arXiv subjects

Xianshu Luo

Publications and source records attributed to Xianshu Luo.

13 recordsLinked to original sources

arXiv2025

Thermally Induced Refractive Index Trimming of Visible-Light Silicon Nitride Waveguides Using Suspended Heaters

We demonstrate refractive index trimming of visible-light silicon nitride (SiN) waveguides using suspended heater structures. The thermal isolation of the suspended heaters enabled a semi-uniform temperature distribution with estimated temperatures of $\sim$350°C in the waveguides without reaching potentially damaging temperatures in the titanium nitride resistive heaters. The thermal isolation also enabled trimming temperatures to be reached with a moderate power dissipation of 30 to 40 mW. At a wavelength of 561 nm, modal effective index changes up to $-8.3 \times 10^{-3}$ were observed following thermal trimming, and the index changes were stable over an observation period of 97 days. The devices were fabricated as part of our visible-light integrated photonics platform on 200-mm diameter silicon wafers. The suspended heaters also functioned as efficient thermo-optic phase shifters with power dissipation for a $π$ phase shift of about $1.2-1.8$ mW. The trimming method was applied to set the bias points of thermo-optic Mach-Zehnder interferometer switches to reduce the bias power of five devices from $0.29-2.32$ mW to $0.1-0.16$ mW. Thermal trimming at a wavelength of 445 nm was also demonstrated. Through material analysis before and after thermal treatment, we hypothesize that index trimming of the silica (SiO$_2$) waveguide cladding may be a potential underlying mechanism. Additionally, via extrapolations of the measured trimming data, we estimate the thermal aging behavior of the SiN waveguides in the suspended heaters at lower (125 - 250°C) operating temperatures.

physics.optics↗

arXiv2024

Variational learning of integrated quantum photonic circuits

Integrated photonic circuits play a crucial role in implementing quantum information processing in the noisy intermediate-scale quantum (NISQ) era. Variational learning is a promising avenue that leverages classical optimization techniques to enhance quantum advantages on NISQ devices. However, most variational algorithms are circuit-model-based and encounter challenges when implemented on integrated photonic circuits, because they involve explicit decomposition of large quantum circuits into sequences of basic entangled gates, leading to an exponential decay of success probability due to the non-deterministic nature of photonic entangling gates. Here, we present a variational learning approach for designing quantum photonic circuits, which directly incorporates post-selection and elementary photonic elements into the training process. The complicated circuit is treated as a single nonlinear logical operator, and a unified design is discovered for it through variational learning. Engineering an integrated photonic chip with automated control, we adjust and optimize the internal parameters of the chip in real time for task-specific cost functions. We utilize a simple case of designing photonic circuits for a single ancilla CNOT gate with improved success rate to illustrate how our proposed approach works, and then apply the approach in the first demonstration of quantum stochastic simulation using integrated photonics.

quant-ph↗

arXiv2024

CMOS-compatible photonic integrated circuits on thin-film ScAlN

Scandium aluminum nitride (ScAlN) has recently emerged as an attractive material for integrated photonics due to its favorable nonlinear optical properties and compatibility with CMOS fabrication. Despite the promising and versatile material properties, it is still an outstanding challenge to realize low-loss photonic circuits on thin-film ScAlN-on-insulator wafers. Here, we present a systematic study on the material quality of sputtered thin-film ScAlN produced in a CMOS-compatible 200 mm line, and an optimized fabrication process to yield 400 nm thick, fully etched waveguides. With surface polishing and annealing, we achieve micro-ring resonators with an intrinsic quality factor as high as $1.47\times 10^5$, corresponding to a propagation loss of 2.4 dB/cm. These results serve as a critical step towards developing future large-scale, low-loss photonic integrated circuits based on ScAlN.

physics.optics↗

arXiv2024

Implantable silicon neural probes with nanophotonic phased arrays for single-lobe beam steering

In brain activity mapping experiments using optogenetics, patterned illumination is crucial for deterministic and localized stimulation of neurons. However, due to optical scattering in brain tissue, light-emitting implantable devices are needed to bring precise patterned illumination to deep brain regions. A promising solution is silicon neural probes with integrated nanophotonic circuits that form tailored beam emission patterns without lenses. Here, we demonstrate neural probes with grating-based light emitters that generate a single steerable light beam across $> 60\%$ of the steering range with $\ge 4$ dB of background suppression for optogenetic photostimulation. The light emitters, optimized for blue or amber light, combine end-fire optical phased arrays with slab gratings to suppress higher-order sidelobes.

