Unveiling the Universe with Emerging Cosmological Probes
Michele Moresco, Lorenzo Amati, Luca Amendola, Simon Birrer, John P., Blakeslee, Michele Cantiello, Andrea Cimatti, Jeremy Darling, Massimo Della, Valle, Maya Fishbach, Claudio Grillo, Nico Hamaus, Daniel Holz, Luca Izzo,, Raul Jimenez, Elisabeta Lusso, Massimo Meneghetti

TL;DR
This paper reviews emerging cosmological probes beyond standard methods, highlighting their methods, systematics, results, and potential to improve the accuracy and robustness of understanding the universe's accelerated expansion.
Contribution
It provides a comprehensive overview of recent innovative cosmological probes, detailing their methodologies, systematics, and how they complement existing techniques to enhance cosmological measurements.
Findings
Multiple new probes have been developed, including cosmic chronometers and intensity mapping.
Emerging probes show promise in reducing systematic uncertainties.
Synergies between probes can improve constraints on cosmological parameters.
Abstract
The detection of the accelerated expansion of the Universe has been one of the major breakthroughs in modern cosmology. Several cosmological probes (CMB, SNe Ia, BAO) have been studied in depth to better understand the nature of the mechanism driving this acceleration, and they are being currently pushed to their limits, obtaining remarkable constraints that allowed us to shape the standard cosmological model. In parallel to that, however, the percent precision achieved has recently revealed apparent tensions between measurements obtained from different methods. These are either indicating some unaccounted systematic effects, or are pointing toward new physics. Following the development of CMB, SNe, and BAO cosmology, it is critical to extend our selection of cosmological probes. Novel probes can be exploited to validate results, control or mitigate systematic effects, and, most…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
