Opening the Third Generation: The Search for Long-Lived Fundamental Particles

Informacje na temat projektu

OPEN3GEN

Identyfikator umowy o grant: 772357

DOI

10.3030/772357

Projekt został zamknięty

Data podpisania przez KE 23 Kwietnia 2018

Data rozpoczęcia 1 Marca 2019

Data zakończenia 31 Sierpnia 2025

Finansowanie w ramach

• EXCELLENT SCIENCE - European Research Council (ERC)

Koszt całkowity

€ 1 747 286,00

Wkład UE

€ 1 747 286,00

Koordynowany przez

THE UNIVERSITY OF EDINBURGH
United Kingdom

Periodic Reporting for period 3 - OPEN3GEN (Opening the Third Generation: The Search for Long-Lived Fundamental Particles)

Okres sprawozdawczy: 2022-03-01 do 2023-08-31

Podsumowanie kontekstu i ogólnych celów projektu

In the quest to find new underlying physics, the OPEN3GEN team identified a substantial gap that we have unique abilities to address. In collider physics, we focus on high mass and energy and generally neglect an additional axis that we can explore: long lifetimes. We know of four fundamental SM particles with relatively long lifetimes: bottom and charm quarks and tau and muon leptons. Are there more long(er) lifetime particles (LLPs) in nature? Are they related by an underlying symmetry? Many models motivate new LLPs in nature. Our experiments currently have little sensitivity to these particles and we optimize our standard reconstruction algorithms to be sensitive only to the SM lifetimes we know of. Recent years have seen some trend towards searching for LLPs (see Figure 1) but they cover small parts of the mass-lifetime phase space. These searches have neglected the most powerful method: to search for decays of LLPs to third generation SM particles. In a large class of feasible models, third generation searches will be more sensitive for one simple reason: particles decay preferentially to the most massive particles available. The tau mass is ~3500 times the electron mass and so massive new states are commensurately more likely to decay into it: third generation particles have a “privileged role”. However, it is experimentally more challenging to search for decays to third generation particles because 1) they themselves decay to more complex signatures and 2) they have larger background processes.We are opening up this new search axis in fundamental physics by searching for decays of LLPs to pairs of tau leptons. Discovery of LLPs would lead us to a new underlying dynamics, which we can discover and establish the nature of.

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

The project has proceeded with great progress, even despite the setbacks caused by the Covid19 Pandemic. The major milestones of the project to date are
1) The design of a new trigger to record long-lived particles decaying to tau leptons at the ATLAS detector. This is a trigger to record hadronic decay signatures, and simulation shows that this increases the sensitivity to this class of particle by a factor of over two in large lifetime regions.
2) The newly designed trigger was implemented in the trigger menu, meaning that it will be used to record data during the LHC run starting in spring 2022.
3) The hadronic tau identification has been redesigned to be sensitive to long-lived particles decaying to taus. In particular the inclusion of a zero-prong category of taus has more than doubled this sensitivity. In addition to this, the retuning of the recurrent neural network used to identify taus has augmented the sensitivity in the case where charged particles are reconstructed.
4) The analysis framework to search the LHC run 2 data is now advanced, with backgrounds accounted for, and the framework is in place for run 3.
The team has achieved the above aspects of the action with great dedication and productivity throughout the lockdowns.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

Novel neural networks trained to provide sensitivity to record (trigger on) particles decaying from long-lived particles.
Novel neural networks trained to provide sensitivity to identify particles decaying from long-lived particles.
Results are expected on new phase space, first in Run 2 ATLAS data and then in the new Run 3 data, which will open up the new searches more strongly as our new triggers will be recording data.