A Telecom O‑Band Emitter in Diamond Mukherjee, Sounak; Zhang, Zi-Huai; Oblinsky, Daniel G. ...
Nano letters,
04/2023, Letnik:
23, Številka:
7
Journal Article
Recenzirano
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Color centers in diamond are promising platforms for quantum technologies. Most color centers in diamond discovered thus far emit in the visible or near-infrared wavelength range, which are ...incompatible with long-distance fiber communication and unfavorable for imaging in biological tissues. Here, we report the experimental observation of a new color center that emits in the telecom O-band, which we observe in silicon-doped bulk single crystal diamonds and microdiamonds. Combining absorption and photoluminescence measurements, we identify a zero-phonon line at 1221 nm and phonon replicas separated by 42 meV. Using transient absorption spectroscopy, we measure an excited state lifetime of around 270 ps and observe a long-lived baseline that may arise from intersystem crossing to another spin manifold.
Hands-on experimental experience with quantum systems in the undergraduate physics curriculum provides students with a deeper understanding of quantum physics and equips them for the fast-growing ...quantum science industry. Here we present an experimental apparatus for performing quantum experiments with single nitrogen-vacancy (NV) centers in diamond. This apparatus is capable of basic experiments such as single-qubit initialization, rotation, and measurement, as well as more advanced experiments investigating electron-nuclear spin interactions. We describe the basic physics of the NV center and give examples of potential experiments that can be performed with this apparatus. We also discuss the options and inherent trade-offs associated with the choice of diamond samples and hardware. The apparatus described here enables students to write their own experimental control and data analysis software from scratch all within a single semester of a typical lab course, as well as to inspect the optical components and inner workings of the apparatus. We hope that this work can serve as a standalone resource for any institution that would like to integrate a quantum instructional lab into its undergraduate physics and engineering curriculum.
In the past two decades, radar-based human sensing has become a topic of intense research. Unlike vision-based techniques which require the use of camera, radars are unobtrusive and privacy ...preserving in nature. Further, radars are agnostic of the lighting conditions and can be used for through-the-wall imaging thereby making them hugely effective in many situations. Compact, affordable radars have been designed that can be easily integrated with remote monitoring systems. However, the classical machine learning techniques currently used for learning and inferring human actions from radar images are compute intensive, and require large volume of training data, making them unsuitable for deployment on the network edge. In this paper, we propose to use the concepts of neuromorphic computing and Spiking Neural Networks (SNN) to learn human actions from data captured by the radar. To the best our knowledge, this is the first attempt of using SNNs on micro-Doppler data from radars. Our SNN model is capable of learning spatial as well as temporal features from the data and our experiments have resulted in 85% accuracy which is comparable with the classical machine learning approaches that are typically used on similar data. Further, the use of neuromorphic and SNN concepts make our model deployable over evolving neuromorphic edge devices thereby making the entire approach more efficient in terms of data, computation and energy consumption.
Light beam carrying spatially varying state of polarization generates space varying Pancharatnam-Berry geometric phase while propagating through homogeneous anisotropic medium. We show that ...determination of such space varying geometric phase provides a unique way to quantify the space varying polarization state of light using a single-shot interferometric measurement. We demonstrate this concept in a Mach-Zehnder interferometric arrangement using a linearly polarized reference light beam, where full information on the spatially varying polarization state is successfully recovered by quantifying the space varying geometric phase and the contrast of interference. The proposed method enables single-shot measurement of any space varying polarization state of light from the measured interference pattern with a polarized reference beam. This approach shows considerable potential for instantaneous mapping of complex space varying polarization of light in diverse applications, such as astronomy, biomedical imaging, nanophotonics, etc., where high precision and near real-time measurement of spatial polarization patterns are desirable.
