PreprintPDF Available

Precision Measurement of the Specific Activity of 39^{39}Ar in Atmospheric Argon with the DEAP-3600 Detector

Authors:
Preprints and early-stage research may not have been peer reviewed yet.

Abstract and Figures

The specific activity of the beta decay of 39^{39}Ar in atmospheric argon is measured using the DEAP-3600 detector. DEAP-3600, located 2 km underground at SNOLAB, uses a total of (3269 ±\pm 24) kg of liquid argon distilled from the atmosphere to search for dark matter. This detector with very low background uses pulseshape discrimination to differentiate between nuclear recoils and electron recoils and is well-suited to measure the decay of 39^{39}Ar. With 167 live-days of data, the measured specific activity at the time of atmospheric extraction is [0.964 ±\pm 0.001 (stat) ±\pm 0.024 (sys)] Bq/kgatmAr_{\rm atmAr} which is consistent with results from other experiments. A cross-check analysis using different event selection criteria provides a consistent result.
Content may be subject to copyright.
Eur. Phys. J. C (2023) 83:642
https://doi.org/10.1140/epjc/s10052-023-11678-6
Regular Article - Experimental Physics
Precision measurement of the specific activity of 39Ar in
atmospheric argon with the DEAP-3600 detector
DEAP Collaborationa
P. Adhikari6,R.Ajaj
6,28, M. Alpízar-Venegas15, P.-A. Amaudruz26 ,J.Anstey
6,28, G. R. Araujo27,D.J.Auty
1,
M. Baldwin23, M. Batygov13 , B. Beltran1, H. Benmansour21 ,C.E.Bina
1,28, J. Bonatt21 , W. Bonivento10,
M. G. Boulay6, B. Broerman21, J. F. Bueno1, P. M. Burghardt27 , A. Butcher22 , M. Cadeddu10,B.Cai
6,28,
M. Cárdenas-Montes7, S. Cavuoti9,12, M. Chen21, Y. Chen1, S. Choudhary2,B.T.Cleveland
24,13 , J. M. Corning21,
R. Crampton6,28, D. Cranshaw21 , S. Daugherty24,13,6,P.DelGobbo
6,28, K. Dering21, P. Di Stefano21, J. DiGioseffo6,
G. Dolganov17, L. Doria20 , F. A. Duncan24 , M. Dunford6,28 , E. Ellingwood21 , A. Erlandson6,4, S. S. Farahani1,
N. Fatemighomi24,22, G. Fiorillo8,12, S. Florian21,A.Flower
6,21,R.J.Ford
24,13 , R. Gagnon21, D. Gallacher6,
P. García Abia7,S.Garg
6,P.Giampa
21,26 ,29, A. Giménez-Alcázar7, D. Goeldi6,28,V.V.Golovko
4,21, P. Gorel24,13,
K. Graham6, D. R. Grant1, A. Grobov17 , A. L. Hallin1, M. Hamstra6,21 , P. J. Harvey21, S. Haskins6,28, C. Hearns21,
J. Hu1, J. Hucker21 , T. Hugues2, A. Ilyasov17 ,18, B. Jigmeddorj24,13, C. J. Jillings24,13,A.Joy
1,28, O. Kamaev4,
G. Kaur6,A.Kemp
22,21 ,M.Ku´zniak2,6,28,F.LaZia
22,M.Lai
3,10, S. Langrock13,28, B. Lehnert14, A. Leonhardt27,
J. LePage-Bourbonnais6,28, N. Levashko17,18 , J. Lidgard21, T. Lindner26, M. Lissia10, J. Lock6, L. Luzzi7,
I. Machulin17,18 , P. Majewski23, A. Maru6,28, J. Mason6,28, A. B. McDonald21, T. McElroy1,T.McGinn
6,21,
J. B. McLaughlin22,26, R. Mehdiyev6, C. Mielnichuk1, L. Mirasola3,10 , J. Monroe22, P. Nadeau6, C. Nantais21,
C. Ng1, A. J. Noble21 , E. O’Dwyer21, G. Oliviéro6,28, C. Ouellet6,S.Pal
1,28, D. Papi1, P. Pasuthip21,
S. J. M. Peeters25, M. Perry6, V. Pesudo7, E. Picciau10,3,M.-C.Piro
1,28,T.R.Pollmann
27,13 ,21,30 ,F.Rad
6,28,
E. T. Rand4, C. Rethmeier6,F.Retière
26, I. Rodríguez García7, L. Roszkowski2,16, J. B. Ruhland27, R. Santorelli7,
F. G. Schuckman II21, N. Seeburn22, S. Seth6,28, V. Shalamova5, K. Singhrao1, P. Skensved21,N.J.T.Smith
24,13 ,
B. Smith26, K. Sobotkiewich6, T. Sonley24 ,6,28, J. Sosiak6,28, J. Soukup1, R. Stainforth6, C. Stone21, V. Strickland26,6,
M. Stringer21,28 , B. Sur4, J. Tang1, E. Vázquez-Jáuregui15, L. Veloce21,S.Viel
6,28, B. Vyas6, M. Walczak2,
J. Walding22, M. Ward21, S. Westerdale5, J. Willis1, A. Zuñiga-Reyes15
1Department of Physics, University of Alberta, Edmonton, AB T6G 2R3, Canada
2AstroCeNT, Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Rektorska 4, 00-614 Warsaw, Poland
3Physics Department, Università degli Studi di Cagliari, 09042 Cagliari, Italy
4Canadian Nuclear Laboratories, Chalk River, Ontario K0J 1J0, Canada
5Department of Physics and Astronomy, University of California, Riverside, CA 92507, USA
6Department of Physics, Carleton University, Ottawa, ON K1S 5B6, Canada
7Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain
8Physics Department, Università degli Studi “Federico II” di Napoli, 80126 Naples, Italy
9Astronomical Observatory of Capodimonte, Salita Moiariello 16, 80131 Naples, Italy
10 INFN Cagliari, 09042 Cagliari, Italy
11 INFN Laboratori Nazionali del Gran Sasso, 67100 Assergi, AQ, Italy
12 INFN Napoli, 80126 Naples, Italy
13 School of Natural Sciences, Laurentian University, Sudbury, ON P3E 2C6, Canada
14 Nuclear Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
15 Instituto de Física, Universidad Nacional Autónoma de México, A. P. 20-364, 01000 Mexico City, Mexico
16 BP2, National Centre for Nuclear Research, ul. Pasteura 7, 02-093 Warsaw, Poland
17 National Research Centre Kurchatov Institute, Moscow 123182, Russia
18 National Research Nuclear University MEPhI, Moscow 115409, Russia
19 Physics Department, Princeton University, Princeton, NJ 08544, USA
20 PRISMA+ Cluster of Excellence and Institut für Kernphysik, Johannes Gutenberg-Universität Mainz, Mainz 55128, Germany
21 Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6, Canada
22 Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX, UK
23 Rutherford Appleton Laboratory, Harwell Oxford, Didcot OX11 0QX, UK
24 SNOLAB, Lively, ON P3Y 1M3, Canada
25 University of Sussex, Sussex House, Brighton, East Sussex BN1 9RH, UK
26 TRIUMF, Vancouver, BC V6T 2A3, Canada
27 Department of Physics, Technische Universität München, Munich 80333, Germany
0123456789().: V,-vol 123
642 Page 2 of 10 Eur. Phys. J. C (2023) 83:642
28 Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6, Canada
29 Currently at SNOLAB, Lively, ON P3Y 1M3, Canada
30 Currently at Nikhef and the University of Amsterdam, Science Park 1098 XG, Amsterdam, The Netherlands
Received: 27 February 2023 / Accepted: 4 June 2023
© The Author(s) 2023
Abstract The specific activity of the βdecay of 39Ar in
atmospheric argon is measured using the DEAP-3600 detec-
tor. DEAP-3600, located 2km underground at SNOLAB,
uses a total of (3269 ±24) kg of liquid argon distilled from
the atmosphere to search for dark matter. This detector is
well-suited to measure the decay of 39Ar owing to its very
low background levels. This is achieved in two ways: it uses
low background construction materials; and it uses pulse-
shape discrimination to differentiate between nuclear recoils
and electron recoils. With 167 live-days of data, the mea-
sured specific activity at the time of atmospheric extraction
is (0.964 ±0.001stat ±0.024sys) Bq/kgatmAr , which is con-
sistent with results from other experiments. A cross-check
analysis using different event selection criteria and a differ-
ent statistical method confirms the result.
