Computation of time

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Computer science Study of the foundations and applications of computation

Computer science involves the study of or the practice of computation, automation, and information. Computer science spans theoretical disciplines to practical disciplines. Computer science is generally considered an area of academic research and distinct from computer programming.

Computational linguistics is an interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others.

Computational chemistry is a branch of chemistry that uses computer simulation to assist in solving chemical problems. It uses methods of theoretical chemistry, incorporated into computer programs, to calculate the structures and properties of molecules, groups of molecules, and solids. It is necessary because, apart from relatively recent results concerning the hydrogen molecular ion, the quantum many-body problem cannot be solved analytically, much less in closed form. While computational results normally complement the information obtained by chemical experiments, it can in some cases predict hitherto unobserved chemical phenomena. It is widely used in the design of new drugs and materials.

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In theoretical computer science, a nondeterministic Turing machine (NTM) is a theoretical model of computation whose governing rules specify more than one possible action when in some given situations. That is, an NTM's next state is not completely determined by its action and the current symbol it sees, unlike a deterministic Turing machine.

Quantum computing Study of a model of computation

Quantum computing is a type of computation that harnesses the collective properties of quantum states, such as superposition, interference, and entanglement, to perform calculations. The devices that perform quantum computations are known as quantum computers. Though current quantum computers are too small to outperform usual (classical) computers for practical applications, they are believed to be capable of solving certain computational problems, such as integer factorization, substantially faster than classical computers. The study of quantum computing is a subfield of quantum information science.

In computability theory, a system of data-manipulation rules is said to be Turing-complete or computationally universal if it can be used to simulate any Turing machine. This means that this system is able to recognize or decide other data-manipulation rule sets. Turing completeness is used as a way to express the power of such a data-manipulation rule set. Virtually all programming languages today are Turing-complete. The concept is named after English mathematician and computer scientist Alan Turing.

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Outline of academic disciplines Overviews of and topical guides to academic disciplines

An academic discipline or field of study is a branch of knowledge, taught and researched as part of higher education. A scholar's discipline is commonly defined by the university faculties and learned societies to which they belong and the academic journals in which they publish research.

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The Margolus–Levitin theorem, named for Norman Margolus and Lev B. Levitin, gives a fundamental limit on quantum computation (strictly speaking on all forms on computation). The processing rate cannot be higher than 6 × 1033 operations per second per joule of energy. Or stating the bound for one bit:

The simulation hypothesis is a proposal regarding the nature of existence which posits that all of existence is an artificial simulation, such as a computer simulation. Some versions rely on the development of a simulated reality, a proposed technology that would be able to convince its inhabitants that the simulation was "real".

Indeterminacy is a property of formal systems that evolve in time, in which complete information about the internal state of the system at some point in time admits multiple future trajectories.

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In computer science, the analysis of parallel algorithms is the process of finding the computational complexity of algorithms executed in parallel – the amount of time, storage, or other resources needed to execute them. In many respects, analysis of parallel algorithms is similar to the analysis of sequential algorithms, but is generally more involved because one must reason about the behavior of multiple cooperating threads of execution. One of the primary goals of parallel analysis is to understand how a parallel algorithm's use of resources changes as the number of processors is changed.

In the canon law of the Catholic Church, the computation of time, also translated as the reckoning of time, is the manner by which legally-specified periods of time are calculated according to the norm of the canons on the computation of time. The application of laws frequently involves a question of time: generally three months must elapse after their promulgation before they go into effect; some obligations have to be fulfilled within a certain number of days, or weeks, or months. Hence the need of the rules for the computation of time. With the Code of 1917 and the reformed Code of 1983, the legislator has formulated these rules with a clearness and precision that they never had before.