Competition Within Random Growth Models
Download Competition Within Random Growth Models full books in PDF, epub, and Kindle. Read online free Competition Within Random Growth Models ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Random Growth Models
Author | : Michael Damron |
Publisher | : American Mathematical Soc. |
Total Pages | : 274 |
Release | : 2018-09-27 |
Genre | : Mathematics |
ISBN | : 1470435535 |
The study of random growth models began in probability theory about 50 years ago, and today this area occupies a central place in the subject. The considerable challenges posed by these models have spurred the development of innovative probability theory and opened up connections with several other parts of mathematics, such as partial differential equations, integrable systems, and combinatorics. These models also have applications to fields such as computer science, biology, and physics. This volume is based on lectures delivered at the 2017 AMS Short Course “Random Growth Models”, held January 2–3, 2017 in Atlanta, GA. The articles in this book give an introduction to the most-studied models; namely, first- and last-passage percolation, the Eden model of cell growth, and particle systems, focusing on the main research questions and leading up to the celebrated Kardar-Parisi-Zhang equation. Topics covered include asymptotic properties of infection times, limiting shape results, fluctuation bounds, and geometrical properties of geodesics, which are optimal paths for growth.
Competition and Growth
Author | : Philippe Aghion |
Publisher | : MIT Press |
Total Pages | : 115 |
Release | : 2008-01-25 |
Genre | : Business & Economics |
ISBN | : 0262512025 |
Though competition occupies a prominent place in the history of economic thought, among economists today there is still a limited, and sometimes contradictory, understanding of its impact. In Competition and Growth, Philippe Aghion and Rachel Griffith offer the first serious attempt to provide a unified and coherent account of the effect competition policy and deregulated entry has on economic growth. The book takes the form of a dialogue between an applied theorist calling on "Schumpeterian growth" models and a microeconometrician employing new techniques to gauge competition and entry. In each chapter, theoretical models are systematically confronted with empirical data, which either invalidates the models or suggests changes in the modeling strategy. Aghion and Griffith note a fundamental divorce between theorists and empiricists who previously worked on these questions. On one hand, existing models in industrial organization or new growth economics all predict a negative effect of competition on innovation and growth: namely, that competition is bad for growth because it reduces the monopoly rents that reward successful innovators. On the other hand, common wisdom and recent empirical studies point to a positive effect of competition on productivity growth. To reconcile theory and evidence, the authors distinguish between pre- and post-innovation rents, and propose that innovation may be a way to escape competition, an idea that they confront with microeconomic data. The book's detailed analysis should aid scholars and policy makers in understanding how the benefits of tougher competition can be achieved while at the same time mitigating the negative effects competition and imitation may have on some sectors or industries.
Random Fluctuations and Pattern Growth: Experiments and Models
Author | : Harry Eugene Stanley |
Publisher | : Springer Science & Business Media |
Total Pages | : 366 |
Release | : 2012-12-06 |
Genre | : Science |
ISBN | : 9400926537 |
Proceedings of the NATO Advanced Study Institute, Cargèse, Corsica, France, 18-31 July, 1988
Non-equilibrium Surface Growth for Competitive Growth Models and Applications to Conservative Parallel Discrete Event Simulations
Author | : Poonam Santosh Verma |
Publisher | : |
Total Pages | : |
Release | : 2007 |
Genre | : Computer algorithms |
ISBN | : |
Non-equilibrium surface growth for competitive growth models in (1+1) dimensions, particularly mixing random deposition (RD) with correlated growth process which occur with probability p are studied. The composite mixtures are found to be in the universality class of the correlated growth process, and a nonuniversal exponent _ is identified in the scaling in p. The only effects of the RD admixture are dilations of the time and height scales which result in a slowdown of the dynamics of building up the correlations. The bulk morphology is taken into account and is reflected in the surface roughening, as well as the scaling behavior. It is found that the continuum equations and scaling laws for RD added, in particular, to Kardar-Parisi-Zhang (KPZ) processes are partly determined from the underlying bulk structures. Nonequilibrium surface growth analysis are also applied to a study of the static and dynamic load balancing for a conservative update algorithm for Parallel Discrete Event Simulations (PDES). This load balancing is governed by the KPZ equation. For uneven load distributions in conservative PDES simulations, the simulated (virtual) time horizon (VTH) per Processing Element (PE) and the simulated time horizon per volume element Nv are used to study the PEs progress in terms of utilization. The width of these time horizons relates to the desynchronization of the system of processors, and is related to the memory requirements of the PEs. The utilization increases when dynamic, rather than static, load balancing is performed.
