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Abir Mondal

Publications and source records attributed to Abir Mondal.

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Optimizing Oscilloscope based Acquisition for Pulsed Optically Detected Magnetic Resonance Measurements

Ensembles of nitrogen vacancy (NV) defect centers in diamond have emerged as a promising platform for fundamental studies and applications in quantum sensing and quantum information processing. Here, we demonstrate the use of a digital oscilloscope for acquiring pulsed optically detected magnetic resonance (ODMR) data from an ensemble of NV centers in diamond. The oscilloscope facilitates improved signal visualization, and simplifies system debugging. We show that on-board waveform averaging in the oscilloscope enables more efficient measurements. The detection scheme, and data processing are optimized to allow fast acquisition of high quality data. The system noise, and its impact on the measurements is analyzed in detail. The data processing method is shown to effectively suppress a broad range of noise spectral components, thereby reducing the total noise in the processed data. Furthermore, the introduction of an analog low pass filter in the signal path is shown to improve the measurement by removing aliasing. The framework developed in this work can be extended to other detection techniques and material platforms for ODMR. We expect that the insights developed here will guide the design, and development of dedicated instruments for ODMR in future.

quant-ph

A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages

The expanding influence of social media platforms over the past decade has impacted the way people communicate. The level of obscurity provided by social media and easy accessibility of the internet has facilitated the spread of hate speech. The terms and expressions related to hate speech gets updated with changing times which poses an obstacle to policy-makers and researchers in case of hate speech identification. With growing number of individuals using their native languages to communicate with each other, hate speech in these low-resource languages are also growing. Although, there is awareness about the English-related approaches, much attention have not been provided to these low-resource languages due to lack of datasets and online available data. This article provides a detailed survey of hate speech detection in low-resource languages around the world with details of available datasets, features utilized and techniques used. This survey further discusses the prevailing surveys, overlapping concepts related to hate speech, research challenges and opportunities.

cs.CL