Particle swarm optimization of silicon photonic crystal waveguide transition

Intelligently optimized global analysis of time resolved spectra with particle swarm optimization

Time-resolved spectroscopy, especially transient absorption spectroscopy (TAS), provides valuable insights to excited state dynamics. Analyzing TAS data involves fitting complex kinetic traces at various probe wavelengths using different rate equations. Conventional TAS global fitting methods require domain experts to establish physically valid models and provide good initial guesses to generate converged solutions. This poses challenges for non-experts who seek to utilize TAS, thus limiting its broader application and impact. To address this problem, we propose an intelligent optimization framework based on the particle swarm optimization (PSO) algorithm. In the proposed method, the PSO algorithm acts as the global fitting method to find the optimal values of the target variables or unknown parameters in the kinetics models. The target solution is optimized by iteratively updating candidate solutions with respect to an objective feedback signal. We demonstrated the effectiveness of the proposed PSO-based global fitting method with both synthetic and experimental datasets. The results show that our proposed method can successfully find the optimal target values in the global fitting process automatically, thus eliminating the iterative manual labor traditionally required. The proposed intelligent optimization framework provides a novel approach for automatic global fitting of TAS data, which significantly enhances the accessibility and utilization of the TAS methodology.

Slow-Light-Enhanced Polarization Division Multiplexing Infrared Absorption Spectroscopy for On-Chip Wideband Multigas Detection in a 1D Photonic Crystal Waveguide

Slow-light photonic crystal waveguide (PCW) gas sensors based on infrared absorption spectroscopy play a pivotal role in enhancing the on-chip interaction between light and gas molecules, thereby significantly boosting sensor sensitivity. However, two-dimensional (2D) PCWs are limited by their narrow mode bandwidth and susceptibility to polarization, which restricts their ability for multigas measurement. Due to quasi-TE and quasi-TM mode guiding characteristics in one-dimensional (1D) PCW, a novel slow-light-enhanced polarization division multiplexing infrared absorption spectroscopy was proposed for on-chip wideband multigas detection. The optimized 1D PCW gas sensor experimentally shows an impressive slow-light mode bandwidth exceeding 100 nm (TM, 1500-1550 nm; TE, 1610-1660 nm) with a group index ranging from 4 to 25 for the two polarizations. The achieved bandwidth in the 1D PCW is 2-3 times that of the reported quasi-TE polarized 2D PCWs. By targeting the absorption lines of different gas species, multigas detection can be realized by modulating the lasers and demodulating the absorption signals at different frequencies. As an example, we performed dual-gas measurements with the 1D PCW sensor operating in TE mode at 1.65 μm for methane (CH4) detection and in TM mode at 1.53 μm for acetylene (C2H2) detection. The 1 mm long sensor achieved a remarkable limit of detection (LoD) of 0.055% for CH4 with an averaging time of 17.6 s, while for C2H2, the LoD was 0.18%. This polarization multiplexing sensor shows great potential for on-chip gas measurement because of the slow-light enhancement in the light-gas interaction effect as well as the large slow-light bandwidth for multigas detection.

A novel planning framework for efficient spot-scanning proton arc therapy via particle swarm optimization (SPArc-particle swarm)

Objective.Delivery efficiency is the bottleneck of spot-scanning proton arc therapy (SPArc) because of the numerous energy layers (ELs) ascending switches. This study aims to develop a new algorithm to mitigate the need for EL ascending via water equivalent thickness (WET) sector selection followed by particle swarm optimization (SPArc-particle swarm).Approach.SPArc-particle swarmdivided the full arc trajectory into the optimal sectors based on K-means clustering analysis of the relative mean WET. Within the sector, particle swarm optimization was used to minimize the total energy switch time, optimizing the energy selection integrated with the EL delivery sequence and relationship. This novel planning framework was implemented on the open-source platform matRad (Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ). Three representative cases (brain, liver, and prostate cancer) were selected for testing purposes. Two kinds of plans were generated: SPArc_seq and SPArc-particle swarm. The plan quality and delivery efficiency were evaluated.Main results. With a similar plan quality, the delivery efficiency was significantly improved using SPArc-particle swarmcompared to SPArc_seq. More specifically, it reduces the number of ELs ascending switching compared to the SPArc_seq (from 21 to 7 in the brain, from 21 to 5 in the prostate, from 21 to 6 in the liver), leading to a 16%-26% reduction of the beam delivery time (BDT) in the SPArc treatment.Significance. A novel planning framework, SPArc-particle swarm, could significantly improve the delivery efficiency, which paves the roadmap towards routine clinical implementation.

