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Neuromorphic quantum computing (abbreviated as ‘n.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 ...
Quil is a quantum instruction set architecture that first introduced a shared quantum/classical memory model. It was introduced by Robert Smith, Michael Curtis, and William Zeng in A Practical Quantum Instruction Set Architecture. [1]
Quantum lambda calculi are extensions of the classical lambda calculus introduced by Alonzo Church and Stephen Cole Kleene in the 1930s. The purpose of quantum lambda calculi is to extend quantum programming languages with a theory of higher-order functions. The first attempt to define a quantum lambda calculus was made by Philip Maymin in 1996 ...
This intermediate-scale is defined by the quantum volume, which is based on the moderate number of qubits and gate fidelity. The term NISQ was coined by John Preskill in 2018. [6] [2] According to Microsoft Azure Quantum's scheme, NISQ computation is considered level 1, the lowest of the quantum computing implementation levels. [7] [8]
The book is suitable as an introduction to quantum computing for computer scientists, mathematicians, and physicists, requiring of them only a background in linear algebra and the theory of complex numbers, [2] [3] although reviewer Donald L. Vestal suggests that additional background in the theory of computation, abstract algebra, and information theory would also be helpful. [4]
For combinatorial optimization, the quantum approximate optimization algorithm (QAOA) [6] briefly had a better approximation ratio than any known polynomial time classical algorithm (for a certain problem), [7] until a more effective classical algorithm was proposed. [8] The relative speed-up of the quantum algorithm is an open research question.
In a quantum circuit, the vectors are used to represent the state of the qubits and different matrices are used to represent the gate that is applied on the qubits. Since linear algebra is a major component of the quantum simulation, Field Programmable Gate Arrays could be used to accelerate the simulation of quantum computing. FPGA is a kind ...
Quantum networks form an important element of quantum computing and quantum communication systems. Quantum networks facilitate the transmission of information in the form of quantum bits, also called qubits, between physically separated quantum processors. A quantum processor is a machine able to perform quantum circuits on a certain number of ...
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