1 Introduction
Argon is used as a target material in a variety of existing
and future particle detectors [19]. Commercially available
argon is obtained by distillation from the Earth’s atmosphere
where it has a natural abundance of about 0.93% [10]. While
atmospheric argon primarily consists of the stable isotope
40Ar, trace amounts of cosmogenically created, radioactive
39Ar are also present and represent a background in low-
threshold detectors. The isotope 39Ar decays via unique first-
forbidden βdecay with a half-life of T1/2=(269 ±9)years
and a Q-value of (565 ±5) keV [1113].
While the production of 39Ar in the atmosphere is in equi-
librium, measurements of ice cores and tree rings by Gu
et al. [14] show the 39Ar/Ar ratio has varied by as much
as 17% in the past 2500 years. Recent measurements of
the specific activity of 39Ar in atmospheric argon, SAr39 ,
were realized by the WARP collaboration with a result of
SAr39 =(1.01±0.02stat ±0.08sys)Bq/kgatmAr [15] and by the
ArDM collaboration with SAr39 =(0.95 ±0.05)Bq/kgatmAr
[16].
This paper describes the measurement of the 39Ar spe-
cific activity using the DEAP-3600 detector [9], located
2 km underground in Creighton Mine at SNOLAB in Sud-
F. A. Duncan and T. McGinn: Deceased.
ae-mail: deap-papers@snolab.ca (corresponding author)
bury, Ontario, Canada. DEAP-3600 is a dark matter exper-
iment with a liquid argon (LAr) target which achieves low-
background levels due to both its use of low-background
construction materials and implementation of pulse-shape
discrimination (PSD). The PSD technique is able to differen-
tiate between nuclear recoils and electron recoils; it achieves
an expected leakage of electron recoil events into the dark
matter search region of interest of fewer than 1 event per year
of data. The large mass of atmospheric argon and the very
low background levels achieved with this experiment [17,18]
enable the precision specific activity measurement presented
here. The specific activity is calculated by estimating the total
number of 39Ar decays Nwithin a certain live-time Tlive as
shown in Eq. 1.
SAr39 =N
Tlive ·mLAr
,(1)
where mLAr is the mass of LAr in the detector.
A brief description of DEAP-3600 is provided in Sect. 2.
A dedicated estimate of the LAr mass in DEAP-3600 is pre-
sented in Sect. 3. The dataset and livetime calculation, as
well as the event selection are described in Sect.4. The mea-
surement of Nis presented in Sect. 5, alongside details on
the SAr39 calculation, the systematic uncertainties, and the
results. Section 6briefly describes an updated version of the
measurement from Ref. [19] which appears here as a cross-
check. Concluding remarks are given in Sect.7.
2 The detector and data acquisition system
The DEAP-3600 experiment operated an ultra-pure LAr tar-
get of over 3 tonnes held in a spherical acrylic vessel (AV)
with 85 cm radius from November 2016 to April 2020. The
atmospheric argon for the LAr target was procured from Air
Liquide.
Connected to the top of the AV is an acrylic neck surround-
ing a liquid nitrogen (LN2) filled stainless steel cooling coil
which condenses the gaseous argon (GAr) contained in the
top of the AV. The AV was partially filled with the GAr/LAr
interface approximately 55 cm above the equator. After fill-
ing with LAr the detector was sealed and this volume of argon
remained within the AV for the duration of data taking. Cool-
ing of the LAr was achieved by continuous circulation of LN2
within the cooling coil.
123
Eur. Phys. J. C (2023) 83:642 Page 3 of 10 642
Fig. 1 A cross-section of the DEAP-3600 detector components located
inside the water Cherenkov muon veto detector (not shown)
Coated on the inner surface of the AV is a layer of tetra-
phenyl butadiene (TPB). The TPB wavelength-shifts the
128 nm ultraviolet (UV) scintillation light from the LAr tar-
get into the visible spectrum with a peak at 420 nm [20]. This
light is detected by 255 photomultiplier tubes (PMTs) which
point inward and are optically coupled to the AV by acrylic
light guides. The PMTs are distributed in rings around the AV,
with the PMTs in each ring having the same vertical position.
The AV and PMTs are enclosed in a stainless steel shell which
is continuously flushed with radon-scrubbed nitrogen gas.
Installed on the outer surface of the shell are 48 PMTs which
point outward and, combined with the water held within a
cylindrical tank surrounding the shell, act as a muon veto
system. This muon veto system detects Cherenkov light pro-
duced by muon interactions within the water. A schematic of
the detector is shown in Fig.1.
Temperature sensors are placed around the AV at 85 loca-
tions along filler blocks which are mounted in the spaces
between the PMTs. The sensors are spread around the AV
and placed at distances of 0.9 m, 1.1 m, or 1.3 m from the
centre of the AV. These sensors, along with the temperature
and pressure within the LN2cooling system, are monitored
and logged using a slow control system.
Within the data acquisition system (DAQ) each PMT is
connected to a channel on a custom-built signal condition-
ing board (SCB) which achieves the high voltage decou-
pling and shapes the signals. The SCB outputs are trans-
mitted to high-gain (CAEN V1720) and low-gain (CAEN
V1740) waveform digitizers. These digitizers convert a con-
tinuous analogue signal to a discrete digital signal using
analogue-to-digital converters (ADCs). The summed input
from each SCB is also passed to a digitizer and trigger mod-
ule (DTM) which resolves the trigger criteria based on two
rolling charge integrals: a narrow integral Qnover a 177 ns
window and a wide integral Qwover a 3.1 μs window. The
promptness of the signal is computed by the Qn/Qwfrac-
tion. Five trigger regions are defined based on these three
variables. A prescaling factor of 100 is applied to events
in the energy range of Qn≈[50,565]keVee in the low
Qn/Qwregion. This prescaling predominantly affects 39Ar
decays and reduces the available statistics by storing only
the observed PMT waveforms for precisely 1 out of every
100 events. In a 24h period, roughly 2.7×10639
Ar events
remain after the prescaling. The timestamp of every event,
included those which are prescaled, is recorded in the data.
