# Comparison of the performance of RF photonic transversal signal processors based on microcombs using discrete components versus integrated chips

David Moss

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David Moss. Comparison of the performance of RF photonic transversal signal processors based on microcombs using discrete components versus integrated chips. 2024. hal-04491289

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# Comparison of the performance of RF photonic transversal signal processors based on microcombs using discrete components versus integrated chips

David J. Moss

David J. Moss

Optical Sciences Center, Swinburne University of Technology, Hawthorn, VIC 3122, Australia

e-mail: dmoss@swin.edu.au.

## Abstract

RF photonic transversal signal processors, which combine reconfigurable electrical digital signal processing and high-bandwidth photonic processing, provide a powerful solution for achieving adaptive high-speed information processing. Recent progress in optical microcomb technology provides compelling multi-wavelength sources with compact footprint, yielding a variety of microcomb-based RF photonic transversal signal processors implemented by either discrete or integrated components. Although operating based on the same principle, processors in these two forms exhibit distinct performance. This letter presents a comparative investigation into their performance. First, we compare the performance of state-of-the-art processors, focusing on the processing accuracy. Next, we analyze various factors that contribute to the performance differences, including tap number and imperfect response of experimental components. Finally, we discuss the potential for future improvement. These results provide a comprehensive comparison of microcomb-based RF photonic transversal signal processors implemented using discrete and integrated components and provide insights for their future development.

*Index Terms*—RF photonics, optical microcombs, optical signal processing, photonic integration.

## I. INTRODUCTION

Driven by the exponential growth of data capacity, there has been a rapid increase in the demand for high-speed information processing. Radio-frequency (RF) photonics, which utilize photonic hardware and technologies to process high-bandwidth RF signals, provides speed advantages over electrical signal processing with intrinsic bandwidth limitations [1]. Among the various schemes to implement RF photonic processors, RF photonic transversal signal processors have garnered significant interest due to their exceptional reconfigurability, allowing for the realization of diverse processing functions without the need for changing any hardware [2-36].
In RF photonic transversal signal processors, a number of wavelength channels are needed to facilitate high reconfigurability and ensure high processing accuracy. In addition, a wide channel spacing between these wavelength channels is necessary to ensure a large operational bandwidth. Recent advances in optical microcomb technology provide a competitive solution to meet these requirements by generating a substantial number of widely spaced wavelengths from a micro-scale resonator, together with added benefits of significantly reduced device footprint, power consumption, and complexity [37]. In contrast, conventional multi-wavelength sources, such as discrete laser arrays [38], fiber Bragg grating arrays [39], laser frequency combs generated by electro-optic (EO) modulation [40], and mode-locked fiber lasers [41] suffer from limitations in one form or another, such as a limited number of wavelength channels and insufficient channel spacings.

Early implementations of microcomb-based RF photonic transversal signal processors simply replaced conventional multi-wavelength sources with optical microcombs while retaining all other components as discrete devices [1, 2-36]. Although this already yields significant benefits, there is much more to be gained by increasing the level of integration for the entire processing system, particularly with respect to the system size, power consumption, and cost. Recently, several processors comprised entirely of integrated components have also been demonstrated [42, 43]. Despite based on the same operation principle, the processors implemented by discrete and integrated components present different processing performance.

In this paper, we provide a comparative study of the performance of microcomb-based RF photonic transversal signal processors implemented by discrete and integrated components. First, we compare the performance of state-of-the-art processors, focusing on the processing accuracy. Next, we conduct analysis of multiple factors that induce the performance differences, including tap number and imperfect response of experimental components. Finally, we discuss the potential for future development. These results provide a comprehensive comparison and valuable perspectives for these processors with high reconfigurability for diverse signal processing applications.

## II. MICROCOMB-BASED RF PHOTONIC TRANSVERSAL SIGNAL PROCESSORS

RF transversal signal processors are implemented based on the transversal filter structure in digital signal processing, which features a finite impulse response and has found applications in a wide range of signal processing functions [1]. Implementing these processors by using RF photonic technology can yield significantly higher processing bandwidth compared to their electronic counterparts [1], and the use of optical microcombs provides a powerful multiwavelength source that is critical for the RF photonic system. Fig. 1(a) illustrates the operation principle of a microcomb-based RF photonic transversal signal processor. The processor employs an optical microcomb as a multiwavelength source, which simultaneously generates numerous wavelength channels
as discrete taps. Input RF signal is modulated onto each wavelength channel via EO modulation, producing multiple RF replicas. Next, optical spectral shaping is applied to weight these modulated replicas, and time delay is introduced between adjacent wavelength channels. Finally, the weighted and delayed RF replicas are added together through photodetection to generate the final RF output of the processor. After going through the processing flow in Fig. 1(a), the output RF signal $s(t)$ can be given by [1].

$$s(t) = \sum_{n=0}^{M-1} a_n f(t - n\Delta T), \qquad (1)$$

where $f(t)$ is the input RF signal, $M$ is the tap number, $a_n$ ($n = 0, 1, 2, \dots, M-1$) is the tap weight of the $n^{th}$ tap, and $\Delta T$ is the time delay between adjacent wavelength channels. Therefore, the system's impulse response can be expressed as [1].

$$h(t) = \sum_{n=0}^{M-1} a_n \delta(t - n\Delta T), \qquad (2)$$

After Fourier transformation from Eq. (2), the spectral transfer function of the processor can be described as

$$H(\omega) = \text{FT}[h(t)] = \sum_{n=0}^{M-1} a_n e^{-j\omega n \Delta T}, \qquad (3)$$

According to Eqs. (1) – (3), different processing functions can be realized by appropriately setting the tap coefficients $a_n$ ($n = 0, 1, 2, \dots, M-1$) without changing the hardware, which allows for a high reconfigurability for the processor.
<figure><img src="image_2.png" /><figcaption>**Fig. 1.** (a) Schematic illustration of the operation principle of a microcomb-based RF photonic transversal signal processor. (b) Schematic of a microcomb-based RF photonic transversal signal processor implemented by discrete components. (c) Schematic of an on-chip microcomb-based RF photonic transversal signal processor implemented by integrated components. EOM: electro-optic modulator. RF: radio frequency. PD: photodetector. CW laser: continuous-wave laser. EDFA: erbium-doped fibre amplifier. PC: polarization controller. MRR: microring resonator. SMF: single-mode fibre. OSS: optical spectral shaper. BPD: balanced photodetector. BPD: balanced photodetector. ART: anti-reflection termination.</figcaption></figure>

Based on the operation principle in **Fig. 1(a)**, microcomb-based RF photonic transversal signal processors can be practically implemented into two forms. The first form is illustrated in **Fig. 1(b)**, where all the components are discrete devices except for an integrated microring resonator (MRR) used to generate optical microcombs. The second is comprised entirely of integrated components, as shown in **Fig. 1(c)**. To simplify our discussion, we will refer to the processors implemented in these two forms as discrete and integrated processors. Early microcomb-based RF photonic transversal signal processors were in the form of discrete processors [1, 2], while more recently, some integrated processors have been demonstrated [42, 43]. Although the operation principle remains consistent across these two forms, their different components result in distinct performance. In the following, we compare their performance in **Section III** and discuss their potential for improvement in **Section IV**.

### III. PERFORMANCE COMPARISON OF DISCRETE AND INTEGRATED PROCESSORS

In this section, we compare the performance of discrete and integrated processors shown in **Figs. 1(b)** and (c), respectively. Although the size, weight, and power consumption (SWaP) of integrated processors are greatly reduced compared with the discrete processors, the state-of-the-art integrated processors suffer from limited tap
numbers due to the restrictions imposed by the integrated components. Currently, integrated processors with only 8 [42] and 12 taps [43] have been demonstrated, whereas discrete processors have been implemented with up to 80 taps [1, 44]. The difference in the tap numbers results in a difference in the processing accuracy [44]. In addition, the imperfect response of experimental components also induces processing errors. These mainly include noise of microcombs, chirp of the EOM, errors in the delay element, and errors of the spectral shaping module [44].

**Table I** summarizes parameters of the components in the three processors that we investigate, including a discrete processor (Processor 1) and two integrated processors (Processors 2 and 3). There are two integrated processors: one with the same tap number as that in Ref. [42] and the other with an increased tap number to demonstrate the potential for improvement. To characterize the errors induced by imperfect experimental components, optical signal-to-noise ratios (OSNRs), chirp parameters ($\alpha$), error of the delay element ($t_v$), and random tap coefficient errors (RTCEs) are introduced. These parameters are all set based on the real processors in Refs. [43-47]. For comparison, we assume that the three processors employ the same microcomb with a comb spacing of 0.4 nm (~50 GHz). We also assume that the time delay between adjacent taps in Eq. (3) is $\Delta T = 33.4$ ps to ensure the same operation bandwidth.

