HVeVR2

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SuperCDMS Public Documentation

HVeV Run 2


Abstract This Public Documentation accompanies the results on electron-recoiling dark matter (ERDM) from a 3 week long run of a 1g HVeV detector in the Northwestern ADR. During this run, one week of data (roughly 12 hours per day for 7 days) was acquired at 100V bias with a charge resolution of 0.03 electron-hole pairs, and 3 days at 60V with a resolution of 0.05 electron-hole pairs. Co-57 and laser calibrations were acquired, and a 0V control sample was also acquired over multiple days. The resulting limits for DM-electron scattering and DM absorption are given below, along with plots approved for public release.
These results are published in arXiv:2005.14067


 

 

All results assume a relic DM density of ρDM = 0.3 GeV/cm3. All limits are at 90% confidence level. is the DM-electron scattering cross section. FDM is the DM form factor where FDM = 1 (FDM ∝ 1/q2) corresponds to a DM model with a heavy (ultra light) dark photon mediator. q is the momentum transfer. mDM is the DM mass. More detailed information on the assumed DM models and astrophysical parameters can be found in the US Cosmic Visions Community Report.
 
Num. Result Topic Last Updated Download Comments
1 Experimental Setup August 16th, 2019 png, pdf Photograph of the HVeV R2 detector

Picture of the HVeV R2 detector (left) with side RF veto (right) inside of the copper housing.
2 Experimental Setup January 30th, 2020 png, pdf Photograph of the HVeV R2 detector

Picture of the HVeV detector seen from the side
3 Experimental Setup January 30th, 2020 jpg, pdf Photograph of the HVeV R2 detector installed in the ADR

Picture of the HVeV detector installed in the ADR at Northwestern University. (ArXiv:1903.06517). The ADR has two salt pills, GGG operating around 300 mK and FAA operating around 50 mK. The detector is thermally linked to the FAA salt, with temperature stabilized to 50 mK or 52 mK during the operation. A superconducting magnetic field shield, the Nb can, is mounted on the FAA stage around the detector box. The cold electronic readout device, SQUIDs, are mounted on a thermal stage operated at 1.3 K.
4 Experimental Setup January 30th, 2020 jpg, pdf Photograph of the experimental set-up at the Northwestern University

Photograph of the experimental set-up at the Northwestern University, including the ADR, the computers controlling the cryostat, the data acquisition system.
5 Experimental Setup February 21st, 2020 png, pdf Drawing of the TES mask

Drawing of the sensor mask used for the HVeV R2 detector. Two channels with the same-area are visible and their contacts highlighted with darker squares.
6 Data Acquisition February 21st, 2020 png,pdf Exposure figure

Summary of total exposure as a function of wall time during the run by data type.
7 Detector Response February 21st, 2020 png, pdf Phonon resolution on each day of acquisition

Phonon resolution as measured using laser calibration data for each day of Run 2. Variations are due to noise changes and change in TES bias point day to day. With a few exceptions, we consistently achieve a resolution of ~3.2 eV in the first electron-hole peak. The first point is inconsistent with the others because of an excessively noisy power supply that was replaced starting day 2.
8 Detector Response February 21st, 2020 png, pdf Charge resolution on each day of acquisition

Charge resolution as measured using laser calibration data for each day of Run 2. Variations are due to changes in noise, but largely are determined by the voltage bias used for each calibration as expected due to NTL gain. Resolution for points at the same bias are consistent throughout the run. The first point is inconsistent with the others because of an excessively noisy power supply that was replaced starting day 2.
9 Detector Response February 21st, 2020 png, pdf Relative gain.

Scatter plot comparing the inner and the outer channel for one day of background data: both channel have the same gain thanks to the same-area sensor design of the TES mask. The two anti-diagonal dashed lines indicate the first (lower left) and the second (upper right) electron-hole pair peaks.
10 Detector Response February 21st, 2020 png, pdf Convertion between temperature monitor reading and fridge temperature.

The ADR temperature was monitored during all the runs and recoded each second. The temperature value was recorded in volt which can be then converted with the law reported in this figure.
11 Detector Response February 21st, 2020 png, pdf Base temperature during data taking as a function of time.