The DTM makes the decision to trigger based on the
summed value of Qnfrom all 255 PMTs and sends a trig-
ger signal to the digitizers if this value passes a threshold of
19 PE. Each digitizer channel records PMT waveforms for
16 μs upon receiving a trigger signal, including a pre-trigger
window of 2.4μs. The data acquisition system is operated by
MIDAS [21] and the data are analyzed with RAT [22], a soft-
ware framework built on Geant4 [23] and ROOT [24]. The
observed charge in each PMT is integrated over a window
of [28, 10000] ns relative to the event time. This charge
is divided by the single photoelectron (PE) charge for each
PMT measured through independent calibration [25]. The
resulting PE number provides the energy estimator for the
data. The PSD variable Fprompt distinguishes nuclear recoil
events at high Fprompt from 39Ar decays and electron recoil
backgrounds (ERB) at low Fprompt. For this measurement it
is defined as the fraction of PE detected in a time window of
[28, 150] ns around the event time and is calculated as
Fprompt =150 ns
t=−28 ns PE(t)
10 μs
t=−28 ns PE(t)
.(2)
The ERB is composed of events generated by both γ-rays
emitted by trace radioactivity in detector components and
β-decays which scatter on electrons in the LAr.
A more detailed description of the DEAP-3600 detector
can be found in Ref. [9].
3 Liquid argon mass estimate
The LAr mass is determined by evaluating both its den-
sity and its volume within the AV. This method previously
resulted in a LAr mass of (3279 ±96)kg [17]. That result
has been refined for this work.
Two inputs are required to evaluate the volume of LAr in
the detector: the AV radius and the LAr height within the AV.
123
642 Page 4 of 10 Eur. Phys. J. C (2023) 83:642
The internal radius of the AV was measured during its con-
struction. After correcting for the thermal contraction that
occurred during cool-down using a temperature-dependent
coefficient measured in Ref. [26] the AV radius is determined
to be (845.6 ±0.9) mm. The LAr height is measured by tak-
ing advantage of the total internal reflection of the UV light at
the GAr/LAr interface. The TPB re-emits light isotropically
and so the photon detection rates for each PMT depend on
the area of visible TPB immersed in the LAr. The rates for
every PMT ring are averaged and the distribution is fit with
an analytic model of the corresponding immersed area. This
method is validated by comparing the data to Monte Carlo
simulations of 39Ar decays within the LAr while varying the
simulated LAr height. The best fit is found at a LAr height
of (550 ±10)mm above the equator and is stable across the
dataset. The systematic uncertainty on the LAr height is the
dominant source of uncertainty for the LAr mass estimate.
A cross-check using the position reconstruction of detected
events to evaluate the LAr height provides a consistent result.
In this cross-check, a template fit in the reconstructed verti-
cal position of 39Ar decay events is performed by comparing
simulations with different LAr height values to the data his-
togram.
The LAr density is a function of its temperature. This
temperature is constrained by the liquid–vapor transition of
the argon in the AV and by the liquid–vapor transition of the
nitrogen in the cooling coil. As the pressure in both systems is
constantly recorded, the average LAr temperature is known
within a few degrees K, and thus the effective density can be
established to 0.5% precision.
The possibility of argon bubbles is also investigated, the
presence of which would reduce the total mass of LAr. Using
the behavior of nitrogen as a reference [27] a limiting case
is considered where all of the exterior heat entering the LAr
creates bubbles. This worst-case scenario indicates that at
most 6.3 kg of LAr is displaced by bubbles.
A toy Monte Carlo sampling the probability distribution
functions (PDFs) of the AV radius, the LAr height, the LAr
density, and bubble displacement is used to determine the
central value of the LAr mass and its uncertainty. Flat PDFs
are used for the constraints on the LAr density and the bubble
displacement, while the AV radius and LAr height PDFs are
considered Gaussian. According to this method, during the
data-taking period of this measurement the DEAP-3600 AV
contained mLAr =(3269 ±24)kg of LAr.
4 Data selection and livetime calculation
4.1 Run selection
The dataset is divided into discrete runs during which signals
from the LAr are recorded. A single run is typically about
22 h long, though this can vary between just a few minutes
and up to about 2 days. The runs examined here are from
the same 2016-2017 dataset used for the dark matter search
published by the DEAP collaboration [17] with the additional
restriction that runs are at least 18 h long. This requirement is
imposed to ensure sufficient statistics to fit the γ-dominated
region of the ERB spectrum in each run.
The selection of runs is based on stability criteria con-
cerning the cooling system of the AV, the charge distribu-
tions in the PMTs, and the efficiency of the trigger. A data
cleaning cut is applied to each run to reject events occurring
within δtcut =32 μs of the previous event, which removes
δti32μs of livetime per event i; the total number of events
removed by this cut is NDCcut . Low-level cuts are then applied
to reject events recorded from pulse injections by periodic
monitoring triggers and events with inconsistent data acqui-
sition readouts such as busy signals, for a total of NLLcut
events. The events removed by these cuts, along with all
remaining physics triggers Nphys , are taken into account in
the run-dependent livetime calculation shown in Eq.3.
Tlive =Trun NDCcut
i=1δtiNLLcut ·δtcut
Nphys ·tcut δtint ). (3)
Here, Tlive is the livetime for a run, Trun is the total time of that
run, and δtint =10 μs corresponds to the charge integration
window during which the detector can record a pile-up event,
while the time between δtint and δtcut is dead time. The value
of Nphys includes the prescaled triggers as the timestamp of
each of these events is stored. Testing of the algorithm was
performed using values of δtcut ranging from 20 μsupto
250 μs for a selection of data runs. For each δtcut value the
livetime and specific activity of each run were calculated. We
observed negligibly small variations in the measured specific
activity as a function of δtcut, as expected.
An offline reduction is applied where precisely 1 out of
every 100 events from outside the prescaled trigger region is
kept in order to remove boundary effects and obtain a smooth
spectrum.
4.2 Event selection
In addition to the data cleaning and low-level cuts described
in the previous section, event selection cuts are applied. Pile-
up needs to be taken into account given the high rate of 39Ar
decays and the length of the event window: approximately
5% of recorded events are expected to contain 2 or more
decays. Additionally, a triggered event can follow an energy
deposit which occurred during time in which DAQ was busy
and unable to record (deadtime). The late scintillation light
from this previous, unrecorded energy deposit can reach into
the beginning of the triggered event. Since the full energy
of the previous energy deposit is not visible in the digitized
123
Eur. Phys. J. C (2023) 83:642 Page 5 of 10 642
trace, this type of pile-up is hard to model. While this analysis
endeavours to keep pile-up events and account for them in
the specific activity calculation, events with this pre-trigger
pileup are not suitable analysis candidates.
To select events without pre-trigger pile-up the time at
which the event occurred within the trigger window must be
in the range [2250, 2700] ns, and it is required that fewer
than 4 pulses are recorded by the PMTs in the first 1600 ns
of the event. These cuts do not remove a significant number
of events, and the majority of the events removed are at very
low energies. These removed events are mainly outside the
range of the fits described in Sect. 5.1.