<table><caption>TABLE I. COMPARISON OF COMPONENTS' PARAMETERS IN DISCRETE AND INTEGRATED PROCESSORS</caption><tbody><tr><th rowspan="2">Discrete processor</th><th>No.</th><th>Tap No.</th><th>OSNR of microcombs</th><th>Chirp parameter of the EOM</th><th>Errors of the delay element</th><th>RTCE of the spectral shaping module</th></tr><tr><td>1</td><td><i>M</i> = 80 [44]</td><td>OSNR: 20 dB [44]</td><td>α: 0.1 [47]</td><td><i>t</i><sub>v</sub>: 4% [44]</td><td>RTCE: 5% [44]</td></tr><tr><th rowspan="4">Integrated processors</th><th>No.</th><th>Tap No.</th><th>OSNR of microcombs</th><th>Chirp parameter of the EOM</th><th>Error of the delay element</th><th>RTCE of the spectral shaping module</th></tr><tr><td>2</td><td><i>M</i> = 8 [42]</td><td>OSNR: 20 dB [44]</td><td>α: 0.8 [45]</td><td><i>t</i><sub>v</sub>: 3% [43]</td><td>RTCE: 9% [46]</td></tr><tr><th>No.</th><th>Tap No.</th><th>OSNR of microcombs</th><th>Chirp parameter of the EOM</th><th>Error of the delay element</th><th>RTCE of the spectral shaping module</th></tr><tr><td>3</td><td><i>M</i> = 20</td><td>OSNR: 20 dB [44]</td><td>α: 0.8 [45]</td><td><i>t</i><sub>v</sub>: 3% [43]</td><td>RTCE: 9% [46]</td></tr></tbody></table>

Compared with discrete EOM, the integrated EOM has a relatively high chirp parameter in **Table I**, mainly because achieving an accurate bias point and precise electrode placement is more challenging for integrated devices [47]. The lower accuracy for the delay element in the discrete processor is mainly caused by the high-order dispersion of the dispersive medium (e.g., optical fibre), which results in non-uniform time delays between adjacent wavelength channels [44]. In contrast, in integrated processors time delay is introduced by integrated optical delay lines (e.g., Si spiral waveguides), which exhibit a higher accuracy owing to the precise control over the amount of delay achieved by designing specific length and refractive index profile [48]. The accuracy differences between the integrated and discrete spectral shaping modules are more noticeable. Although the integrated spectral shaping modules have much lower tap numbers, they have lower spectral shaping accuracy
compared to their discrete counterparts. This is due to the fact that commercial discrete waveshapers based on mature liquid crystal on silicon (LCoS) technology offer much better accuracy for amplitude and phase control, as well as inter-channel synchronization [49].

In our following analysis, three typical signal processing functions including first-order differentiation (DIF), integration (INT), and Hilbert transform (HT) are taken as examples to compare the accuracy of discrete and integrated processors. The tap numbers required to achieve these processing functions are designed based on our previous work in Refs. [1]. To quantify the comparison of processing accuracy, the root mean square error (RMSE) is introduced to compare the deviation between the processors’ outputs and the ideal results, which is expressed as

$$RMSE = \sqrt{\frac{\sum_{i=1}^{k} (y_i - y_{i-1})^2}{k}} \quad (4)$$

where k is the number of sampled points, $Y_1, Y_2, \dots, Y_n$ are the values of the ideal result, and $y_1, y_2, \dots, y_n$ are the values of the output of the processors.

<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Temporal waveform of Gaussian input pulse and output waveforms from Processors 1 – 3 that perform (a) differentiation (DIF), (b) integration (INT), and (c) Hilbert transform (HT). The processors’ outputs with errors induced by (1) only limited tap numbers and (2) both limited tap numbers and experimental errors are shown, together with the ideal processing result for comparison.</figcaption></figure>
**Figs. 2(a) – (c)** show the outputs of Processors 1 – 3 in **Table I** that perform DIF, INT, and HT, respectively. The input RF signal is a Gaussian pulse with a full-width-at-half-maximum (FWHM) of ~0.17 ns. Here we show the processors’ outputs with errors induced by (1) only limited tap numbers and (2) both limited tap numbers and experimental errors. The ideal processing results are also shown for comparison. Deviations between the processors’ outputs and the ideal results are observed for all three functions, and the deviations become more significant when taking into account the experimental errors.

**Fig. 3** compares RMSEs of the processors in **Fig. 2**. The higher processing accuracy of the discrete processor, compared to the integrated processors, is reflected by the lower RMSEs of Processor 1 for all three processing functions. In addition, the RMSEs of Processor 3 are lower compared to Processor 2, which indicates a higher processing accuracy achieved by increasing the tap number. According to the results in **Fig. 3**, the primary factor that contributes to the degradation of accuracy for integrated processors is the limited tap number. Whereas for discrete processors with a sufficiently large tap number, the processing inaccuracy is mainly induced by the imperfect response of experimental components. We also note that the differences in RMSEs among Processors 1 – 3 are more prominent for the INT than the other two processing functions, indicating a higher requirement for a greater number of taps to improve the processing accuracy of INT. In addition, experimental errors have a substantial impact on the RMSEs of DIF, whereas their impact on HT is very small.

<figure><img src="image_4.png" /><figcaption>**Fig. 3.** Comparison of root mean square errors (RMSEs) of Processors 1 – 3 that perform (a) DIF, (b) INT, and (c) HT. The RMSEs of processors’ outputs with errors induced by (1) only limited tap numbers and (2) both limited tap numbers and experimental errors are shown.</figcaption></figure>

## IV. POTENTIAL FOR IMPROVEMENT

In this section, we discuss the potential for improvement for both the discrete and integrated processors. In **Fig. 4(a)**, we quantitatively analyze the influence of tap number *M* on the processing accuracy, where the parameters of the input signal and the processor components are kept the same as those in **Fig. 2**. Similar to that in **Figs. 2** and **3**, we show the results with errors induced by (1) only limited tap numbers and (2) both limited tap numbers and experimental errors. It is evident that when assuming no experimental errors, both discrete and integrated processors exhibit the same RMSE values at the same *M*, as they possess identical comb spacing and time delay.
When experimental errors are considered, the RMSEs no longer exhibit a monotonic decrease with the tap number *M* as observed when assuming no experimental errors. This can be attributed to the accumulated experimental errors as *M* increases, such as increased shaping errors in both discrete and integrated processors, as well as the increased errors of time delay induced by higher-order dispersion in discrete processors [44].

When considering experimental errors, DIF, INT, and HT require a tap number of 20, 20, and 80 to achieve a RMSE of ~0.05, respectively. Although this can be easily achieved by the discrete processor, it is challenging for the state-of-the-art integrated processors due to the significantly increased complexity and degraded processing accuracy for $M \ge 20$. The increased complexity results from the increased numbers of MRRs, micro-heaters, and spiral waveguides in **Fig. 1(c)**. Although integrated processors have the advantage of monotonically integrating a large number of these building blocks, achieving their precise tuning and control can be challenging, especially when dealing with a large number of taps. On the other hand, fabrication errors, additional loss, and thermal drifts in these building blocks degrade the cooperative operation of different wavelength channels, and the processing errors resulting from these factors increase super linearly with the tap number.

<figure><img src="image_5.png" /><figcaption>**Fig. 4.** Influence of the tap number and experimental errors on processing accuracy of the discrete and integrated processors. (a) RMSEs of processors that perform (i) DIF, (ii) INT, and (iii) HT as a function of tap number *M*. The RMSEs of processors' outputs with errors induced by (1) only limited tap numbers and (2) both limited tap numbers and experimental errors are shown. (b) Temporal waveform of Gaussian input pulse and output waveforms of discrete and integrated processors that perform (i) DIF, (ii) INT, and (iii) HT. The processors' outputs with errors induced by (1) limited tap number and (2) both the limited tap number and experimental errors are shown, together with the ideal processing result for comparison.</figcaption></figure>

**Fig. 4(b)** compares the output waveforms of both discrete and integrated processors with the same tap number *M* = 80. Compared to the discrete processor, the experimental errors have more significant influence on the processing accuracy of the integrated processor. Note that we have not taken into account any additional processing
errors resulting from factors that may degrade the cooperative operation of different wavelength channels, as discussed earlier. Considering these factors could lead to even higher errors.

