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Anthony Lasenby

Researcher at University of Cambridge

Publications -  651
Citations -  117889

Anthony Lasenby is an academic researcher from University of Cambridge. The author has contributed to research in topics: Cosmic microwave background & Planck. The author has an hindex of 143, co-authored 630 publications receiving 105090 citations. Previous affiliations of Anthony Lasenby include University of Manchester.

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H I absorption measurements over the Galactic center Radio Arc region

Abstract: The compact array of the VLA was used to study H I absorption in a 100-pc region in the center of the Galaxy. An absence of gas was observed at 40-50 km/s across the Radio Arc, suggesting that the '40 km/s molecular cloud' possibly associated with Sgr A is placed behind the Arc. At +20 km/s, the observations show absorption by material which could be depolarizing much of the synchrotron emission from the Arc filaments. The kinematic structure revealed by high-resolution molecular and radio recombination line observations is confirmed by the distribution of H I gas at -10 to -60 km/s.
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Planck intermediate results LII. Planet flux densities

Yashar Akrami, +187 more
TL;DR: In this article, the authors compare the results of the Planck HFI and the Wilkinson Microwave Anisotropy Probe (WMAP) to the results from the Atacama Cosmology Telescope (ACT) to obtain a best fit value for the spectral index of Saturn's ring system of beta(ring) = 2 : 30 +/− 0 : 03 over the 30-1000 GHz frequency range.

Astrophysical and cosmological consequences of a gauge theory of gravity.

TL;DR: In this article, a new gauge-theory description of gravity is presented, employing gauge fields in a flat background spacetime, ensuring that all physical relations are independent of the position and orientation of the matter fields in this background.
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Towards a framework for testing general relativity with extreme-mass-ratio-inspiral observations

TL;DR: This work adapts and applies a generalised model for extreme-mass-ratio inspirals constructed on deformed black-hole spacetimes to find order-of-magnitude computational gains over regular nested sampling in the case of synthetic data generated from the null model.
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Nested sampling for physical scientists

TL;DR: In this paper , the authors review Skilling's nested sampling algorithm for Bayesian inference and more broadly multi-dimensional integration and make recommendations for best practice when using NS and by summarizing potential limitations and optimizations of NS.