A second coherent radio burst spanning 704-4032 MHz with spectral index -2.18, 54% linear and 22% circular polarization, and an orthogonal polarization angle jump was detected from 2XMM J104608.7-594306, showing rare radio activity in sources thought to be radio-quiet.
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4 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
A public catalogue provides geometric and photogeometric distances plus uncertainties for 1.47 billion Gaia EDR3 stars derived via probabilistic inference with a three-dimensional Galactic prior.
Differentiable optical simulation models telescope jitter blurring and shows that two-dimensional jitter models avoid systematic bias in binary separation measurements for the TOLIMAN exoplanet mission.
A feedforward neural network delivers probabilistic climate classifications and uncertainty estimates for the Sahara Desert from 1960-1989 data, tracking temporal shifts via fluctuation analysis.
citing papers explorer
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A bright wideband radio burst from the isolated neutron star 2XMM J104608.7$-$594306
A second coherent radio burst spanning 704-4032 MHz with spectral index -2.18, 54% linear and 22% circular polarization, and an orthogonal polarization angle jump was detected from 2XMM J104608.7-594306, showing rare radio activity in sources thought to be radio-quiet.
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Estimating distances from parallaxes. V: Geometric and photogeometric distances to 1.47 billion stars in Gaia Early Data Release 3
A public catalogue provides geometric and photogeometric distances plus uncertainties for 1.47 billion Gaia EDR3 stars derived via probabilistic inference with a three-dimensional Galactic prior.
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Mitigating effects of telescope jitter through differentiable forward-modeling
Differentiable optical simulation models telescope jitter blurring and shows that two-dimensional jitter models avoid systematic bias in binary separation measurements for the TOLIMAN exoplanet mission.
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Probabilistic Classification and Uncertainty Quantification of Sahara Desert Climate Using Feedforward Neural Networks
A feedforward neural network delivers probabilistic climate classifications and uncertainty estimates for the Sahara Desert from 1960-1989 data, tracking temporal shifts via fluctuation analysis.