Unconventional computing: Difference between revisions

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==Background==

The general theory of [[computation]] allows for a variety of models.{{clarify|issue="models"methods seems like an undefined technical term or needless jargon this early in article|date=December 2022}}of computation. Computing technology was first developed using [[Machine (mechanical)|mechanical]] systems and then evolved into the use of electronic devices. Other fields of [[modern physics]] provide additional avenues for development.

===ComputationalModels modelof Computation===

{{main|ComputationalModel modelof computation}}

Computational models use computer programs to simulate and study complex systems using an algorithmic or mechanistic approach. They are commonly used to study complex nonlinear systems for which simple analytical solutions are not readily available.<ref>{{Cite web|title=Computational Modeling|url=https://www.nibib.nih.gov/science-education/science-topics/computational-modeling#:~:text=Computational%20modeling%20is%20the%20use,characterize%20the%20system%20being%20studied.|access-date=2021-04-07|website=www.nibib.nih.gov}}</ref> Experimentation with the model is done by adjusting parameters in the computer and studying the differences in the outcome.<ref>{{Cite web|title=Computational models - Latest research and news {{!}} Nature|url=https://www.nature.com/subjects/computational-models|access-date=2021-04-08|website=www.nature.com}}</ref> Operation theories of the model can be derived or deduced from these computational experiments. Examples of computational models include weather forecasting models, earth simulator models, flight simulator models, molecular protein folding models, and neural network models.

A model of computation describes how the output of a mathematical function is computed given its input. The model describes how units of computations, memories, and communications are organized.<ref>{{cite book|last=Savage|first=John E.|author-link = John E. Savage|title=Models Of Computation: Exploring the Power of Computing|year=1998|publisher=Addison-Wesley|ISBN= 978-0201895391}}</ref> The computational complexity of an algorithm can be measured given a model of computation. Using a model allows studying the performance of algorithms independently of the variations that are specific to particular implementations and specific technology.

A wide variety of models are commonly used; some closely resemble the workings of (idealized) conventional computers, while others do not. Some commonly used models are [[register machine]]s, [[random-access machine]]s, [[Turing machine]]s, [[lambda calculus]], [[rewriting system]]s, [[digital circuit]]s, [[cellular automaton|cellular automata]], and [[Petri net]]s.

===Mechanical computing===