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Quantum cellular automaton

Quantum cellular automaton is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Quantum cellular automaton rather than just read about it. In short: A quantum cellular automaton (QCA) is an abstract model of quantum computation, devised in analogy to conventional models of cellular automata introduced by John von Neumann. The same name may also refer to quantum dot cellular automata, which are a proposed physical implementation of "classical" cellular automata by exploiting quantum mechanical phenomena.

Key takeaways

  • Quantum cellular automaton belongs to physics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Quantum cellular automaton to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Quantum cellular automaton from memory before moving on to harder problems.

Reference excerpt

A quantum cellular automaton (QCA) is an abstract model of quantum computation, devised in analogy to conventional models of cellular automata introduced by John von Neumann. The same name may also refer to quantum dot cellular automata, which are a proposed physical implementation of "classical" cellular automata by exploiting quantum mechanical phenomena. QCA have attracted attention in nanofabrication, due to its extremely small feature size (at the molecular or even atomic scale) and ultra-low power consumption. This makes it a candidate for replacing CMOS technology.

Usage of the term In the context of models of computation or of physical systems, quantum cellular automaton refers to the merger of elements of both (1) the study of cellular automata in conventional computer science and (2) the study of quantum information processing. In particular, the following are features of models of quantum cellular automata:

The computation is considered to come about by parallel operation of multiple computing devices, or cells. The cells are usually taken to be identical, finite-dimensional quantum systems (e.g. each cell is a qubit). Each cell has a neighborhood of other cells. Altogether these form a network of cells, which is usually taken to be regular (e.g. the cells are arranged as a lattice with or without periodic boundary conditions). The evolution of all of the cells has a number of physics-like symmetries. Locality is one: the next state of a cell depends only on its current state and that of its neighbours. Homogeneity is another: the evolution acts the same everywhere, and is independent of time. The state space of the cells, and the operations performed on them, should be motivated by principles of quantum mechanics. Another feature that is often considered important for a model of quantum cellular automata is that it should be universal for quantum computation (i.e. that it can efficiently simulate quantum Turing machines, some arbitrary quantum circuit or simply all other quantum cellular automata). Models which have been proposed recently impose further conditions, e.g. that quantum cellular automata should be reversible and/or locally unitary, and have an easily determined global transition function from the rule for updating individual cells. Recent results show that these properties can be derived axiomatically, from the symmetries of the global evolution.

Models

Early proposals In 1982, Richard Feynman suggested an initial approach to quantizing a model of cellular automata. In 1985, David Deutsch presented a formal development of the subject. Later, Gerhard Grössing and Anton Zeilinger introduced the term "quantum cellular automata" to refer to a model they defined in 1988, although their model had very little in common with the concepts developed by Deutsch and so has not been developed significantly as a model of computation.

Models of universal quantum computation The first formal model of quantum cellular automata to be researched in depth was that introduced by John Watrous. This model was developed further by Wim van Dam, as well as Christoph Dürr, Huong LêThanh, and Miklos Santha, Jozef Gruska. and Pablo Arrighi. However it was later realised that this definition was too loose, in the sense that some instances of it allow superluminal signalling. A second wave of models includes those of Susanne Richter and Reinhard Werner, of Benjamin Schumacher and Reinhard Werner, of Carlos Pérez-Delgado and Donny Cheung, and of Pablo Arrighi, Vincent Nesme and Reinhard Werner. These are all closely related, and do not suffer any such locality issue. In the end one can say that they all agree to picture quantum cellular automata as just some large quantum circuit, infinitely repeating across time and space. Recent reviews of the topic are available here.

Models of physical systems Models of quantum cellular automata have been proposed by David Meyer, Bruce Boghosian and Washington Taylor, and Peter Love and Bruce Boghosian as a means of simulating quantum lattice gases, motivated by the use of "classical" cellular automata to model classical physical phenomena such as gas dispersion. Criteria determining when a quantum cellular automaton (QCA) can be described as quantum lattice gas automaton (QLGA) were given by Asif Shakeel and Peter Love.

Quantum dot cellular automata

A proposal for implementing classical cellular automata by systems designed with quantum dots has been proposed under the name "quantum cellular automata" by Doug Tougaw and Craig Lent, as a replacement for classical computation using CMOS technology. In order to better differentiate between this proposal and models of cellular automata which perform quantum computation, many authors working on this subject now refer to it as "quantum dot cellular automaton".

Models of particle physics Many QCAs that simulate quantum field theories in the continuum limit have been devised, and some of them are variants of QCAs on fermionic cells—the so-called Fermionic Cellular Automata (FCA). The simplest ones are Dirac QCAs that, for low-momentum and low mass regime, behave like a Dirac particle. The massless version of one of the Dirac QCAs, also known as Weyl QCA, was shown to reproduce the dynamics and statistics of the electromagnetic field in vacuum. Some other QCAs that simulate quantum electrodynamics have also been constructed. However, there remain some problems with these models. For instance, it is not clear how to define a free Dirac vacuum in such models that is stable.

See also Quantum finite automata – Quantum analog of probabilistic automataPages displaying short descriptions of redirect targets Quantum Hall effect – Electromagnetic effect in physics

References

Worked examples

Example 1 — a first encounter with Quantum cellular automaton

Start with the simplest possible case. Write down what Quantum cellular automaton claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Quantum cellular automaton before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Quantum cellular automaton ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Quantum cellular automaton

In research
Quantum cellular automaton appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Quantum cellular automaton in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Quantum cellular automaton is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cellular automata, Quantum information science, Richard Feynman, so understanding it makes those chapters shorter.
In everyday life
Look for Quantum cellular automaton outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Quantum cellular automaton in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Quantum cellular automaton means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Quantum cellular automaton out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Quantum cellular automaton in simple terms?

A quantum cellular automaton (QCA) is an abstract model of quantum computation, devised in analogy to conventional models of cellular automata introduced by John von Neumann. The same name may also refer to quantum dot cellular automata, which are a proposed physical implementation of "classical" c…

Why does Quantum cellular automaton matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Quantum cellular automaton?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Quantum cellular automaton.

Tags

  • Cellular automata
  • Quantum information science
  • Richard Feynman

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