To reduce the errors induced by imperfect response of experimental components, employing advanced mode-locking approaches [1] to reduce the noise of microcombs could be beneficial for both discrete and integrated processors. For integrated processors, the chirp of silicon EOM can be mitigated by using push-pull configurations as well as p-n depletion mode structure [47], and proper methods to calibrate the bias point [43]. The shaping errors of integrated spectral shapers can be alleviated via calibration procedures and gradient-descent control [43]. Integrated delay elements introduce additional loss especially when using a waveguide with high propagation loss, and adiabatic Euler bends can be employed to achieve low-loss and low-crosstalk waveguide bends [48]. The use of a wavelength-addressable serial integration scheme can also enable large-scale integration [50]. On the other hand, for discrete processors, there is still room for improving the processing accuracy. Errors of delay elements induced by higher-order dispersion can be reduced by using programmable phase characteristics of optical spectral shapers (OSSs), and the shaping errors can be minimized through employing feedback control [44]. These results have significant implications for all microwave photonics devices [51-97] based on microcomb sources [98-122] and other integrated nonlinear classical and quantum photonic chips [123-172].

## V. CONCLUSION

In summary, we provide a comparative study of the performance between microcomb-based RF photonic transversal signal processors implemented by discrete and integrated components. We first compare the performance of state-of-the-art processors, especially the processing accuracy. Next, analysis of multiple factors that contribute to the performance differences is conducted, including tap number and imperfect response of experimental components. Finally, we discuss the potential for future improvement. Our results show that although current integrated processors are attractive in providing significantly reduced system size, power consumption, and cost, their processing accuracy is not as high as the discrete processors. In addition, there is still room for improvement for both the discrete and integrated processors. The results offer valuable insights for microcomb-based RF photonic transversal signal processors with high reconfigurability for diverse applications.

## Conflict of Interest

The authors declare that there is no conflict of interest for this paper.
REFERENCES

1. Y. Sun, J. Wu, M. Tan, X. Xu, Y. Li, R. Morandotti, A. Mitchell, and D. J. Moss, "Applications of optical microcombs," *Advances in Optics and Photonics*, vol. 15, no. 1, pp. 86-175, 2023.

2. X. Xu, M. Tan, B. Corcoran, J. Wu, A. Boes, T. G. Nguyen, S. T. Chu, B. E. Little, D. G. Hicks, R. Morandotti, A. Mitchell, and D. J. Moss, "11 TOPS photonic convolutional accelerator for optical neural networks," *Nature*, vol. 589, no. 7840, pp. 44-51, 2021/01/01, 2021.

3. Weiwei Han, Zhihui Liu, Yifu Xu, Mengxi Tan, Yuhua Li, Xiaotian Zhu, Yanni Ou, Feifei Yin, Roberto Morandotti, Brent E. Little, Sai Tak Chu, Xingyuan Xu, David J. Moss, and Kun Xu, "Dual-polarization RF Channelizer Based on Microcombs", *Journal of Lightwave Technology* (2023).

4. Mengxi Tan, Xingyuan Xu, Andreas Boes, Bill Corcoran, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Jiayang Wu, Arnan Mitchell, and David J. Moss, "Photonic signal processor for real-time video image processing at 17 Tb/s based on a Kerr microcomb", *Nature Communications Engineering 2* (2023).

5. Yang Li, Yang Sun, Jiayang Wu, Guanghui Ren, Roberto Morandotti, Xingyuan Xu, Mengxi Tan, Arnan Mitchell, and David J. Moss, "Performance analysis of microwave photonic spectral filters based on optical microcombs", *Optics and Lasers in Engineering* (2023).

6. Yang Sun, Jiayang Wu, Yang Li, Xingyuan Xu, Guanghui Ren, Mengxi Tan, Sai Tak Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Optimizing the performance of microcomb based microwave photonic transversal signal processors", *Journal of Lightwave Technology 41* (2023).

7. Yang Sun, Jiayang Wu, Yang Li, Mengxi Tan, Xingyuan Xu, Sai Chu, Brent Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Quantifying the Accuracy of Microcomb-based Photonic RF Transversal Signal Processors", *IEEE Journal of Selected Topics in Quantum Electronics* vol. 29, no. 6, pp. 1-17, Art no. 7500317 (2023).

8. Yunping Bai, Xingyuan Xu, Mengxi Tan, Yang Sun, Yang Li, Jiayang Wu, Roberto Morandotti, Arnan Mitchell, Kun Xu, and David J. Moss, "Photonic multiplexing techniques for neuromorphic computing", *Nanophotonics* 12 (5): 795-817 (2023).

9. Xingyuan Xu, Weiwei Han, Mengxi Tan, Yang Sun, Yang Li, Jiayang Wu, Roberto Morandotti, Arnan Mitchell, Kun Xu, and David J. Moss, "Neuromorphic computing based on wavelength-division multiplexing", *IEEE Journal of Selected Topics in Quantum Electronics* Special Issue on Optical Computing 29 (2) 7400112, March-April (2023).

10. Chawaphon Prayoonyong, Andreas Boes, Xingyuan Xu, Mengxi Tan, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, David J. Moss, and Bill Corcoran, "Frequency comb distillation for optical superchannel transmission", *Journal of Lightwave Technology 39* (23) 7383-7392 (2021). DOI: 10.1109/JLT.2021.3116614.

11. Mengxi Tan, Xingyuan Xu, Jiayang Wu, Bill Corcoran, Andreas Boes, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Integral order photonic RF signal processors based on a soliton crystal micro-comb source", *IOP Journal of Optics* 23 (11) 125701 (2021).

12. Mengxi Tan, Xingyuan Xu, Jiayang Wu, Bill Corcoran, Andreas Boes, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arthur Lowery, Arnan Mitchell, and David J. Moss, ""Highly Versatile Broadband RF Photonic Fractional Hilbert Transformer Based on a Kerr Soliton Crystal Microcomb", *Journal of Lightwave Technology* 39 (24) 7581-7587 (2021). DOI: 10.1109/JLT.2021.3101816.

13. Yuhua Li, Zhe Kang, Kun Zhu, Shiqi Ai, Xiang Wang, Roy R. Davidson, Yan Wu, Roberto Morandotti, Brent E. Little, David J. Moss, And Sai Tak Chu, "All-optical RF frequency spectrum analyzer with a 5 Terahertz bandwidth based on CMOS-compatible high-index doped silica waveguides", *Optics Letters* 46 (7), 1574-1577 (2021).
14. Mengxi Tan, X. Xu, J. Wu, T. G. Nguyen, S. T. Chu, B. E. Little, R. Morandotti, A. Mitchell, and David J. Moss, "Orthogonally polarized Photonic Radio Frequency single sideband generation with integrated micro-ring resonators", IOP Journal of Semiconductors (ISSN 1674-4926) **42** (4), 041305 (2021).

15. Mengxi Tan, X. Xu, J. Wu, T. G. Nguyen, S. T. Chu, B. E. Little, R. Morandotti, A. Mitchell, and David J. Moss, "Photonic Radio Frequency Channelizers based on Kerr Optical Micro-combs", IOP Journal of Semiconductors **42** (4), 041302 (2021).

16. Mengxi Tan, Xingyuan Xu, Jiayang Wu, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "RF and microwave photonic temporal signal processing with Kerr micro-combs", *Advances in Physics X*, VOL. 6, NO. 1, 1838946 (2021).

17. Mengxi Tan, Xingyuan Xu, Andreas Boes, Bill Corcoran, Jiayang Wu, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, David J. Moss, "Photonic RF arbitrary waveform generator based on a soliton crystal micro-comb source", *Journal of Lightwave Technology* **38** (22) Page(s): 6221-6226, Oct 22 (2020).

18. X. Xu, M. Tan, J. Wu, A. Boes, T. G. Nguyen, S. T. Chu, B. E. Little, R. Morandotti, A. Mitchell, and David J. Moss, "Broadband photonic radio frequency channelizer with 90 channels based on a soliton crystal microcomb", *Journal of Lightwave Technology* **38** (18) 5116 - 5121 (2020).

19. Bill Corcoran, Mengxi Tan, Xingyuan Xu, Andrew Boes, Jiayang Wu, Thach Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Ultra-dense optical data transmission over standard fiber with a single chip source", *Nature Communications* **11** Article number: 2568 (2020).

20. X.Xu, M.Tan, J.Wu, A.Boes, B.Corcoran, T.G. Nguyen, S.T. Chu, B.E. Little, R.Morandotti, A.Mitchell, and D. J. Moss, "Photonic RF and microwave integrator with soliton crystal microcombs", *IEEE Transactions on Circuits and Systems: Express Briefs*, Volume: 67, Issue: 12, pp. 3582-3586 (2020).

