low-energy (anti)neutrino physics with...
TRANSCRIPT
Pablo Mosteiro, Princeton University*(Borexino Collaboration)
NOW – September 2014
Low-energy (anti)neutrino physics with Borexino
*Now at INFN-Roma1
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Neutrinos from the primary proton-proton fusion process in the Sun
Low-energy (anti)neutrino physics with Borexino
Nature 512, 383-386 (28 August 2014)
Pablo Mosteiro, Princeton University*(Borexino Collaboration)
NOW – September 2014
*Now at INFN-Roma1
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Scintillation
Ydet and kB are detector parameters
Photoelectrons picked up by photomultipliers (PMTs)
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Energy estimators
Offline, each trigger is analyzed to look for clusters, i.e., scintillation event candidates
After the beginning of each cluster, count the number of PMTs hit within time ДT=230ns
Multiple photons on same PMT count as 1 hit
Analytical formula for variance as well(variations in time, event position, Poisson fluctuations)
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Data selection: cuts
Remove muon-related eventsSelect events within r<3 m; |z|<1.7 m (Fiducial Volume)
Other technical, detector-specific cuts
~450 keV
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pp neutrinos: challenges
pp end point 420keV (recoil energy < 261keV; PMT dark noise)
14C beta-decay spectral shape (end point 156keV)
14C pile-up
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Challenge 1: dark noise
Trigger gate start
16.5 us
…
230 ns
Count number of PMTs hit in each of these windows
Trigger gate end
We can estimate the contribution from dark noise by using a new variable based on random triggers
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Trigger gate start
16.5 us
…
Count number of PMTs hit in each of these windows
Trigger gate end
Spectrum in that variable
Challenge 1: dark noise
230 ns
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Challenge 2: 14C rate
When a trigger contains two events, the second one is not subject to trigger threshold; so the shape is preserved better.
Result used to constrain rate of 14C in final fit
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Challenge 3: 14C pile-up
Rate of 14C in scintillator → RC ~ 40 Bq/100 t
Borexino mass → M = 300 t
Rate of 14C pile-up → (M RC) * RC * 230 ns ~ 100 cpd/100 t
Expected rate of pp ~ 130 cpd/100 t
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Pile-up may come from 14C but also from other detector events
Synthetic pile-up: overlap uncorrelated data with regular events
Result used to constrain rate of pile-up in final fit
Trigger gate start
…
230 ns
Trigger gate end
After-pulsingUncorrelated
data
Challenge 3: 14C pile-up
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Fit results
1) Calculate energy estimator, position, etc, for all events2) Apply cuts
3) Introduce dark noise
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Fit results
1) Calculate energy estimator, position, etc, for all events2) Apply cuts
3) Introduce dark noise4) Constrain 14C
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Fit results
1) Calculate energy estimator, position, etc, for all events2) Apply cuts
3) Introduce dark noise4) Constrain 14C
5) Constrain pile-up
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Fit results
1) Calculate energy estimator, position, etc, for all events2) Apply cuts
3) Introduce dark noise4) Constrain 14C
5) Constrain pile-up6) Perform spectral fit
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Main sources of uncertainty
Pile-up
85Kr rate
Fiducial Volume
Energy Estimator
Synthetic vs. Convolution
Statistics vs. Background
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Systematics estimation
Values obtained by varying fit conditions.The distribution shown is peaked at ~144 cpd/100 t.
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Final resultpp detection rate: 144 ± 13 (stat) ± 10 (syst) cpd/100 t
HM-SSM + LMA-MSW: 131 ± 2 cpd/100 t
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Check the time stability of the Sun (time scale 105 years), which is a crucial assumption in the Standard
Solar Model
Interpretation 3:Solar (in)variability
[Los Alamos Science, 1982]
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the Borexino Collaboration
UMass Amherst
Milano
Perugia
Princeton
Virginia Tech
Genova
JINR Dubna
HeidelbergMünchen
Kurchatov Moscow
Jagiellonian Kraków
St. Petersburg
Paris
Hamburg
Gran Sasso
Houston
Los Angeles
Moscow
Mainz
TU DresdenNapoli
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Thank you!
Thank you all for listening and please let me know if you have any questions
Thanks to the Borexino collaboration; in particular, to the pp working group
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Spectral fitter
Versatile tool for fitting multiple species in multiple configurations, within the Borexino detector
Validated against known Monte Carlo simulations and data
Takes into account energy response, detector geometry, etc
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• Why 230 ns?
