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Optics and Photonics News

Scatterings

Patricia Daukantas, Valerie C. Coffey, Sarah A. Michaud, Stewart Wills

Published Jun 1, 2015• 0 citations
Publisher

Abstract

Monitoring Vitals with Video; Coupling Systems; Slowing Light for Quantum Storage; Photon-Powered Camera; A Better Magnetic Sensor; Exploiting Nonlinear Effects to Enhance Photonic Chips; Nokia to Buy Alcatel-Lucent; Sony Increases Investment in CMOS Sensors; Philips to Sell Majority Stake in Lumileds; Dental Anatomy of Fossils; Staining with Light.

DOI
10.1364/opn.26.6.000009

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The importance of optical signal processing techniques is growing rapidly in recent years due to the exponentially increasing demand for bandwidth, capacity and power efficiency in communications and computing. However, due to their bosonic nature photons do not interact with each other, unless there is a nonlinear medium mediating the interaction. One of the strongest nonlinear effects is the interaction of light waves, photons, with sound-waves, acoustic phonons, which is known as stimulated Brillouin scattering (SBS). This thesis experimentally investigates SBS in photonic chips. It is shown in this thesis that the fundamental interaction strength between light and sound waves can be tailored by using one-dimensional photonic bandgap structures, completely suppressing the effect or alternatively enhancing the interaction to form phase-locked Brillouin frequency combs. It was shown furthermore that efficiently generating SBS on-chip enables the generation of stable RF signals that are widely tunable in frequency. Finally, it is shown in this thesis that SBS enables the storage of light signals on a chip, one of the holy grails of all-optical signal processing. Delaying optical signals is of key importance in optical networks to enable synchronization, buffering, and rerouting. SBS enables large delays by resonantly transferring an optical signal to an acoustic wave, that travels five orders of magnitude slower and retrieving it after a certain storage time. It is demonstrated in this thesis that a Brillouin-based memory (BBM) technique allows storing amplitude and phase of optical data pulses and operate at multiple wavelengths with minimal cross-talk. Replenishing of the acoustic wave to overcome storage time limitations imposed by the lifetime of the acoustic wave as well as non-reciprocal light storage is also shown.

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Summary form only given. Slow light has been explored for building quantum networks, with particular interest in slowing the group velocity of single photons [1], and more recently exploited to enhance the measurement of small phase shifts. Generally, slow-light effects have been characterized as the net effect of a pulse propagating through the slow-light medium, i.e., as a pulse delay time Δt measured with a fast photodiode at the output of the medium [2]. In this work, we use a single-photon imaging camera to observe slow light in situ, and thus provide a direct measurement of spatial pulse compression and temporal dispersion as the pulse travels through the slow light medium, in this case a hyperfine absorption doublet in hot Rb vapor. Our method combines light-in-flight imaging techniques with a camera comprised of an array of single-photon avalanche diodes (SPAD camera) [3] to image the photons scattered by the Rb vapor in the direction of the camera as shown in Fig. 1(a). In addition, the single photon nature of the SPAD detector allows us to obtain a measurement of the single photon group velocity. As shown in Fig. 1(c) and (d), we observe a significant delay, on the order of nanoseconds, in the detection of the photons scattered when the pulse first enters the slow-light medium. This lag in scattered-photon arrival time is a direct visualization of the slowing down of the single-photon group velocity. The pulses used here had a temporal full width at half maximum (FWHM) of τ ~1 ns, with measured group velocities as low as vg~ 0.006c. At these low group velocities we observe a full fractional pulse delay of up to F D = Δt/τ ~ 40 over 7 cm of propagation, and F D ~ 5 for the scattered single photons, which propagate through ~ 1 cm of Rb vapor prior to exiting the cell en-route to the camera.
The importance of optical signal processing techniques is growing rapidly in recent years due to the exponentially increasing demand for bandwidth, capacity and power efficiency in communications and computing. However, due to their bosonic nature photons do not interact with each other, unless there is a nonlinear medium mediating the interaction. One of the strongest nonlinear effects is the interaction of light waves, photons, with sound-waves, acoustic phonons, which is known as stimulated Brillouin scattering (SBS). This thesis experimentally investigates SBS in photonic chips. It is shown in this thesis that the fundamental interaction strength between light and sound waves can be tailored by using one-dimensional photonic bandgap structures, completely suppressing the effect or alternatively enhancing the interaction to form phase-locked Brillouin frequency combs. It was shown furthermore that efficiently generating SBS on-chip enables the generation of stable RF signals that are widely tunable in frequency. Finally, it is shown in this thesis that SBS enables the storage of light signals on a chip, one of the holy grails of all-optical signal processing. Delaying optical signals is of key importance in optical networks to enable synchronization, buffering, and rerouting. SBS enables large delays by resonantly transferring an optical signal to an acoustic wave, that travels five orders of magnitude slower and retrieving it after a certain storage time. It is demonstrated in this thesis that a Brillouin-based memory (BBM) technique allows storing amplitude and phase of optical data pulses and operate at multiple wavelengths with minimal cross-talk. Replenishing of the acoustic wave to overcome storage time limitations imposed by the lifetime of the acoustic wave as well as non-reciprocal light storage is also shown.
Advances in quantum technologies are accelerating the demand for optical quantum state sensors that combine high precision, versatility, and scalability within a unified hardware platform. Quantum reservoir computing offers a powerful route toward this goal by exploiting the nonlinear dynamics of quantum systems to process and interpret quantum information efficiently. Photonic neural networks are particularly well suited for such implementations, owing to their intrinsic sensitivity to photon-encoded quantum information. However, the practical realisation of photonic quantum reservoirs remains constrained by the inherently weak optical nonlinearities of available materials and the technological challenges of fabricating densely coupled quantum networks. To address these limitations, we introduce a hybrid quantum-classical detection protocol that integrates the advantages of quantum reservoirs with the adaptive learning capabilities of analogue neural networks. This synergistic architecture substantially enhances information-extraction accuracy and robustness, enabling low-cost performance improvements of quantum light sensors. Based on the proposed approach, we achieved significant improvements in quantum state classification, tomography, and feature regression, even for reservoirs with a relatively small nonlinearity-to-losses ratio U/γ≈0.02U/γ\approx 0.02U/γ≈0.02 in a network of only five nodes. By reducing reliance on material nonlinearity and reservoir size, the proposed approach facilitates the practical deployment of high-fidelity photonic quantum sensors on existing integrated platforms, paving the way toward chip-scale quantum processors and photonic sensing technologies.