Temperature was stabilized at 50 mK during the run for the first 9 days, after which it was raised to 52 mK in order to increase hold time. Periodic deviations in temperature can be seen, as well as rises in temperature at the end of each day as the fridge runs out of cooling power. Light/yellow-ish colors refer to a high count density and dark/purple colors refer to a low count density.
12 Detector Response February 21st, 2020 png, pdf Laser amplitude as a function of the temperature for twelve series acquired at different temperatures.

We acquired twelve laser series at different temperatures in order to correct for gain variations due to temperature instabilities and drifts. This plot shows the peak position fitted from the laser data as a function of the temperature.
13 Detector Response February 21st, 2020 png, pdf Spread of the HV applied on the detector for different series.

The HV was set each day by hand with a knob and it was recorded each second by the DAQ. We found differences between the average values set each day and we corrected for them in the HV correction. The uncertainties are present in this plot but they are so small that are not visible.
14 Detector Response February 21st, 2020 png, pdf Linearity correction and calibration.

The linearity correction and calibration of the HVeV R2 detector was done with the laser data acquired daily. This plot - showing the energy as a function of the optimum filter amplitude - is an example of the curve used for the calibration and linearity correction in one day.
15 Data February 21st, 2020 png, pdf Combined laser spectra after the corrections and calibration for the 100 V data

Top panel: combined spectra of laser data (black histogram) at 100 V after the corrections (temperature, high voltage, QET absorption, linearity) and the calibration. The red curves represent Gaussian fits to each individual peaks. The expected peak positions are multiples of the photon energy (1.95 eV) plus the NTL gain energy for 1 electron-hole pair (100 eV). Bottom panel: residuals between the laser peak position after the calibration and the expected value.
16 Data February 21st, 2020 png, pdf Combined laser spectra after the corrections and calibration for the 60 V data

Top panel: combined spectra of laser data (black histogram) at 60 V after the corrections (temperature, high voltage, QET absorption, linearity) and the calibration. The red curves represent Gaussian fits to each individual peaks. The expected peak positions are multiples of the photon energy (1.95 eV) plus the NTL gain energy for 1 electron-hole pair (60 eV). Bottom panel: residuals between the laser peak position after the calibration and the expected value.
17 Livetime cuts February 21st, 2020 png, pdf Example of one of the livetime cuts: temperature cut for the 50 mK data.

This histogram shows the temperature distribution before and after the temperature livetime cut for the 50 mK data.
18
Livetime cuts February 21st, 2020 png, pdf
png, pdf
Pie chart of the livetime cuts for the 60 V and 100 V data.

This pie chart shows the percentage of data accepted and removed by the livetime cuts: temperature cut, mean baseline cut and burst cut.
19 Data quality cuts February 21st, 2020 png, pdf Frequency-domain Χ2 cut for the 100 V data

The frequency-domain Χ2 cut belongs to the data quality cuts and was studied with the laser data. This plot shows the frequency-domain Χ2 as a function of the energy. The orange dots represent the peak of the Χ2 distribution for each electron-hole pair peak. The red dots represent 3σ position of the corresponding peak. The red line corresponds to the position of the cut.
20 Data quality cuts February 21st, 2020 png, pdf Time-domain Χ2 cut for the 100 V data

The time-domain Χ2 cut belongs to the data quality cuts and was studied with the laser data. This plot shows the time-domain Χ2 as a function of the energy. The orange dots represent the peak of the Χ2 distribution for each electron-hole pair peak. The red dots represent 3σ position of the corresponding peak. The red line corresponds to the position of the cut.
21
Data quality cuts February 21st, 2020 png, pdf
png, pdf
Cumulative data quality cuts for laser and dark-matter-search data at 100 V

This histogram shows the laser and dark-matter-search spectrum after the application of the data-quality cuts.
22 Trigger February 21st, 2020 png, pdf Trigger efficiency for the 100 V data

