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Rydberg atom-based sensors use atoms dressed by lasers to detect and measure radio frequency electromagnetic fields. The absorptive properties of the atomic gas, configured as a Rydberg atom-based sensor, change in the presence of a radio frequency electromagnetic field. While these sensors are reasonably sensitive, the best conventional radio frequency sensors still outperform Rydberg atom-based sensors with respect to sensitivity. One approach to increase the sensitivity of Rydberg atom-based sensors is to engineer the vapor cell that contains the atomic gas. In this work, we introduce a passive, all-dielectric amplifier integrated into a Rydberg atom-based sensor vapor cell. The vapor cell is a combination of a slot waveguide and a photonic crystal. The structural features of the vapor cell yield a power amplification of ~24 dB. The radio frequency electromagnetic field is coupled adiabatically into the slot waveguide and slowed to increase the interaction between the radio frequency field and the atoms to effectively amplify the incoming signal, i.e., increase the Rabi frequency on the radio frequency transition. The work shows the utility of vapor cell engineering for atom-based quantum technologies and paves the way for other such devices.

Graves' disease is a common condition that is diagnosed clinically by determining the smoothness of the thyroid texture and its morphology in ultrasound images. Currently, the most widely used approach for the automated diagnosis of Graves' disease utilizes Convolutional Neural Networks (CNNs) for both feature extraction and classification. However, these methods demonstrate limited efficacy in capturing texture features. Given the high capacity of wavelets in describing texture features, this research integrates learnable wavelet modules utilizing the Lifting Scheme into CNNs and incorporates a parallel wavelet branch into the ResNet18 model to enhance texture feature extraction. Our model can analyze texture features in spatial and frequency domains simultaneously, leading to optimized classification accuracy. We conducted experiments on collected ultrasound datasets and publicly available natural image texture datasets, our proposed network achieved 97.27% accuracy and 95.60% recall on ultrasound datasets, 60.765% accuracy on natural image texture datasets, surpassing the accuracy of ResNet and conrming the effectiveness of our approach.

Laser sources power extreme data transmission as well as computing acceleration, access to ultrahigh-speed signaling, and sensing for chemicals, distance, and pattern recognition. The ever-growing scale of these applications drives innovation in multi-wavelength lasers for massively parallel processing. We report a nanophotonic Kerr-resonator circuit that consumes the power of an input laser and generates a soliton frequency comb at approaching unit efficiency. By coupling forward and backward propagation, we realize a bidirectional Kerr resonator that supports universal phase matching but also opens excess loss by double-sided emission. Therefore, we induce reflection of the resonator's forward, external-coupling port to favor backward propagation, resulting in efficient, one-sided soliton formation. Coherent backscattering with nanophotonics provides the control to put arbitrary phase-matching and efficient laser-power consumption on equal footing in Kerr resonators. In the overcoupled-resonator regime, we measure 65% conversion efficiency of a 40 mW input pump laser, and the nonlinear circuit consumes 97% of the pump, generating the maximum possible comb power. Our work opens up high-efficiency soliton formation in integrated photonics, exploring how energy flows in nonlinear circuits and enabling laser sources for advanced transmission, computing, quantum sensing, and artificial-intelligence applications.

Nonlinear-wave mixing in optical microresonators offers new perspectives to generate compact optical-frequency microcombs, which enable an ever-growing number of applications. Microcombs exhibit a spectral profile that is primarily determined by their microresonator's dispersion; an example is the $ \operatorname{sech}^2 $ spectrum of dissipative Kerr solitons under anomalous group-velocity dispersion. Here, we introduce an inverse-design approach to spectrally shape microcombs, by optimizing an arbitrary meta-dispersion in a resonator. By incorporating the system's governing equation into a genetic algorithm, we are able to efficiently identify a dispersion profile that produces a microcomb closely matching a user-defined target spectrum, such as spectrally-flat combs or near-Gaussian pulses. We show a concrete implementation of these intricate optimized dispersion profiles, using selective bidirectional-mode hybridization in photonic-crystal resonators. Moreover, we fabricate and explore several microcomb generators with such flexible `meta' dispersion control. Their dispersion is not only controlled by the waveguide composing the resonator, but also by a corrugation inside the resonator, which geometrically controls the spectral distribution of the bidirectional coupling in the resonator. This approach provides programmable mode-by-mode frequency splitting and thus greatly increases the design space for controlling the nonlinear dynamics of optical states such as Kerr solitons., Comment: 16 pages, includes SI

By design access to laser wavelength, especially with integrated photonics, is critical to advance quantum sensors like optical clocks and quantum-information systems, and open opportunities in optical communication. Semiconductor-laser gain provides exemplary efficiency and integration but merely in developed wavelength bands. Alternatively, nonlinear optics requires control of phase matching, but the principle of nonlinear conversion of a pump laser to a designed wavelength is extensible. We report on laser-wavelength access by versatile customization of optical-parametric oscillation (OPO) with a photonic-crystal resonator (PhCR). By controlling the bandgap of a PhCR, we enable OPO generation across a wavelength range of 1234-2093 nm with a 1550 nm pump and 1016-1110 nm with a 1064 nm pump. Moreover, our tunable laser platform offers pump-to-sideband conversion efficiency of >10% and negligible additive optical-frequency noise across the output range. From laser design to simulation of nonlinear dynamics, we use a Lugiato-Lefever framework that predicts the system characteristics, including bi-directional OPO generation in the PhCR and conversion efficiency in agreement with our observations. Our experiments introduce tunable lasers by design with PhCR OPOs, providing critical functionalities in integrated photonics., Comment: 6 pages, 5 figures