Quantum computers are likely to return power consumption from 100 to 1000 times since they operate at very low temperatures at which the processor would work as a superconductor. Also, quantum computers are capable of accelerating machine learning processes, reducing thousands of years of learning to mere seconds. Quantum computers are based on quantum bits which have two possible values either a 0 or 1. And so quantum computers are used by the big tech companies such as IBM and Google. Quantum programming languages are the foundations to interpret ideas into instructions to be carried out by quantum computers. Here are the top quantum programming languages to know for 2022.
Quantum computing language is one of the first implemented quantum programming languages that resembles C language in regards to syntax and data types. It is usually used for writing programs for quantum computers. As every quantum machine has to be controlled by classical devices, the pre-existing quantum programming languages incorporate classical control structures like loops and conditional execution and allow them to operate on classical and quantum data.
Quantum macro assembler was published in 2016. It is a kind of low-level language that is specially used for quantum annealing. The significance of QMASM relieves the programmer from having to know system-specific hardware details while still allowing programs to be expressed at a low level of abstraction.
Silq was originally published in 2020. It is a high-level programming language when compared to the QCL and AMASM. It is written in D language which has 482 stars and 10 contributions on github and is regularly updated too.
QML was published in 2007, it is a Haskell-like quantum programming language that is based on strict linear logic. It has the capability to integrate reversible and irreversible quantum computations. It is a user interface specification and programming languages that allows developers and designers alike to create highly performant, fluidly animated, and visually appealing applications.
Quantum lambda calculus is based on classical lambda calculus introduced in 1930 and was defined for calculations in 1996. It is one of the stronger programming languages than the standard quantum computational models such as the quantum Turing machine or the quantum circuit model.
Semantically QFC and QPL are equivalent. However, in QFC, quantum programs are represented using flowchart syntax, but in the QPL syntactic structure of quantum, programs are represented using textual representations.
There are a few challenges with regard to quantum programming languages. Let's see what they are:
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