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Move over, traditional computing, quantum computing is on its way. According to research by McKinsey, 72% of executives, investors and academics in the quantum computing industry believe that we’ll see a fully fault-tolerant quantum computer by 2035.
Quantum computers, powered by quantum programming languages, will be able to solve computational problems beyond the means of classical computers and open the door to some exciting new outcomes.
For instance, quantum computing will make it easier to train more powerful AI models, which organizations can use to automate tasks and improve predictive forecasting. This will help industries like healthcare to identify new drugs and treatment options at scale.
Below, we’ll examine five of the top quantum computing programming languages and frameworks that researchers can use to help build quantum algorithms.
Knowledge of programming languages for quantum computing might also help you land a job in a lucrative field.
Key Takeaways
- Quantum programming languages are used to build algorithms and programs to run on quantum computers.
- Quantum computers can provide both classical and quantum computations.
- Some of the top quantum programming languages include Q#, Qiskit, and Cirq.
- Quantum programming will be used to enhance the development of AI and other solutions.
What Is a Quantum Programming Language?
A quantum programming language is used to create programs or algorithms that can run on quantum computers. Quantum computers have the ability to perform multiple computations at once, which means that they can manage much more complex algorithms.
That being said, it’s important to note that quantum computers can perform both classical and quantum computations. Likewise, classical computers can run the same algorithms as quantum computers, but they do so at a much slower rate.
What Is the Difference Between Traditional & Quantum Programming?
One core difference between traditional and quantum programming is that classical computing, used by traditional computers, uses bits with a value of 0 or 1, whereas quantum programming uses quantum bits (qubits), which can represent 0 or 1 simultaneously.
This means that quantum programming enables a quantum computer to carry out multiple computations at once. The end result is that a quantum computer can complete complex tasks quicker than a classical computer.
Top 5 Quantum Programming Languages & Frameworks
Some of the top programming languages and frameworks for quantum computing are as follows:
- Q#
- Qiskit
- Cirq
- Quipper
- Forest (PyQuil)
1. Q#
Q# or Q sharp is an open-source programming language developed by Microsoft that is designed to develop and run quantum algorithms.
It is integrated with the .NET framework, which enables it to also interact with computing languages like C# and Python. Q#’s coding language shares some similarities with C#, which makes it a good option for programmers who already know C#.
At the same time, Q# can run against IonQ computers on the Azure Quantum cloud service. This makes it a solid choice for organizations looking to build quantum cloud environments.
Quantum Software Development Workflow
The diagram below represents the stages through which a quantum program goes from idea to complete implementation on Azure Quantum, as well as the tools offered for each stage.
- Interacts with C# and Python
- Simple syntax
- Offers a range of libraries and development kits available
- Small user community
- Limited hardware support outside of the Microsoft ecosystem
2. Qiskit
Qiskit is an open-source computing framework and quantum development kit produced by IBM. With Qiskit, developers can write quantum programs and algorithms in Python. Users can also use it to build repeatable quantum workflows.
The Qiskit quantum SDK also gives users tools they can use to build and visualize quantum circuits, as well as tools for the optimization and scheduling of QPUs.
In the future, IBM plans to launch the Qiskit Code Assistant, which will use generative AI to automatically generate Qiskit code for quantum computers.
- Write quantum code in Python
- Easy-to-read syntax
- Lots of resources available to learn about Qiskit
- Run quantum programs with IonQ
- Quantum circuit representation can be complex
- Limited quantum hardware support
3.Cirq
Cirq is an open-source Python library and framework developed by Google that’s designed for writing, manipulating, and optimizing quantum circuits to run against quantum computers and simulators.
According to Google, “Cirq provides useful abstractions for dealing with today’s noisy intermediate-scale quantum computers, where details of the hardware are vital to achieving state-of-the-art results.”
- Simple syntax
- Integration with Google Cloud Marketplace
- Mockup quantum hardware with a quantum virtual machine
- Limited quantum hardware support
- Small user community
4. Quipper
Quipper is a scalable programming language that can be used to program non-trivial quantum algorithms and generate quantum gate representations with trillions of gates.
It not only acts as a circuit description language, which can provide gate-by-gate descriptions of circuit fragments, but can also simulate quantum circuits.
The language itself is easy to use with versatile syntax, making it a flexible choice for programmers new to quantum computing.
- Scalable
- Versatile syntax
- Supports hierarchical circuits
- Not dependent on any model of quantum hardware
- Limited user community
- Limited resources available
5. Forest (PyQuil)
Forest is a full-stack programming and quantum computing execution environment created by Rigetti Computing, which includes the PyQuil Python library for writing quantum programs.
Forest is designed to give programmers the ability to execute parametrically controlled quantum circuits. Users can also use Forest to simulate algorithms via Rigetti’s Quantum Virtual Machine running in the cloud.
- Full-stack
- Easy-to-read syntax
- Simulate quantum algorithms
- Limited resources
- Limited hardware support
The Future of Quantum Computer Programming
At the moment, quantum computing is largely theoretical, with most industry leaders not expecting innovations until 2035.
Nonetheless, quantum software development has the potential to be a force multiplier in the global economy. BCC Research anticipates that the global quantum computing market will increase from $713.4 million in 2022 to $6.5 billion by 2028.
Quantum computing has the potential to be extremely beneficial to the development of AI models. It will enable researchers to build more powerful algorithms, accelerating processes like training, inference, data mining, pattern recognition, and decision-making.
However, quantum computer programming also has the potential to introduce new risks.
One of the most significant is that quantum computers will be able to decrypt the RSA encryption that many enterprise solutions rely on today.
This could enable threat actors and nation-states to access large amounts of data that is currently encrypted if providers embrace post-quantum cryptography and other quantum computer-proof encryption solutions.
The Bottom Line: Why Should You Learn Quantum Programming Languages?
If you are interested in quantum computers, learning quantum programming languages is a great way to explore the possibilities of this emerging field.
No one knows the limits of what’s possible with quantum development at the moment, so now is an ideal time to advance your coding capabilities and familiarize yourself with the latest quantum application development tools.
FAQs
Are there quantum programming languages?
What is the MIT quantum programming language?
Can Python be used for quantum computing?
Does quantum computing require coding?
How to program a quantum computer?
References
- What is quantum computing? | McKinsey (Mckinsey)
- Cirq ?|? Google Quantum AI (Quantumai)
- Global Quantum Computing Market Size and Share Analysis Report (Bccresearch)