Top panel: comparison of the combined laser spectrum at 50 mK triggered with the laser TTL and triggered with the trigger used for the dark-matter-search data. Bottom panel: ratio of the histograms reported on the top panel, the trigger theshold at 50 mK is 29 eV. For this analysis, the lower limit of the region of interest was set at 50 eV to simplify the treatment of trigger effects. Note that the same procedure was applied to the 52 mK data and we found a threshold of 37 eV.
23 Efficiency February 21st, 2020 png, pdf Cut Efficiency for the 100 V data

Efficiency as a function of the energy for the 100 V data. The efficiency is fit with the red curve and the fit uncertainty is highlighted with the band. The fit curve and its uncertainty are used to set the limit.
24 Efficiency February 21st, 2020 png, pdf Cut Efficiency for the 60 V data

Efficiency as a function of the energy for the 60 V data. The efficiency is fit with the red curve and the fit uncertainty is highlighted with the band. The fit curve and its uncertainty are used to set the limit.
25 Data March 27st, 2020 png, pdf Cumulative laser calibration spectrum with cuts applied with 100 V data

Laser calibration data for all 100 V data. The data are plotted in three cases: (1) after the corrections and the calibration; (2) after the livetime cuts; (3) the data quality cuts.
26 Data March 27st, 2020 png, pdf Cumulative laser calibration spectrum with cuts applied with 60 V data

Laser calibration data for all 60 V data. The data are plotted in three cases: (1) after the corrections and the calibration; (2) after the livetime cuts; (3) the data quality cuts.
27 Data March 27st, 2020 png, pdf Dark-matter-search spectrum with 100 V data

Dark-matter-search spectrum with the 100 V data. The data are plotted in three cases: (1) after the corrections and the calibration; (2) after the livetime cuts; (3) the data quality cuts.
28 Data March 27st, 2020 png, pdf Dark-matter-search spectrum with 60 V data

Dark-matter-search spectrum with the 60 V data. The data are plotted in three cases: (1) after the corrections and the calibration; (2) after the livetime cuts; (3) the data quality cuts.
29 Data February 21st, 2020 png, pdf Partition distribution as a function of the energy for the dark-matter-search data

Partition as a function of the energy. Positive (negative) values of partition indicate that the event occurred closer to the inner (outer) channel
30
Limits February 21st, 2020 png, pdf
png, pdf
Dark matter electron-recoil limit with FDM=1 for the 100 V data

Dark matter electron-recoil FDM=1 Poisson limits with the 90% unblinded 100 V (blue) and 60 V (black) data with Fano factor. The uncertainty band represents the minimum and maximum values from the different assumptions of Fano factor in the ionization model (F = 1e-4, 0.3), as well as from the systematic uncertainties propagated in the limit calculation. The references for this plot can be found at the bottom of this page.
31
Limits February 21st, 2020 png, pdf
png, pdf
Dark matter electron-recoil limit with FDM ∝ 1/q2 for the 100 V data

Dark matter electron-recoil FDM ∝ 1/q2 Poisson limits with the 90% unblinded 100 V (blue) and 60 V (black) data with Fano factor. The uncertainty band represents the minimum and maximum values from the different assumptions of Fano factor in the ionization model (F = 1e-4, 0.3), as well as from the systematic uncertainties propagated in the limit calculation. The references for this plot can be found at the bottom of this page.
32
Limits February 21st, 2020 png, pdf
png, pdf
Dark matter dark photon absorption limit for the 100 V data

Dark photon absorption Poisson limits with the 90% unblinded 100 V (blue) and 60 V (black) data with Fano factor. The uncertainty band represents the minimum and maximum values from the different assumptions of Fano factor in the ionization model (F = 1e-4, 0.3), as well as from the systematic uncertainties propagated in the limit calculation. The divergence of the 60V and 100V limit at high mass is because the 6th eh peak for the 60 V is out of the region of interest, and so limits are only calculated with the 5th peak. The references for this plot can be found at the bottom of this page.
33
Limits February 21st, 2020 png, pdf
png, pdf
Dark matter axion-like particle limit for the 100 V data