Competition and Growth
Author | : J. K. Sengupta |
Publisher | : Springer |
Total Pages | : 185 |
Release | : 2004-10-14 |
Genre | : Business & Economics |
ISBN | : 0230505317 |
Jati K. Sengupta examines the market dynamics of the evolution of industry and the impact of new technology with R&D and knowledge capital. The book builds the theory of innovations in the contexts of the high-tech industries of today such as computing and telecommunications.
Competition Theory in Ecology
Author | : Peter A. Abrams |
Publisher | : Oxford University Press |
Total Pages | : 336 |
Release | : 2022-08-25 |
Genre | : Science |
ISBN | : 0192648098 |
Competition between species arises when two or more species share at least some of the same limited resources. It is likely to affect all species, as well as many higher-level aspects of community and ecosystem dynamics. Interspecific competition shares many of the same features as density dependence (intraspecific competition) and evolution (competition between genotypes). In spite of this, a robust theoretical framework is not yet in place to develop a more coherent understanding of this important interaction. Despite its prominence in the ecological literature, the theory seems to have lost direction in recent decades, with many synthetic papers promoting outdated ideas, failing to use resource-based models, and having little utility in applied fields such as conservation and environmental management. Competition theory has done little to incorporate new findings regarding consumer-resource interactions in the context of larger food webs containing behaviourally or evolutionarily adapting components. Overly simple models and methods of analysis continue to be influential. Competition Theory in Ecology represents a timely opportunity to address these shortcomings and suggests a more useful approach to modelling that can provide a basis for future models that have greater predictive ability in both ecology and evolution. The book concludes with some broader observations on the lack of agreement on general principles to use in constructing mathematical models to help understand ecological systems. It argues that a more open discussion and debate of the underlying structure of ecological theory is now urgently required to move the field forward.
Individual-Based Models and Approaches In Ecology
Author | : D. L. DeAngelis |
Publisher | : CRC Press |
Total Pages | : 577 |
Release | : 2018-01-18 |
Genre | : Mathematics |
ISBN | : 1351090364 |
Until fairly recently, populations were handled as homogenized averages, which made modeling feasible but which ignored the essential fact that in any population there is a great variety of individuals of different ages, sizes, and degrees of fitness. Recently, because of the increased availability of affordable computer power, approaches have been developed which are able to recognize individual differences. Individual-based models are of great use in the areas of aquatic ecology, terrestrial ecology, landscape or physiological ecology, terrestrial ecology, landscape or physiological ecology, and agriculture. This book discusses which biological problems individual-based models can solve, as well as the models' inherent limitations. It explores likely future directions of theoretical development in these models, as well as currently feasible management applications and the best mathematical approaches and computer languages to use. The book also details specific applications to theory and management.
A Biologist's Guide to Mathematical Modeling in Ecology and Evolution
Author | : Sarah P. Otto |
Publisher | : Princeton University Press |
Total Pages | : 745 |
Release | : 2011-09-19 |
Genre | : Science |
ISBN | : 1400840910 |
Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own. The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction. Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists. A how-to guide for developing new mathematical models in biology Provides step-by-step recipes for constructing and analyzing models Interesting biological applications Explores classical models in ecology and evolution Questions at the end of every chapter Primers cover important mathematical topics Exercises with answers Appendixes summarize useful rules Labs and advanced material available