Project description
Enabling simultaneous analysis of past, present and future CMB data
The cosmic microwave background (CMB) is an ‘echo’ of the first light emitted in the Universe during the Big Bang. Detecting this CMB requires instrumentation of unprecedented sensitivity. An open-source Bayesian CMB Gibbs sampler called Commander was recently used to successfully derive new state-of-the-art frequency maps based on data from two advanced CMB experiments. Building on this sampler, the ERC-funded Commander project aims to scale the processing power by 1 000 times and integrate pioneering corrections that optimally exploit synergies between experiments. This will pave the way to integrating data from past, present and future experiments and potentially enable the world's first detection of primordial gravitational waves.
Objective
Detecting inflationary gravitational waves from the Big Bang and mapping cosmic structure formation rank among the most important goals in modern cosmology, and detailed cosmic microwave background (CMB) measurements is a uniquely powerful probe of these effects. However, the predicted signatures are tiny, and their detections require unprecedented instrumental sensitivity and systematics control. In this project I propose to develop one single massively parallel end-to-end framework for the joint analysis of past, present and future CMB experiments, and use this to combine current data from WMAP, Planck LFI+HFI and others with forthcoming measurements from Simons Observatory (SO), all processed at the level of time ordered data (TOD). I will also prepare for the analysis of future CMB experiments, including LiteBIRD, CMB-S4, and a Voyage 2050 CMB spectral distortion probe. This framework will build on an Open Source Bayesian CMB Gibbs sampler called Commander that has already played a transformational role in the field for more than two decades, and that has recently been used successfully to derive new state-of-the-art frequency maps for both Planck LFI and WMAP. However, the existing code only scales well up to O(100) computing cores, and I propose in this project a new organization that will scale it up to O(100,000) cores, as required for next-generation experiments. I will also implement a wide range of ground-breaking TOD-level corrections for key systematic effects (non-linear ADCs, cosmic ray glitches, atmospheric fluctuations, detector cross-correlations etc.) that optimally exploit synergies between experiments. Once operational, I will use this global framework to establish a new state-of-the-art model of the microwave sky; shed new light on several hotly debated LCDM tensions; and, perhaps, make the world's first detection of primordial gravitational waves. This work represents a paradigm shift in the field of computational cosmology.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
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Call for proposal
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(opens in new window) ERC-2023-ADG
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0313 Oslo
Norway
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