Tag Archives: data analysis

Search for light dark matter interactions enhanced by the Migdal effect in XENON1T

When a particle elastically scatters off a xenon nucleus, it has been assumed that electron clouds immediately follow the motion of the nucleus, but in reality it takes some time for the atomic electrons to catch up, resulting in ionization and excitation of the atom. This effect is called the Migdal effect, which was predicted by A. B. Migdal and recently reformulated in the context of Dark Matter searches by Ibe. et al. While the elastic scattering of WIMPs produces nuclear recoils, the Migdal effect predicts secondary electronic recoils that can accompany a nuclear recoil. Unlike nuclear recoils, electronic recoils lose negligible energy as heat, because electrons have small masses compared with xenon nuclei. This results in a lower energy threshold for electronic recoil signals – in XENON1T, down to about 1 keV. Therefore, searching for the electronic recoil signals induced by the Migdal effect enables a significant boost of XENON1T’s sensitivity to low-mass dark matter, based on this lowered threshold. In this search, we adopted an approach that utilizes the ionization signal only (so-called S2-only analysis), as well as both scintillation and ionization signals (S1-S2 analysis), which enables to lower the detection threshold. We interpreted the results in different cases: spin-(in)dependent (SI/SD) WIMP-nucleon interaction and the scenario where the interaction is mediated by a scalar force mediator (light mediator). The results for the spin-(in)dependent WIMP-nucleon interaction are shown in the following figure:
 
We set the most stringent upper limits on the SI and SD WIMP-nucleon interaction cross-sections for masses below 1.8 GeV and 2 GeV, respectively. Together with the standard nuclear recoil search, XENON1T results have thus reached unprecedented sensitivities to both low-mass (sub-GeV) and high-mass (GeV – TeV) WIMPs. An open access pre-print of the paper can of course be found on the arxiv.

Light Dark Matter Search Results from XENON1T

XENON1T recently released a preprint with new world-leading constraints on light dark matter particles.

The challenge of light dark matter

The XENON1T detector aims find the signals of dark matter bouncing off xenon atoms.
If such a collision happens, it produces two signals: a small light flash (S1), and a cloud of free electrons that can be drifted up and extracted out of the detector (S2).

Figure: How dark matter would make S1 and S2 signals in the XENON1T detector.

However, dark matter lighter than about six times the proton mass (6 GeV/c^2) cannot push the heavy xenon atoms (131 GeV/c^2) enough to make efficiently detectable S1s. XENON1T needs both S1 and S2 to accurately reconstruct where in the detector the event happened. The time between the S1 and S2 signals reveals the depth of the event. Events at the top and bottom edge of the detector are common due to radioactive backgrounds. If we cannot reject these events, dark matter searches will not be efficient. Thus, most strong constraints on light dark matter have, until now, come from different detectors, mostly using ultra-low temperature crystals made of Germanium, Silicone, or Calcium Tungstate.

The S2-only technique

XENON1T’s new preprints use an “S2-only analysis”, where events without S1s are still considered. Advances in detector construction and analysis techniques led to a thousand times lower background level than previously achieved in S2-only searches.

For example, the S2 electron cloud becomes broader as it drifts upward, like a drop of ink spreading out in water. The deeper the event, the broader the cloud, and the longer the S2 signal lasts. Thus XENON1T could reject most of the events at the top and bottom, even without the S1, by rejecting very short and very long S2 signals.

The results

Most theorists predict that dark matter would collide with the heavy xenon nuclei and produce “nuclear recoils”. For these, the S2-only technique is sensitive to 2-3x lower energies than traditional analyses. Thus, we get improved constraints on light dark matter:

Figure: New XENON1T limits (black lines) on light dark matter. The colored lines show previous results, including other results from XENON1T in blue.

In some models, dark matter collides with electrons around the nucleus, and produces “electronic recoils”. These make much larger S2 signals than nuclear recoils of the same S1 size. S2-only searches thus improve the energy threshold for these models by as much as a factor of ten. Combined with the lower background, XENON1T’s S2-only results thus improve the constraints on such models by several orders of magnitude:

Figure: New XENON1T limits on scattering of dark matter on electrons. (The dashed line is the same analysis repeated with more conservative assumptions.)

For more information, please see our arXiv preprint at https://arxiv.org/abs/1907.11485.

 

Signal Reconstruction, Calibration and Event Selection in XENON1T

Since the first release of dark matter search results based on the 1 tonne-year exposure of the XENON1T experiment, the collaboration has published more WIMP signal searches based on the same dataset. Those articles are usually written in a brief way and are focusing on the communication of the scientific results.

In order to give more details on the XENON1T dark matter analysis, we have previously published a paper focusing on the signal and background models and the statistical inference using this data. It has been complemented by a new article that reveals details on the challenges of detector characterization and data preparation before it is ready to be used for model building and statistical inference in order to make statements on dark matter.

The XENON1T experiment performed two science runs between October 2016 and February 2018, reaching a total data livetime of 279 days. During that time the detector had to be operated in a very stable mode in order to ensure undistorted signals. If some conditions change over time they have to be modeled over time in order to account for them in the take them into account during data analysis and include them into the models. One example for those changes are the ones at the photosensors. Each sensor has an individual amplification factor, i.e. gain, that is a function of the applied high voltage. few sensors developed malfunctions during the science runs because of which the amplification factor decreased over time or the voltage had to be reduced resulting in a sudden decreased of the amplification. Those variations are shown in red and black for two sensors as a function of time in the following figure while green, blue and magenta show stable sensors which are representative for the majority of the XENON1T light detectors.

 

Measured photosensor amplification factor as a function of time for three representative stable sensors (green, blue and magenta) and two examples where the amplification decreased due to malfunctions (red and black).

As soon as the detector operation conditions are modeled the data is put through selection criteria that reduce the number of background-like signatures and therefore enhance the signal to background ratio. The criteria are grouped into four general types:

 

Acceptance of dark matter signal events after incrementally applying data selection criteria in order to reduce background-like signatures. The acceptance is shown as function of the signal parameters S1 and S2.

Modelling how an electronic or nuclear recoil will look like in the detector is crucial both to know the shape of a WIMP signal, and to model the backgrounds well. XENON1T uses a comprehensive fit to multiple calibration sources to constrain the distributions of  backgrounds and signals in the analysis space; S1, S2 and the radius from the center axis of the detector. Some background components are harder to model directly, and are estimated by using sidebands or other data samples. In the XENON1T analysis, coincidences between unrelated, lone S1 and S2 events were modeled this way, in addition to the surface background– events occurring close to or at the detector wall.

The models of each background and the signal, for two separate science runs, are put together in a likelihood, which is a mathematical function of the WIMP signal strength as well as nuisance parameters. These are unknowns that could change the analysis, such as the true expectation value for each background component. The likelihood also contains multiple terms representing measurements of nuisance parameter, which constrain them when the likelihood is fitted to the data collected by XENON1T. The value of the likelihood evaluated at a specific signal strength has a random distribution which is estimated using simulated realizations of the experimental outcome. The final statistical limits are computed by comparing the likelihood computed on the actual data with the distributions found from the simulations: