Polarization measurements of the Crab Pulsar with POLAR

POLAR is a dedicated Gamma-Ray Burst polarimeter making use of Compton-scattering which took data from the second Chinese spacelab, the Tiangong-2 from September 2016 to April 2017. It has a wide Field of View of $\sim6$ steradians and an effective area of $\sim400\ cm^2$ at 300 keV. These features make it one of the most sensitive instruments in its energy range (15-500 keV), and therefore capable of almost continuously monitoring persistent sources such as pulsars. Significant folded pulsation from both PSR B0531+21 (the Crab Pulsar) and PSR B1509-58 has been observed. Observations of the Crab Pulsar with POLAR have previously been used for phase-resolved spectroscopy of the Crab Pulsar to calibrate the instrumental responses of POLAR. In this work, we investigate a polarimetric joint-fitting method for observations of the Crab Pulsar with POLAR. Unlike a GRB observation with POLAR, the observations of the Crab Pulsar are complicated by multiple observational datasets during which the polarization plane rotates as well. So before fitting, we have to correct the modulation curves under different datasets, by taking into account the rotations of the Crab Pulsar's relative position in the detctor's local coordinate, and the changes of detector response in different datasets. Despite these difficulties and the low signal to background for such sources constraining, polarization measurements were possible with the POLAR data. We will present the methodology briefly, which could be applied to any wide FoV polarimeter, and polarization results of the Crab pulsar with POLAR. Finally, the inferred ability of pulsar detection with POLAR-2 (the successor of POLAR) will also be discussed.Comment: 8 pages, 7 figures, 2 tables, 37th International Cosmic Ray Conference (ICRC2021) proceeding

Measuring the Cosmic X-ray Background accurately

Measuring the Cosmic X-ray Background (CXB) is a key to understand the Active Galactic Nuclei population, their absorption distribution and their average spectra. However, hard X-ray instruments suffer from time-dependent backgrounds and cross-calibration issues. The uncertainty of the CXB normalization remain of the order of 20%. To obtain a more accurate measurement, the Monitor Vsego Neba (MVN) instrument was built in Russia but not yet launched to the ISS (arXiv:1410.3284). We follow the same ideas to develop a CXB detector made of four collimated spectrometers with a rotating obturator on top. The collimators block off-axis photons below 100 keV and the obturator modulates on-axis photons allowing to separate the CXB from the instrumental background. Our spectrometers are made of 20 mm thick CeBr$_{3}$ crystals on top of a SiPM array. One tube features a $\sim$20 cm$^2$ effective area and more energy coverage than MVN, leading to a CXB count rate improved by a factor of $\sim$10 and a statistical uncertainty $\sim$0.5% on the CXB flux. A prototype is being built and we are seeking for a launch opportunity.Comment: 8 pages, 5 figures, 37th International Cosmic Ray Conference (ICRC2021

Measuring the Cosmic X-ray Background accurately

Synthesis models of the diffuse Cosmic X-ray Background (CXB) suggest that it can be resolved into discrete sources, primarily Active Galactic Nuclei (AGNs). Measuring the CXB accurately offers a unique probe to study the AGN population in the nearby Universe. Current hard X-ray instruments suffer from the time-dependent background and cross-calibration issues. As a result, their measurements of the CXB normalization have an uncertainty of the order of $\sim$15%. In this paper, we present the concept and simulated performances of a CXB detector, which could be operated on different platforms. With a 16-U CubeSat mission running for more than two years in space, such a detector could measure the CXB normalization with $\sim$1% uncertainty

"What Apps Did You Use?": Understanding the Long-term Evolution of Mobile App Usage

Peer reviewe

User Experience Design Professionals' Perceptions of Generative Artificial Intelligence

Among creative professionals, Generative Artificial Intelligence (GenAI) has sparked excitement over its capabilities and fear over unanticipated consequences. How does GenAI impact User Experience Design (UXD) practice, and are fears warranted? We interviewed 20 UX Designers, with diverse experience and across companies (startups to large enterprises). We probed them to characterize their practices, and sample their attitudes, concerns, and expectations. We found that experienced designers are confident in their originality, creativity, and empathic skills, and find GenAI's role as assistive. They emphasized the unique human factors of "enjoyment" and "agency", where humans remain the arbiters of "AI alignment". However, skill degradation, job replacement, and creativity exhaustion can adversely impact junior designers. We discuss implications for human-GenAI collaboration, specifically copyright and ownership, human creativity and agency, and AI literacy and access. Through the lens of responsible and participatory AI, we contribute a deeper understanding of GenAI fears and opportunities for UXD.Comment: accepted to CHI 202

Power Optimization in Multi-IRS Aided Delay-Constrained IoVT Systems

With the advancement of video sensors in the Internet of Things, Internet of Video Things (IoVT) systems, capable of delivering abundant and diverse information, have been increasingly deployed for various applications. However, the extensive transmission of video data in IoVT poses challenges in terms of delay and power consumption. Intelligent reconfigurable surface (IRS), as an emerging technology, can enhance communication quality and consequently improve system performance by reconfiguring wireless propagation environments. Inspired by this, we propose a multi-IRS aided IoVT system that leverages IRS to enhance communication quality, thereby reducing power consumption while satisfying delay requirements. To fully leverage the benefits of IRS, we jointly optimize power control for IoVT devices and passive beamforming for IRS to minimize long-term total power consumption under delay constraints. To solve this problem, we first utilize Lyapunov optimization to decouple the long-term optimization problem into each time slot. Subsequently, an alternating optimization algorithm employing optimal solution-seeking and fractional programming is proposed to effectively solve the optimization problems at each time slot. Simulation results demonstrate that the proposed algorithm significantly outperforms benchmark algorithms in terms of long-term total power consumption. Moreover, a trade-off between the number of IRS elements and system performance is also proved

Enhanced Sparsification via Stimulative Training

Sparsification-based pruning has been an important category in model compression. Existing methods commonly set sparsity-inducing penalty terms to suppress the importance of dropped weights, which is regarded as the suppressed sparsification paradigm. However, this paradigm inactivates the dropped parts of networks causing capacity damage before pruning, thereby leading to performance degradation. To alleviate this issue, we first study and reveal the relative sparsity effect in emerging stimulative training and then propose a structured pruning framework, named STP, based on an enhanced sparsification paradigm which maintains the magnitude of dropped weights and enhances the expressivity of kept weights by self-distillation. Besides, to find an optimal architecture for the pruned network, we propose a multi-dimension architecture space and a knowledge distillation-guided exploration strategy. To reduce the huge capacity gap of distillation, we propose a subnet mutating expansion technique. Extensive experiments on various benchmarks indicate the effectiveness of STP. Specifically, without fine-tuning, our method consistently achieves superior performance at different budgets, especially under extremely aggressive pruning scenarios, e.g., remaining 95.11% Top-1 accuracy (72.43% in 76.15%) while reducing 85% FLOPs for ResNet-50 on ImageNet. Codes will be released soon.Comment: 26 page