21. Mengxi Tan, Xingyuan Xu, Jiayang Wu, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Photonic RF and microwave filters based on 49GHz and 200GHz Kerr microcombs", *Optics Communications* **465**, Article: 125563 (2020).

22. Xingyuan Xu, Mengxi Tan, Jiayang Wu, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, Bill Corcoran, Damien Hicks, and David J. Moss, "Photonic perceptron based on a Kerr microcomb for scalable high speed optical neural networks", *Laser and Photonics Reviews* **14** (8) 2000070 (2020).

23. Mengxi Tan, Xingyuan Xu, Bill Corcoran, Jiayang Wu, Andy Boes, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "RF and Microwave Fractional Differentiator based on Photonics", *IEEE Transactions on Circuits and Systems: Express Briefs*, Volume: 67, Issue: 11, 2767-2771 (2020).

24. Xingyuan Xu, Mengxi Tan, Jiayang Wu, Andreas Boes, Bill Corcoran, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Photonic RF phase-encoded signal generation with a microcomb source", *Journal of Lightwave Technology* **38** (7) 1722-1727 (2020).

25. X.Xu, J.Wu, Mengxi Tan, T.G. Nguyen, S.T. Chu, B. E. Little, R.Morandotti, A.Mitchell, and David J. Moss, "Broadband microwave frequency conversion based on an integrated optical micro-comb source", *Journal of Lightwave Technology* **38** (2) 332-338 (2020).

26. Mengxi Tan, Xingyuan Xu, Bill Corcoran, Jiayang Wu, Andy Boes, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Broadband microwave and RF photonic fractional Hilbert transformer based on a 50GHz integrated Kerr micro-comb", *Journal of Lightwave Technology* **37** (24) 6097 – 6104 (2019).
27. Xingyuan Xu, Mengxi Tan, Jiayang Wu, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Microcomb-based photonic RF signal processing", *IEEE Photonics Technology Letters* **31** (23) 1854-1857 (2019).

28. Xingyuan Xu, Mengxi Tan, Jiayang Wu, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Advanced adaptive photonic RF filters based on an optical micro-comb source with 80 taps", *Journal of Lightwave Technology* **37** (4) 1288-1295 (2019).

29. Xingyuan Xu, Mengxi Tan, Jiayang Wu, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "High performance RF filters via bandwidth scaling with Kerr micro-combs", *Applied Physics Letters Photonics* **4**, 026102 (2019).

30. Xingyuan Xu, Jiayang Wu, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, David J. Moss, "Integrated Kerr micro-comb sources for photonic microwave applications", in Laser Resonators, Microresonators, and Beam Control XX, Alexis V. Kudryashov; Alan H. Paxton; Vladimir S. Ilchenko; Lutz Aschke, Editors, Proceedings of SPIE Vol. **10518** (SPIE, Bellingham, WA 2018), 105180B. DOI: 10.1117/12.2292938

31. X. Xu, J.Wu, T.G. Nguyen, S.T. Chu, B.E. Little, R.Morandotti, A.Mitchell, and D.J. Moss, "Broadband RF Channelizer based on an Integrated Optical Frequency Comb Source", *Journal of Lightwave Technology* **36** (19) 4519-4526 (2018).

32. Xingyuan Xu, Jiayang Wu, Thach G. Nguyen, Tania Moein, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Photonic microwave true time delays for phased array antennas using a 49GHz FSR integrated optical micro-comb source", *Photonics Research Journal* **6** (5) B30-B36 (2018).

33. J.Wu, X. Xu, T.G. Nguyen, S.T. Chu, B.E. Little, R.Morandotti, A.Mitchell, and D.J. Moss, "RF photonics: An optical micro-combs' perspective", *IEEE Journal of Selected Topics in Quantum Electronics* **24** (4) 1-20, Article: 6101020 (2018).

34. Xingyuan Xu, Jiayang Wu, Mehrdad Shoeiby, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Advanced RF and microwave functions based on an integrated optical frequency comb source", *Optics Express* **26** (3), 2569-2583 (2018).

35. Xingyuan Xu, Jiayang Wu, Mehrdad Shoeiby, Thach G. Nguyen, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Reconfigurable broadband microwave photonic intensity differentiator based on an integrated optical frequency comb source", *Applied Physics Letters Photonics* **2** (9) 096104 (2017).

36. Thach G. Nguyen, Mehrdad Shoeiby, Sai T. Chu, Brent E. Little, Roberto Morandotti, Arnan Mitchell, and David J. Moss, "Integrated frequency comb source based Hilbert transformer for wideband microwave photonic phase analysis", *Optics Express* **23** (17) 22087 (2015).

37. L. Chang, S. Liu, and J. E. Bowers, "Integrated optical frequency comb technologies," *Nature Photonics*, vol. 16, no. 2, pp. 95-108, 2022/02/01, 2022.

38. J. Zhang, and J. Yao, "Photonic true-time delay beamforming using a switch-controlled wavelength-dependent recirculating loop," *Journal of Lightwave Technology*, vol. 34, no. 16, pp. 3923-3929, 2016.

39. G. Yu, W. Zhang, and J. Williams, "High-performance microwave transversal filter using fiber Bragg grating arrays," *IEEE Photonics Technology Letters*, vol. 12, no. 9, pp. 1183-1185, 2000.

40. V. R. Supradeepa, C. M. Long, R. Wu, F. Ferdous, E. Hamidi, D. E. Leaird, and A. M. Weiner, "Comb-based radiofrequency photonic filters with rapid tunability and high selectivity," *Nature Photonics*, vol. 6, no. 3, pp. 186-194, 2012/03/01, 2012.

41. A. Ortigosa-Blanch, J. Mora, J. Capmany, B. Ortega, and D. Pastor, "Tunable radio-frequency photonic filter based on an actively mode-locked fiber laser," *Optics Letters*, vol. 31, no. 6, pp. 709-711, 2006/03/15, 2006.
42. H. Shu, L. Chang, Y. Tao, B. Shen, W. Xie, M. Jin, A. Netherton, Z. Tao, X. Zhang, R. Chen, B. Bai, J. Qin, S. Yu, X. Wang, and J. E. Bowers, "Microcomb-driven silicon photonic systems," *Nature*, vol. 605, no. 7910, pp. 457-463, 2022/05/01, 2022.

43. B. Bai, Q. Yang, H. Shu, L. Chang, F. Yang, B. Shen, Z. Tao, J. Wang, S. Xu, W. Xie, W. Zou, W. Hu, J. E. Bowers, and X. Wang, "Microcomb-based integrated photonic processing unit," *Nature Communications*, vol. 14, no. 1, pp. 66, 2023/01/05, 2023.

44. Y. Sun, J. Wu, Y. Li, M. Tan, X. Xu, S. T. Chu, B. E. Little, R. Morandotti, A. Mitchell, and D. J. Moss, "Quantifying the Accuracy of Microcomb-based Photonic RF Transversal Signal Processors," *IEEE Journal of Selected Topics in Quantum Electronics*, **29** (6) Article no. 7500317 pp. 1-18 (2023). doi: 10.1109/JSTQE.2023.3266276.

45. C. E. Rogers Iii, J. L. Carini, J. A. Pechkis, and P. L. Gould, "Characterization and compensation of the residual chirp in a Mach-Zehnder-type electro-optical intensity modulator," *Optics Express*, vol. 18, no. 2, pp. 1166-1176, 2010/01/18, 2010.

46. A. N. Tait, T. F. d. Lima, M. A. Nahmias, B. J. Shastri, and P. R. Prucnal, "Continuous Calibration of Microring Weights for Analog Optical Networks," *IEEE Photonics Technology Letters*, vol. 28, no. 8, pp. 887-890, 2016.

47. G. Sinatkas, T. Christopoulos, O. Tsilipakos, and E. E. Kriezis, "Electro-optic modulation in integrated photonics," *Journal of Applied Physics*, vol. 130, no. 1, 2021.

48. X. Ji, J. Liu, J. He, R. N. Wang, Z. Qiu, J. Riemensberger, and T. J. Kippenberg, "Compact, spatial-mode-interaction-free, ultralow-loss, nonlinear photonic integrated circuits," *Communications Physics*, vol. 5, no. 1, pp. 84, 2022/04/07, 2022.

49. A. N. Tait, H. Jayatilleka, T. F. De Lima, P. Y. Ma, M. A. Nahmias, B. J. Shastri, S. Shekhar, L. Chrostowski, and P. R. Prucnal, "Feedback control for microring weight banks," *Optics Express*, vol. 26, no. 20, pp. 26422-26443, 2018/10/01, 2018.

