arXiv subjects

Robert Parsons

Publications and source records attributed to Robert Parsons.

6 recordsLinked to original sources

arXiv2025

Highly Uniform Thermally Undercut Silicon Photonic Devices in a 300 mm CMOS Foundry Process

Silicon photonic devices fundamental to high-density wavelength-division multiplexed (DWDM) optical links and photonic switching networks, such as resonant modulators and Mach-Zehnder interferometers (MZIs), are highly sensitive to fabrication variations and operational temperature swings. However, thermal tuning to compensate for fabrication and operational temperature variations can result in prohibitive power consumption, challenging the scalability of energy-efficient photonic integrated circuits (PICs). In this work, we develop and demonstrate a wafer-scale thermal undercut process in a 300 mm complementary metal oxide semiconductor (CMOS) foundry that dramatically improves the thermal isolation of thermo-optic devices by selectively removing substrate material beneath the waveguides and resonators. This approach significantly reduces the power required for thermal tuning across multiple device architectures, achieving almost a 5$\times$ improvement in tuning efficiency in a state-of-the-art 4.5 $\mu$m radius microdisk modulator and a 40$\times$ improvement in efficiency for a MZI phase shifter. To the best of the authors' knowledge, we demonstrate the first wafer-scale comparison of non-undercut and undercut silicon photonic devices using comprehensive wafer-scale measurements across 64 reticles of a 300 mm silicon-on-insulator (SOI) wafer. Further, we demonstrate a comprehensive wafer-scale analysis of the influence of undercut trench opening geometry on device tuning efficiency. Notably, we observe highly uniform performance across the full 300 mm wafer for multiple device types, emphasizing that our process can be scaled to large-scale photonic circuits with high yield. These results open new opportunities for large-scale integrated photonic circuits using thermo-optic devices, paving the way for scalable, low-power silicon photonic systems.

physics.optics↗

arXiv2024

A Hybrid Approach to Event Reconstruction for Atmospheric Cherenkov Telescopes Combining Machine Learning and Likelihood Fitting

The imaging atmospheric Cherenkov technique provides potentially the highest angular resolution achievable in astronomy at energies above the X-ray waveband. High-resolution measurements provide the key to progress on many of the major questions in high-energy astrophysics, including the sites of particle acceleration to PeV energies. The potential of the next-generation CTA observatory in this regard can be realised with the help of improved algorithms for the reconstruction of the air-shower direction and energy. Hybrid methods combining likelihood-fitting techniques with neural networks represent a particularly promising approach and have recently been applied to the reconstruction of astrophysical neutrinos. Here, we present the FreePACT algorithm, a hybrid reconstruction method for IACTs. In this, making use of the neural ratio estimation technique from the field of likelihood-free inference, the analytical likelihood used in traditional image likelihood fitting is replaced by a neural network that approximates the charge probability density function for each pixel in the camera. The performance of this algorithm is demonstrated using simulations of the planned CTA southern array. For this setup, FreePACT provides significant performance improvements over analytical likelihood techniques, with improvements in angular and energy resolution of 25% or more over a wide energy range and an angular resolution as low as 40 arcseconds at energies above 50 TeV for observations at 20 degrees zenith angle. It also yields more accurate estimations of the uncertainties on the reconstructed parameters and speeds up the reconstruction compared to analytical likelihood techniques while showing the same stability with respect to changes in the observation conditions. Therefore, the FreePACT method is a promising upgrade over the current state-of-the-art likelihood event reconstruction techniques.

