Publications by authors named "Dylan Renaud"

The surge in artificial intelligence applications calls for scalable, high-speed, and low-energy computation methods. Computing with photons is promising due to the intrinsic parallelism, high bandwidth, and low latency of photons. However, current photonic computing architectures are limited by the speed and energy consumption associated with electronic-to-optical data transfer, i.

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We demonstrate a low half-wave voltage (0.7 V), high-bandwidth modulator in thin-film lithium niobate operating at near-infrared wavelengths (850 nm) and show the ability to transmit 60 GBd signals with direct electrical driving (400 mVpp). This paves the way for high-bandwidth, low-power, and compact optical engines for short-range optical communication.

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Practical quantum networks will require multi-qubit quantum nodes. This in turn will increase the complexity of the photonic circuits needed to control each qubit and require strategies to multiplex memories. Integrated photonics operating at visible to near-infrared (VNIR) wavelength range can provide solutions to these needs.

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Integrated electro-optic (EO) modulators are fundamental photonics components with utility in domains ranging from digital communications to quantum information processing. At telecommunication wavelengths, thin-film lithium niobate modulators exhibit state-of-the-art performance in voltage-length product (VL), optical loss, and EO bandwidth. However, applications in optical imaging, optogenetics, and quantum science generally require devices operating in the visible-to-near-infrared (VNIR) wavelength range.

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In WSe monolayers, strain has been used to control the energy of excitons, induce funneling, and realize single-photon sources. Here, we developed a technique for probing the dynamics of free excitons in nanoscale strain landscapes in such monolayers. A nanosculpted tapered optical fiber is used to simultaneously generate strain and probe the near-field optical response of WSe monolayers at 5 K.

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In this study, we investigate and validate a novel approach to assess and remove additive noise for optical coherence tomography (OCT) imaging. Our method first generates a map of additive noise for the OCT image through Doppler variation analysis. We then remove the additive noise from the real and imaginary parts of the complex OCT signal through pixelwise Wiener filtering.

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