50. E. Kuramochi, K. Nozaki, A. Shinya, K. Takeda, T. Sato, S. Matsuo, H. Taniyama, H. Sumikura, and M. Notomi, "Large-scale integration of wavelength-addressable all-optical memories on a photonic crystal chip," *Nature Photonics*, vol. 8, no. 6, pp. 474-481, 2014/06/01, 2014.

51. M. T. Murphy, T. Udem, R. Holzwarth, A. Sizmann, L. Pasquini, C. Araujo-Hauck, H. Dekker, S. D'Odorico, M. Fischer, T. W. Hänsch, and A. Manescau, "High-precision wavelength calibration of astronomical spectrographs with laser frequency combs," Monthly Notices of the Royal Astronomical Society **380**, 839-847 (2007).

52. T. Steinmetz, T. Wilken, C. Araujo-Hauck, R. Holzwarth, T. W. Hänsch, L. Pasquini, A. Manescau, S. D'Odorico, M. T. Murphy, T. Kentischer, W. Schmidt, and T. Udem, "Laser Frequency Combs for Astronomical Observations," Science **321**, 1335-1337 (2008).

53. C. H. Li, A. J. Benedick, P. Fendel, A. G. Glenday, F. X. Kärtner, D. F. Phillips, D. Sasselov, A. Szentgyorgyi, and R. L. Walsworth, "A laser frequency comb that enables radial velocity measurements with a precision of 1 cm s⁻¹," Nature **452**, 610-612 (2008).

54. S. Zhu, M. Li, X. Wang, N. H. Zhu, Z. Z. Cao, and W. Li, "Photonic generation of background-free binary phase-coded microwave pulses," Opt. Lett. **44**, 94-97 (2019).

55. Z. Li, W. Li, H. Chi, X. Zhang, and J. Yao, "Photonic Generation of Phase-Coded Microwave Signal With Large Frequency Tunability," *IEEE Photonics Technology Letters* **23**, 712-714 (2011).

56. W. Liu, L. Gao, and J. Yao, "Photonic generation of triangular waveforms based on a polarization modulator in a Sagnac loop," in *2013 IEEE International Topical Meeting on Microwave Photonics (MWP)* (2013), pp. 68-71.

57. D. Hillerkuss, R. Schmogrow, T. Schellinger, M. Jordan, M. Winter, G. Huber, T. Vallaitis, R. Bonk, P. Kleinow, F. Frey, M. Roeger, S. Koenig, A. Ludwig, A. Marculescu, J. Li, M. Hoh, M. Dreschmann, J. Meyer, S. Ben Ezra, N. Narkiss, B. Nebendahl, F. Parmigiani, P. Petropoulos, B. Resan, A. Oehler, K. Weingarten, T. Ellermeyer, J. Lutz, M. Moeller, M. Huebner, J. Becker, C. Koos, W. Freude, and J. Leuthold, "26 Tbit s⁻¹ line-rate super-channel transmission utilizing all-optical fast Fourier transform processing," Nat. Photonics **5**, 364-371 (2011).
58. V. Ataie, E. Temprana, L. Liu, E. Myslivets, B. P. Kuo, N. Alic, and S. Radic, "Ultrahigh Count Coherent WDM Channels Transmission Using Optical Parametric Comb-Based Frequency Synthesizer," Journal of Lightwave Technology 33, 694-699 (2015).

59. C. Weimann, P. C. Schindler, R. Palmer, S. Wolf, D. Bekele, D. Korn, J. Pfeifle, S. Koeber, R. Schmogrow, L. Alloatti, D. Elder, H. Yu, W. Bogaerts, L. R. Dalton, W. Freude, J. Leuthold, and C. Koos, "Silicon-organic hybrid (SOH) frequency comb sources for terabit/s data transmission," Opt. Express 22, 3629-3637 (2014).

60. J. Chou, Y. Han, and B. Jalali, "Adaptive RF-photonic arbitrary waveform generator," IEEE Photonics Technology Letters 15, 581-583 (2003).

61. S. T. Cundiff, and A. M. Weiner, "Optical arbitrary waveform generation," Nat. Photonics 4, 760-766 (2010).

62. A. Rashidinejad, Y. Li, and A. M. Weiner, "Recent Advances in Programmable Photonic-Assisted Ultrabroadband Radio-Frequency Arbitrary Waveform Generation," IEEE Journal of Quantum Electronics 52, 1-17 (2016).

63. A. Sano, T. Kobayashi, S. Yamanaka, A. Matsuura, H. Kawakami, Y. Miyamoto, K. Ishihara, and H. Masuda, "102.3-Tb/s (224 × 548-Gb/s) C- and extended L-band all-Raman transmission over 240 km using PDM-64QAM single carrier FDM with digital pilot tone," in OFC/NFOEC (2012), pp. 1-3.

64. "G.694.1 : Spectral grids for WDM applications: DWDM frequency grid," https://www.itu.int/rec/T-REC-G.694.1-202010-I/en.

65. J. Pfeifle, V. Vujicic, R. T. Watts, P. C. Schindler, C. Weimann, R. Zhou, W. Freude, L. P. Barry, and C. Koos, "Flexible terabit/s Nyquist-WDM super-channels using a gain-switched comb source," Opt. Express 23, 724-738 (2015).

66. J. R. Barry, and E. A. Lee, "Performance of coherent optical receivers," Proc. IEEE 78, 1369-1394 (1990).

67. W. Freude, R. Schmogrow, B. Nebendahl, M. Winter, A. Josten, D. Hillerkuss, S. Koenig, J. Meyer, M. Dreschmann, M. Huebner, C. Koos, J. Becker, and J. Leuthold, "Quality metrics for optical signals: Eye diagram, Q-factor, OSNR, EVM and BER," in 2012 14th International Conference on Transparent Optical Networks (ICTON) (2012), pp. 1-4.

68. M. Mazur, M. G. Suh, A. Fülöp, J. Schröder, V. T. Company, M. Karlsson, K. Vahala, and P. Andrekson, "High Spectral Efficiency Coherent Superchannel Transmission With Soliton Microcombs," Journal of Lightwave Technology 39, 4367-4373 (2021).

69. Y. Geng, H. Zhou, X. Han, W. Cui, Q. Zhang, B. Liu, G. Deng, Q. Zhou, and K. Qiu, "Coherent optical communications using coherence-cloned Kerr soliton microcombs," Nat. Commun. 13, 1070 (2022).

70. J. Capmany, and D. Novak, "Microwave photonics combines two worlds," Nat. Photonics 1, 319-330 (2007).

71. J. Yao, "Microwave Photonics," Journal of Lightwave Technology 27, 314-335 (2009).

72. T. Okoshi, and K. Kikuchi, *Coherent optical fiber communications* (Springer Science & Business Media, 1988).

73. G. Li, "Recent advances in coherent optical communication," Adv. Opt. Photon. 1, 279-307 (2009).

74. R. Schmogrow, B. Nebendahl, M. Winter, A. Josten, D. Hillerkuss, S. Koenig, J. Meyer, M. Dreschmann, M. Huebner, C. Koos, J. Becker, W. Freude, and J. Leuthold, "Error Vector Magnitude as a Performance Measure for Advanced Modulation Formats," IEEE Photonics Technology Letters 24, 61-63 (2012).

75. X. Xie, Y. Dai, Y. Ji, K. Xu, Y. Li, J. Wu, and J. Lin, "Broadband Photonic Radio-Frequency Channelization Based on a 39-GHz Optical Frequency Comb," IEEE Photonics Technology
Letters **24**, 661-663 (2012).

76. W. Wang, R. L. Davis, T. J. Jung, R. Lodenkamper, L. J. Lembo, J. C. Brock, and M. Wu, "Characterization of a coherent optical RF channelizer based on a diffraction grating," *IEEE Transactions on Microwave Theory and Techniques* **49**, 1996-2001 (2001).

77. A. Dutt, C. Joshi, X. Ji, J. Cardenas, Y. Okawachi, K. Luke, A. L. Gaeta, and M. Lipson, "On-chip dual-comb source for spectroscopy," *Sci. Adv.* **4**, 9 (2018).

78. C. Bao, Z. Yuan, H. Wang, L. Wu, B. Shen, K. Sung, S. Leifer, Q. Lin, and K. Vahala, "Interleaved difference-frequency generation for microcomb spectral densification in the mid-infrared," *Optica* **7**, 309-315 (2020).