Electron recoil events, which are dominated by 39Ar
decays at lower energies and γbackgrounds at higher ener-
gies, are selected with the requirement 0.1 Fprompt 0.5.
These events, along with 39Ar-39Ar pileup events and 39Ar
signal events, are shown in Fig.2. A more in-depth discussion
of the electron recoil events can be found in Ref. [18].
This analysis also makes use of a peak-finding algorithm
based which examines the PMT waveforms to count the num-
ber of “sub-events” within the trigger window. The algorithm
counts pulses from each PMT in the event window to look
for statistically significant increases in the pulse count and
is able to identify sub-events separated by as little as 50 ns.
When tested using MC the algorithm was able to correctly
identify 96% of 39Ar-39Ar pile-up events, and only 0.1%
of single 39Ar were incorrectly identified as having multiple
sub-events. The number of sub-events is used to select pile-up
candidates in order to perform a data-driven estimate of the
double 39Ar pile-up cut efficiency as described in Sect. 5.2.
5 Specific activity measurement
The specific activity of 39Ar is measured individually for
each run in the dataset. Each measurement is based on a fit
to the low Fprompt energy spectrum and consists of an 39Ar
β-decay spectrum (single 39Ar), a spectrum with two 39 Ar
decays occurring within the same trigger window (double
39Ar pile-up), and a spectrum containing all non-39 Ar ERB
events scaled to the activities measured in Ref. [18]. The
ERB and double 39Ar pile-up input spectra are generated by
simulating events within the DEAP-3600 detector using the
RAT software. The single 39Ar component is built directly
from the theoretical model provided by Kostensalo et al. [28].
Each of the three model components is normalized using a
parameter in the fits. Energy scale PE and detector resolution
effects σ(PE) in the form of a Gaussian term are applied to
all three model components, parameterized as
PE =p0+p1·E+p2·E2,
σ(PE)=p3·PE +p4·PE2.
(4)
The constant energy scale parameter p0is fixed in the fits to
a value obtained by measuring PMT baselines. The number
of 39Ar decays is split into two main components as
N=Nsingle +Npileup,(5)
with the number of single 39Ar decays Nsingle and the number
of 39Ar decays which are part of a pile-up event Npileup.The
latter number includes double 39Ar decays, triple 39 Ar decays
(three 39Ar decays in one trigger window), pile-up of 39Ar
decays with ERB decays, and pile-up of 39Ar decays with
high Fprompt events (Fprompt >0.5).
5.1 Fitting the energy spectrum
This analysis uses Minuit in ROOT [29] to fit the three input
spectra to data. The fit performs a chi-square minimization
as
χ2=
nb
iMiDi
Mi2
+P,(6)
with the number of bins nbin the data histogram, the data con-
tent Diin bin iand the model contribution Mi. The parameter
Pis a penalty term applied to a shape nuisance parameter a0,
which corrects the theoretical 39Ar input spectrum linearly
in energy to fit the data; it is constructed to account for the
differences a0=0.01 observed between the Kostensalo et
al. [28] and the Behrens and Janecke [30]39Ar β-shapes and
is calculated as
P=a0
a0
.(7)
The closer a0is to zero, the more the spectrum fits the shape
by Kostensalo et al. The fit model is adapted from the model
used for the energy response fits in Ref. [17].
The fit range for this measurement is [200, 11000] PE and
is chosen to avoid trigger efficiency effects at low PE and to
provide a handle for the fit to scale ndouble and nERB beyond
the 39Ar endpoint at high PE. This range includes the 40 Kγ-
emission peak at 1460 keV [18] (approximately 10,500 PE)
and allows the ERB spectrum normalization to be determined
in the fit. This analysis is performed with nbcorresponding
toabinwidthofb=20 PE which was chosen to provide
sufficient statistics to define the 40K peak. The 39 Ar β-shape
nuisance parameter is an output of the fit. Details of the fit
inputs and outputs are provided in Table 1, along with the
other parameter values taken as input to the specific activity
measurement. Figure 2shows an example fit using this model
for one data run. The parameters from each fit are examined
to look for trends across the dataset and for issues such as
getting stuck at the boundaries of their allowed ranges: no
such issues are observed.
123
642 Page 6 of 10 Eur. Phys. J. C (2023) 83:642
Tabl e 1 Parameters, their values and constraints, and the resulting con-
tributions to the uncertainty for the specific activity measurement. Neg-
ligibly small systematic uncertainties are indicated with ‘–’. The domi-
nant uncertainty on SAr39 arises from the uncertainties on event selection
cut efficiency values as determined with the data-driven method (d-d)
and the Monte Carlo method (MC)
Parameter Symbol Value Constraints Absolute uncertainty
on SAr39
[Bq/kgatmAr]
Fit range [200, 11000] PE Fixed 0.001
Histogram bin width b20 PE Fixed 0.001
Constant energy scale parameter p0(1.3±0.4)PE Fixed
Linear energy scale term p1[7.1, 7.3] PE/keV Free-floating, run-dependent 0.009
Quadratic energy scale term p2 Not considered in this method
Linear resolution parameter p3[1.67, 1.73] PE Free-floating, run-dependent 0.009
Quadratic resolution parameter p4[2.1, 3.8] ×104Free-floating, run-dependent 0.001
39Ar β-shape nuisance parameter a0Free-floating, constrained 0.001
by a penalty term
39Ar normalization nFree floating, run-dependent
Double 39Ar pile-up normalization ndouble Free floating, run-dependent
ERB normalization nERB Free-floating, run-dependent
85Kr normalization nKr85 Upper limit, see Sect. 5.2 0.010
Liquid argon mass mLAr (3269 ±24)kg Measured, see Sect. 30.007
Live-time Tlive 167 d [sum of all runs] Measured, see Sect. 4
Cut efficiency on single 39Ar ε0.983 [d–d], 0.999 [MC]
Measured, see Sect. 5.2 0.016
Cut efficiency on double 39Ar pile-up εdouble Run- & energy-dependent
Fig. 2 The top panel shows an example fit on one run including the
39Ar, ERB, and 39Ar pile-up components which form the fit function.
The fit range from 200–11,000 PE is shown by the vertical dashed lines.
The bottom panel shows the residual between the fit function and data
normalized to the square root of the contents in the observed PE distri-
bution. The fit is extrapolated below the lower bound to count events
in the low-energy region where the trigger efficiency is not 100%. The
slight mismodelling of the ERB spectrum as apparent in the residual
plot does not significantly affect the final result. The reduced chi-square
for this run is given by χ2/ndf =687.42/531 =1.29. The run shown
here is approximately 28.5h long
5.2 Calculating the specific activity
The number of 39Ar single decays Nsingle is obtained from
the single 39Ar spectrum fit result integral nas
Nsingle =n·apresc
ε·b,(8)
with the bin width bof the fitted data histogram, a trigger
prescaling correction factor apresc =100 and the cut effi-
ciency ε. The main, data-driven method used to estimate this
cut efficiency involves defining a loose event selection for
the denominator spectrum of events present before the cuts
with an Fprompt <0.7 requirement; this loose event selection
removes the unwanted Cherenkov and nuclear recoil events.
