MCQST photonic waveguides filter light for quantum communication

Researchers at the Technical University of Munich (TUM) and the Munich Center for Quantum Science and Technology (MCQST) are pursuing a more scalable method for generating single photons crucial to quantum communication by suppressing unwanted light frequencies. Unlike previous technologies relying on precisely tuned resonators, the team utilizes photonic crystal waveguides, nanostructures that block pathways for unwanted photon emission while preserving desired frequencies.

Initial experiments demonstrate a threefold increase in the proportion of desired photons, achieving 72 percent compared to the 23 percent attained with earlier methods. “If photons are generated too quickly, it’s difficult for us to control their properties,” explains Andreas Reiserer, professor of quantum networks at TUM, highlighting the benefits of this new approach.

Photonic Crystal Waveguides Suppress Unwanted Frequencies for Single Photons

Unlike prior technologies that relied on amplifying specific frequencies with resonators, this new method actively suppresses unwanted light frequencies through the use of photonic crystal waveguides. These nanostructures, measuring only a few micrometers, function by creating patterns that block pathways for photon emission at undesirable wavelengths, preserving the desired frequencies. The team’s design circumvents a key limitation of resonators, which operate within a narrow frequency range and demand precise tuning to the photon source.

Photonic crystal waveguides offer greater flexibility; they do not require such precise tuning, making them compatible with a wider range of emitters and enabling the simultaneous use of multiple photon sources within a single device, a feat difficult to achieve with resonator-based systems. Initial experiments utilized erbium as the photon source, an element already integrated into existing fiber-optic technologies, suggesting potential for seamless integration with current infrastructure.

This slower rate of photon generation, while a change from previous methods, is actually advantageous for quantum communication protocols. Florian Burger, the first author of the published research, highlights the broader implications of this work, stating, “Quantum networks are expected to connect many quantum systems with one another one day.

This requires interfaces that can reliably transfer information from a quantum system to individual photons and then transmit them, for example, via optical fibers.” The research, published in Nature Communications, was funded by the Federal Ministry of Education and Research and the Free State of Bavaria.

If photons are generated too quickly, it’s difficult for us to control their properties.

Andreas Reiserer, professor of quantum networks at TUM

Beyond efficiency gains, the photonic crystal waveguide approach offers increased scalability and flexibility. “Our approach is therefore significantly better suited for many emitters than the resonators used to date,” Reiserer asserts. This work lays the foundation for future quantum networks.

Quantum networks are expected to connect many quantum systems with one another one day. This requires interfaces that can reliably transfer information from a quantum system to individual photons and then transmit them, for example, via optical fibers. Our work lays the foundation for this.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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