A telecom O-band emitter in diamond Mukherjee, Sounak; Zhang, Zi-Huai; Oblinsky, Daniel G ...
arXiv (Cornell University),
11/2022
Paper, Journal Article
Odprti dostop
Color centers in diamond are promising platforms for quantum technologies. Most color centers in diamond discovered thus far emit in the visible or near-infrared wavelength range, which are ...incompatible with long-distance fiber communication and unfavorable for imaging in biological tissues. Here, we report the experimental observation of a new color center that emits in the telecom O-band, which we observe in silicon-doped bulk single crystal diamonds and microdiamonds. Combining absorption and photoluminescence measurements, we identify a zero-phonon line at 1221 nm and phonon replicas separated by 42 meV. Using transient absorption spectroscopy, we measure an excited state lifetime of around 270 ps and observe a long-lived baseline that may arise from intersystem crossing to another spin manifold.
Survival (time-to-event) analysis is commonly used in clinical research. Key features of performing a survival analysis include checking proportional hazards assumptions, reporting CIs for hazards ...ratios and relative risks, graphically displaying the findings, and analyzing with consideration of competing risks. This article provides a brief overview of important statistical considerations for survival analysis. Censoring schemes, different methods of survival function estimation, and ways to compare survival curves are described. We also explain competing risk and how to model survival data in the presence of it. Different kinds of bias that influence survival estimation and avenues to model the data under these circumstances are also described. Several analysis techniques are accompanied by graphical representations illustrating proper reporting strategies. We provide a list of guiding statements for researchers and reviewers.
Case-control studies are one of the major observational study designs for performing clinical research. The advantages of these study designs over other study designs are that they are relatively ...quick to perform, economical, and easy to design and implement. Case-control studies are particularly appropriate for studying disease outbreaks, rare diseases, or outcomes of interest. This article describes several types of case-control designs, with simple graphical displays to help understand their differences. Study design considerations are reviewed, including sample size, power, and measures associated with risk factors for clinical outcomes. Finally, we discuss the advantages and disadvantages of case-control studies and provide a checklist for authors and a framework of considerations to guide reviewers’ comments.
The world is experiencing a pandemic due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), also known as COVID-19. The USA is also suffering from a catastrophic death toll from ...COVID-19. Several studies are providing preliminary evidence that short- and long-term exposure to air pollution might increase the severity of COVID-19 outcomes, including a higher risk of death. In this study, we develop a spatiotemporal model to estimate the association between exposure to fine particulate matter PM2.5 and mortality accounting for several social and environmental factors. More specifically, we implement a Bayesian zero-inflated negative binomial regression model with random effects that vary in time and space. Our goal is to estimate the association between air pollution and mortality accounting for the spatiotemporal variability that remained unexplained by the measured confounders. We applied our model to four regions of the USA with weekly data available for each county within each region. We analyze the data separately for each region because each region shows a different disease spread pattern. We found a positive association between long-term exposure to PM2.5 and the mortality from the COVID-19 disease for all four regions with three of four being statistically significant. Data and code are available at our GitHub repository. Supplementary materials accompanying this paper appear on-line.
IoT-based automated systems require efficient online time-series analysis and forecasting and there is a growing requirement to enable such processing at the low-cost constrained edge devices. ...Classical approaches such as Online Autoregressive Integrated Moving Average (Online ARIMA), Seasonal ARIMA (SARIMA) etc. and Artificial Neural Network (ANN) based techniques including Long-short Term Memory (LSTM) do not cater to this niche requirement due to their memory and computation power requirements. Neuromorphic computing and bio-plausible spiking neural networks, being both data and energy efficient, may offer a better solution. In this work, a novel spiking reservoir based network is proposed for online time series forecasting that relies on temporal spike encoding with a feedback driven online learning mechanism. The proposed network is capable of avoiding rapidly fading memory problem. The prediction accuracy of the network (tested on nine time-series datasets) outperforms conventional methods like SARIMA, Online ARIMA, Stacked LSTM, achieving up to 8% higher R2 score while using negligible buffer memory.
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