CRESST is a direct dark matter search experiment based on cryogenic particle detectors to search for nuclear recoil events induced by the elastic scattering of dark matter particles off nuclei. The setup is installed in a deep underground site under the Gran Sasso massif in Italy with the detector modules operating at about 15mK.
The first phase of the CRESST experiment (CRESST I) used sapphire crystals as target material. Energy deposited in these crystal via a particle interaction is detected as a heat signal read out with superconducting phase transition thermometers - transition edge sensors (TES).
The detector modules for CRESST II and CRESST III were developed based on scintillating CaWO4 crystals as absorbers. In this crystal a particle interaction produces mainly heat in the form of phonons, as for sapphire. In addition a small amount of the energy deposited is emitted as scintillation light. As the amount of light produced differs for different kinds of particles, this leads to an efficient means of eliminating the most common backgrounds.
We list here the available datasets from CRESST-II and CRESST-III. The data can be downloaded for use or dynamically visualised within the repository. Please note the appropriate sources listed for citation when using data from the CRESST Collaboration.
The XENON experiment is a 3500kg liquid xenon (LXe) detector to search for Dark Matter. It is a dual-phase time projection chamber (TPC) housed at the INFN Laboratori Nazionali del Gran Sasso. Particles recoiling in LXe produce photons (scintillation) and electrons (ionization).
The photons are detected as the “S1” signal with 248 3-in. photomultiplier tubes (PMTs) positioned above and below the LXe target. Electric fields drift the electrons upward and extract them into gaseous xenon, where electroluminescence produces a secondary scintillation “S2” signal.
In most analyses, the ratio between S1 and S2 differentiates electronic recoils (ERs), caused by β particles and γ rays, from nuclear recoils (NRs), caused by neutrons or some DM particles. The interaction position, reconstructed from the S2 light pattern and the time difference between S1 and S2, discriminates DM candidates from most external radioactive backgrounds.
We list here the available datasets from the XENON Experiment. The data can be downloaded for use or dynamically visualised within the repository. Please note the appropriate sources listed for citation when using data from the XENON Collaboration.
ANAIS is an experiment developed by the Nuclear and Astroparticle Physics group of the University of Zaragoza which pursues this elusive dark matter detection by looking at the annual modulation of the expected interaction rates in a target of sodium iodide, material which produces small scintillations when a particle interacts and deposits some energy. This modulation is a distinctive feature stemming from the Earth revolution around the Sun which changes periodically the relative velocity of the incoming Dark Matter particles to the detector and, because of that, the energy deposited. DAMA-LIBRA experiment at Gran Sasso Underground Laboratory has reported the presence of modulation in its data with a high statistical significance; ANAIS could confirm it and help to understand the different systematics involved.
ANAIS is the large scale conclusion of previous studies carried out with different prototypes by the University of Zaragoza group at the Canfranc Underground Laboratory, Spain. ANAIS-112 is using 112.5 kg of NaI(Tl) crystals to study the expected annual modulation in the galactic dark matter signal distributed in 9 modules of 12.5 kg each.
ANAIS-112 is taking data at the Canfranc Underground Laboratory since 3 August 2017. In 2019 first results, corresponding to 1.5 years of data, and in 2021 the results of 3 years were published. They are compatible with the absence of modulation and incompatible with the DAMA/LIBRA positive modulation with a sensitivity of 2.5-2.7 sigma for the 3 years result, confirming the sensitivity estimates. DAMA/LIBRA result is at reach with 3 sigmas of significance in 5 years of data. Recently, the sensitivity has been improved by developing a new machine-learning event selection protocol. This improvement will allow testing DAMA/LIBRA with 3 sigmas of significance with the first 3 years of data.
We list here the available datasets from the ANAIS experiment. The data can be downloaded for use or dynamically visualised within the repository. Please note the appropriate sources listed for citation when using data from the ANAIS Collaboration.
