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Q is a programming language for array processing, developed by Arthur Whitney. It is proprietary software, commercialized by Kx Systems. Q serves as the query language for kdb+, a disk based and in-memory, column-based database. Kdb+ is based on the language k, a terse variant of the language APL. Q is a thin wrapper around k, providing a more ...
Q# works in conjunction with classical languages such as C#, Python and F#, and is designed to allow the use of traditional programming concepts in quantum computing, including functions with variables and branches as well as a syntax-highlighted development environment with a quantum debugger. [1] [5] [6]
List of software for Monte Carlo molecular modeling; Comparison of software for molecular mechanics modeling; Molecular design software; Molecule editor; Molecular modeling on GPUs; List of software for nanostructures modeling; Semi-empirical quantum chemistry method; Computational chemical methods in solid-state physics, with periodic boundary ...
Q Language is the second implemented imperative quantum programming language. [52] Q Language was implemented as an extension of C++ programming language. It provides classes for basic quantum operations like QHadamard, QFourier, QNot, and QSwap, which are derived from the base class Qop. New operators can be defined using C++ class mechanism.
Cython provides optional manual memory management by letting the user import malloc, realloc, and free from C, which they can then use in Python code. [ 19 ] D provides programmers with full control over its own garbage collector, including the ability to disable it outright.
SymPy is simple to install and to inspect because it is written entirely in Python with few dependencies. [ 4 ] [ 5 ] [ 6 ] This ease of access combined with a simple and extensible code base in a well known language make SymPy a computer algebra system with a relatively low barrier to entry.
These can be accessed programmatically using the Python-based Qiskit framework, or via graphical interface with the IBM Q Experience GUI. [15] Both are based on the OpenQASM standard for representing quantum operations. There is also a tutorial and online community. [16] Currently available simulators and quantum devices are:
Q-learning can identify an optimal action-selection policy for any given finite Markov decision process, given infinite exploration time and a partly random policy. [2] "Q" refers to the function that the algorithm computes: the expected reward—that is, the quality—of an action taken in a given state. [3]