Before you talk about quantum programming’, you should leave your past programming experience aside and start a clean slate; Because quantum programming is not just a way to run our existing programs faster. Quantum Programming logic and approach are different from modern programming and are based on different paradigms.

Quantum Programming is the process of programming sequences of commands, called Quantum Programs, that can run on a Quantum Computer. Quantum Programming Languages, on the other hand, make use of high–level structures to express Quantum Algorithms.

The Development of Quantum Programming

The first studies on Quantum Programming were made in the early 2000s. However, these researches have generally been limited to theoretical studies and simple programming languages. These limitations are that there is not enough interest in Quantum Computing yet. Furthermore, the practical barriers separating us from Quantum Computers were so significant that questions about programming such hypothetical machines seemed irrelevant. However, with substantial experimental advances, recently designed universal Quantum Computers have reversed this trend.

These developments have brought the question of “How do we program a quantum computer?”. To answer this question correctly, we need to describe the basic operations of Quantum Algorithms to describe natural and well–structured programming languages. Ideally, a Quantum Programming Language should allow us to implement existing Quantum Algorithms and facilitate the discovery of new ones. On the other hand, to be compilable, when a Quantum Algorithm is implemented in a programming language, it must be converted into a set of operations that can be physically performed on the hardware. This compilation should be conducted to continue the computational advantage we hope to achieve using a Quantum Computer. Quantum compilers are essential for the creation of quantum advantage.

Recent advances in practical Quantum Computing revive old questions about Quantum Programming and raise new questions that Quantum Programming can help answer.

Indeed, it has been crucial to understanding what to do with the first–generation Quantum Computers looming on the horizon. To describe computational problems that can be solved with such devices, one must move from an asymptotic understanding of Quantum Algorithms to a more concrete solution.

Scalable Quantum Programming Languages ​​and efficient Quantum Compilers can assist in understanding and minimizing the tangible cost of Quantum Algorithms.

How is Quantum Programming Done?

Quantum Programming; It can be done on IBM Quantum Experience, Microsoft Azure Quantum, D–Wave Leap Cloud, or through quantum development kits.

Here are a few options where you can do quantum programming:

• Use of the programmable Microsoft Quantum Development Kit (Quantum Development Kit) with the Q# programming language developed by Microsoft (alternatively, it can be programmed with Python),
• Using the Python programming language and IBM’s open–source Qiskit library.

Quantum Programming is currently in its infancy. Nevertheless, it is used to solve complex Quantum Algorithms. In addition, problems that are close to impossible to solve and take a long time to be solved by the classical computer can be solved very quickly.

Quantum Programming Languages

Quantum Languages, Quantum Programming Languages, and Quantum Platforms.

First, he called assembly languages ​​such as OpenQASM and Quil quantum languages. These languages ​​directly tell the device what operations to perform.

On top of these Quantum Languages ​​are Quantum Programming Languages. There are currently over fifty open–source Quantum Programming Language Projects, and this number will likely increase as the days go by and new companies are established. LaRose’s article has discussed four of these with serious teams behind them, Forest, Qiskit, ProjectQ, and Quantum Development Kit (Q#).

To access Rigetti’s computer, you need to contact them in advance and reserve a specific time for yourself. During that time, you have the opportunity to perform the operation you want and test your programs.

Qiskit is IBM’s language and directly gives IBM’s computers an interface arrangement. You do not need to reserve time to access these computers, but your transactions are put in a queue, and your results are sent to you via e–mail when they are done. Although this provides convenience in trials, it is annoying that you do not know when to get the result (usually, it does not exceed one day). On the other hand, this is much easier and more convenient than Rigetti’s processes if you only want access to run your experiment algorithms.

Project is an open–access programming language developed by a team at ETH Zurich. Although he does not have his computer, he has a chance to access IBM’s computers. It is a language that can be tried for those who want to examine the features of language transition and prefer an academic way instead of channeling to companies’ products.

Finally, Quantum Development Kit (QDK or Q#) is a language developed by Microsoft and can be used through Visual Studio. Microsoft does not yet have its Quantum Computer. Still, unlike IBM or Rigetti, it is expected to perform much better than others if the entire system they build on topological qubits can be implemented in hardware. For this reason, Microsoft has already developed its programming language and has begun to spread it among researchers interested in the field. In addition, it offers simulators up to 40 qubits in the cloud via Azure to keep the interest alive. It also seems more likely that people used to C# will prefer this language.

Many large companies such as Google and IBM carry out necessary studies to develop Quantum Programming. In addition, training on quantum programming is given in many schools such as Princeton and Harvard, and students are offered a study area to improve themselves.

Just as Classical Computers only do calculations, in the beginning, Quantum Programming can go through the same paths. It is planned to be used in many fields such as medical, bioinformatics, and Artificial Intelligence (AI) in the coming years. Although it may seem very distant to us, we may soon begin to see its traces in our daily lives.