Membrane computing (or MC) is an area within computer science that seeks to discover new computational models from the study of biological cells, particularly of the cellular membranes. It is a sub-task of creating a cellular model. Membrane computing deals with distributed and parallel computing models, processing multisets of symbol objects in a localized manner. Thus, evolution rules allow for evolving objects to be encapsulated into compartments defined by membranes. The communications between compartments and with the environment play an essential role in the processes. The various types of membrane systems are known as P systems after Gheorghe Păun who first conceived the model in 1998. An essential ingredient of a P system is its membrane structure, which can be a hierarchical arrangement of membranes, as in a cell, or a net of membranes (placed in the nodes of a graph), as in a tissue or a neural net. P systems are often depicted graphically with drawings. The intuition behind the notion of a membrane is a three-dimensional vesicle from biology. However the concept itself is more general, and a membrane is seen as a separator of two regions. The membrane provides for selective communication between the two regions. As per Gheorghe Păun, the separation is of the Euclidean space into a finite “inside” and an infinite “outside”. The selective communication is where the computing comes in. Graphical representations may have numerous elements, according to the variation of the model that is being studied. For example, a rule may produce the special symbol δ, in which case the membrane that contains it is dissolved and all its contents move up in the region hierarchy. The variety of suggestions from biology and the range of possibilities to define the architecture and the functioning of a membrane-based multiset processing device are practically endless. Indeed, the membrane computing literature contains a very large number of models. Thus, MC is not merely a theory related to a specific model, it is a framework for devising compartmentalized models. Chemicals are modeled by symbols, or alternatively by strings of symbols. The region, which is defined by a membrane, can contain other symbols or strings (collectively referred to as objects) or other membranes, so that a P system has exactly one outer membrane, called the skin membrane, and a hierarchical relationship governing all its membranes under the skin membrane. If objects are symbols, then their multiplicity within a region matters; however multi-sets are also used in some string models. Regions have associated rules that define how objects are produced, consumed, passed to other regions and otherwise interact with one another. The nondeterministic maximally parallel application of rules throughout the system is a transition between system states, and a sequence of transitions is called a computation. Particular goals can be defined to signify a halting state, at which point the result of the computation would be the objects contained in a particular region. Alternatively the result may be made up of objects sent out of the skin membrane to the environment. Many variant models have been studied, and interest has focused on proving computational universality for systems with a small number of membranes, for the purpose of solving NP-complete problems such as Boolean satisfiability (SAT) problems and the traveling salesman problem (TSP). The P systems may trade space and time complexities and less often use models to explain natural processes in living cells. The studies devise models that may at least theoretically be implemented on hardware. To date, the P systems are nearly all theoretical models that have never been reduced to practice, although a practical system is given in. (Wikipedia).
What Is Quantum Computing | Quantum Computing Explained | Quantum Computer | #Shorts | Simplilearn
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Quantum Computer in a Nutshell (Documentary)
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Quantum Computers, Explained With Quantum Physics
Quantum computers aren’t the next generation of supercomputers—they’re something else entirely. Before we can even begin to talk about their potential applications, we need to understand the fundamental physics that drives the theory of quantum computing. (Featuring Scott Aaronson, John Pr
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Current computing technology utilizes a binary computation system—that is, it reads code embedded with states of "on" or "off" (one or zero) to perform calculations. But scientists have been working to expand on the inherent limitations of such logic systems by using the fuzzy nature of su
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The landscape of Quantum Computing in Python (Tomas Babej)
Quantum computing is an exciting scientific field that is coming out of the lab to the real world (e.g. IBM, Google). Let's dive into basics of quantum computing and overview the tools that are available in Python. By the end of the talk, you will use them to program a quantum computer you
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Computer Basics: What Is a Computer?
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Quantum Computing for Beginners | How to get started with Quantum Computing
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Kevin Hoffman — Building a Containerless Future with WebAssembly
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How Proteins Get Where They’re Supposed to Go in Cells - T. Miller - 5/11/2016
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Black Hole Dynamics at large D by Shiraz Minwalla
Discussion Meeting The Future of Gravitational-Wave Astronomy ORGANIZERS: Parameswaran Ajith, K. G. Arun, B. S. Sathyaprakash, Tarun Souradeep and G. Srinivasan DATE: 19 August 2019 to 22 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore This discussion meeting, organized in c
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Multiscale modeling and simulations to bridge molecular... - 3 October 2018
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PROGRAM STATISTICAL BIOLOGICAL PHYSICS: FROM SINGLE MOLECULE TO CELL ORGANIZERS: Debashish Chowdhury (IIT-Kanpur, India), Ambarish Kunwar (IIT-Bombay, India) and Prabal K Maiti (IISc, India) DATE: 11 October 2022 to 22 October 2022 VENUE: Ramanujan Lecture Hall 'Fluctuation-and-noise' a
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9/23/17 Thomas Pollard - Cells on the Move
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Nanoscale mathematical modeling of synaptic transmission... - 10 October 2018
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4: Hodgkin-Huxley Model Part 1 - Intro to Neural Computation
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From playlist MIT 9.40 Introduction to Neural Computation, Spring 2018
Dynamic Spatiotemporal Determinants Modulate the Selectivity and Promiscuity by Nagarajan Vaidehi
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Operating system for beginners || Operating system basics
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Multiscale modeling and simulations to bridge molecular... - 5 October 2018
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