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Axions and relatives across different mass scales

Periodic Reporting for period 3 - AxScale (Axions and relatives across different mass scales)

Période du rapport: 2021-11-01 au 2022-10-31

The AxScale project aims at testing one of the most prominent ideas to explain the Dark Matter content observed in our universe. This idea is that Dark Matter are so-called "Axions". Dark Matter is a substance whose presence can be inferred from indirect observation by noticing its gravitational effects but no one has managed so far to directly detect it and thus learn more about its properties. The quest for the nature of Dark Matter belongs to a set of unsolved problems in fundamental physics for which a direct use of society is impossible to predict. However, history has proven that it's often exploring these fundamental questions that don't seem to have any practical implications, which then have a tremendous effect on society (think of Einstein's theory of relativity that needs to be understood to make a GPS work).
The AxScale project stands out by the fact that it searches for axions in two vastly differing set-ups and thereby can partially cross-check its own findings.
For some masses of the axion - if it exists - they could be found in either an accelerator-based (NA62) or a table-top cavity-based experiments (RADES). Both set-ups however can also test axion masses in regions only accessible to them: Higher masses at the accelerator-based setup and really small couplings at the table-top experiments.
For the NA62 part of AxScale, the progress is manifold. Firstly, a challenge is of more theoretical nature: the accurate prediction of yields of axions in its different incarnations has to be realized, and the sources of possible backgrounds of searches for these particles have to be understood and modeled. For the yield prediction, several publications were released and the code for the experiment's software updated accordingly. The possible backgrounds have been assessed and methods developed to improve computing speed in a fashion that enable the modeling of such backgrounds at an equivalent statistics of the data taken.
Secondly, a more practical challenge is to take the data, and analyze it. For some channels, this has been achieved. For others, especially in so called-beam dump mode, measures have been taken to use lessons learned to be very efficient and prepared for an upcoming data-taking.

For the RADES part of AxScale, there are similar theoretical and practical challenges: For the modeling part, we were able to show how to build cavities which are scalable in length for the axion search at a vastly unexplored mass-range in dipole magnets. We summarized these findings in publications. We also showed how to tune these cavities in principle and are taking steps to further increase their sensitivity by improving their quality factor. Eventually, we want to design and build cavities that will work in a unique dipole magnet dedicated solely to axion research. For the practical challenges, we finished our first data-taking run, and submitted our analysis results for publication
A stand-out feature of the project is in the fact that it puts much weight on both the theoretical and experimental aspects of the work.
In several phenomenological studies within the NA62 part of the project regarding the predicted axion yield, simulations have been carefully cross-checked against previous experimental literature which makes the predictions very robust. Similarly, in the RADES part of the project, theoretical developments on the cavity design and the analysis of data are both performed in the team. In this fashion, some studies in the RADES group have been shown to also be useful for bigger experimental sibblings like MADMAX and have put RADES among the few direct axion search contenders for axion Dark Matter above 25 mueV.
Until the end of the project, we can expect several more search results and some preparatory measures to continue those searches efficiently at larger parameter space if no discovery has be made by then.
RADES cavity from first data run 2018