arXiv subjects

Rijil Thomas

Publications and source records attributed to Rijil Thomas.

3 recordsLinked to original sources

arXiv2026

Benchmarking Dual-Polarization Silicon Nitride Photonic Integrated Circuits for Trapped-Ion Quantum Technologies

Trapped ions are one of the most advanced platforms for quantum technologies, with applications ranging from quantum computing to precision timekeeping. A crucial step towards more compact and scalable systems involves integrating photonic integrated circuits (PICs) into surface ion traps to enable on-chip light delivery and optical addressing of individual ions. Currently, most implementations rely solely on transverse-electric (TE) mode grating couplers, where the emitted light is polarized in the plane of the chip. In this work, we design, fabricate and characterize silicon nitride (Si$_3$N$_4$) PIC components, including incoupling structures, splitters, and grating couplers that support both TE and transverse-magnetic (TM) modes with comparable optical losses. We benchmark the PIC at 760\,nm, which is a typical wavelength for Yb$^{+}$-applications. The fabricated grating couplers enable the outcoupling of collimated free-space beams for both polarizations, exhibiting distinct emission angles. This dual-polarization capability gives more flexibility in polarization control and expands the accessible optical design space for trapped-ion quantum technologies.

physics.optics↗

arXiv2024

Sputtered Aluminum Nitride Waveguides for the Telecommunication Spectrum with less than 0.16 dB/cm Loss

We report the fabrication and characterization of photonic waveguides from sputtered aluminum nitride (AlN). The AlN films were deposited on 6" silicon substrates with a 3 $\mu$m buried silicon oxide layer using reactive DC magnetron sputtering at a temperature of 700{\deg}C. The resulting uncladded polycrystalline waveguides exhibit propagation losses of 0.137 $\pm$ 0.005 dB/cm at wavelengths of 1310 nm and 0.154 $\pm$ 0.008 dB/cm at a wavelength of 1550 nm in the TE polarization. These results are the best reported for sputtered AlN waveguides in the C-band and the first report in the O-band. These performances are comparable to those of the best-reported AlN waveguides, which are epitaxially grown by metal-organic chemical vapor deposition (MOCVD) on sapphire substrates. Our findings highlight the potential of sputtered AlN for photonic platforms working in the telecom spectrum.

physics.optics↗

arXiv2024

Hardware Realization of Neuromorphic Computing with a 4-Port Photonic Reservoir for Modulation Format Identification

The fields of machine learning and artificial intelligence drive researchers to explore energy-efficient, brain-inspired new hardware. Reservoir computing encompasses recurrent neural networks for sequential data processing and matches the performance of other recurrent networks with less training and lower costs. However, traditional software-based neural networks suffer from high energy consumption due to computational demands and massive data transfer needs. Photonic reservoir computing overcomes this challenge with energy-efficient neuromorphic photonic integrated circuits or NeuroPICs. Here, we introduce a reservoir NeuroPIC used for modulation format identification in C-band telecommunication network monitoring. It is built on a silicon-on-insulator platform with a 4-port reservoir architecture consisting of a set of physical nodes connected via delay lines. We comprehensively describe the NeuroPIC design and fabrication, experimentally demonstrate its performance, and compare it with simulations. The NeuroPIC incorporates non-linearity through a simple digital readout and achieves close to 100% accuracy in identifying several configurations of quadrature amplitude modulation formats transmitted over 20 km of optical fiber at 32 GBaud symbol rate. The NeuroPIC performance is robust against fabrication imperfections like waveguide propagation loss, phase randomization, etc. and delay line length variations. Furthermore, the experimental results exceeded numerical simulations, which we attribute to enhanced signal interference in the experimental NeuroPIC output. Our energy-efficient photonic approach has the potential for high-speed temporal data processing in a variety of applications.

physics.app-ph↗