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Python For Quantum Computers

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ARTICLE SUMMARY

Quantum computing is one of the important emerging technologies today, as data scientists, software engineers, or women in tech, get familiar with quantum technology and its current status. one of the main ways to program a quantum computer today is through python, but what are your options to do so?

Quantum computing is one of the most rapidly advancing technologies. Many companies and research labs are racing to deliver functional quantum hardware to the market as soon as possible. It is one of those fields where every little bit of progress is a significant advancement.

There’s no perfect quantum computer capable of running good algorithms like Shor’s and Grover’s algorithms. However, current quantum machines are advancing rapidly. During the next decade, IBM speculates that quantum computers will offer an undeniable advantage by solving many unsolvable problems on a classical computer.

On the software side, some researchers predict that the market need for quantum programmers will grow exponentially over the next decade. As a result, companies such as Google, IBM, and Microsoft are putting in considerable effort and a massive amount of funds to train the next generation of quantum researchers/ programmers.

There are many options for using a classical programming language to write quantum code. I will sort them from most to least popular.

  • Qiskit: Qiskit (Quantum Information Science Kit) is a Python library developed and maintained by IBM Research in 2017. It is the most popular and widely used quantum programming library. One of the reasons Qiskit is popular is its very active and thriving community. Also, you can run your codes written in Python on actual IBM quantum computers.
  • Cirq: This is an unofficial Python library developed by Google developers to write and run tests on Google’s quantum computers. You can use Cirq to write and simulate quantum algorithms. However, Google doesn’t allow anyone to run code on their devices.
  • Pyquil: A Python library built by Rigetti to write and implement quantum algorithms on Rigetti machines using a quantum instruction language called Quil (also developed by Rigetti). 

No matter what library you choose to start implementing quantum algorithms, you must do so on a gate-level. This is because gates are the building blocks of quantum circuits. Fundamentally, any quantum algorithm can be represented with a series of gates applied to some quantum registers. 

Personally, I started programming quantum computers with Qiskit and still use it extensively — not just because it’s written in Python but also because I can run my code on a quantum computer. Yes, the results are bad now, but it is still intriguing that you can run code on a quantum computer.

Suppose you want to learn more about quantum computing and quantum algorithms. In that case, the Qiskit textbook offers in-depth written explanations of many algorithms and code implementation using Python.

Qiksit textbook is also constantly under development, and new chapters covering more advanced and complex topics are being added regularly. The book explains things with simple language using many graphics to help the reader visualize the concepts presented.

The book explains and implements advanced topics such as quantum-classical hybrid neural networks and a little bit about quantum machine learning.

However, suppose you would like to choose another library, like Cirq or PyQuil. In that case, you can learn more about installing and using these libraries from the PyQuil documentation or Cirq homepage. Regardless of which library you choose, if you know the basics of quantum algorithms, you can easily implement them using any of those libraries because they all work fundamentally the same.

Let’s implement the same quantum code using all nine abovementioned approaches to make things easier. Then, you can inspect how a circuit is implemented and decide which looks more attractive.

In most quantum programming, you build a circuit that applies your algorithm using quantum gates, equivalent to classical gates. For example, let’s try to implement a quantum circuit that creates a superposition between two qubits. First, you need to know the magic gate that makes superpositions. It’s called the Hadamard Gate. You give it 0 or 1, which returns an equal superposition of 0 and 1.

Qiskit quantum programming

The concepts of quantum computing may seem complex and challenging to wrap your head around at first. But, I like to believe that the problem is not with the concepts themselves; instead, it is how they were presented and explained.

I have been working on quantum computing for over five years now. During my journey, I have used various materials and resources to learn and implement different quantum computing concepts. So, I know how difficult it is to get into the field and fully understand its logic.

I am a fan of learning and exploring new things, but I also know that we perform better when we focus our power on learning one thing at a time.

I suggest you start with a quantum library based on a classical programming language. By doing that, you’re only focusing on getting used to the quantum way of thinking and not learning to use a specific programming language. 

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