Unconventional computing
No attempt is made[dubious – discuss] to build a functioning computer through the mechanical collisions of billiard balls.
[5] Examples of analog computing devices include slide rules, nomograms, and complex mechanisms for process control and protective relays.
These methods model their computational operations based on non-standard paradigms, and are currently mostly in the research and development stage.
The reservoir, which can be virtual or physical, is made up of individual non-linear units that are connected in recurrent loops, allowing it to store information.
Training is performed only at the readout stage, as the reservoir dynamics are fixed, and this framework allows for the use of naturally available systems, both classical and quantum mechanical, to reduce the effective computational cost.
This approach aims to take advantage of the human ability to grasp and manipulate physical objects in order to facilitate collaboration, learning, and design.
Characteristics of tangible user interfaces include the coupling of physical representations to underlying digital information and the embodiment of mechanisms for interactive control.
[15] The term "human computer" refers to individuals who perform mathematical calculations manually, often working in teams and following fixed rules.
In the past, teams of people were employed to perform long and tedious calculations, and the work was divided to be completed in parallel.
[18] This approach is characterized by the use of large numbers of simple robots and promotes scalability through the use of local communication methods such as radio frequency or infrared.
All-optical computers aim to eliminate the need for these conversions, leading to reduced electrical power consumption.
Atomtronics is a form of computing that involves the use of ultra-cold atoms in coherent matter-wave circuits, which can have components similar to those found in electronic or optical systems.
[26][27] These circuits have potential applications in several fields, including fundamental physics research and the development of practical devices such as sensors and quantum computers.
Fluidic devices operate without moving parts and can use nonlinear amplification, similar to transistors in electronic digital logic.
[28][29] Quantum computers use qubits, which are analogous to classical bits but can exist in multiple states simultaneously, to perform operations.
These devices typically consist of a central processing unit (such as an integrated circuit) and several components that interact with their surroundings, such as sensors.
Data is represented by variations in chemical concentrations,[42] and the goal of this type of computing is to use the smallest stable structures, such as single molecules, as electronic components.
It offers advantages over DNA computing, such as a larger number of building blocks and more flexible interactions, but has not yet been practically realized due to the limited availability of specific monoclonal antibodies.
While these systems have largely remained theoretical,[46] some have been shown to have the potential to solve NP-complete problems and have been proposed as hardware implementations for unconventional computing.
It encompasses a range of computational paradigms including artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, and more, which can be implemented using traditional electronic hardware or alternative physical media such as biomolecules or trapped-ion quantum computing devices.
[49][50] These systems can be implemented using a variety of hardware, such as memristors,[51] spintronic memories, and transistors,[52][53] and can be trained using a range of software-based approaches, including error backpropagation[54] and canonical learning rules.
Cellular automata are discrete models of computation consisting of a grid of cells in a finite number of states, such as on and off.
There are four primary classifications of cellular automata, ranging from patterns that stabilize into homogeneity to those that become extremely complex and potentially Turing-complete.
In order for a computation to be reversible, the relation between states and their successors must be one-to-one, and the process must not result in an increase in physical entropy.
Chaotic systems can be used to create logic gates and can be rapidly switched between different patterns, making them useful for fault-tolerant applications and parallel computing.