Optical fractal in cryogenic environments based on distributed feedback Bragg photonic crystals

We studied the optical fractal effect of the one-dimensional distributed feedback Bragg photonic crystals formed by semiconductor GaAs and dielectric TiO2. Light wave is transmitted in the intermediate dielectric slab and reflected back by the periodic photonic crystals at both ends, forming multiple fractal resonance output. The transmission channels expand exponentially by thickening the bulk in a cryogenic environment. The quality factor of each fractal resonant state improves with a greater periodic number of crystals. Furthermore, central wave of resonance has a blue-shift as the external pressure increases, while the influence of environment temperature on the fractal resonance could be ignored. It is hoped that our study can highlight the potential of these findings for designing multi-channel communication filters in cryogenic environments.

OFDR analysis of Si photonics FMCW LiDAR chip

We experimentally analyzed the internal reflection and loss of each component in a Si photonics frequency-modulated continuous-wave light detection and ranging (FMCW LiDAR) device using optical frequency domain reflectometry (OFDR) with a spatial resolution of better than 2.5 µm. Sweeping the incident laser wavelength by 120 nm, the reflections and losses of wire waveguides, widened waveguides, and optical switches on the chip were individually revealed. The slow-light grating (SLG) beam scanner, which has a limited working wavelength range, was evaluated with a spatial resolution of >10 µm by narrowing the wavelength sweep range. Consequently, a strong reflection was observed at the transition between the wire waveguide and the SLG, which can be a noise source in the FMCW LiDAR. Additionally, this study showed that the OFDR can be an important analysis tool for Si photonics integrated circuits. To our knowledge, this is the first demonstration, showing that the OFDR can be an important analysis tool for Si photonic integrated circuits.

A Comprehensive Review of Bio-Inspired Optimization Algorithms Including Applications in Microelectronics and Nanophotonics

The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at an accelerated pace. Because of that, in spite of the fact that there are a lot of surveys and reviews in the field, they quickly become dated. Thus, it is of importance to keep pace with the current developments. In this review, we first consider a possible classification of bio-inspired multiparameter optimization methods because papers dedicated to that area are relatively scarce and often contradictory. We proceed by describing in some detail some more prominent approaches, as well as those most recently published. Finally, we consider the use of biomimetic algorithms in two related wide fields, namely microelectronics (including circuit design optimization) and nanophotonics (including inverse design of structures such as photonic crystals, nanoplasmonic configurations and metamaterials). We attempted to keep this broad survey self-contained so it can be of use not only to scholars in the related fields, but also to all those interested in the latest developments in this attractive area.

Ultra-narrow, highly efficient power splitters and waveguides that exploit the TE01 Mie-resonant bandgap

In this paper, ultra-narrow and highly-efficient straight and Ω-shaped waveguides, and Y-shaped and T-shaped optical power splitters composed of two rows of two-dimensional germanium rods in air are designed and simulated. The position-disordering effect on the waveguides is considered. Finite-difference time-domain numerical simulation results for two rows of straight and Ω-shaped waveguides with no position disordering at the normalized frequency of a λ=0.327 show optical transmission of 90%, and two rows of Y-shaped and T-shaped power splitters with no position disordering have transmissions >46% for each output branch at the normalized frequency of a λ=0.327. Also, the straight and Ω-shaped waveguides with four rows of germanium rods tolerated position disordering of η = 10%. The proposed ultra-narrow waveguides and power splitters are vital components in high-density and all-dielectric optical integrated circuits.

Si photonic crystal slow-light waveguides optimized through informatics technology

We modeled the photonic bands of SiO₂-cladded Si lattice-shifted photonic crystal waveguides via machine learning and found a structure that generates low-dispersion slow light with a group index of approximately 20 in the full C-band at telecom wavelengths. The normalized delay-bandwidth product is as large as 0.45, which is close to the theoretical upper limit. The transition structure between this waveguide and a Si-channel waveguide was designed using an evolutional optimization, and a C-band average loss of 0.116 dB/transition was calculated. These results prove the possibility of further enhancing the versatility of slow light.

Space-time-domain observation of high-speed optical beam scanning in a thermo-optic Si photonic crystal slow-light beam scanner

We developed a thermo-optically controlled nonmechanical optical beam scanner using a Si photonic crystal slow-light waveguide with a diffraction grating to achieve on-chip light detection and ranging (LIDAR). This Letter applies pre-emphasis signals to the thermo-optic control, and the cutoff frequency increases to 500 kHz. Observing the beam scanning in the space-time domain showed that the turn-on and turn-off times of the scanner for a rectangular drive voltage were 10 µs and reduced to 2.7 µs when the pre-emphasis signals were optimized. This new, to the best of our knowledge, result enables a frame rate of 29 fps for 12,800 resolution points in LIDAR.