astro-ph.HE↗

arXiv2023

3D photonics for ultra-low energy, high bandwidth-density chip data links

Artificial intelligence (AI) hardware is positioned to unlock revolutionary computational abilities across diverse fields ranging from fundamental science [1] to medicine [2] and environmental science [3] by leveraging advanced semiconductor chips interconnected in vast distributed networks. However, AI chip development has far outpaced that of the networks that connect them, as chip computation speeds have accelerated a thousandfold faster than communication bandwidth over the last two decades [4, 5]. This gap is the largest barrier for scaling AI performance [6, 7] and results from the disproportionately high energy expended to transmit data [8], which is two orders of magnitude more intensive than computing [9]. Here, we show a leveling of this long-standing discrepancy and achieve the lowest energy optical data link to date through dense 3D integration of photonic and electronic chips. At 120 fJ of consumed energy per communicated bit and 5.3 Tb/s bandwidth per square millimeter of chip area, our platform simultaneously achieves a twofold improvement in both energy consumption and bandwidth density relative to prior demonstrations [10, 11]. These improvements are realized through employing massively parallel 80 channel microresonator-based transmitter and receiver arrays operating at 10 Gb/s per channel, occupying a combined chip footprint of only 0.32 mm2. Furthermore, commercial complementary metal-oxide-semiconductor (CMOS) foundries fabricate both the electronic and photonic chips on 300 mm wafers, providing a clear avenue to volume scaling. Through these demonstrated ultra-energy efficient, high bandwidth data communication links, this work eliminates the bandwidth bottleneck between spatially distanced compute nodes and will enable a fundamentally new scale of future AI computing hardware without constraints on data locality.

physics.optics↗

arXiv2023

Process Variation-Aware Compact Model of Strip Waveguides for Photonic Circuit Simulation

We report a novel process variation-aware compact model of strip waveguides that is suitable for circuit-level simulation of waveguide-based process design kit (PDK) elements. The model is shown to describe both loss and -- using a novel expression for the thermo-optic effect in high index contrast materials -- the thermo-optic behavior of strip waveguides. A novel group extraction method enables modeling the effective index's ($n_{\mathrm{eff}}$) sensitivity to local process variations without the presumption of variation source. Use of Euler-bend Mach-Zehnder interferometers (MZIs) fabricated in a 300~mm wafer run allow model parameter extraction at widths up to 2.5~$μ$m (highly multi-mode) with strong suppression of higher-order mode excitation. Experimental results prove the reported model can self-consistently describe waveguide phase, loss, and thermo-optic behavior across all measured devices over an unprecedented range of optical bandwidth, waveguide widths, and temperatures.

physics.optics↗

arXiv2019

A Template-based $γ$-ray Reconstruction Method for Air Shower Arrays

We introduce a new Monte Carlo template-based reconstruction method for air shower arrays, with a focus on shower core and energy reconstruction of $γ$-ray induced air showers. The algorithm fits an observed lateral amplitude distribution of an extensive air shower against an expected probability distribution using a likelihood approach. A full Monte Carlo air shower simulation in combination with the detector simulation is used to generate the expected probability distributions. The goodness of fit can be used to discriminate between $γ$-ray and hadron induced air showers. As an example, we apply this method to the High Altitude Water Cherenkov $γ$-ray Observatory and its recently installed high-energy upgrade. The performance of this method and the applicability to air shower arrays with mixed detector types makes it a promising reconstruction approach for current and future instruments.

astro-ph.IM↗

arXiv2011

Escape from Vela X

Whilst the Vela pulsar and its associated nebula are often considered as the archetype of a system powered by a \sim10^4 year old isolated neutron star, many features of the spectral energy distribution of this pulsar wind nebula are both puzzling and unusual. Here we develop a model that for the first time relates the main structures in the system, the extended radio nebula (ERN) and the X-ray cocoon through continuous injection of particles with a fixed spectral shape. We argue that diffusive escape of particles from the ERN can explain the steep Fermi-LAT spectrum. In this scenario Vela X should produce a distinct feature in the locally-measured cosmic ray electron spectrum at very high energies. This prediction can be tested in the future using the Cherenkov Telescope Array (CTA). If particles are indeed released early in the evolution of PWNe and can avoid severe adiabatic losses, PWN provide a natural explanation for the rising positron fraction in the local CR spectrum.

astro-ph.HE↗