79. I. Coddington, W. C. Swann, and N. R. Newbury, "Coherent dual-comb spectroscopy at high signal-to-noise ratio," *Phys. Rev. A* **82**, 043817 (2010).

80. X. Zou, B. Lu, W. Pan, L. Yan, A. Stöhr, and J. Yao, "Photonics for microwave measurements," *Laser Photon. Rev.* **10**, 711-734 (2016).

81. I. Coddington, N. Newbury, and W. Swann, "Dual-comb spectroscopy," *Optica* **3**, 414-426 (2016).

82. C. Bao, Z. Yuan, L. Wu, M. G. Suh, H. Wang, Q. Lin, and K. J. Vahala, "Architecture for microcomb-based GHz-mid-infrared dual-comb spectroscopy," *Nat. Commun.* **12**, 6573 (2021).

83. Y. S. Jang, H. Liu, J. Yang, M. Yu, D. L. Kwong, and C. W. Wong, "Nanometric Precision Distance Metrology via Hybrid Spectrally Resolved and Homodyne Interferometry in a Single Soliton Frequency Microcomb," *Phys. Rev. Lett.* **126**, 023903 (2021).

84. E. S. Lamb, D. R. Carlson, D. D. Hickstein, J. R. Stone, S. A. Diddams, and S. B. Papp, "Optical-Frequency Measurements with a Kerr Microcomb and Photonic-Chip Supercontinuum," *Physical Review Applied* **9**, 024030 (2018).

85. B. Wang, Z. Yang, X. Zhang, and X. Yi, "Vernier frequency division with dual-microresonator solitons," *Nat. Commun.* **11**, 3975 (2020).

86. R. Wang, L. Chen, H. Hu, Y. Zhao, C. Zhang, W. Zhang, and X. Zhang, "Precise dynamic characterization of microcombs assisted by an RF spectrum analyzer with THz bandwidth and MHz resolution," *Opt. Express* **29**, 2153-2161 (2021).

87. T. Tan, Z. Yuan, H. Zhang, G. Yan, S. Zhou, N. An, B. Peng, G. Soavi, Y. Rao, and B. Yao, "Multispecies and individual gas molecule detection using Stokes solitons in a graphene over-modal microresonator," *Nat. Commun.* **12**, 6716 (2021).

88. K. Minoshima, and H. Matsumoto, "High-accuracy measurement of 240-m distance in an optical tunnel by use of a compact femtosecond laser," *Appl. Opt.* **39**, 5512-5517 (2000).

89. I. Coddington, W. C. Swann, L. Nenadovic, and N. R. Newbury, "Rapid and precise absolute distance measurements at long range," *Nat. Photonics* **3**, 351-356 (2009).

90. C. Urmson, J. Anhalt, D. Bagnell, C. Baker, R. Bittner, M. Clark, J. Dolan, D. Duggins, T. Galatali, and C. Geyer, "Autonomous driving in urban environments: Boss and the urban challenge," *Journal of field Robotics* **25**, 425-466 (2008).

91. B. Behroozpour, P. A. Sandborn, M. C. Wu, and B. E. Boser, "Lidar system architectures and circuits," *IEEE Communications Magazine* **55**, 135-142 (2017).

92. M. Cui, M. G. Zeitouny, N. Bhattacharya, S. A. van den Berg, and H. P. Urbach, "Long distance measurement with femtosecond pulses using a dispersive interferometer," *Opt. Express* **19**, 6549-6562 (2011).

93. S. A. van den Berg, S. van Eldik, and N. Bhattacharya, "Mode-resolved frequency comb interferometry for high-accuracy long distance measurement," *Scientific Reports* **5**, 14661 (2015).

94. R. A. McCracken, J. M. Charsley, and D. T. Reid, "A decade of astrocombs: recent advances in frequency combs for astronomy [Invited]," *Opt. Express* **25**, 15058-15078 (2017).
95. Q. Yang, X. Yi, K. Y. Yang, and K. Vahala, "Counter-propagating solitons in microresonators," Nat. Photonics **11**, 560-564 (2017).

96. M. Ferrera, C. Reimer, A. Pasquazi, M. Peccianti, M. Clerici, L. Caspani, S. T. Chu, B. E. Little, R. Morandotti, and D. J. Moss, "CMOS compatible integrated all-optical radio frequency spectrum analyzer," Opt. Express **22**, 21488-21498 (2014).

97. Y. Li, Z. Kang, K. Zhu, S. Ai, X. Wang, R. R. Davidson, Y. Wu, R. Morandotti, B. E. Little, D. J. Moss, and S. T. Chu, "All-optical RF spectrum analyzer with a 5 THz bandwidth based on CMOS-compatible high-index doped silica waveguides," Opt. Lett. **46**, 1574-1577 (2021).

98. A. Pasquazi, et al., "Sub-picosecond phase-sensitive optical pulse characterization on a chip", Nature Photonics, vol. 5, no. 10, pp. 618-623 (2011).

99. Bao, C., et al., Direct soliton generation in microresonators, Optics Letters vol. 42, 2519 (2017).

100. M. Ferrera et al., "CMOS compatible integrated all-optical RF spectrum analyzer", Optics Express, vol. 22, no. 18, 21488 - 21498 (2014).

101. M. Kues, et al., "Passively modelocked laser with an ultra-narrow spectral width", Nature Photonics, vol. 11, no. 3, pp. 159, 2017.

102. L. Razzari, et al., "CMOS-compatible integrated optical hyper-parametric oscillator," Nature Photonics, vol. 4, no. 1, pp. 41-45, 2010.

103. M. Ferrera, et al., "Low-power continuous-wave nonlinear optics in doped silica glass integrated waveguide structures," Nature Photonics, vol. 2, no. 12, pp. 737-740, 2008.

104. M. Ferrera et al., "On-Chip ultra-fast 1st and 2nd order CMOS compatible all-optical integration", Opt. Express, vol. 19, (23)pp. 23153-23161 (2011).

105. D. Duchesne, M. Peccianti, M. R. E. Lamont, et al., "Supercontinuum generation in a high index doped silica glass spiral waveguide," Optics Express, vol. 18, no. 2, pp. 923-930, 2010.

106. H Bao, L Olivieri, M Rowley, ST Chu, BE Little, R Morandotti, DJ Moss, et al, "Turing patterns in a fiber laser with a nested microresonator: Robust and controllable microcomb generation", Physical Review Research vol. 2 (2), 023395 (2020).

107. M. Ferrera, et al., "On-chip CMOS-compatible all-optical integrator", Nature Communications, vol. 1, Article 29, 2010.

108. A. Pasquazi, et al., "All-optical wavelength conversion in an integrated ring resonator," Optics Express, vol. 18, no. 4, pp. 3858-3863, 2010.

109. A. Pasquazi, Y. Park, J. Azana, et al., "Efficient wavelength conversion and net parametric gain via Four Wave Mixing in a high index doped silica waveguide," Optics Express, vol. 18, no. 8, pp. 7634-7641, 2010.

110. M. Peccianti, M. Ferrera, L. Razzari, et al., "Subpicosecond optical pulse compression via an integrated nonlinear chirper," Optics Express, vol. 18, no. 8, pp. 7625-7633, 2010.

111. Little, B. E. et al., "Very high-order microring resonator filters for WDM applications", IEEE Photonics Technol. Lett. vol. 16, 2263-2265 (2004).

112. M. Ferrera et al., "Low Power CW Parametric Mixing in a Low Dispersion High Index Doped Silica Glass Micro-Ring Resonator with Q-factor > 1 Million", Optics Express, vol. 17, no. 16, pp. 14098-14103 (2009).

113. M. Peccianti, et al., "Demonstration of an ultrafast nonlinear microcavity modelocked laser", Nature Communications, vol. 3, pp. 765, 2012.

114. A. Pasquazi, et al., "Self-locked optical parametric oscillation in a CMOS compatible microring resonator: a route to robust optical frequency comb generation on a chip," Optics Express, vol. 21, no. 11, pp. 13333-13341, 2013.

115. A. Pasquazi, et al., "Stable, dual mode, high repetition rate mode-locked laser based on a microring resonator," Optics Express, vol. 20, no. 24, pp. 27355-27362, 2012.

116. Pasquazi, A. et al. Micro-combs: a novel generation of optical sources. Physics Reports vol.
729, 1-81 (2018).

117. Moss, D. J. et al., "New CMOS-compatible platforms based on silicon nitride and Hydex for nonlinear optics", Nature photonics vol. 7, 597 (2013).