Axion-like particle Poisson limits with the 90% unblinded 100 V (blue) and 60 V (black) data with Fano factor. The uncertainty band represents the minimum and maximum values from the different assumptions of Fano factor in the ionization model (F = 1e-4, 0.3), as well as from the systematic uncertainties propagated in the limit calculation. The divergence of the 60V and 100V limit at high mass is because the 6th eh peak for the 60 V is out of the region of interest, and so limits are only calculated with the 5th peak. The references for this plot can be found at the bottom of this page.
34 Limits February 21st, 2020 png, pdf Absorption cross section

Real part of the complex conductivity, s1, as a function of photon energy for Si. The nominal curve follows the method used in Ref. [Y. Hochberg et al. Phys. Rev. D, 95:023013, 2017]. The upper and lower curves were determined using data from an extensive literature search, and applying analytic temperature reductions to estimate the photoelectric absorption cross section at the operating temperature of the detector. The references for this plot can be found at the bottom of this page.
35 Modeling February 21st, 2020 png, pdf Impact ionization model for the HVeV Run 2 detector.

Energy spectrum shape obtained from the modelization of impact ionization with a photon signal.
36 Modeling February 21st, 2020 png, pdf Trapping model for the HVeV Run 2 detector.

Energy spectrum shape obtained from the modelization of trapping with a photon signal.
37 Modeling February 21st, 2020 png, pdf Fit of the laser data with the trapping and impact ionization model

Top panel: Fit of the laser data with the trapping and impact ionization model. Bottom panel: Residuals between the data and the fit.
38
Data February 21st, 2020 png, pdf
png, pdf
Comparison between the HVeV Run 1 data and the HVeV Run 2 data.

This plot shows the comparison between the two spectra acquired during HVeV Run 1 and Run 2. The two histograms have the same binning to present the different structures. An additional point is added on top of each electron-hole pair in order to highlight the event rate contained in a 3 σ window around the peak (corresponding to the counts in the peak). Each point has a 3 σ uncertainty on the number of counts. The yellow curve represents the electron-recoil dark matter model with FDM ∝ 1/q2 with a mass of 1 GeV/c2 for an impact ionization of 2 % and for a trapping of 11 %. The uncertainty considers a trapping varing in the range 0 - 15 %.

 



References for Fig. 30 and 31:
  1. SuperCDMS HVeV R1
  2. R. Agnese, et al. First dark matter constraints from a SuperCDMS single-charge sensitive detector. Phys. Rev. Lett., 121:051301, 2018.
  3. DAMIC
  4. A. Aguilar-Arevalo, et al. Constraints on light dark matter particles interacting with electrons from DAMIC at SNOLAB. Phys. Rev. Lett., 123:181802, 2019.
  5. SENSEI
  6. O. Abramoff, et al. SENSEI: Direct-detection constraints on sub-GeV dark matter from a shallow underground run using a prototype skipper CCD. Phys. Rev. Lett., 122:161801, 2019.
  7. XENON10
  8. R. Essig, et al. Newconstraints and prospects for sub-GeV dark matter scattering off electrons in XENON. Phys. Rev. D, 96:043017,2017.
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  9. XENON1T
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References for Fig. 32 and 33:
  1. SuperCDMS Soudan
  2. T. Aralis, et al. Constraints on dark photons and axion-like particles from SuperCDMS Soudan, arXiv: 1911.11905, 2019.
  3. XENON10 and XENON100
  4. I. M. Bloch, et al. Searching for dark absorption with direct detection experiments. J. High Energy Phys., 2017:1029, 2017.
  5. SuperCDMS HVeV R1
  6. R. Agnese, et al. First dark matter constraints from a SuperCDMS single-charge sensitive detector. Phys. Rev. Lett., 121:051301, 2018.
  7. DAMIC
  8. A. Aguilar-Arevalo, et al. Constraints on light dark matter particles interacting with electrons from DAMIC at SNOLAB. Phys. Rev. Lett., 123:181802, 2019.
  9. SENSEI
  10. O. Abramoff, et al. SENSEI: Direct-detection constraints on sub-GeV dark matter from a shallow underground run using a prototype skipper CCD. Phys. Rev. Lett., 122:161801, 2019.
  11. Stellar constraints
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    M. M. Miller-Bertolami, et al. Revisiting the axion bounds from the galactic white dwarf luminosity function. JCAP, 1410:069, 2014.

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