Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

Proceedings of AUTOMATA 2010: 16th International workshop on cellular automata and discrete complex systems

International audienceThese local proceedings hold the papers of two catgeories: (a) Short, non-reviewed papers (b) Full paper

Collective analog bioelectronic computation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 677-710).In this thesis, I present two examples of fast-and-highly-parallel analog computation inspired by architectures in biology. The first example, an RF cochlea, maps the partial differential equations that describe fluid-membrane-hair-cell wave propagation in the biological cochlea to an equivalent inductor-capacitor-transistor integrated circuit. It allows ultra-broadband spectrum analysis of RF signals to be performed in a rapid low-power fashion, thus enabling applications for universal or software radio. The second example exploits detailed similarities between the equations that describe chemical-reaction dynamics and the equations that describe subthreshold current flow in transistors to create fast-and-highly-parallel integrated-circuit models of protein-protein and gene-protein networks inside a cell. Due to a natural mapping between the Poisson statistics of molecular flows in a chemical reaction and Poisson statistics of electronic current flow in a transistor, stochastic effects are automatically incorporated into the circuit architecture, allowing highly computationally intensive stochastic simulations of large-scale biochemical reaction networks to be performed rapidly. I show that the exponentially tapered transmission-line architecture of the mammalian cochlea performs constant-fractional-bandwidth spectrum analysis with O(N) expenditure of both analysis time and hardware, where N is the number of analyzed frequency bins. This is the best known performance of any spectrum-analysis architecture, including the constant-resolution Fast Fourier Transform (FFT), which scales as O(N logN), or a constant-fractional-bandwidth filterbank, which scales as O (N2).(cont.) The RF cochlea uses this bio-inspired architecture to perform real-time, on-chip spectrum analysis at radio frequencies. I demonstrate two cochlea chips, implemented in standard 0.13m CMOS technology, that decompose the RF spectrum from 600MHz to 8GHz into 50 log-spaced channels, consume < 300mW of power, and possess 70dB of dynamic range. The real-time spectrum analysis capabilities of my chips make them uniquely suitable for ultra-broadband universal or software radio receivers of the future. I show that the protein-protein and gene-protein chips that I have built are particularly suitable for simulation, parameter discovery and sensitivity analysis of interaction networks in cell biology, such as signaling, metabolic, and gene regulation pathways. Importantly, the chips carry out massively parallel computations, resulting in simulation times that are independent of model complexity, i.e., O(1). They also automatically model stochastic effects, which are of importance in many biological systems, but are numerically stiff and simulate slowly on digital computers. Currently, non-fundamental data-acquisition limitations show that my proof-of-concept chips simulate small-scale biochemical reaction networks at least 100 times faster than modern desktop machines. It should be possible to get 103 to 106 simulation speedups of genome-scale and organ-scale intracellular and extracellular biochemical reaction networks with improved versions of my chips. Such chips could be important both as analysis tools in systems biology and design tools in synthetic biology.by Soumyajit Mandal.Ph.D

Artificial Brownian motors: Controlling transport on the nanoscale

In systems possessing spatial or dynamical symmetry breaking, Brownian motion combined with symmetric external input signals, deterministic or random, alike, can assist directed motion of particles at the submicron scales. In such cases, one speaks of "Brownian motors". In this review the constructive role of Brownian motion is exemplified for various one-dimensional setups, mostly inspired by the cell molecular machinery: working principles and characteristics of stylized devices are discussed to show how fluctuations, either thermal or extrinsic, can be used to control diffusive particle transport. Recent experimental demonstrations of this concept are reviewed with particular attention to transport in artificial nanopores and optical traps, where single particle currents have been first measured. Much emphasis is given to two- and three-dimensional devices containing many interacting particles of one or more species; for this class of artificial motors, noise rectification results also from the interplay of particle Brownian motion and geometric constraints. Recently, selective control and optimization of the transport of interacting colloidal particles and magnetic vortices have been successfully achieved, thus leading to the new generation of microfluidic and superconducting devices presented hereby. Another area with promising potential for realization of artificial Brownian motors are microfluidic or granular set-ups.....Comment: 57 pages, 39 figures; submitted to Reviews Modern Physics, revised versio

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Isolated Quantum Systems: Dynamics and Phase Structure Far From Equilibrium

Statistical mechanics characterizes systems in or near equilibrium using in terms of a handful of "state" variables, e.g. temperature, rather than infinitely many degrees of freedom. Statistical physics describes the expansion of the early universe, aspects of black holes, and most fruitfully, phases of matter and their properties. Quantum considerations have improved this understanding over time and revealed new phenomena, especially in complicated "strongly correlated" systems. Topological phases of matter, e.g., are of both fundamental and practical interest: these phases cannot be distinguished locally, unlike ice and water, which also allows them to store and process quantum information in a "fault-tolerant" manner, recently proposed for application to quantum computation. However, above zero temperature, thermal effects can overwrite this information.Recent experiments on isolated systems have raised fundamental questions and revealed new routes to quantum computing. We now know that entanglement, generated dynamically as a quantum state evolves, "hides" local information about the past, producing familiar equilibrium states, described by a temperature. However, many systems do not thermalize: strong disorder can lead to MBL, which supports numerous phenomena forbidden in equilibrium and can protect quantum information at infinite temperature. In particular, both MBL and thermal systems are robust phases of matter, with a novel, athermal phase transition between them. This thesis begins with an overview of MBL and thermalization, followed by an overview of exactly soluble quantum systems. We then turn to an important result in the field by this author: we introduce the first nontrivial example of an integrable Floquet model and comment on its solution and salient features. We then discuss how integrable models can provide insight into quantum thermalization, e.g. in terms of entanglement growth and demonstrating that conserved charges diffuse. We then investigate thermalization away from the integrable limit, also known as "quantum chaos." We review the standard techniques in this field and, briefly, several important results, before reproducing work by this author establishing definitively the long-conjectured result that the onset of thermalization in the presence of a conserved charge is governed by diffusion of said charge. We then investigate the interplay of conventional and topological order with nonequilibrium phase structure, with applications to quantum computation in mind. We review localization-protected quantum order in several models. We then investigate two models with non-Abelian symmetry, and show that MBL in such models can only realize if the symmetry breaks spontaneously to an Abelian subgroup. Finally, we conclude by examining open quantum systems, where we find several counterintuitive results that show that baths can, in some cases, enhance localization in certain systems, which may have use in realizing quantum computation

College of Engineering

Cornell University Courses of Study Vol. 91 1999/200

College of Engineering

Cornell University Courses of Study Vol. 91 1999/200

College of Engineering

Cornell University Courses of Study Vol. 93 2001/200