The numerator spectrum for the efficiency calculation con-
tains those events which pass the selection cuts described in
Sect. 4.2.
First, the efficiency εlowerPE is calculated over the range
[300, 3000] PE, which is dominated by single 39Ar events, by
taking the ratio of the two spectra bin-by-bin. Then, to extract
the efficiency εfor single 39Ar events, a correction is applied
to εlowerPE to account for the presence of double 39Ar pile-up
in the sample. The cut efficiency εdouble is calculated bin-
by-bin in the PE histogram of each run over the range [300,
3000] PE with an additional event selection requirement for
123
Eur. Phys. J. C (2023) 83:642 Page 7 of 10 642
the numerator and denominator spectra to select events which
contain exactly two sub-events. The efficiency for single 39Ar
events is calculated bin-by-bin by next solving for εiusing
the bin-dependent εlowerPE and εdouble values in the following
equation as
εlowerPE,i=εi·xi+εdouble,i·(1xi), (9)
where xiis the fraction of single 39Ar events measured by the
fits in bin i. The value for εis then calculated as the average
of the εivalues as any energy dependence here is negligible.
The resulting data-driven value of εis calculated run-by-run
and each value is used in the calculations for its respective
run. The average εis 0.983.
As a cross-check to this data-driven method, the cut effi-
ciency values are evaluated using the Monte Carlo simu-
lated samples of the 39Ar decays and the double 39 Ar pile-up
described earlier. While the simulations do not describe the
data perfectly, this method yields clean spectra of these two
event classes which can be individually analyzed. With the
Monte Carlo method εMC =0.999. We evaluate the specific
activity SAr39 using both εand εMC as inputs to Eq. 8and
take the difference as a systematic uncertainty. This differ-
ence is the dominant source of systematic uncertainty for this
measurement.
The number of 39Ar decays that are part of pile-up events
is split into the different components as
Npileup =Ndouble +Ntriple +NERB,Ar39 +NhFp,Ar39.
(10)
Here, Ndouble is the number of 39Ar decays that are part of
a double 39Ar pile-up event, Ntriple is the number of 39 Ar
decays that are part of a triple pile-up event, NERB,Ar39 is the
number of 39Ar decays which pile-up with a ERB recoil, and
NhFp,Ar39 is the number of 39Ar decays which pile-up with
ahighFprompt process such as Cherenkov light or a nuclear
recoil. Ndouble is obtained from the double 39Ar spectrum fit
result integral ndouble as
Ndouble =ndouble ·apresc
εdouble ·b·2.(11)
Here, εdouble is the cut efficiency on double 39Ar pile-up
events described above, and the factor 2 corrects for 2 39Ar
decays in 1 double pile-up event. The energy-dependence of
εdouble over the wider range of the pile-up spectrum is taken
into account by applying this correction bin-by-bin.
Ndouble is utilized to calculate the single 39Ar rate RAr39
from a first-order pile-up calculation as shown in Eq.12.
RAr39 =Ndouble
2·Tlive ·δtint
.(12)
RAr39 is used to determine the remaining pile-up components
which are estimated with first-order pile-up approximations
as
Ntriple =3·R3
Ar39 ·δt2
int ·Tlive,
NERB,Ar39 =RAr39 ·RERB ·δtint ·Tlive,
NhFp,Ar39 =RAr39 ·RhFp ·δtint ·Tlive,
(13)
where the factor of 3 in Ntriple accounts for the 3 39 Ar decays
in each of these pile-up events. The ERB rate RERB =(10.5±
0.6)Hz and the high Fprompt rate RhFp =(270 ±3)Hz are
established from the fit output nERB and from the rate of
events observed in the high Fprompt window in the dataset,
respectively. The pile-up rates can be calculated by dividing
the quantities in Eq. 13 by Tlive.
Beyond the ERB measured in Ref. [18], the dataset con-
sidered in this analysis may contain a small number of 85Kr
β-decay events. The 85Kr beta spectrum has an endpoint
energy of 687.0 keV; this is in the region dominated by the
double 39Ar pileup events. Uncertainty in the amplitude of
a peak at 600.66 keV from the 226Ra chain makes obtain-
ing the 85Kr from fitting the energy spectrum challenging.
The 85Kr activity is studied a posteriori by repeating the fit
including the 85Kr β-shape from Ref. [31] with a normaliza-
tion parameter nKr85, while also varying the energy response
parameters and the 39Ar endpoint within their uncertainties.
No cuts are made to remove the double 39Ar pileup so that
both the nominal fits and the fits including a 85Kr spectrum
are performed on the same data. These fit results suggest that
at most 0.01 Bq/kgatmAr of 85Kr is present in our dataset.
This limit is considered as an additional source of systematic
uncertainty.
5.3 Results
The specific activity of 39Ar is evaluated for each run by
combining Eqs. 8,11 and 13 with Eq. 1. The run-by-run
results are presented in Fig. 3which includes an exponential
fit to the measured specific activity over time. This fit is used
to determine the specific activity value at the start of the
dataset.
Uncertainties due to the liquid argon mass estimate and
related to the determination of cut efficiencies were discussed
in Sects. 3and 5.2 respectively. Additional systematic uncer-
tainties on the specific activity measurement are evaluated
as follows. For each run, the fit is repeated with the lin-
ear energy scale parameter p1fixed to its central value for
that run plus or minus 0.15 PE/keV. The uncertainties on the
other energy scale and resolution parameters p0,p3and p4
are likewise propagated to the measurement by repeating the
fits with fixed parameters set according to their uncertainties
determined in the energy response measurement described
123
642 Page 8 of 10 Eur. Phys. J. C (2023) 83:642
in Ref. [17]. Uncertainties due to the choice of the histogram
bin width (varied to 10 PE and to 40 PE) and the choice of
the fit range (lower bound increased to 500 PE) are evalu-
ated in a similar manner. Theoretical β-shape uncertainties
are accounted for by repeating the fit with a0fixed to 0, and
then fixed to the median value found over the entire dataset.
The systematic uncertainty due to the ERB normalization is
negligible, and so any systematics associated with the MC
generation of the spectra used in the fits is similarly negligi-
ble. Optical model uncertainties within the MC do not affect
the pile-up spectrum shape used in the fits. The systematic
uncertainty due to the double 39Ar pile-up spectrum shape
and normalization are negligible. The impact of each source
of systematic uncertainty on the result is detailed in Table 1.
The statistical uncertainty of 0.001 Bq/kgatmAr shown in
Fig. 3is calculated by propagating the uncertainties on the
ERB and the high Fprompt background rates, and the fit uncer-
tainties on the single 39Ar and the double 39 Ar pile-up nor-
malization parameters. The fit uncertainty of the 39Ar spec-
trum dominates the statistical uncertainty.
A correction is applied to the measured specific activity
determined from the exponential fit to account for the age of
the argon. The correction factor is calculated as
ηt=2ˆ(tage/T1/2), (14)
where tage =(1.0±0.5) y is the average time between atmo-
spheric extraction of the argon and the start of the data-taking
period. Multiplying by ηtcorrects for the approximately
0.26 % drop in the activity before data were taken. Cosmo-
genic activation of 39Ar during the time after the argon was
extracted from the atmosphere is negligible.