physics.optics↗

arXiv2024

Room-temperature waveguide-coupled silicon single-photon avalanche diodes

Single photon detection is important for a wide range of low-light applications, including quantum information processing, spectroscopy, and light detection and ranging (LiDAR). A key challenge in these applications has been to integrate single-photon detection capability into photonic circuits for the realization of complex photonic microsystems. Short-wavelength ($λ$ < 1.1 $μ$m) integrated photonics platforms that use silicon (Si) as photodetectors offer the opportunity to achieve single-photon avalanche diodes (SPADs) that operate at or near room temperature. Here, we report the first waveguide-coupled Si SPAD. The device is monolithically integrated in a Si photonic platform and operates in the visible spectrum. The device exhibited a single photon detection efficiency of > 6% for wavelengths of 488 nm and 532 nm with an excess voltage less than 20% of the breakdown voltage. The dark count rate was below 100 kHz at room temperature, with the possibility of improving by approximately 35% by reducing the temperature to -5$^{\circ}$C.

physics.optics↗

arXiv2024

Implantable Photonic Neural Probes with Out-of-Plane Focusing Grating Emitters

We have designed, fabricated, and characterized implantable silicon neural probes with nanophotonic grating emitters that focus the emitted light at a specified distance above the surface of the probe for spatially precise optogenetic targeting of neurons. Using the holographic principle, we designed gratings for wavelengths of 488 and 594 nm, targeting the excitation spectra of the optogenetic actuators Channelrhodopsin-2 and Chrimson, respectively. The measured optical emission pattern of these emitters in non-scattering medium and tissue matched well with simulations. To our knowledge, this is the first report of focused spots with the size scale of a neuron soma in brain tissue formed from implantable neural probes.

physics.optics↗

arXiv2023

Rigorous noise reduction with quantum autoencoders

Reducing noise in quantum systems is a major challenge towards the application of quantum technologies. Here, we propose and demonstrate a scheme to reduce noise using a quantum autoencoder with rigorous performance guarantees. The quantum autoencoder learns to compresses noisy quantum states into a latent subspace and removes noise via projective measurements. We find various noise models where we can perfectly reconstruct the original state even for high noise levels. We apply the autoencoder to cool thermal states to the ground state and reduce the cost of magic state distillation by several orders of magnitude. Our autoencoder can be implemented using only unitary transformations without ancillas, making it immediately compatible with the state of the art. We experimentally demonstrate our methods to reduce noise in a photonic integrated circuit. Our results can be directly applied to make quantum technologies more robust to noise.

quant-ph↗

arXiv2023

Efficient option pricing with unary-based photonic computing chip and generative adversarial learning

In the modern financial industry system, the structure of products has become more and more complex, and the bottleneck constraint of classical computing power has already restricted the development of the financial industry. Here, we present a photonic chip that implements the unary approach to European option pricing, in combination with the quantum amplitude estimation algorithm, to achieve a quadratic speedup compared to classical Monte Carlo methods. The circuit consists of three modules: a module loading the distribution of asset prices, a module computing the expected payoff, and a module performing the quantum amplitude estimation algorithm to introduce speed-ups. In the distribution module, a generative adversarial network is embedded for efficient learning and loading of asset distributions, which precisely capture the market trends. This work is a step forward in the development of specialized photonic processors for applications in finance, with the potential to improve the efficiency and quality of financial services.

quant-ph↗

arXiv2023

Implantable Photonic Neural Probes with 3D-Printed Microfluidics and Applications to Uncaging

Advances in chip-scale photonic-electronic integration are enabling a new generation of foundry-manufacturable implantable silicon neural probes incorporating nanophotonic waveguides and microelectrodes for optogenetic stimulation and electrophysiological recording in neuroscience research. Further extending neural probe functionalities with integrated microfluidics is a direct approach to achieve neurochemical injection and sampling capabilities. In this work, we use two-photon polymerization 3D printing to integrate microfluidic channels onto photonic neural probes, which include silicon nitride nanophotonic waveguides and grating emitters. The customizability of 3D printing enables a unique geometry of microfluidics that conforms to the shape of each neural probe, enabling integration of microfluidics with a variety of existing neural probes while avoiding the complexities of monolithic microfluidics integration. We demonstrate the photonic and fluidic functionalities of the neural probes via fluorescein injection in agarose gel and photoloysis of caged fluorescein in solution and in flxed brain tissue.

