Google AI Quantum team announced two releases at the First International Workshop on Quantum Software and Quantum Machine Learning(QSML) yesterday. Firstly the public alpha release of Cirq, an open source framework for NISQ computers. The second release is OpenFermion-Cirq, an example of a Cirq-based application enabling near-term algorithms.
Noisy Intermediate Scale Quantum (NISQ) computers are devices including ~50 – 100 qubits and high fidelity quantum gates enhance the quantum algorithms such that they can understand the power that these machines uphold.
However, quantum algorithms for the quantum computers have their limitations such as
- A poor mapping between the algorithms and the machines
- Also, some quantum processors have complex geometric constraints
These and other nuances inevitably lead to wasted resources and faulty computations. Cirq comes as a great help for researchers here. It is focussed on near-term questions, which help researchers to understand whether NISQ quantum computers are capable of solving computational problems of practical importance. It is licensed under Apache 2 and is free to be either embedded or modified within any commercial or open source package.
With Cirq, researchers can write quantum algorithms for specific quantum processors. It provides a fine-tuned user control over quantum circuits by,
- specifying gate behavior using native gates,
- placing these gates appropriately on the device, and
- scheduling the timing of these gates within the constraints of the quantum hardware.
Other features of Cirq include:
- Allows users to leverage the most out of NISQ architectures with optimized data structures to write and compile the quantum circuits.
- Supports running of the algorithms locally on a simulator
- Designed to easily integrate with future quantum hardware or larger simulators via the cloud.
Google AI Quantum team also released OpenFermion-Cirq, which is an example of a CIrq-based application that enables the near-term algorithms. OpenFermion is a platform for developing quantum algorithms for chemistry problems.
OpenFermion-Cirq extends the functionality of OpenFermion by providing routines and tools for using Cirq for compiling and composing circuits for quantum simulation algorithms.
An instance of the OpenFermion-Cirq is, it can be used to easily build quantum variational algorithms for simulating properties of molecules and complex materials.
While building Cirq, the Google AI Quantum team worked with early testers to gain feedback and insight into algorithm design for NISQ computers. Following are some instances of Cirq work resulting from the early adopters:
- Zapata Computing: simulation of a quantum autoencoder (example code, video tutorial)
- QC Ware: QAOA implementation and integration into QC Ware’s AQUA platform (example code, video tutorial)
- Quantum Benchmark: integration of True-Q software tools for assessing and extending hardware capabilities (video tutorial)
- Heisenberg Quantum Simulations: simulating the Anderson Model
- Cambridge Quantum Computing: integration of proprietary quantum compiler t|ket> (video tutorial)
- NASA: architecture-aware compiler based on temporal-planning for QAOA (slides) and simulator of quantum computers (slides)
The team also announced that it is using Cirq to create circuits that run on Google’s Bristlecone processor. Their future plans include making the Bristlecone processor available in cloud with Cirq as the interface for users to write programs for this processor.
To know more about both the releases, check out the GitHub repositories of each Cirq and OpenFermion-Cirq.