The specific activity of 39Ar in atmospheric argon is mea-
sured to be
SAr39 =(0.964 ±0.001stat ±0.024sys)Bq/kgatmAr .
6 Cross-check analysis
Here we present a cross-check to our result which is an update
of an earlier analysis, the details of which are described in
Ref. [19]. This analysis used the Bayesian Analysis Toolkit
(BAT) [32] software to fit the input spectra to the data
and extract the model parameters. BAT uses Markov Chain
Monte Carlo to generate posterior probability distributions
of the fit parameters based on prior probability distributions
and a likelihood function input by the user. This cross-check
also differs from the analysis presented in previous sections
by applying a different set of event selection cuts than those
described in Sect. 4.2. A cut on the event time within the trig-
ger window was not applied, and the peak-finding algorithm
Fig. 3 The measured specific activity of 39Ar versus run time for the
entire dataset. The exponential trendline fit is shown, with the average
statistical uncertainty depicted as an error band. The systematic uncer-
tainty band is wider than the y-axis range shown here
to count “sub-events” was used to remove the majority of
pileup events. The data cleaning cut to remove events close
in time to a previous event was not applied. Otherwise, the
same criteria described in Sect. 4were applied and a fit was
performed on each run in the dataset.
The detector response model in the fit included a constant
energy scale parameter p0, a linear energy scale parameter
p1, a quadratic energy scale parameter p2, and a linear reso-
lution parameter p3. The quadratic resolution parameter p4
was not considered in these fits. The p1,p2, and p3model
parameters were given flat priors in the fits and allowed to
float. The p0parameter was fixed in the fits.
The nominal input 39Ar spectrum used was from Behrens
and Janecke [30]. Each fit returned the normalization of this
spectrum and was given a flat prior. In addition to the 39Ar
spectrum, the inputs to the fit were an ERB spectrum and an
MC-generated spectrum of double 39Ar pileup events which
survive the cuts. Each fit returned the normalization param-
eters for these spectra; at the input stage these were given
Gaussian priors with a mean value of 1, which corresponded
to a normalization based on an assumed event rate and the
known runtime. All three normalization parameters were
allowed to float in the fits, and the posterior values were used
to calculate the 39Ar specific activity. The single 39Ar events
counted through the fit outputs of this cross-check method
and that described in Sect. 5.1 do not differ significantly. An
additional set of fits was performed using the Kostensalo et
al. spectrum [28]. The measured specific activity differed by
a negligible amount between these fits and those using the
nominal spectrum.
The result in Ref. [19] has been updated here to include the
updated LAr mass, the new data-driven cut efficiency esti-
mates, the revised livetime calculation, and the correction for
the age of the argon. This method yields the following value
123
Eur. Phys. J. C (2023) 83:642 Page 9 of 10 642
Tabl e 2 Summary of specific activity measurements of 39 Ar by differ-
ent collaborations
Measurement Specific activity [Bq/kgatmAr ]
WA R P [ 15]1.01±0.02stat ±0.08sys
ArDM [16]0.95±0.05
DEAP-3600 (this work) 0.964 ±0.001stat ±0.024sys
for the specific activity of 39Ar at the time of atmospheric
extraction: (0.97 ±0.001stat ±0.03sys)Bq/kgatmAr .
7 Conclusion
A measurement of the specific activity of 39Ar in atmospheric
argon using the LAr target of the DEAP-3600 detector has
been presented. This result is the most precise measure-
ment of the specific activity of 39Ar in atmospheric argon
to date and agrees with existing measurements which are
summarized in Table 2. The high precision of this mea-
surement is owing to a combination of factors including the
low-background nature of DEAP-3600, the large number of
decays observed in each data run, and the precise measure-
ment of the LAr target mass. The statistical uncertainties
here are much smaller than the systematic uncertainties due
to the high statistics of the data. The dominant systematic
uncertainties arise from the event selection cut efficiencies,
the energy scale and energy resolution parameters, and the
possible presence of 85Kr within the LAr.
This precision measurement is an important input to the
background models of experiments operating with argon as
a medium. It will benefit current experiments, help to inform
the design of future detectors, and support measurements in
radiometric dating which use the 39Ar/Ar ratio as an input.
Acknowledgements We thank the Natural Sciences and Engineer-
ing Research Council of Canada (NSERC), the Canada Founda-
tion for Innovation (CFI), the Ontario Ministry of Research and
Innovation (MRI), and Alberta Advanced Education and Technol-
ogy (ASRIP), the University of Alberta, Carleton University, Queen’s
University, the Canada First Research Excellence Fund through the
Arthur B. McDonald Canadian Astroparticle Physics Research Insti-
tute, Consejo Nacional de Ciencia y Tecnología Project No. CONA-
CYT CB-2017-2018/A1-S-8960, DGAPA UNAM Grants No. PAPIIT
IN108020 and IN105923, and Fundación Marcos Moshinsky, the Euro-
pean Research Council Project (ERC StG 279980), the UK Sci-
ence and Technology Facilities Council (STFC) (ST/K002570/1 and
ST/R002908/1), the Leverhulme Trust (ECF-20130496), the Russian
Science Foundation (Grant No. 21-72-10065), the Spanish Ministry
of Science and Innovation (PID2019-109374GB-I00) and the Com-
munity of Madrid (2018-T2/ TIC-10494), the International Research
Agenda Programme AstroCeNT (MAB/2018/7) funded by the Foun-
dation for Polish Science (FNP) from the European Regional Devel-
opment Fund, and the European Union’s Horizon 2020 research and
innovation program under grant agreement No 952480 (DarkWave).
Studentship support from the Rutherford Appleton Laboratory Particle
Physics Division, STFC and SEPNet PhD is acknowledged. We thank
SNOLAB and its staff for support through underground space, logisti-
cal, and technical services. SNOLAB operations are supported by the
CFI and Province of Ontario MRI, with underground access provided by
Vale at the Creighton mine site. We thank Vale for their continuing sup-
port, including the work of shipping the acrylic vessel underground. We
gratefully acknowledge the support of the Digital Research Alliance of
Canada, Calcul Québec, the Centre for Advanced Computing at Queen’s
University, and the Computational Centre for Particle and Astrophysics
(C2PAP) at the Leibniz Supercomputer Centre (LRZ) for providing the
computing resources required to undertake this work.
Data Availability Statement This manuscript has no associated data or
the data will not be deposited. [Authors’ comment: The data used in this
paper requires approximately 150 TB of disk space and its interpretation
requires an extensive understanding of the detector. Therefore, making
the data publicly available is impractical. Access to the data may be
granted on request to the DEAP collaboration.]
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adaptation,
distribution and reproduction in any medium or format, as long as you
give appropriate credit to the original author(s) and the source, pro-
vide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article
are included in the article’s Creative Commons licence, unless indi-
cated otherwise in a credit line to the material. If material is not
included in the article’s Creative Commons licence and your intended
use is not permitted by statutory regulation or exceeds the permit-
ted use, you will need to obtain permission directly from the copy-
right holder. To view a copy of this licence, visit http://creativecomm
ons.org/licenses/by/4.0/.