• It is the minimum time needed to separate two clusters, below which the characteristic time of the scintillator (~100 ns) makes it very hard to tell apart.
• More time, more dark noise, and not so much scintillation light.
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Solar (in)variability
[Los Alamos Science, 1982]
The solar neutrino problem could be explained by the MSW effect, but alternatively it could be explained by
variations in the solar photon luminosity in the past 105
years.
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• Event at given position and energy -> what is distribution of npmts_dt1 variable?
107 MC events at center
Scintillation line shape
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Simulation Validation
Using GEANT4 and a detailed Borexino-specific package for geometry and detector effects
Source: 139Ce (166keV gamma)
Location: 12cm from center
kB=0.0099 cm/MeV
kB=0.0104 cm/MeV
kB=0.0109 cm/MeV
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Pile-up check against simulations
Assuming that most pile-up comes from 14C overlapping with itself
Generate sample of 14C events and randomly overlap events with a time displacement equal to 1/(14C rate)
Rate consistent with estimate from “synthetic method”
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Parent Daughter Decay Energy Half LifeMode [MeV]
238U 234Th ↵ 4.27 4.47⇥109 yr234Th 234Pa � 0.273 24.1 d234Pa 234U � 2.20 6.70 hr234U 230Th ↵ 4.86 2.45⇥105 yr230Th 226Ra ↵ 4.77 7.54⇥104 yr226Ra 222Rn ↵ 4.87 1.60⇥103 yr222Rn 218Po ↵ 5.59 3.82 d218Po 214Pb ↵ 6.12 3.10 min214Pb 214Bi � 1.02 26.8 min214Bi 214Po � 3.27 19.9 min214Po 210Pb ↵ 7.88 0.164 ms210Pb 210Bi � 0.0635 22.3 yr210Bi 210Po � 1.43 5.01 d210Po 206Pb ↵ 5.41 138 d206Pb stable
238U chain: 214Bi-Po coincidences
Efficiency: 89% [Bellini et al 2014]
Diffusion
Long half-life
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Direct? Real-time?
Direct: the measurement is made by detecting electron recoils triggered by pp neutrinos. Indirect measurement is made by measuring other neutrinos, then inferring the pp neutrino flux by assuming the Standard Solar Model is valid.
Real-time: the neutrinos are detected one-by-one, via their interactions with electrons, and their energies can be inferred. Other experiments are not able to count individual events and integrate over a range of energies.
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Systematics: Fiducial Volume
Effect ~ 8%
Some freedom in choosing the fiducial volume
Smaller volume will have reduced statistics
Larger volume will include radioactivity from the vessels and end caps
But some variation should be tolerated
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Systematics: Energy Estimator
Effect ~ 8%
Entire analysis can be re-done with a time window of 400 ns, instead of 230ns
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Stainless Steel SphereExternal water tank
Nylon Inner VesselNylon Outer Vessel
Fiducial volume
InternalPMTs
Scintillator
Buffer
WaterRopes
Steel platesfor extrashielding
Borexino Detector
MuonPMTs
P>1 = 0.004
Checks: threshold for photoelectron detection
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Solar abundance problem
Low-metallicity model [Asplund, Grevesse, Sauval & Scott 2009] → more recent calculations, inconsistent
with observations
High-metallicity model [Grevesse & Sauval 1998] →
outdated calculations, consistent with observations
Difference in pp flux is ~1% → out of reach for
Borexino at present59
Solar abundance problem
With 14C rate of ~40 /s/100 t, and scintillator time constant of ~100 ns [Bellini et al 2014], must separate pile-up events by hit time profiles (soft α/β cut).
Considerable work on simulations to reproduce data very accurately at low energies.
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Checks: 87Rbβ emitter with Q-value of 283.3 keV
Endpoint of pp-induced e- recoil spectrum: 261 keV
Assumption: relative abundances as in crust (both alkali metals)
A(40K) < 0.4 cpd/100 t [Bellini et al 2010]
A(87Rb) < 0.1 cpd/100 t61
Checks: 87Rb (continued)Recent measurement of purified NaI has 87Rb enriched by
~200 with respect to 40K [Calaprice et al unpublished]
A(40K) < 0.4 cpd/100 t [Bellini et al 2010]
A(87Rb) < 0.1 cpd/100 t x 200 = 20 cpd/100 t
Δpp=8 cpd/100 t~6%
Not included because our purification is
done in liquid
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