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The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work -- a possibility that has sparked discussions on the integrity of student evaluations in the age of artificial intelligence (AI). To date, it is unclear how such tools perform compared to students on university-level courses. Further, students' perspectives regarding the use of such tools, and educators' perspectives on treating their use as plagiarism, remain unknown. Here, we compare the performance of ChatGPT against students on 32 university-level courses. We also assess the degree to which its use can be detected by two classifiers designed specifically for this purpose. Additionally, we conduct a survey across five countries, as well as a more in-depth survey at the authors' institution, to discern students' and educators' perceptions of ChatGPT's use. We find that ChatGPT's performance is comparable, if not superior, to that of students in many courses. Moreover, current AI-text classifiers cannot reliably detect ChatGPT's use in school work, due to their propensity to classify human-written answers as AI-generated, as well as the ease with which AI-generated text can be edited to evade detection. Finally, we find an emerging consensus among students to use the tool, and among educators to treat this as plagiarism. Our findings offer insights that could guide policy discussions addressing the integration of AI into educational frameworks., Comment: 17 pages, 4 figures

The omnipresent digitalization trend has enabled a number of related malicious activities, ranging from data theft to disruption of businesses, counterfeiting of devices, and identity fraud, among others. Hence, it is essential to implement security schemes and to ensure the reliability and trustworthiness of electronic circuits. Toward this end, the concept of physically unclonable functions (PUFs) has been established at the beginning of the 21st century. However, most PUFs have eventually, at least partially, fallen short of their promises, which are unpredictability, unclonability, uniqueness, reproducibility, and tamper resilience. That is because most PUFs directly utilize the underlying microelectronics, but that intrinsic randomness can be limited and may thus be predicted, especially by machine learning. Optical PUFs, in contrast, are still considered as promising---they can derive strong, hard-to-predict randomness independently from microelectronics, by using some kind of "optical token." Here we propose a novel concept for plasmonics-enhanced optical PUFs, or peo-PUFs in short. For the first time, we leverage two highly nonlinear phenomena in conjunction by construction: (i) light propagation in a silicon disk resonator, and (ii) surface plasmons arising from nanoparticles arranged randomly on top of the resonator. We elaborate on the physical phenomena, provide simulation results, and conduct a security analysis of peo- PUFs for secure key generation and authentication. This study highlights the good potential of peo-PUFs, and our future work is to focus on fabrication and characterization of such PUFs., Comment: IEEE/OSA J. Lightwave Technology (JLT), 2019

An RF-photonic filter and down-converter system based on a compact and fully tunable silicon optical filter has been demonstrated and analyzed. Its frequency down-conversion was implemented using optical heterodyne detection with an injection locked laser. This system filters a 1.25 GHz-wide signal with > 20 dB filter rejection and a very broad 20 GHz center tuning range. The frequency down-conversion process is operated in a low-IF mode to avoid laser low frequency noises. Measured system Spurious-Free Dynamic Range (SFDR) of 94.3 dB*Hz2/3 [dB*Hz superscript 2/3] has been limited by the optical losses from I/O coupling and measurement setup. We examined experimentally that 105.3 dB*Hz2/3 [dB*Hz superscript 2/3] SFDR is achievable if the encountered optical loss were reduced to the filter's intrinsic loss. Based on the excellent agreements between measured and simulated results, we explore the critical improvements of the silicon photonic devices needed for the system to achieve 118 dB*Hz2/3 [dB*Hz superscript 2/3] SFDR and briefly review the status of the component technologies., United States. Defense Advanced Research Projects Agency. Electronic and Photonic Integrated Circuit (EPIC) Program, United States. Defense Advanced Research Projects Agency. Microsystems Technology Office (Contract No. HR0011-05-C-0027)

We present a fully tunable multistage narrowband optical pole-zero notch filter that is fabricated in a silicon complementary metal oxide semiconductor (CMOS) foundry. The filter allows for the reconfigurable and independent tuning of the center frequency, null depth, and bandwidth for one or more notches simultaneously. It is constructed using a Mach-Zehnder interferometer (MZI) with cascaded tunable all-pass filter (APF) ring resonators in its arms. Measured filter nulling response exhibits ultranarrow notch 3 dB BW of 0.6350 GHz, and nulling depth of 33 dB. This filter is compact and integrated in an area of 1.75 mm2. Using this device, a novel method to cancel undesired bands of 3 dB bandwidth of < 910 MH[superscript 2] in microwave-photonic systems is demonstrated. The ultranarrow filter response properties have been realized based on our developed low-propagation loss silicon channel waveguide and tunable ring-resonator designs. Experimentally, they yielded a loss of 0.25 dB/cm and 0.18 dB/round trip, respectively., United States. Defense Advanced Research Projects Agency (project EPIC), Massachusetts Institute of Technology. Microsystems Technology Laboratories (Contract HR0011-05-C-0027)