social sciences. The theme of "more is different" appears in a different way in the present v- ume, from the viewpoint of what we call "adaptive networks." Adaptive networks uniquely combine dynamics on a network with dynamical adaptive changes of the underlying network topology, and thus they link classes of mechanisms that were previously studied in isolation. Here adding one and one certainly does not make two, but gives rise to a number of new phenomena, including highly robust se- organization of topology and dynamics and other remarkably rich dynamical beh- iors.

Multilayer networks is a rising topic in Network Science which characterizes the structure and the function of complex systems formed by several interacting networks. Multilayer networks research has been propelled forward by the wide realm of applications in social, biological and infrastructure networks and the large availability of network data, as well as by the significance of recent results, which have produced important advances in this rapidly growing field. This book presents a comprehensive account of this emerging field. It provides a theoretical introduction to the main results of multilayer network science.

The field of ultracold atomic physics has developed rapidly during the last two decades, and currently encompasses a broad range of topics in physics, with a variety of important applications in topics ranging from quantum computing and simulation to quantum metrology, and can be used to probe fundamental many-body effects such as superconductivity and superfluidity. Beginning with the underlying and including the most cutting-edge experimental developments, this textbook covers essential topics such as Bose-Einstein condensation of alkali atoms, studies of BEC-BCS crossover in degenerate Fermi gas, synthetic gauge fields and Hubbard models, and many-body localization and dynamical gauge fields. Key physical concepts, such as symmetry and universality highlight the connections between different systems, and theory is developed with plain derivations supported by experimental results. This self-contained and modern text will be invaluable for researchers, graduate students and advanced undergraduates studying cold atom physics, from both a theoretical and experimental perspective.

This book covers developments in the theory of oscillations from diverse viewpoints, reflecting the fields multidisciplinary nature. It introduces the state-of-the-art in the theory and various applications of nonlinear dynamics. It also offers the first treatment of the asymptotic and homogenization methods in the theory of oscillations in combination with Pad approximations. With its wealth of interesting examples, this book will prove useful as an introduction to the field for novices and as a reference for specialists.

In the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the current volume. Two research communities which have used graphical or network formalisms to particular advantage are the belief network community and the neural network community. Belief networks arose within computer science and statistics and were developed with an emphasis on prior knowledge and exact probabilistic calculations. Neural networks arose within electrical engineering, physics and neuroscience and have emphasised pattern recognition and systems modelling problems. This volume draws together researchers from these two communities and presents both kinds of networks as instances of a general unified graphical formalism. The book focuses on probabilistic methods for learning and inference in graphical models, algorithm analysis and design, theory and applications. Exact methods, sampling methods and variational methods are discussed in detail. Audience: A wide cross-section of computationally oriented researchers, including computer scientists, statisticians, electrical engineers, physicists and neuroscientists.

Computer Simulation Studies in Condensed-Matter Physics VIII covers recent developments in this field presented at the 1995 workshop, such as new algorithms, methods of analysis, and conceptual developments. This volume is composed of three parts. The first part contains invited papers that deal with simulational studies of classical systems. The second part is devoted to invited papers on quantum systems, including new results for strongly correlated electron and quantum spin models. The final part comprises contributed presentations.

One of the great intellectual challenges for the next few decades is the question of brain organization. What is the basic mechanism for storage of memory? What are the processes that serve as the interphase between the basically chemical processes of the body and the very specific and nonstatistical operations in the brain? Above all, how is concept formation achieved in the human brain? I wonder whether the spirit of the physics that will be involved in these studies will not be akin to that which moved the founders of the "rational foundation of thermodynamics". C. N. Yang! 10 The human brain is said to have roughly 10 neurons connected through about 14 10 synapses. Each neuron is itself a complex device which compares and integrates incoming electrical signals and relays a nonlinear response to other neurons. The brain certainly exceeds in complexity any system which physicists have studied in the past. Nevertheless, there do exist many analogies of the brain to simpler physical systems. We have witnessed during the last decade some surprising contributions of physics to the study of the brain. The most significant parallel between biological brains and many physical systems is that both are made of many tightly interacting components.

Interacting many-body systems are the main subjects of research in theoretical condensed matter physics, and they are the source of both the interest and the difficulty in this field. In order to understand the macroscopic properties of matter in terms of macroscopic knowledge, many analytic and approximate methods have been introduced. The contributions to this proceedings volume focus on the most recent developments of computational approaches in condensed matter physics. Monte Carlo methods and molecular dynamics simulations applied to strongly correlated classical and quantum systems such as electron systems, quantum spin systems, spin glassss, coupled map systems, polymers and other random and comlex systems are reviewed. Comprising easy to follow introductions to each field covered and also more specialized contributions, this proceedings volume explains why computational approaches are necessary and how different fields are related to each other.