118. H. Bao, et al., Laser cavity-soliton microcombs, Nature Photonics, vol. 13, no. 6, pp. 384-389, Jun. 2019.

119. Antonio Cutrona, Maxwell Rowley, Debayan Das, Luana Olivieri, Luke Peters, Sai T. Chu, Brent L. Little, Roberto Morandotti, David J. Moss, Juan Sebastian Totero Gongora, Marco Peccianti, Alessia Pasquazi, "High Conversion Efficiency in Laser Cavity-Soliton Microcombs", Optics Express Vol. 30, Issue 22, pp. 39816-39825 (2022).
https://doi.org/10.1364/OE.470376

120. M. Rowley, P. Hanzard, A. Cutrona, H. Bao, S. Chu, B. Little, R. Morandotti, D. J. Moss, G. Oppo, J. Gongora, M. Peccianti and A. Pasquazi, "Self-emergence of robust solitons in a micro-cavity", Nature vol. 608 (7922) 303-309 (2022).

121. A. Cutrona, M. Rowley, A. Bendahmane, V. Cecconi, L. Peters, L. Olivieri, B. E. Little, S. T. Chu, S. Stivala, R. Morandotti, D. J. Moss, J. S. Totero-Gongora, M. Peccianti, A. Pasquazi, "Nonlocal bonding of a soliton and a blue-detuned state in a microcomb laser", Nature Communications Physics vol. 6 (2023).

122. A. Cutrona, M. Rowley, A. Bendahmane, V. Cecconi, L. Peters, L. Olivieri, B. E. Little, S. T. Chu, S. Stivala, R. Morandotti, D. J. Moss, J. S. Totero-Gongora, M. Peccianti, A. Pasquazi, "Stability Properties of Laser Cavity-Solitons for Metrological Applications", Applied Physics Letters vol. 122 (12) 121104 (2023); doi: 10.1063/5.0134147.

123. Kues, M. et al. "Quantum optical microcombs", Nature Photonics 13, (3) 170-179 (2019).
doi:10.1038/s41566-019-0363-0

124. C. Reimer, L. Caspani, M. Clerici, et al., "Integrated frequency comb source of heralded single photons," Optics Express, vol. 22, no. 6, pp. 6535-6546, 2014.

125. C. Reimer, et al., "Cross-polarized photon-pair generation and bi-chromatically pumped optical parametric oscillation on a chip", Nature Communications, vol. 6, Article 8236, 2015.
DOI: 10.1038/ncomms9236

126. L. Caspani, C. Reimer, M. Kues, et al., "Multifrequency sources of quantum correlated photon pairs on-chip: a path toward integrated Quantum Frequency Combs," Nanophotonics, vol. 5, no. 2, pp. 351-362, 2016.

127. C. Reimer et al., "Generation of multiphoton entangled quantum states by means of integrated frequency combs," Science, vol. 351, no. 6278, pp. 1176-1180, 2016.

128. M. Kues, et al., "On-chip generation of high-dimensional entangled quantum states and their coherent control", Nature, vol. 546, no. 7660, pp. 622-626, 2017.

129. P. Roztocki et al., "Practical system for the generation of pulsed quantum frequency combs," Optics Express, vol. 25, no. 16, pp. 18940-18949, 2017.

130. Y. Zhang, et al., "Induced photon correlations through superposition of two four-wave mixing processes in integrated cavities", Laser and Photonics Reviews, vol. 14, no. 7, pp. 2000128, 2020.
DOI: 10.1002/lpor.202000128

131. C. Reimer, et al., "High-dimensional one-way quantum processing implemented on d-level cluster states", Nature Physics, vol. 15, no.2, pp. 148-153, 2019.

132. P. Roztocki et al., "Complex quantum state generation and coherent control based on integrated frequency combs", Journal of Lightwave Technology 37 (2) 338-347 (2019).

133. S. Sciara et al., "Generation and Processing of Complex Photon States with Quantum Frequency Combs", IEEE Photonics Technology Letters 31 (23) 1862-1865 (2019). DOI: 10.1109/LPT.2019.2944564.

134. Stefania Sciara, Piotr Roztocki, Bennet Fisher, Christian Reimer, Luis Romero Cortez,
William J. Munro, David J. Moss, Alfonso C. Cino, Lucia Caspani, Michael Kues, J. Azana, and Roberto Morandotti, "Scalable and effective multilevel entangled photon states: A promising tool to boost quantum technologies", Nanophotonics 10 (18), 4447-4465 (2021). DOI:10.1515/nanoph-2021-0510.

135. L. Caspani, C. Reimer, M. Kues, et al., "Multifrequency sources of quantum correlated photon pairs on-chip: a path toward integrated Quantum Frequency Combs," Nanophotonics, vol. 5, no. 2, pp. 351-362, 2016.

136. Yuning Zhang, Jiayang Wu, Yang Qu, Yunyi Yang, Linnan Jia, Baohua Jia, and David J. Moss, "Enhanced supercontinuum generated in SiN waveguides coated with GO films", Advanced Materials Technologies 8 (1) 2201796 (2023). DOI: 10.1002/admt.202201796.

137. Yuning Zhang, Jiayang Wu, Linnan Jia, Yang Qu, Baohua Jia, and David J. Moss, "Graphene oxide for nonlinear integrated photonics", Laser and Photonics Reviews 17 2200512 (2023). DOI:10.1002/lpor.202200512.

138. Jiayang Wu, H. Lin, D. J. Moss, T.K. Loh, Baohua Jia, "Graphene oxide: new opportunities for electronics, photonics, and optoelectronics", Nature Reviews Chemistry 7 (3) 162-183 (2023). DOI:10.1038/s41570-022-00458-7.

139. Yang Qu, Jiayang Wu, Yuning Zhang, Yunyi Yang, Linnan Jia, Baohua Jia, and David J. Moss, "Photo thermal tuning in GO-coated integrated waveguides", Micromachines 13 1194 (2022). doi.org/10.3390/mi13081194

140. Yuning Zhang, Jiayang Wu, Yunyi Yang, Yang Qu, Houssein El Dirani, Romain Crochemore, Corrado Sciancalepore, Pierre Demongodin, Christian Grillet, Christelle Monat, Baohua Jia, and David J. Moss, "Enhanced self-phase modulation in silicon nitride waveguides integrated with 2D graphene oxide films", IEEE Journal of Selected Topics in Quantum Electronics 29 (1) 5100413 (2023). DOI: 10.1109/JSTQE.2022.3177385

141. Yuning Zhang, Jiayang Wu, Yunyi Yang, Yang Qu, Linnan Jia, Baohua Jia, and David J. Moss, "Enhanced spectral broadening of femtosecond optical pulses in silicon nanowires integrated with 2D graphene oxide films", Micromachines 13 756 (2022). DOI:10.3390/mi13050756.

142. Linnan Jia, Jiayang Wu, Yuning Zhang, Yang Qu, Baohua Jia, Zhigang Chen, and David J. Moss, "Fabrication Technologies for the On-Chip Integration of 2D Materials", Small: Methods 6, 2101435 (2022). DOI:10.1002/smtd.202101435.

143. Yuning Zhang, Jiayang Wu, Yang Qu, Linnan Jia, Baohua Jia, and David J. Moss, "Design and optimization of four-wave mixing in microring resonators integrated with 2D graphene oxide films", Journal of Lightwave Technology 39 (20) 6553-6562 (2021). DOI:10.1109/JLT.2021.3101292. Print ISSN: 0733-8724, Online ISSN: 1558-2213 (2021).

144. Yuning Zhang, Jiayang Wu, Yang Qu, Linnan Jia, Baohua Jia, and David J. Moss, "Optimizing the Kerr nonlinear optical performance of silicon waveguides integrated with 2D graphene oxide films", Journal of Lightwave Technology 39 (14) 4671-4683 (2021). DOI: 10.1109/JLT.2021.3069733.

145. Yang Qu, Jiayang Wu, Yuning Zhang, Yao Liang, Baohua Jia, and David J. Moss, "Analysis of four-wave mixing in silicon nitride waveguides integrated with 2D layered graphene oxide films", Journal of Lightwave Technology 39 (9) 2902-2910 (2021). DOI: 10.1109/JLT.2021.3059721.

146. Jiayang Wu, Linnan Jia, Yuning Zhang, Yang Qu, Baohua Jia, and David J. Moss, "Graphene oxide: versatile films for flat optics to nonlinear photonic chips", Advanced Materials 33 (3) 2006415, pp.1-29 (2021). DOI:10.1002/adma.202006415.

