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1. Unified k-space theory of optical coherence tomography

   https://doi.org/10.1364/AOP.417102  

   Zhou, Kevin C.; Qian, Ruobing; Dhalla, Al-Hafeez; Farsiu, Sina; Izatt, Joseph A. (January 2021, Advances in Optics and Photonics)

   We present a general theory of optical coherence tomography (OCT), which synthesizes the fundamental concepts and implementations of OCT under a common 3D k -space framework. At the heart of this analysis is the Fourier diffraction theorem, which relates the coherent interaction between a sample and plane wave to the Ewald sphere in the 3D k -space representation of the sample. While only the axial dimension of OCT is typically analyzed in k -space, we show that embracing a fully 3D k -space formalism allows explanation of nearly every fundamental physical phenomenon or property of OCT, including contrast mechanism, resolution, dispersion, aberration, limited depth of focus, and speckle. The theory also unifies diffraction tomography, confocal microscopy, point-scanning OCT, line-field OCT, full-field OCT, Bessel beam OCT, transillumination OCT, interferometric synthetic aperture microscopy (ISAM), and optical coherence refraction tomography (OCRT), among others. Our unified theory not only enables clear understanding of existing techniques but also suggests new research directions to continue advancing the field of OCT. 

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2. Assessment of Models for Extracting Thermal Conductivity From Frequency Domain Thermoreflectance Experiments

   https://doi.org/10.1115/HT2020-8920  

   Saurav, Siddharth; Mazumder, Sandip (July 2020, Proceedings of the ASME Summer Heat Transfer Conference, SHTC2020)

   Abstract The Fourier heat conduction and the hyperbolic heat conduction equations were solved numerically to simulate a frequency-domain thermoreflectance (FDTR) experimental setup. Numerical solutions enable use of realistic boundary conditions, such as convective cooling from the various surfaces of the substrate and transducer. The equations were solved in time domain and the phase lag between the temperature at the center of the transducer and the modulated pump laser signal were computed for a modulation frequency range of 200 kHz to 200 MHz. It was found that the numerical predictions fit the experimentally measured phase lag better than analytical frequency-domain solutions of the Fourier heat equation based on Hankel transforms. The effects of boundary conditions were investigated and it was found that if the substrate (computational domain) is sufficiently large, the far-field boundary conditions have no effect on the computed phase lag. The interface conductance between the transducer and the substrate was also treated as a parameter, and was found to have some effect on the predicted thermal conductivity, but only in certain regimes. The hyperbolic heat conduction equation yielded identical results as the Fourier heat conduction equation for the particular case studied. The thermal conductivity value (best fit) for the silicon substrate considered in this study was found to be 108 W/m/K, which is slightly different from previously reported values for the same experimental data. 

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3. An improved training scheme for deep neural network ultrasound beamforming

   https://doi.org/10.1109/ULTSYM.2019.8925953  

   Vienneau, Emelina; Luchies, Adam; Byram, Brett (October 2019, 2019 IEEE International Ultrasonics Symposium (IUS))

   Deep neural networks have been shown to be effective adaptive beamformers for ultrasound imaging. However, when training with traditional L p norm loss functions, model selection is difficult because lower loss values are not always associated with higher image quality. This ultimately limits the maximum achievable image quality with this approach and raises concerns about the optimization objective. In an effort to align the optimization objective with the image quality metrics of interest, we implemented a novel ultrasound-specific loss function based on the spatial lag-one coherence and signal-to-noise ratio of the delayed channel data in the short-time Fourier domain. We employed the R-Adam optimizer with look ahead and cyclical learning rate to make the training more robust to initialization and local minima, leading to better model performance and more reliable convergence. With our custom loss function and optimization scheme, we achieved higher contrast-to-noise-ratio, higher speckle signal-to-noise-ratio, and more accurate contrast ratio reconstruction than with previous deep learning and delay-and-sum beamforming approaches. 

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4. Vernier microcombs for integrated optical atomic clocks

   https://doi.org/10.1038/s41566-025-01617-0  

   Wu, Kaiyi; O’Malley, Nathan P; Fatema, Saleha; Wang, Cong; Girardi, Marcello; Alshaykh, Mohammed S; Ye, Zhichao; Leaird, Daniel E; Qi, Minghao; Torres-Company, Victor; et al (April 2025, Nature Photonics)

   Abstract Kerr microcombs have drawn substantial interest as mass-manufacturable, compact alternatives to bulk frequency combs. This could enable the deployment of many comb-reliant applications previously confined to laboratories. Particularly enticing is the prospect of microcombs performing optical frequency division in compact optical atomic clocks. Unfortunately, it is difficult to meet the self-referencing requirement of microcombs in these systems owing to the approximately terahertz repetition rates typically required for octave-spanning comb generation. In addition, it is challenging to spectrally engineer a microcomb system to align a comb mode with an atomic clock transition with a sufficient signal-to-noise ratio. Here we adopt a Vernier dual-microcomb scheme for optical frequency division of a stabilized ultranarrow-linewidth continuous-wave laser at 871 nm to an ~235 MHz output frequency. This scheme enables shifting an ultrahigh-frequency (~100 GHz) carrier-envelope offset beat down to frequencies where detection is possible and simultaneously placing a comb line close to the 871 nm laser—tuned so that, if frequency doubled, it would fall close to the clock transition in¹⁷¹Yb⁺. Our dual-comb system can potentially combine with an integrated ion trap towards future chip-scale optical atomic clocks. 

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5. On the Determination of Thermal Conductivity From Frequency Domain Thermoreflectance Experiments

   https://doi.org/10.1115/1.4052655  

   Saurav, Siddharth; Mazumder, Sandip (January 2022, Journal of Heat Transfer)

   Abstract The Fourier and the hyperbolic heat conduction equations were solved numerically to simulate a frequency-domain thermoreflectance (FDTR) experiment. Numerical solutions enable isolation of pump and probe laser spot size effects and use of realistic boundary conditions. The equations were solved in time domain and the phase lag between the temperature of the transducer (averaged over the probe laser spot) and the modulated pump laser signal was computed for a modulation frequency range of 200 kHz–200 MHz. Numerical calculations showed that extracted values of the thermal conductivity are sensitive to both the pump and probe laser spot sizes, while analytical solutions (based on Hankel transform) cannot isolate the two effects. However, for the same effective (combined) spot size, the two solutions are found to be in excellent agreement. If the substrate (computational domain) is sufficiently large, the far-field boundary conditions were found to have no effect on the computed phase lag. The interface conductance between the transducer and the substrate was found to have some effect on the extracted thermal conductivity. The hyperbolic heat conduction equation yielded almost the same results as the Fourier heat conduction equation for the particular case studied. The numerically extracted thermal conductivity value (best fit) for the silicon substrate considered in this study was found to be about 82–108 W/m/K, depending on the pump and probe laser spot sizes used. 

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