Tag Archives: calibration

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:

XENON1T Calibrations Talk at APS April Meeting

At the 2018 April Meeting of APS last weekend, I presented a brief summary of how and why we calibrate the XENON1T detector. The April Meeting is one of the largest American physics conferences and covers a broad range of research, from nuclear and particle physics to gravitation and cosmology. Below you can see one of the slides that I presented:

This shows how we use data from calibrations to understand every piece of physics in our detector, from a particle entering and hitting a xenon atom to the measurement of the light and charge produced by this interaction. Combining the many different calibrations we do, we develop a complete model of XENON1T which is then used in a statistics framework to determine whether the background data we’ve taken contains WIMPs. Stay tuned as it won’t be too long before we can release those results as well!

Results from a Calibration of XENON100 Using a Source of Dissolved Radon-220

With 2 tonnes of target material, XENON1T is currently the largest liquid xenon detector in the search for dark matter. The detector’s immense volume greatly increases our chances of successfully observing that rare scatter of a dark matter particle off a xenon atom that we have sought for more than a decade, like casting a larger net to catch more fish. However, the size also makes it considerably more difficult for us to know how our detector would respond to the scatters of dark matter or to the scatters of electrons or gamma rays that would obscure our view of dark matter. These electrons and gammas come from ambient radon, impurities in the xenon, and even the detector components themselves. While their effects can be reduced through an appropriate selection of location and the materials, they cannot be completely eliminated. Hence, it is necessary to understand how our detector responds to electrons and gammas in contrast to dark matter. A thorough understanding of these backgrounds is arguably the single most crucial part of our endeavor.

Historically, in XENON10 and XENON100, we used external radioactive sources of cobalt and thorium, which emit gammas. Unfortunately, a drawback of XENON1T’s size is that it hobbles the rate of interactions in the central region of the detector, which is the most important for us in understanding our detector. For this reason, we needed to identify an internal, or dissolved, radioactive source that can be injected directly into the detector’s liquid xenon target volume.

One possibility is a source of 220Rn, which we characterize using the XENON100 detector. The source is well suited to calibrate our detector because it can imitate the effects of ambient radon (222Rn). The radioactive decay of 212Pb (a daughter of 220Rn) generates an electron just like 214Pb (a daughter of 222Rn), and thus their responses are very similar. The only thing we have to verify is that we can spread the 212Pb atoms throughout the detector volume. Due to the particular design of XENON100, many gamma events from other 220Rn daughters prevent us from identifying which events arise from 212Pb. So, we use the distribution of 212Bi, the daughter of 212Pb, to clearly show that 212Pb reaches even the centermost part of the detector. This distribution is shown in the figure below. Once that calibration is done, we do not have to proactively clean our detector, as would be the case with alternatives. Since the half-life of 212Pb is about half a day, we just wait a few days for the detector to return to normal.

The source also provides alpha particles that prove useful in understanding our background. The alpha particles of 216Po and 220Rn enable us to easily pinpoint their locations at the time of decay. And because they happen in quick succession (about 0.1 seconds), the daughter 216Po can be paired with its parent 220Rn. These pairs show us the trajectory of 216Po in the liquid xenon and how long it takes to decay. With both the time and the displacement, we can calculate the average velocity of the 216Po atom. If we then determine the velocities of all identified RnPo pairs, we can create a map of atomic motion in the full xenon volume of a given detector, as shown here:

In the case of XENON100, we find that atoms move at speeds up to 8 mm/s. They move in a single convection cell with a small contribution that results from an electric field applied to the xenon volume. This aspect tells us that an appreciable fraction of 216Po atoms is left ionized after the decay of 220Rn.

In general, a known map of atomic motion motivates two additional techniques to help us understand the backgrounds. Firstly, such a map enables us to identify the presence of “dead regions” through which liquid xenon does not flow very well. This feature is important for keeping the xenon free of impurities. Secondly, with sufficiently slow atomic motion or sufficiently large detector volumes, we could match 214Pb to its parent 222Rn or 218Po following a method similar to the one described previously for 220Rn. This tagging process would clearly distinguish 214Pb background events from the coveted dark matter event.

All of the finer details about this dissolved radon source can be found in the dedicated publication in Phys. Rev. D: E. Aprile et al. (XENON), Results from a calibration of XENON100 using a source of dissolved radon-220, Phys. Rev. D 95, 072008 (2017). This publication is of course also available as a pre-print as arXiv:1611.03585.