physics.optics↗

arXiv2022

A photonic chip-based machine learning approach for the prediction of molecular properties

Machine learning methods have revolutionized the discovery process of new molecules and materials. However, the intensive training process of neural networks for molecules with ever-increasing complexity has resulted in exponential growth in computation cost, leading to long simulation time and high energy consumption. Photonic chip technology offers an alternative platform for implementing neural networks with faster data processing and lower energy usage compared to digital computers. Photonics technology is naturally capable of implementing complex-valued neural networks at no additional hardware cost. Here, we demonstrate the capability of photonic neural networks for predicting the quantum mechanical properties of molecules. To the best of our knowledge, this work is the first to harness photonic technology for machine learning applications in computational chemistry and molecular sciences, such as drug discovery and materials design. We further show that multiple properties can be learned simultaneously in a photonic chip via a multi-task regression learning algorithm, which is also the first of its kind as well, as most previous works focus on implementing a network in the classification task.

cs.ET↗

arXiv2022

Microcantilever-integrated photonic circuits for broadband laser beam scanning

Laser beam scanning is central to many applications, including displays, microscopy, three-dimensional mapping, and quantum information. Reducing the scanners to microchip form factors has spurred the development of very-large-scale photonic integrated circuits of optical phased arrays and focal plane switched arrays. An outstanding challenge remains to simultaneously achieve a compact footprint, broad wavelength operation, and low power consumption. Here, we introduce a laser beam scanner that meets these requirements. Using microcantilevers embedded with silicon nitride nanophotonic circuitry, we demonstrate broadband, one- and two-dimensional steering of light with wavelengths from 410 nm to 700 nm. The microcantilevers have ultracompact ~0.1 mm$^2$ areas, consume ~31 to 46 mW of power, are simple to control, and emit a single light beam. The microcantilevers are monolithically integrated in an active photonic platform on 200-mm silicon wafers. The microcantilever-integrated photonic circuits miniaturize and simplify light projectors to enable versatile, power-efficient, and broadband laser scanner microchips.

physics.optics↗

arXiv2022

Monolithically integrated, broadband, high-efficiency silicon nitride-on-silicon waveguide photodetectors in a visible-light integrated photonics platform

Visible and near-infrared spectrum photonic integrated circuits are quickly becoming a key technology to address the scaling challenges in quantum information and biosensing. Thus far, integrated photonic platforms in this spectral range have lacked integrated photodetectors. Here, we report the first silicon nitride-on-silicon waveguide photodetectors that are monolithically integrated in a visible light photonic platform on silicon. Owing to a leaky-wave silicon nitride-on-silicon design, the devices achieved a high external quantum efficiency of > 60% across a record wavelength span from $λ$ ~400 nm to ~640 nm, an opto-electronic bandwidth up to 9 GHz, and an avalanche gain-bandwidth product up to 173 $\pm$ 30 GHz. As an example, a photodetector was integrated with a wavelength-tunable microring in a single chip for on-chip power monitoring.

physics.optics↗

arXiv2021

Power-Efficient Silicon Nitride Thermo-Optic Phase Shifters for Visible Light

We demonstrate power-efficient, thermo-optic, silicon nitride waveguide phase shifters for blue, green, and yellow wavelengths. The phase shifters operated with low power consumption due to a suspended structure and multi-pass waveguide design. The devices were fabricated on 200-mm silicon wafers using deep ultraviolet lithography as part of an active visible-light integrated photonics platform. The measured power consumption to achieve a $π$ phase shift (averaged over multiple devices) was 0.78, 0.93, 1.09, and 1.20 mW at wavelengths of 445, 488, 532, and 561 nm, respectively. The phase shifters were integrated into Mach-Zehnder interferometer switches, and $10- 90$\% rise(fall) times of about 570(590) $μ$s were measured.

physics.optics↗