Speech by Toyosaburo Taniguchi Dr. Kubo, Chairman, Distinguished Guests, and Friends, I am very happy, pleased and honored to be here this evening with so many distinguished guests, friends, and scholars from within this country and from different parts of the world. The Taniguchi Foundation wishes to extend a warm and sincere welcome to the many participants of the Ninth International Symposium on the Theory of Condensed Matter, which se ries was inaugurated eight years ago through the strenuous efforts of Dr. Ryogo Kubo, who is gracing us today with his presence. We are deeply indebted to Dr. Kubo, Dr. Suzuki, and their associates, who havE' spent an enormous amount of time and effort to make this particular symposium possible. We are convinced that the foundation should not be considered as what makes our symposium a success. The success is entirely due, I feel, to the continuous efforts of the Organizing Committee and of all those who have lent their support to this program. In this sense, your words of praise about the symposium, if any, should be directed to all of them. So far, I have met in person a total of 62 participants in this Division from 12 countries: Argentina, Belgium, Canada, Denmark, the Federal Republic of Germany, France, Ireland, Israel, Rumania, Switzerland, the United Kingdom, and the United States of America, with 133 participants from Japan. Those friends I have been privileged to make, I shall always treasure."

This book was originally conceived as a continuation in theme of the collec- tive monograph Limits of Predictability (Yu. A. Kravtsov, Ed. , Springer Series in Synergetics, Vol. 60, Springer-Verlag, Heidelberg, 1993). The main thrust of that book was to examine the various effects and factors (system non- stationarity, measurement noise, predictive model accuracy, and so on) that may limit, in a fundamental fashion, our ability to mathematically predict physical and man-made phenomena and events. Particularly interesting was the diversity of fields from which the papers and examples were drawn, in- cluding climatology, physics, biophysics, cybernetics, synergetics, sociology, and ethnogenesis. Twelve prominant Russian scientists, and one American (Prof. A. J. Lichtman) discussed their philosophical and scientific standpoints on the problem of the limits of predictability in their various fields. During the preparation of that book, the editor (Yu. A. K) had the great pleasure of interacting with world-renowned Russian scientists such as oceanologist A. S. Monin, geophysicist V. I. Keilis-Borok, sociologist I. V. Bestuzhev-Lada, histo- rian L. N. Gumilev, to name a few. Dr. Angela M. Lahee, managing editor of the Synergetics Series at Springer, was enormously helpful in the publishing of that book. In 1992, Prof. H. Haken along with Dr. Lahee kindly supported the idea of publishing a second volume on the theme of nonlinear system predictability, this time with a more international flavor.

At the present moment, after the success of the renormalization group in providing a conceptual framework for studying second-order phase tran sitions, we have a nearly satisfactory understanding of the statistical me chanics of classical systems with a non-random Hamiltonian. The situation is completely different if we consider the theory of systems with a random Hamiltonian or of chaotic dynamical systems. The two fields are connected; in fact, in the latter the effects of deterministic chaos can be modelled by an appropriate stochastic process. Although many interesting results have been obtained in recent years and much progress has been made, we still lack a satisfactory understanding of the extremely wide variety of phenomena which are present in these fields. The study of disordered or chaotic systems is the new frontier where new ideas and techniques are being developed. More interesting and deep results are expected to come in future years. The properties of random matrices and their products form a basic tool, whose importance cannot be underestimated. They playa role as important as Fourier transforms for differential equations. This book is extremely interesting as far as it presents a unified approach for the main results which have been obtained in the study of random ma trices. It will become a reference book for people working in the subject. The book is written by physicists, uses the language of physics and I am sure that many physicists will read it with great pleasure."

This volume contains the written versions of lectures held at the "23. Internationale Universit tswochen fUr Kernphysik" in Schladming, Austria, in February 1984. Once again the generous support of our sponsors, the Austrian Ministry of Science and Research, the Styrian Government and others, had made it possible to organize this school. The aim of the topics chosen for the meeting was to present different aspects of stochastic methods and techniques. These methods have opened up new ways to attack problems in a broad field ranging from quantum mechanics to quantum field theory. Thanks to the efforts of the lecturers it was possible to take this development into account and show relations to areas where stochastic methods have been used for a long time. Due to limited space only short manuscript versions of the many seminars presented could be included. The lecture notes were reexamined by the authors after the school and are now published in their final form. It is a pleasure to thank all the lecturers for their efforts which made it possible to speed up publication. Thanks are also due to Mrs. Neuhold for her careful typing of the notes. H. Mitter L. Pittner Acta Physica Austriaca, Suppl. XXVI, 3-52 (1984) (c) by Springer-Verlag 1984 STOCHASTIC PROCESSES - QUANTUM PHYSICS+ by L. STREIT Universitat Bielefeld BiBoS D-4800 Bielefeld. FR Germany I.

