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Better noise control in photonic quantum processors

10.04.2024 - New device enables fast reprogramming with reduced power consumption.

Scientists have created a reprogrammable light-based processor, a world-first, that they say could usher in a new era of quantum computing and communication. In the future, large-scale quantum computers promise to be able to solve complex problems that would be impossible for today’s computers. Lead researcher Alberto Peruzzo from RMIT University in Australia said the team’s photonic processor could help enable successful quantum computations, by minimizing light losses.

 

“Our design makes the quantum photonic quantum computer more efficient in terms of light losses, which is critical for being able to keep the computation going,” said Peruzzo. “If you lose light, you have to restart the computation.” Other potential advances included improved data transmission capa­bilities for unhackable communi­cations systems and enhanced sensing applications in environ­mental monitoring and healthcare, Peruzzo said. The team reprogrammed a photonics processor in a range of experiments, achieving a performance equivalent to 2,500 devices, by applying varying voltages. “This innovation could lead to a more compact and scalable platform for quantum photonic processors,” Peruzzo said.

His colleague Yang Yang said the device was “fully controllable”, enabled fast reprogramming with reduced power consumption and replaced the need for making many tailored devices. “We experi­mentally demonstrated different physical dynamics on a single device,” he said. “It's like having a switch to control how particles behave, which is useful for both understanding the quantum world and creating new quantum techno­logies.”  

Mirko Lobino from the University of Trento in Italy made the innovative photonic device, using a lithium niobate crystal, and Yogesh Joglekar from Indiana University Purdue University Indianapolis in the United States brought his expertise in condensed matter physics. Lithium niobate has unique optical and electro-optic properties, making it ideal for various appli­cations in optics and photonics. “My group was involved in the fabri­cation of the device, which was parti­cularly challenging because we had to minia­turize a large number of electrodes on top of the waveguides to achieve this level of reconfigurability,” Lobino said. “Programmable photonic processors offer a new route to explore a range of phenomena in these devices that will potentially unlock incredible advance­ments in technology and science,” Joglekar said.

Meanwhile, Peruzzo’s team has also developed a world-first hybrid system that combines machine learning with modelling to program photonic processors and help control the quantum devices. Peruzzo said the control of a quantum computer was crucial to ensure the accuracy and efficiency of data processing. “One of the biggest challenges to the device's output accuracy is noise, which describes the interference in the quantum environ­ment that impacts how qubits perform,” he said. “There are a whole range of industries that are developing full-scale quantum computing, but they are still fighting against the errors and ineffi­ciencies caused by noise,” Peruzzo said.

Attempts to control qubits typically relied on assumptions about what noise was and what caused it, Peruzzo said. “Rather than make assumptions, we developed a protocol that uses machine learning to study the noise while also using modelling to predict what the system does in response to the noise,” he said. With the use of the quantum photonic processors, Peruzzo said this hybrid method could help quantum computers perform more precisely and effi­ciently, impacting how we control quantum devices in the future. “We believe our new hybrid method has the potential to become the mainstream control approach in quantum computing,” Peruzzo said.  

Akram Youssry from RMIT said the results of the newly-developed approach showed significant improvement over the traditional methods of modelling and control, and could be applied to other quantum devices beyond photonic processors. “The method helped us uncover and understand aspects of our devices that are beyond the known physical models of this technology,” he said. “This will help us design even better devices in the future.”

Peruzzo said startup companies in quantum computing could be created around his team’s photonic device design and quantum control method, which they would continue to study in terms of appli­cations and their full potential. “Quantum photonics is one of the most promising quantum industries, because the photonics industry and manu­facturing infra­structure are very well established,” he said. Quantum machine-learning algorithms have potential advantages over other methods in certain tasks, especially when dealing with large datasets.

“Imagine a world where computers work millions of times faster than they do today, where we can send information securely without any fear of it being inter­cepted, and where we can solve problems in seconds that would currently take years. This isn't just fantasy – it's the potential future powered by quantum techno­logies, and research like ours is paving the way”, Peruzzo said. (Source: RMIT)

References: Y. Yang et al.: Programmable high-dimensional Hamiltonian in a photonic waveguide array, Nat. Commun. 15, 50 (2024); DOI: 10.1038/s41467-023-44185-z • A. Youssry et al.: Experimental graybox quantum system identification and control, npj Quantum Inf. 10, 9 (2024); DOI: 10.1038/s41534-023-00795-5

Link: Quantum Photonics Laboratory, RMIT University, Melbourne, Australia

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Digital tools or software can ease your life as a photonics professional by either helping you with your system design or during the manufacturing process or when purchasing components. Check out our compilation:

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