Abstract

Quantum machine learning is an exciting field applying the benefits of quantum physics to machine learning, a branch of artificial intelligence. The interplay between these two has yielded significant breakthroughs in the last few years, unlocking significant quantum speed-ups for application such as image recognition. Among the different quantum platforms, photonics stands as being extremely suitable for machine learning task as optical interferometric networks enable the processing of high-dimensional or multi-level states. Remarkably, photonic quantum processors do not require challenging entangling gates or entangled input states for outperforming its classical counterpart. Furthermore, tuneable photonic integrated circuits even allow for increased energy efficiency and enhanced computational speed already for small-scale systems, even when being operated in the classical domain.
Photonic quantum processors for quantum machine learning tasks also offer significant advantages on the hardware side. Single photons are resistant to different and even harsh environmental conditions, are tolerant to noise, and can be operated at ambient conditions without the need of vacuum chambers and cryogenics. These benefits, along with the possibility of processing photons via integrated networks, in form of a stable solid, make quantum photonics technology the most suitable architecture for space applications and thus for bringing the benefits of quantum computing into space.
Hence, photonic quantum processors break the ground and enable quantum machine learning for data analysis on satellites, for instance, for Earth observation missions. Such missions are safety-relevant and play a central role in many fields, reaching from climate studies and population growth to fire detection and many more. However, with the increasing importance of this field and the growing amount of data being collected by satellites, it has become highly desirable, if not necessary, to perform edge computing directly on satellites. This allows to process data close to its origin in order to economize on expensive communication resources.
With this project we want to demonstrate the world’s first quantum computer in space in 2025, building on our pioneering work on photonic quantum machine learning. The project funds are essential for continuing and finalizing the developments of a space-proof integrated photonic quantum machine learning processor. This quantum computer prototype, consisting of a single-photon source, a tunable photonic integrated processor and a detection unit, is planned to be launched via a small-satellite in summer 2025. Shortly thereafter we aim to demonstrate quantum-enhanced image recognition directly on the satellite, using Earth observation pictures taken by the onboard camera. The project’s results will prove the applicability of multi-dimensional photonic processors for real-life applications on satellites. It will also strengthen Austria’s pioneering role in quantum technology by being the first country to demonstrate quantum machine learning in space. Since this project holds the potential of initializing quantum computing in space as a new market, the Austrian quantum technology start-up “QUBO Technology GmbH” will bring in business and commercial expertise to build the foundation for developing commercial applications an to build an Austrian space technology business.