activity
20012023
most citedBeyondPlanck III. Commander3

36 citations · 266 across the 32 of their papers we have counts for

collaborators

32 papers

astro-ph.IM2023

Requirements analysis for HPC\&HTC infrastructures integration in ESCAPE Science Analysis Platform

S. Bertocco, D. Goz, S. A. Russo +2

ESCAPE (European Science Cluster of Astronomy and Particle physics ESFRI research infrastructures) is a project to set up a cluster of ESFRI (European Strategy Forum on Research In…

astro-ph.IM2023★ 1 cited

Feasibility of access EGI resources through the ESCAPE developed ESFRI Science Analysis Platform

Giuliano Taffoni, Sara Bertocco, Dave Morris +5

The EU ESCAPE project is developing ESAP, ESFRI 1 Scientific Analysis Platform, as an API gateway that enables the seamless integration of independent services accessing distribute…

astro-ph.CO2022★ 7 cited

BeyondPlanck IV. On end-to-end simulations in CMB analysis -- Bayesian versus frequentist statistics

M. Brilenkov, K. S. F. Fornazier, L. T. Hergt +48

End-to-end simulations play a key role in the analysis of any high-sensitivity CMB experiment, providing high-fidelity systematic error propagation capabilities unmatched by any ot…

astro-ph.IM2022

Rosetta: a container-centric science platform for resource-intensive, interactive data analysis

Stefano Alberto Russo, Sara Bertocco, Claudio Gheller +1

Rosetta is a science platform for resource-intensive, interactive data analysis which runs user tasks as software containers. It is built on top of a novel architecture based on fr…

astro-ph.CO2022★ 9 cited

BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation

A. Basyrov, A. -S. Suur-Uski, L. P. L. Colombo +37

We present Planck LFI frequency sky maps derived within the BeyondPlanck framework. This framework draws samples from a global posterior distribution that includes instrumental, as…

astro-ph.CO2022★ 17 cited

BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation

L. P. L. Colombo, J. R. Eskilt, S. Paradiso +36

We present posterior sample-based cosmic microwave background (CMB) constraints from Planck LFI and WMAP observations derived through global end-to-end Bayesian processing. We use…