Quantum Annealing Aids in Designing Optimal Ultrathin Optical Diodes, Advances Photonics

Scientists from the University of Notre Dame, Kyung Hee University, and Oak Ridge National Laboratory have used a quantum annealing-enhanced active learning scheme to design an ultrathin metamaterial optical diode. The team identified optimal designs of 130 nm-thick optical diodes at three specific wavelengths, maximizing the quality of optical isolation. The research could significantly advance applications in optical information processing, photonic integrated circuits, and ultrafast pump-probe spectroscopy by providing a method for automatically identifying optimal designs of thin-film optical diodes, leading to the development of more efficient and compact photonic systems.

What is Quantum Annealing-aided Design of an Ultrathin Metamaterial Optical Diode?

Quantum annealing-aided design of an ultrathin metamaterial optical diode is a research project conducted by a team of scientists from the University of Notre Dame, Kyung Hee University, and Oak Ridge National Laboratory. The team used a quantum annealing-enhanced active learning scheme to automatically identify optimal designs of 130 nm-thick optical diodes. An optical diode is a stratified volume diffractive film discretized into rectangular pixels, where each pixel is assigned to either a metal or dielectric. The proposed scheme identifies the optimal material states of each pixel, maximizing the quality of optical isolation at given wavelengths.

The team successfully identified optimal structures at three specific wavelengths: 600, 800, and 1000 nm. In the best-case scenario, when the forward transmissivity is 85%, the backward transmissivity is 0.1%. Electromagnetic field profiles reveal that the designed diode strongly supports surface plasmons coupled across counterintuitive metal-dielectric pixel arrays. This yields the transmission of first-order diffracted light with a high amplitude. In contrast, backward transmission has decoupled surface plasmons that redirect Poynting vectors back to the incident medium, resulting in near attenuation of its transmission. The team also experimentally verified the optical isolation function of the optical diode.

Why are Thin-film Optical Diodes Important?

Thin-film optical diodes are important elements for miniaturizing photonic systems. However, the design of optical diodes relies on empirical and heuristic approaches. This poses a significant challenge for identifying optimal structural models of optical diodes at given wavelengths. The team’s research leverages a quantum annealing-enhanced active learning scheme to automatically identify optimal designs of 130 nm-thick optical diodes, overcoming this challenge.

Optical diodes permit light to transmit in one direction (forward direction) but block it in the reverse direction (backward direction). This property is needed for various optical applications such as optical information processing, photonic integrated circuits, and ultrafast pump-probe spectroscopy. The figure-of-merit (FoM) of an optical diode can be defined as the difference between the forward and backward transmissivities.

How Does the Quantum Annealing-aided Design Work?

The quantum annealing-aided design identifies the optimal material states of each pixel in an optical diode, maximizing the quality of optical isolation at given wavelengths. The team successfully identified optimal structures at three specific wavelengths: 600, 800, and 1000 nm. In the best-case scenario, when the forward transmissivity is 85%, the backward transmissivity is 0.1%.

Electromagnetic field profiles reveal that the designed diode strongly supports surface plasmons coupled across counterintuitive metal-dielectric pixel arrays. This yields the transmission of first-order diffracted light with a high amplitude. In contrast, backward transmission has decoupled surface plasmons that redirect Poynting vectors back to the incident medium, resulting in near attenuation of its transmission.

What are the Challenges in Designing Optical Diodes?

Designing optical diodes is a complex task that relies on empirical and heuristic approaches. Identifying an appropriate structural model for a desired wavelength within the same or adjacent electromagnetic bands remains challenging and complex. This is because the geometries of stratified volume diffractive films can be arbitrary without specific rules of thumb or preferred guidelines.

The team’s research overcomes this challenge by leveraging a quantum annealing-enhanced active learning scheme to automatically identify optimal designs of 130 nm-thick optical diodes. This approach identifies the optimal material states of each pixel, maximizing the quality of optical isolation at given wavelengths.

What are the Applications of Optical Diodes?

Optical diodes have a wide range of applications in the field of photonics. They permit light to transmit in one direction (forward direction) but block it in the reverse direction (backward direction). This property is needed for various optical applications such as optical information processing, photonic integrated circuits, and ultrafast pump-probe spectroscopy.

The team’s research has the potential to significantly advance these applications by providing a method for automatically identifying optimal designs of thin-film optical diodes. This could lead to the development of more efficient and compact photonic systems.

What are the Future Implications of this Research?

The team’s research has significant implications for the future of photonics. By providing a method for automatically identifying optimal designs of thin-film optical diodes, the team has opened up new possibilities for the miniaturization of photonic systems. This could lead to the development of more efficient and compact photonic systems, advancing various optical applications such as optical information processing, photonic integrated circuits, and ultrafast pump-probe spectroscopy.

Furthermore, the team’s research demonstrates the potential of quantum annealing-enhanced active learning schemes in overcoming complex design challenges. This approach could be applied to other areas of photonics, potentially leading to further advancements in the field.