Funded by SCOAP3.SCOAP
3supports the goals of the International
Year of Basic Sciences for Sustainable Development.
References
1. G. Fiorillo, Nucl. Phys. B Proc. Suppl. 150, 372 (2006). https://
doi.org/10.1016/j.nuclphysbps.2004.10.091
2. G. Aad et al. (ATLAS Collaboration), Eur. Phys. J. C 70, 723
(2010). https://doi.org/10.1140/epjc/s10052-010- 1354-y
3. P.D. Meyers et al. (DarkSide Collaboration), Phys. Proc. 61, 124
(2015). https://doi.org/10.1016/j.phpro.2014.12.021
4. C.E. Aalseth et al. (DarkSide-20k Collaboration), Eur. Phys. J. Plus
(2018). https://doi.org/10.1140/epjp/i2018-11973- 4
5. M. Agostini et al., Eur. Phys. J. C 75, 506 (2015). https://doi.org/
10.1140/epjc/s10052- 015-3681- 5
6. P. Abratenko et al. (MicroBooNE Collaboration), Phys. Rev.
Lett. 130, 011801 (2023). https://doi.org/10.1103/PhysRevLett.
130.011801
7. B. Abi et al. (DUNE Collaboration), J. Instrum. 15(12), P12004
(2020). https://doi.org/10.1088/1748-0221/15/ 12/P12004
8. B. Abi et al. (DUNE Collaboration), J. Instrum. 15(08), T08008
(2020). https://doi.org/10.1088/1748-0221/15/ 08/T08008
9. P.-A. Amaudruz et al. (DEAP Collaboration), Astropart. Phys. 108,
1 (2019). https://doi.org/10.1016/j.astropartphys.2018.09.006
10. A.N. Cox (ed.), Allen’s Astrophysical Quantities,4th
edn. (Springer, New York, 2001). https://doi.org/10.1007/
978-1- 4612-1186-0
11. H. Loosli, Earth Planet. Sci. Lett. 63(1), 51 (1983). https://doi.org/
10.1016/0012-821X(83)90021-3
12. R.W. Stoenner, O.A. Schaeffer, S. Katcoff, Science 148(3675),
1325 (1965). https://doi.org/10.1126/science.148.3675.1325
123
642 Page 10 of 10 Eur. Phys. J. C (2023) 83:642
13. M. Wang et al., Chin. Phys. C 36(12), 003 (2012). https://doi.org/
10.1088/1674-1137/36/12/003
14. J.-Q. Gu et al., Chem. Geol. 583, 120480 (2021). https://doi.org/
10.1016/j.chemgeo.2021.120480
15. P. Benetti et al. (WARP Collaboration), Nucl. Instrum. Methods
Phys. Res. A 574(1), 83 (2007). https://doi.org/10.1016/ j.nima.
2007.01.106
16. J. Calvo et al. (ArDM Collaboration), J. Cosmol. Astropart. Phys.
2018(12), 011 (2018). https://doi.org/10.1088/1475-7516/2018/
12/011
17. R. Ajaj et al. (DEAP Collaboration), Phys. Rev. D 100, 022004
(2019). https://doi.org/10.1103/PhysRevD.100.022004
18. R. Ajaj et al. (DEAP Collaboration), Phys. Rev. D 100, 072009
(2019). https://doi.org/10.1103/PhysRevD.100.072009
19. M. Dunford, A search for the neutrinoless double electron cap-
ture of 36Ar and a measurement of the specific activity of 39 Ar
in atmospheric argon with the DEAP-3600 Detector. Ph.D. thesis,
Carleton University, Department of Physics (2018). https://doi.org/
10.22215/etd/2018- 13483
20. R. Francini, R.M. Montereali, E. Nichelatti, M.A. Vincenti, N.
Canci, E. Segreto, F. Cavanna, F.D. Pompeo, F. Carbonara, G. Fio-
rillo, F. Perfetto, J. Instrum. 8(09), C09010 (2013). https://doi.org/
10.1088/1748-0221/8/09/C09010
21. T. Lindner, J. Phys. Conf. Ser. 664(8), 082026 (2015). https://doi.
org/10.1088/1742- 6596/664/8/ 082026
22. T. Bolton et al., RAT (is an Analysis Tool) User’s Guide (2018).
https://rat.readthedocs.io/en/ latest/
23. S. Agostinelli et al. (GEANT4 Collaboration), Nucl. Instrum.
Methods Phys. Res. A 506(3), 250 (2003). https://doi.org/10.1016/
S0168-9002(03)01368- 8
24. R. Brun, F. Rademakers, Nucl. Instrum. Methods Phys.
Res. A 389(1), 81 (1997). https://doi.org/10.1016/
S0168-9002(97)00048- X
25. P.-A. Amaudruz et al. (DEAP Collaboration), Nucl. Instrum. Meth-
ods Phys. Res. A 922, 373 (2019). https://doi.org/10.1016/ j.nima.
2018.12.058
26. G. Hartwig, Polymer Properties at Room and Cryogenic Temper-
atures (Plenum Press, New York, 1994). https://doi.org/10.1007/
978-1- 4757-6213-6
27. N. Fdida et al., ILASS—Europe 2010, 23rd Annual Conference
on Liquid Atomization and Spray Systems (2010). https://api.
semanticscholar.org/CorpusID:59934048
28. J. Kostensalo, J. Suhonen, K. Zuber, J. Phys. G Nucl. Phys. 45(2),
025202 (2018). https://doi.org/10.1088/1361-6471/aa958e
29. F. James, M. Winkler. MINUIT User’s Guide (2004). https://
inspirehep.net/literature/1258345
30. H. Behrens, J. Jänecke, in “Numerical Tables for Beta-
Decay and Electron Capture” in SpringerMaterials, ed. by
H. Schopper (Springer, Berlin, 1969). https://doi.org/10.1007/
10201072_3.https://materials.springer.com/lb/docs/sm_lbs_
978-3- 540-36068-1_3
31. S.J. Haselschwardt, J. Kostensalo, X. Mougeot, J. Suhonen, Phys.
Rev. C 102, 065501 (2020). https://doi.org/10.1103/PhysRevC.
102.065501
32. A. Caldwell, D. Kollár, K. Kröninger, Comput. Phys. Commun.
180(11), 2197 (2009). https://doi.org/10.1016/j.cpc.2009.06.026
123
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
We present a search for eV-scale sterile neutrino oscillations in the MicroBooNE liquid argon detector, simultaneously considering all possible appearance and disappearance effects within the 3+1 active-to-sterile neutrino oscillation framework. We analyze the neutrino candidate events for the recent measurements of charged-current νe and νμ interactions in the MicroBooNE detector, using data corresponding to an exposure of 6.37×1020 protons on target from the Fermilab booster neutrino beam. We observe no evidence of light sterile neutrino oscillations and derive exclusion contours at the 95% confidence level in the plane of the mass-squared splitting Δm412 and the sterile neutrino mixing angles θμe and θee, excluding part of the parameter space allowed by experimental anomalies. Cancellation of νe appearance and νe disappearance effects due to the full 3+1 treatment of the analysis leads to a degeneracy when determining the oscillation parameters, which is discussed in this Letter and will be addressed by future analyses.
