Unconventional computing
Unconventional computing is computing by any of a wide range of new or unusual methods.
The term unconventional computation was coined by Cristian S. Calude and John Casti and used at the First International Conference on Unconventional Models of Computation in 1998.
Background
The general theory of computation allows for a variety of methods of computation. Computing technology was first developed using mechanical systems and then evolved into the use of electronic devices. Other fields of modern physics provide additional avenues for development.Models of Computation
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. 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 conventional computers, while others do not. Some commonly used models are register machines, random-access machines, Turing machines, lambda calculus, rewriting systems, digital circuits, cellular automata, and Petri nets.
Mechanical computing
Historically, mechanical computers were used in industry before the advent of the transistor.Mechanical computers retain some interest today, both in research and as analogue computers. Some mechanical computers have a theoretical or didactic relevance, such as billiard-ball computers, while hydraulic ones like the MONIAC or the Water integrator were used effectively.
Analog computing
An analog computer is a type of computer that uses analog signals, which are continuous physical quantities, to model and solve problems. These signals can be electrical, mechanical, or hydraulic in nature. Analog computers were widely used in scientific and industrial applications, and were often faster than digital computers at the time. However, they started to become obsolete in the 1950s and 1960s and are now mostly used in specific applications such as aircraft flight simulators and teaching control systems in universities. Examples of analog computing devices include slide rules, nomograms, and complex mechanisms for process control and protective relays. The Antikythera mechanism, a mechanical device that calculates the positions of planets and the Moon, and the planimeter, a mechanical integrator for calculating the area of an arbitrary 2D shape, are also examples of analog computing.Electronic digital computers
Most modern computers are electronic computers with the Von Neumann architecture based on digital electronics, with extensive integration made possible following the invention of the transistor and the scaling of Moore's law.Unconventional computing is, "an interdisciplinary research area with the main goal to enrich or go beyond the standard models, such as the Von Neumann computer architecture and the Turing machine, which have dominated computer science for more than half a century". These methods model their computational operations based on non-standard paradigms, and are currently mostly in the research and development stage.
This computing behavior can be "simulated" using classical silicon-based micro-transistors or solid state computing technologies, but it aims to achieve a new kind of computing.
Generic approaches
These are unintuitive and pedagogical examples that a computer can be made out of almost anything.Physical objects
A billiard-ball computer is a type of mechanical computer that uses the motion of spherical billiard balls to perform computations. In this model, the wires of a Boolean circuit are represented by paths for the balls to travel on, the presence or absence of a ball on a path encodes the signal on that wire, and gates are simulated by collisions of balls at points where their paths intersect.A domino computer is a mechanical computer that uses standing dominoes to represent the amplification or logic gating of digital signals. These constructs can be used to demonstrate digital concepts and can even be used to build simple information processing modules.
Both billiard-ball computers and domino computers are examples of unconventional computing methods that use physical objects to perform computation.
Reservoir computing
Reservoir computing is a computational framework derived from recurrent neural network theory that involves mapping input signals into higher-dimensional computational spaces through the dynamics of a fixed, non-linear system called a reservoir. 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. One key benefit of reservoir computing is that it allows for a simple and fast learning algorithm, as well as hardware implementation through physical reservoirs.Tangible computing
Tangible computing refers to the use of physical objects as user interfaces for interacting with digital information. 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. There are five defining properties of tangible user interfaces, including the ability to multiplex both input and output in space, concurrent access and manipulation of interface components, strong specific devices, spatially aware computational devices, and spatial reconfigurability of devices.Human computing
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. The term has also been used more recently to describe individuals with exceptional mental arithmetic skills, also known as mental calculators.Human-robot interaction
Human-robot interaction, or HRI, is the study of interactions between humans and robots. It involves contributions from fields such as artificial intelligence, robotics, and psychology. Cobots, or collaborative robots, are designed for direct interaction with humans within shared spaces and can be used for a variety of tasks, including information provision, logistics, and unergonomic tasks in industrial environments.Swarm computing
Swarm robotics is a field of study that focuses on the coordination and control of multiple robots as a system. Inspired by the emergent behavior observed in social insects, swarm robotics involves the use of relatively simple individual rules to produce complex group behaviors through local communication and interaction with the environment. 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.Physics approaches
Optical computing
Optical computing is a type of computing that uses light waves, often produced by lasers or incoherent sources, for data processing, storage, and communication. While this technology has the potential to offer higher bandwidth than traditional computers, which use electrons, optoelectronic devices can consume a significant amount of energy in the process of converting electronic energy to photons and back. All-optical computers aim to eliminate the need for these conversions, leading to reduced electrical power consumption. Applications of optical computing include synthetic-aperture radar and optical correlators, which can be used for object detection, tracking, and classification.Spintronics
Spintronics is a field of study that involves the use of the intrinsic spin and magnetic moment of electrons in solid-state devices. It differs from traditional electronics in that it exploits the spin of electrons as an additional degree of freedom, which has potential applications in data storage and transfer, as well as quantum and neuromorphic computing. Spintronic systems are often created using dilute magnetic semiconductors and Heusler alloys.Atomtronics
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. These circuits have potential applications in several fields, including fundamental physics research and the development of practical devices such as sensors and quantum computers.Fluidics
Fluidics, or fluidic logic, is the use of fluid dynamics to perform analog or digital operations in environments where electronics may be unreliable, such as those exposed to high levels of electromagnetic interference or ionizing radiation. Fluidic devices operate without moving parts and can use nonlinear amplification, similar to transistors in electronic digital logic. Fluidics are also used in nanotechnology and military applications.Quantum computing
Quantum computing, perhaps the most well-known and developed unconventional computing method, is a type of computation that utilizes the principles of quantum mechanics, such as superposition and entanglement, to perform calculations. Quantum computers use qubits, which are analogous to classical bits but can exist in multiple states simultaneously, to perform operations. While current quantum computers may not yet outperform classical computers in practical applications, they have the potential to solve certain computational problems, such as integer factorization, significantly faster than classical computers. However, there are several challenges to building practical quantum computers, including the difficulty of maintaining qubits' quantum states and the need for error correction. Quantum complexity theory is the study of the computational complexity of problems with respect to quantum computers.Neuromorphic quantum computing
Neuromorphic Quantum Computing is an unconventional type of computing that uses neuromorphic computing to perform quantum operations. It was suggested that quantum algorithms, which are algorithms that run on a realistic model of quantum computation, can be computed equally efficiently with neuromorphic quantum computing.Both traditional quantum computing and neuromorphic quantum computing are physics-based unconventional computing approaches to computations and don't follow the von Neumann architecture. They both construct a system that represents the physical problem at hand, and then leverage their respective physics properties of the system to seek the "minimum". Neuromorphic quantum computing and quantum computing share similar physical properties during computation.