Quantum computing with differentiable quantum transforms

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Quantum computing is an interdisciplinary field developing a new type of computer based on quantum mechanics. A number of quantum algorithms exist that are capable of solving socially- and industrially-relevant problems, across a spectrum of domains, that are considered intractable for regular computers. Developing algorithms, in particular those that provide a meaningful speedup, is extremely challenging. Currently, most quantum programming is done by writing software in regular languages, augmented by quantum software libraries. Quantum software enables researchers to go beyond the theory, and prototype and test algorithms on both simulators and real hardware. However, the benefits are not merely one-way: just as the requirements of research inform the development of software, features unlocked by software drive further research.This research is a partnership between UBC and Xanadu Quantum Technologies, a Toronto-based startup that develops the open-source software library PennyLane. PennyLane is tailored for designing algorithms for quantum machine learning through application of autodifferentiation to quantum programs. The software has recently been augmented with a new feature called differentiable quantum transforms. Transforms modify and manipulate quantum programs. Their implementation within the autodifferentiation framework of PennyLane has unlocked the ability to train and learn transforms. Through this partnership, we will explore how this software can help us develop novel methods for compiling and optimizing quantum algorithms, mitigating noise in quantum hardware, and simulating noisy devices. Quantum computers are challenging to build and to scale to large sizes; we have many devices today, however they are considered small, and are quite noisy. The software and methods developed in this research will enable us to reduce the resources required to run and test many quantum algorithms, as well as obtain more accurate results when running on today's devices.