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Quantum sensing with solid-state spins offers the promise of high spatial resolution, bandwidth, and dynamic range at sensitivities comparable to more mature quantum sensing technologies, such as atomic vapor cells and superconducting devices. However, despite comparable theoretical sensitivity limits, the performance of bulk solid-state quantum sensors has so far lagged behind these more mature alternatives. A recent review~\cite{barry2020sensitivity} suggests several paths to improve performance of magnetometers employing nitrogen-vacancy defects in diamond, the most-studied solid-state quantum sensing platform. Implementing several suggested techniques, we demonstrate the most sensitive nitrogen-vacancy-based bulk magnetometer reported to date. Our approach combines tailored diamond growth to achieve low strain and long intrinsic dephasing times, the use of double-quantum Ramsey and Hahn echo magnetometry sequences for broadband and narrowband magnetometry respectively, and P1 driving to further extend dephasing time. Notably, the device does not include a flux concentrator, preserving the fixed response of the NVs to magnetic field. The magnetometer realizes a broadband \textcolor{mhsnew}{near-}DC sensitivity $\sim 460$~fT$\cdot$s$^{1/2}$ and a narrowband AC sensitivity $\sim 210$~fT$\cdot$s$^{1/2}$. We describe the experimental setup in detail and highlight potential paths for future improvement.

We present nuReality, a virtual reality 'VR' environment designed to test the efficacy of vehicular behaviors to communicate intent during interactions between autonomous vehicles 'AVs' and pedestrians at urban intersections. In this project we focus on expressive behaviors as a means for pedestrians to readily recognize the underlying intent of the AV's movements. VR is an ideal tool to use to test these situations as it can be immersive and place subjects into these potentially dangerous scenarios without risk. nuReality provides a novel and immersive virtual reality environment that includes numerous visual details (road and building texturing, parked cars, swaying tree limbs) as well as auditory details (birds chirping, cars honking in the distance, people talking). In these files we present the nuReality environment, its 10 unique vehicle behavior scenarios, and the Unreal Engine and Autodesk Maya source files for each scenario. The files are publicly released as open source at www.nuReality.org, to support the academic community studying the critical AV-pedestrian interaction.

Emotion recognition or emotion prediction is a higher approach or a special case of sentiment analysis. In this task, the result is not produced in terms of either polarity: positive or negative or in the form of rating (from 1 to 5) but of a more detailed level of analysis in which the results are depicted in more expressions like sadness, enjoyment, anger, disgust, fear, and surprise. Emotion recognition plays a critical role in measuring the brand value of a product by recognizing specific emotions of customers' comments. In this study, we have achieved two targets. First and foremost, we built a standard Vietnamese Social Media Emotion Corpus (UIT-VSMEC) with exactly 6,927 emotion-annotated sentences, contributing to emotion recognition research in Vietnamese which is a low-resource language in natural language processing (NLP). Secondly, we assessed and measured machine learning and deep neural network models on our UIT-VSMEC corpus. As a result, the CNN model achieved the highest performance with the weighted F1-score of 59.74%. Our corpus is available at our research website., Comment: PACLING 2019

Treatment of lab-grown diamond by electron irradiation and annealing has enabled quantum sensors based on negatively-charged nitrogen-vacancy (NV$^\text{-}$) centers to demonstrate record sensitivities. \cite{Clevenson2015,Wolf2015,Barry2016,Chatzidrosos2017}. Here we investigate the irradiation and annealing process applied to 28 diamond samples using a new ambient-temperature, all-optical approach. As the presence of the neutrally-charged nitrogen-vacancy (NV$^\text{0}$) center is deleterious to sensor performance, this photoluminescence decomposition analysis (PDA) is first employed to determine the concentration ratio of NV$^\text{-}$ to NV$^0$ in diamond samples from the measured photoluminescence spectrum. The analysis hinges on (i) isolating each NV charge state's emission spectrum and (ii) measuring the NV$^\text{-}$ to NV$^0$ emission ratio, which is found to be 2.5$\pm$0.5 under low-intensity 532 nm illumination. Using the PDA method, we measure the effects of irradiation and annealing on conversion of substitutional nitrogen to NV centers. Combining these measurements with a phenomenological model for diamond irradiation and annealing, we extract an estimated monovacancy creation rate of $0.52\pm 0.26$ cm$^{\text{-1}}$ for 1 MeV electron irradiation and an estimated monovacancy diffusion coefficient of 1.8 nm$^2$/s at 850~$^\circ$C. Finally we find that irradiation doses $\gtrsim 10^{18}$ e$^\text{-}$/cm$^2$ deteriorate the NV$^\text{-}$ decoherence time $T_2$ whereas $T_1$ is unaffected up to the the maximum investigated dose of $5\times 10^{18}$ e$^\text{-}$/cm$^2$., Comment: 19 pages, 10 figures

We present a combined theoretical and experimental study of solid-state spin decoherence in an electronic spin bath, focusing specifically on ensembles of nitrogen vacancy (NV) color centers in diamond and the associated substitutional nitrogen spin bath. We perform measurements of NV spin free induction decay times $T_2^*$ and spin-echo coherence times $T_2$ in 25 diamond samples with nitrogen concentrations [N] ranging from 0.01 to 300\,ppm. We introduce a microscopic model and perform numerical simulations to quantitatively explain the degradation of both $T_2^*$ and $T_2$ over four orders of magnitude in [N]. Our results resolve a long-standing discrepancy observed in NV $T_2$ experiments, enabling us to describe NV ensemble spin coherence decay shapes as emerging consistently from the contribution of many individual NV., Comment: 6 pages, 4 figures + supplement

Solid-state spin systems including nitrogen-vacancy (NV) centers in diamond constitute an increasingly favored quantum sensing platform. However, present NV ensemble devices exhibit sensitivities orders of magnitude away from theoretical limits. The sensitivity shortfall both handicaps existing implementations and curtails the envisioned application space. This review analyzes present and proposed approaches to enhance the sensitivity of broadband ensemble-NV-diamond magnetometers. Improvements to the spin dephasing time, the readout fidelity, and the host diamond material properties are identified as the most promising avenues and are investigated extensively. Our analysis of sensitivity optimization establishes a foundation to stimulate development of new techniques for enhancing solid-state sensor performance., Comment: 73 pages, 36 figures, 17 tables