147. Y. Qu, J. Wu, Y. Zhang, L. Jia, Y. Yang, X. Xu, S. T. Chu, B. E. Little, R. Morandotti, B. Jia, and D. J. Moss, "Graphene oxide for enhanced optical nonlinear performance in CMOS compatible integrated devices", Paper No. 11688-30, PW21O-OE109-36, 2D Photonic
Materials and Devices IV, SPIE Photonics West, San Francisco CA March 6-11 (2021).
doi.org/10.1117/12.2583978

148. Yang Qu, Jiayang Wu, Yunyi Yang, Yuning Zhang, Yao Liang, Houssein El Dirani, Romain Crochemore, Pierre Demongodin, Corrado Sciancalepore, Christian Grillet, Christelle Monat, Baohua Jia, and David J. Moss, "Enhanced nonlinear four-wave mixing in silicon nitride waveguides integrated with 2D layered graphene oxide films", Advanced Optical Materials vol. 8 (21) 2001048 (2020). DOI: 10.1002/adom.202001048. arXiv:2006.14944.

149. Yuning Zhang, Yang Qu, Jiayang Wu, Linnan Jia, Yunyi Yang, Xingyuan Xu, Baohua Jia, and David J. Moss, "Enhanced Kerr nonlinearity and nonlinear figure of merit in silicon nanowires integrated with 2D graphene oxide films", ACS Applied Materials and Interfaces vol. 12 (29) 33094-33103 June 29 (2020). DOI:10.1021/acsami.0c07852

150. Jiayang Wu, Yunyi Yang, Yang Qu, Yuning Zhang, Linnan Jia, Xingyuan Xu, Sai T. Chu, Brent E. Little, Roberto Morandotti, Baohua Jia,\* and David J. Moss\*, "Enhanced nonlinear four-wave mixing in microring resonators integrated with layered graphene oxide films", Small vol. 16 (16) 1906563 April 23 (2020). DOI: 10.1002/smll.201906563

151. Jiayang Wu, Yunyi Yang, Yang Qu, Xingyuan Xu, Yao Liang, Sai T. Chu, Brent E. Little, Roberto Morandotti, Baohua Jia, and David J. Moss, "Graphene oxide waveguide polarizers and polarization selective micro-ring resonators", Paper 11282-29, SPIE Photonics West, San Francisco, CA, 4 - 7 February (2020). doi: 10.1117/12.2544584

152. Jiayang Wu, Yunyi Yang, Yang Qu, Xingyuan Xu, Yao Liang, Sai T. Chu, Brent E. Little, Roberto Morandotti, Baohua Jia, and David J. Moss, "Graphene oxide waveguide polarizers and polarization selective micro-ring resonators", Laser and Photonics Reviews vol. 13 (9) 1900056 (2019). DOI:10.1002/lpor.201900056.

153. Yunyi Yang, Jiayang Wu, Xingyuan Xu, Sai T. Chu, Brent E. Little, Roberto Morandotti, Baohua Jia, and David J. Moss, "Enhanced four-wave mixing in graphene oxide coated waveguides", Applied Physics Letters Photonics vol. 3 120803 (2018). doi: 10.1063/1.5045509.

154. Linnan Jia, Yang Qu, Jiayang Wu, Yuning Zhang, Yunyi Yang, Baohua Jia, and David J. Moss, "Third-order optical nonlinearities of 2D materials at telecommunications wavelengths", Micromachines (MDPI), 14, 307 (2023). https://doi.org/10.3390/mi14020307.

155. Hamed Arianfard, Saulius Juodkazis, David J. Moss, and Jiayang Wu, "Sagnac interference in integrated photonics", Applied Physics Reviews vol. 10 (1) 011309 (2023). doi: 10.1063/5.0123236. (2023).

156. Hamed Arianfard, Jiayang Wu, Saulius Juodkazis, and David J. Moss, "Optical analogs of Rabi splitting in integrated waveguide-coupled resonators", Advanced Physics Research 2 (2023). DOI: 10.1002/apxr.202200123.

157. Hamed Arianfard, Jiayang Wu, Saulius Juodkazis, and David J. Moss, "Spectral shaping based on optical waveguides with advanced Sagnac loop reflectors", Paper No. PW22O-OE201-20, SPIE-Opto, Integrated Optics: Devices, Materials, and Technologies XXVI, SPIE Photonics West, San Francisco CA January 22 - 27 (2022). doi: 10.1117/12.2607902

158. Hamed Arianfard, Jiayang Wu, Saulius Juodkazis, David J. Moss, "Spectral Shaping Based on Integrated Coupled Sagnac Loop Reflectors Formed by a Self-Coupled Wire Waveguide", IEEE Photonics Technology Letters vol. 33 (13) 680-683 (2021). DOI:10.1109/LPT.2021.3088089.

159. Hamed Arianfard, Jiayang Wu, Saulius Juodkazis and David J. Moss, "Three Waveguide Coupled Sagnac Loop Reflectors for Advanced Spectral Engineering", Journal of Lightwave Technology vol. 39 (11) 3478-3487 (2021). DOI: 10.1109/JLT.2021.3066256.

160. Hamed Arianfard, Jiayang Wu, Saulius Juodkazis and David J. Moss, "Advanced Multi-
Functional Integrated Photonic Filters based on Coupled Sagnac Loop Reflectors", Journal of Lightwave Technology vol. 39, Issue: 5, 1400-1408 (2021). DOI:10.1109/JLT.2020.3037559.

161. Hamed Arianfard, Jiayang Wu, Saulius Juodkazis and David J. Moss, "Advanced multi-functional integrated photonic filters based on coupled Sagnac loop reflectors", Paper 11691-4, PW210-OE203-44, Silicon Photonics XVI, SPIE Photonics West, San Francisco CA March 6-11 (2021). doi.org/10.1117/12.2584020

162. Jiayang Wu, Tania Moein, Xingyuan Xu, and David J. Moss, "Advanced photonic filters via cascaded Sagnac loop reflector resonators in silicon-on-insulator integrated nanowires", Applied Physics Letters Photonics vol. 3 046102 (2018). DOI:/10.1063/1.5025833

163. Jiayang Wu, Tania Moein, Xingyuan Xu, Guanghui Ren, Arnan Mitchell, and David J. Moss, "Micro-ring resonator quality factor enhancement via an integrated Fabry-Perot cavity", Applied Physics Letters Photonics vol. 2 056103 (2017). doi: 10.1063/1.4981392.

164. Linnan Jia, Dandan Cui, Jiayang Wu, Haifeng Feng, Tieshan Yang, Yunyi Yang, Yi Du, Weichang Hao, Baohua Jia, David J. Moss, "BiOBr nanoflakes with strong nonlinear optical properties towards hybrid integrated photonic devices", Applied Physics Letters Photonics vol. 4 090802 (2019). DOI: 10.1063/1.5116621

165. Linnan Jia, Jiayang Wu, Yunyi Yang, Yi Du, Baohua Jia, David J. Moss, "Large Third-Order Optical Kerr Nonlinearity in Nanometer-Thick PdSe2 2D Dichalcogenide Films: Implications for Nonlinear Photonic Devices", ACS Applied Nano Materials vol. 3 (7) 6876-6883 (2020). DOI:10.1021/acsnanm.0c01239.

166. E.D Ghahramani, DJ Moss, JE Sipe, "Full-band-structure calculation of first-, second-, and third-harmonic optical response coefficients of ZnSe, ZnTe, and CdTe", Physical Review B 43 (12), 9700 (1991).

167. C Grillet, C Smith, D Freeman, S Madden, B Luther-Davies, EC Magi, ... "Efficient coupling to chalcogenide glass photonic crystal waveguides via silica optical fiber nanowires", Optics Express vol. 14 (3), 1070-1078 (2006).

168. S Tomljenovic-Hanic, MJ Steel, CM de Sterke, DJ Moss, "High-Q cavities in photosensitive photonic crystals" Optics Letters vol. 32 (5), 542-544 (2007).

169. M Ferrera et al., "On-Chip ultra-fast 1st and 2nd order CMOS compatible all-optical integration", Optics Express vol. 19 (23), 23153-23161 (2011).

170. VG Ta'eed et al., "Error free all optical wavelength conversion in highly nonlinear As-Se chalcogenide glass fiber", Optics Express vol. 14 (22), 10371-10376 (2006).

171. M Rochette, L Fu, V Ta'eed, DJ Moss, BJ Eggleton, "2R optical regeneration: an all-optical solution for BER improvement", IEEE Journal of Selected Topics in Quantum Electronics vol. 12 (4), 736-744 (2006).

172. TD Vo, et al., "Silicon-chip-based real-time dispersion monitoring for 640 Gbit/s DPSK signals", Journal of Lightwave Technology vol. 29 (12), 1790-1796 (2011).