Article
Full-text available
We present high-precision theoretical predictions for the electron energy spectra for the ground-state to ground-state β decays of Pb214, Pb212, and Kr85 most relevant to the background of liquid xenon dark matter detectors. The effects of nuclear structure on the spectral shapes are taken into account using large-scale shell-model calculations. Final spectra also include atomic screening and exchange effects. The impact of nuclear structure effects on the Pb214 and Pb212 spectra below ≈100 keV, pertinent for several searches for new physics, are found to be comparatively larger than those from the atomic effects alone. We find that the full calculation for Pb214 (Pb212) predicts 15.0%–23.2% (12.1%–19.0%) less event rate in a 1–15 keV energy region of interest compared to the spectrum calculated as an allowed transition when using values of the weak axial vector coupling in the range gA=0.7–1.0. The discrepancy highlights the importance of both a proper theoretical treatment and the need for direct measurements of these spectra for a thorough understanding of β decay backgrounds in future experiments.
Article
Full-text available
The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. This TDR is intended to justify the technical choices for the far detector that flow down from the high-level physics goals through requirements at all levels of the Project. Volume I contains an executive summary that introduces the DUNE science program, the far detector and the strategy for its modular designs, and the organization and management of the Project. The remainder of Volume I provides more detail on the science program that drives the choice of detector technologies and on the technologies themselves. It also introduces the designs for the DUNE near detector and the DUNE computing model, for which DUNE is planning design reports. Volume II of this TDR describes DUNE's physics program in detail. Volume III describes the technical coordination required for the far detector design, construction, installation, and integration, and its organizational structure. Volume IV describes the single-phase far detector technology. A planned Volume V will describe the dual-phase technology.
Article
Full-text available
DEAP-3600 is a single-phase liquid argon (LAr) direct-detection dark matter experiment, operating 2 km underground at SNOLAB (Sudbury, Canada). The detector consists of 3279 kg of LAr contained in a spherical acrylic vessel. This paper reports on the analysis of a 758 tonne·day exposure taken over a period of 231 live-days during the first year of operation. No candidate signal events are observed in the WIMP-search region of interest, which results in the leading limit on the WIMP-nucleon spin-independent cross section on a LAr target of 3.9×10−45 cm2 (1.5×10−44 cm2) for a 100 GeV/c2 (1 TeV/c2) WIMP mass at 90% C.L. In addition to a detailed background model, this analysis demonstrates the best pulse-shape discrimination in LAr at threshold, employs a Bayesian photoelectron-counting technique to improve the energy resolution and discrimination efficiency, and utilizes two position reconstruction algorithms based on the charge and photon detection time distributions observed in each photomultiplier tube.
Article
Full-text available
The ArDM experiment completed a single-phase commissioning run in 2015 with an active liquid argon target of nearly one tonne in mass. The analysis of the data and comparison to simulations allowed for a test of the crucial detector properties and confirmed the low background performance of the setup. The statistical rejection power for electron recoil events using the pulse shape discrimination method was estimated using data from a Cf-252 neutron calibration source. Electron and nuclear recoil band profiles were found to be well described by Gaussian distributions. Employing such a model we derive values for the electron recoil statistical rejection power of more than 108^8 in the tonne-scale liquid argon target for events with more than 50 detected photons at a 50% acceptance for nuclear recoils. The Rn-222 emanation rate of the ArDM cryostat at room temperature was found to be 65.6±\pm0.4 μ\muHz/l, and the Ar-39 specific activity from the employed atmospheric argon to be 0.95±\pm0.05 Bq/kg. The cosmic muon flux at the Canfranc underground site was determined to be between 2 and 3.5×103m2s1\times 10^{-3}m^{2}s^{-1} . These results pave the way for the next physics run of ArDM in the double-phase operational mode.
Article
Full-text available
The Dark matter Experiment using Argon Pulse-shape discrimination (DEAP) has been designed for a direct detection search for particle dark matter using a single-phase liquid argon target. The projected cross section sensitivity for DEAP-3600 to the spin-independent scattering of Weakly Interacting Massive Particles (WIMPs) on nucleons is 1046 cm210^{-46}~\rm{cm}^{2} for a 100 GeV/c2c^2 WIMP mass with a fiducial exposure of 3 tonne-years. This paper describes the physical properties and construction of the DEAP-3600 detector.
Article
The radioactive isotope ³⁹Ar is an ideal tracer for ocean ventilation, groundwater flow, and for dating mountain glaciers. With a half-life of 269 years, it covers the age range from a few tens to about 1800 years. We evaluate the input history of the atmospheric ³⁹Ar in the past 2500 years. By measuring the ³⁹Ar/Ar ratios of a modern argon sample and two old argon samples collected in 1959 and 1961, respectively, the anthropogenic contribution to the atmospheric ³⁹Ar in the past 60 years is determined to be less than 15%. The temporal variation of the atmospheric ³⁹Ar in the past 2500 years is calculated based on a cosmic-ray record derived from ice cores and tree rings. It is found that the atmospheric ³⁹Ar/Ar ratio has changed by as much as 17% in that period of time. This input variation has to be taken into account and corrected for in future ³⁹Ar dating applications.
Article
The DEAP-3600 experiment is searching for weakly interacting massive particles dark matter with a 3.3 ×103kg single phase liquid argon (LAr) target, located 2.1 km underground at SNOLAB. The experimental signature of dark matter interactions is kilo electron volt–scale Ar40 nuclear recoils producing 128 nm LAr scintillation photons observed by photomultiplier tubes. The largest backgrounds in DEAP-3600 are electronic recoils (ERs) induced by β and γ rays originating from internal and external radioactivity in the detector material. A background model of the ER interactions in DEAP-3600 was developed and is described in this work. The model is based on several components which are expected from radioisotopes in the LAr, from ex situ material assay measurements, and from dedicated independent in situ analyses. This prior information is used in a Bayesian fit of the ER components to a 247.2 d dataset to model the radioactivity in the surrounding detector materials. Pulse-shape discrimination separates ER and NR events. However, detailed knowledge of the ER background and activity of detector components sets valuable constraints on NR backgrounds including neutrons and alphas. In addition, the activity of Ar42 in LAr in DEAP-3600 is determined by measuring the daughter decay of K42. This cosmogenically activated trace isotope is a relevant background at higher energies for other rare event searches using atmospheric argon, e.g., DarkSide-20k, GERDA, or LEGEND. The specific activity of Ar42 in the atmosphere is found to be 40.4±5.9 μBq/kg of argon.
Article
The Hamamatsu R5912-HQE photomultiplier-tube (PMT) is a novel high-quantum efficiency PMT. It is currently used in the DEAP-3600 dark matter detector and is of significant interest for future dark matter and neutrino experiments where high signal yields are needed. We report on the methods developed for in-situ characterization and monitoring of DEAP's 255 R5912-HQE PMTs. This includes a detailed discussion of typical measured single-photoelectron charge distributions, correlated noise (afterpulsing), dark noise, double, and late pulsing characteristics. The characterization is performed during the detector commissioning phase using laser light injected through a light diffusing sphere and during normal detector operation using LED light injected through optical fibres.