QuantumGuru recent articles have been on applications of quantum computers in addressing real world use cases. For the last three decades, software has been at the forefront of technology development and its application and scalability for general masses. Hence, this article is about some software frameworks that we foresee may influence quantum computer programming.
Software for classical computers is highly matured, but the computing enhancement brought by quantum computing will require significant changes in the current software paradigm. Tech giants like Google, IBM, Microsoft and Amazon are investing billions of dollars to bring commercially viable quantum computers – hardware to start with. However, all of these are software companies and invest considerably in software to enable programming of quantum computers. New age startups like Cambridge quantum, Orange Quantum, Qblox etc. are working creatively to overcome similar barriers. For example. Cambridge quantum, a company that creates agnostic quantum software, has merged with Honeywell Quantum Solutions, a quantum hardware company that uses trapped-ions for quantum computing to create Quantinuum, a blend of Quantum Continuum.
Some open source software in development for the post quantum era are:
1. Quantify
The open-source software platform is for qubit calibration and characterization routines. Qblox provides a completely open-source software stack, called Quantify, to control experiments on Qblox Cluster and SPI hardware. Quantify is a python-based, high-level data acquisition platform focused on providing all the necessary tools for Quantum Computing experiments. It is built on top of QCoDeS, and is the successor of the extensively tested PyQED measurement environment. The simple software framework enables setting-up typical characterization experiments and advanced experimental procedures with ease-of-use.
2. lambeq
lambeq is the world’s first software toolkit for quantum natural language processing (QNLP). It is capable of converting sentences into a quantum circuit. It is designed to accelerate the development of practical, real-world QNLP applications such as automated dialogue, text mining, language translation, text-to-speech, language generation and bioinformatics. lambeq has been released on a fully open-sourced basis for the benefit of the world’s quantum computing community. lambeg ecosystem is rapidly growing and includes quantum computing researchers, developers and users. lambeq works seamlessly with Cambridge Quantum’s TKET, the world’s leading and fastest-growing quantum software development platform that is also open-source. This provides QNLP developers with access to the broadest possible range of quantum computers.
3. pyQuil
PyQuil is a Python library for quantum programming using Quil. Quil is a quantum instruction language developed by Rigetti Computing. PyQuil has the following three main functions:
- Easily generates Quil programs from quantum gates and classical operations
- Compiles and simulates Quil programs using the Quil Compiler (quilc) and the Quantum Virtual Machine (QVM)
- Executes Quil programs on real quantum processors (QPUs) using Quantum Cloud Services (QCS)
4. Pennylane
Pennylane is a cross-platform Python library for differentiable programming of quantum computers. It aims to build rich and flexible hybrid quantum-classical models. It trains a quantum computer similar to that of a neural network. Pennylane connects to quantum hardware using standard neural networks frameworks such as PyTorch, TensorFlow, JAX, Keras or NumPy. It is fully device independent and executes the same quantum circuit on different quantum backends. Plugins are needed in order to access even more devices, including Strawberry Fields, Amazon Braket, IBM Q, Google Cirq, Rigetti Forest, Qulacs, Pasqal, Honeywell, and more
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