This book on "Polymer Fracture" might as well have been called "Kinetic Theory of Polymer Fracture." The term "kinetic theory," however, needs some de finition or, at least, some explanation. A kinetic theory deals with and particu larly considers the effect of the existence and discrete size, of the motion and of the physical properties of molecules on the macroscopic behavior of an ensemble, gaseous or other. A kinetic theory of strength does have to consider additional aspects such as elastic and anelastic deformations, chemical and physical reactions, and the sequence and distribution of different disintegration steps. In the last fifteen years considerable progress has been made in the latter do mains. The deformation and rupture of molecular chains, crystals, and morphologi cal structures have been intensively investigated. The understanding of the effect of those processes on the strength of polymeric materials has especially been furthered by the development and application of spectroscopical methods (ESR, IR) and of the tools offracture mechanics. It is the aim of this book to relate the conventional and successful statistical, parametrical, and continuum mechanical treatment of fracture phenomena to new results on the behavior of highly stressed molecular chains."

One high-level ability of the human brain is to understand what it has learned. This seems to be the crucial advantage in comparison to the brain activity of other primates. At present we are technologically almost ready to artificially reproduce human brain tissue, but we still do not fully understand the information processing and the related biological mechanisms underlying this ability. Thus an electronic clone of the human brain is still far from being realizable. At the same time, around twenty years after the revival of the connectionist paradigm, we are not yet satisfied with the typical subsymbolic attitude of devices like neural networks: we can make them learn to solve even difficult problems, but without a clear explanation of why a solution works. Indeed, to widely use these devices in a reliable and non elementary way we need formal and understandable expressions of the learnt functions. of being tested, manipulated and composed with These must be susceptible other similar expressions to build more structured functions as a solution of complex problems via the usual deductive methods of the Artificial Intelligence. Many effort have been steered in this directions in the last years, constructing artificial hybrid systems where a cooperation between the sub symbolic processing of the neural networks merges in various modes with symbolic algorithms. In parallel, neurobiology research keeps on supplying more and more detailed explanations of the low-level phenomena responsible for mental processes.

There are numerous technological materials - such as metals, polymers, ceramics, concrete, and many others - that vary in properties and serviceability. However, the almost universal common theme to most real materials is that their properties depend on the scale at which the analysis or observation takes place and at each scale "probabilities" play an important role. Here the word "probabilities" is used in a wider than the classical sense. In order to increase the efficiency and serviceability of these materials, researchers from NATO, CP and other countries were brought together to exchange knowledge and develop avenues for progress and applications in the st 21 century. The workshop began by reviewing progress in the subject area over the past few years and by identifying key questions that remain open. One point was how to observe/measure material properties at different scales and whether a probabilistic approach, at each scale, was always applicable and advantageous. The wide range of materials, from wood to advanced metals and from concrete to complex advanced composites, and the diversity of applications, e.g. fatigue, fracture, deformation, etc., were recognized as "obstacles" in identifying a "universal" approach.

This volume contains papers presented at the Thirteenth Taniguchi Symposium on the Theory of Condensed Matter, which was held at Kashikojima (in Ise Shima National Park), Japan, from 6th to 9th November, 1990. The topic of the symposium was Molecular Dynamics Simulations. The general objective of this series of the Taniguchi Symposia is to encour age developing fields of great promise in condensed matter physics. Our theme, molecular dynamics (MD) simulations, certainly fulfills this requirement, be cause the field is developing at a remarkable pace and its future is considered almost boundless. It was in the 1950s that the original idea of the MD methods was first pro posed and applied to the study of physical systems composed of many particles. In fact, the invention of the MD techniques occurred soon after the construction of the first computers. For almost 35 years since then, MD methods, together with Monte Carlo methods, have played major parts in the drama of computer simulations. The triumph of MD simulations is not confined to numerical aspects of detailed analyses of physical systems. MD simulations have verified some un expected facts and introduced some new concepts, all of which had never been predicted previously from analytical theories. The occurrence of the Alder tran sition in a system of repulsive particles and the behavior of the long-time tails of the velocity autocorrelation function for a liquid are just two examples of the results achieved by means of MD studies."