beam n e ’s from antineutrinos – update –
DESCRIPTION
Part 1: n from m + reweighing Part 2: New ideas. Beam n e ’s from antineutrinos – Update –. David Jaffe, Pedro Ochoa. November 13 th 2006. Nearly all come from m + → e + + n e + n m. True energy of true n m at the ND. Reminder. - PowerPoint PPT PresentationTRANSCRIPT
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Beam e’s from antineutrinos – Update –
David Jaffe, Pedro Ochoa
November 13th 2006
Part 1: from + reweighing Part 2: New ideas
2
Need to tag antineutrinos coming from + decay:
One of the backgrounds in e analysis: intrinsic beam e‘s
E (GeV)The technique:),(),,()( KK v
datavv
Need high purity at low E
This is what we are trying to measure
Very little contribution from µ+ above this energy (Ecut)
Ecut
True energy of true at the ND
Nearly all come from +→ e+ + e +
Reminder
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Suggested in last collaboration meeting.
Used carrot and thus required mupi trees (thanks Chris!)
from + reweighting
from +
raw MCreweighed MC
reweighed MCraw MC
Used SKZP “a la Boston” to reweigh the + and K+ parents of the +:
Raw MC Reweighed MC
#events 455.3 472.4
(1.93x1019 POT)
4
pz
pt
Why so little change?
pz
pt
Plotted +,+ weights as a function of pt, pz to make sure no error:
The + parents get weights very close to 1:
parents(# events)
+ parent type(+ ~ 96%)
5
Current status (see minos-doc 2218)
Main idea of scaling methods (cf. minos-doc 1971) is:
),()(),( KECK MCvv
),(),,()( KK vdatavv
No reweighting applied to the MC
Overall technique:
Main idea of fit method is:
),(),( , KK FITMCvv
Scale method 1: C(E) from horn-off data/MC ratio, Ecut < E < Ehigh
Scale method 2: C(E) from horn-off data/MC ratio, Elow < E < Ecut
Stan’s method: C(E) from horn-off data/MC ratio, all E
Scale method 4: C(E) from horn-on data/MC ratio, E > Ecut
Scale method 5 (retired): C(E) from horn-on data/MC ratio, all E
Results in next slide were obtained with Ecut = 10 GeV, Elow = 4 GeV and Ehigh = 16 GeV
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Current status (see minos-doc 2218)
from + decay
E < Ecut
data-(Fit or Scaled) MC, Ecut < E < 30 GeV
raw MC 375.8 ± 15.1 (stat) 72.8 ± 6.5 (stat)
reweighed MC 373.4 ± 15.1 (stat) 99.1 ± 9.1 (stat)
Scale method 1 1015.6 ± 130.6 (stat) -1636.9
Scale method 2 1001.8 ± 130.7 (stat) -1655.6
Stan’s method 654.8 ± 289.5 (stat) -257.2 ± 298.8 (stat)
Scale method 4 1640.7 ± 126.6 (stat) 132.4± 122.2 (stat)
Fit method 546.4 ± 131.8 (stat) -21.4 ± 124.1 (stat)
“Scale method 5” was removed. See first two backup slides for more details.
Fit method needs to be revisited: SKZP “a la Boston” not very appropriate for
antineutrinos since not much variation in pt,pz space. Considerable fraction of antineutrinos not produced in
target (cf. minos-docs 2042 and 2376)
Should be real nubars from + if
data/MC from horn-off is trust-
worthy in this region
Should be ~0 by construction
Should be real nubars from +
Expected to be highly
negative by construction
Note: le010z185i data POT=1.93x1019
le010z000i data POT=2.77x1018
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New ideas
How about using the pHE data? Antineutrinos from + are the only ones affected by focusing (?) Can do pHE-LE and extract the two + components that way (?)
KKL
+
Plots scaled to 1.0x1020 POT
All plots until slide 10 are true E of true
antineutrinos.
All available stats for
pHE
LE pME
pHE
8
But also significant differences in the other components:
from -,K-:
LEpHE
LE/pHE ratio
from +
LEMEpHE
Indeed + component is considerably affected by focusing:
from -,K-
9
Where are the -,K- differences coming from?
Plots made by A. Himmel from Caltech
(See backup slide on antineutrino provenance for more information)
10
LE/pHE ratio for plots in previous slide:
Plots made by A. Himmel from Caltech
Note: error bars are probably wrong
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What about using the pME data?
from -,K-
LEpME
Antineutrinos from -,K- are almost identical in LE and pME !
Checked that nubar-PID selection does as good in pME as in LE:
For now neglecting ~0.3% difference in purity between
LE and pME
nubar-PID in pME
all
NC
vv
Selected events at 1.9x1019 POT
from -,K-
pME - LE
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from -,K-
LEpME
(reweighed)
Checked with SKZP reweighing, just in case:
Selected events at 1.9x1019 POT
Idea is to take (pME-LE) data difference and fit with MC shapes using two scaling parameters “parLE” and “parME”:
from +
pME
parME
from +
LE
parLE
pME-LEFit
from -,K-
pME – LE
13
How well could this work? Use fitted shapes instead of histograms:
from -,K- from -,K-
from + from +
pME
pME LE
LE
Selected events at 1.0x1018 POT
14
Assume: infinite MC statistics (pME and LE)infinite LE data statistics
Create fake pME data set for 1e18 POT by fluctuating smooth histograms with Poisson stats. For example:
fluct
fluct
from -,K-
from +
pME
pME
Sum of these two is fake pME data set
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(pME-LE) fake data set as a function of pME POT:
(pME-LE)SMOOTH at 1e18 POT
pME POT
(pME-LE)FAKE at 1e18 POT
(pME-LE)FAKE at 1e19 POT
(pME-LE)FAKE at 1e20 POT
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Used TMinuit with MIGRAD for the fit, with two parameters “parLE” and “parME”
parLE and parME are started at 1.0 and cannot be negative.
Fit fake data set
with
Used
This is an example for pME-POT=1e18
bins LEpME
LE
K
ME
K
LEMEFAKE
FAKE
vvparLEvparMEvLEpME2
,,2)(
from -,K-)ME
( from -,K-)LE
from +
pME
parME
from +
LE
parLE
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Fake data set and fit are repeated 5,000 times.
Could this work with our current amount of pME POT ~ 1e18 ?
Does not work at this POT !
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What about 1e19 POT ?
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5e19 POT2.5e19 POT
At other values of pME POT:
7.5e19 POT 1e20 POT
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What about systematics?
One systematic is our assessment of from -,K-)ME - ( from -,K-)LE:
Need to get this from MC and not from fit (need more pME stats)
Proper way to estimate error might be looking how much variation with reweighing.
Other systematics (cross-sections, … etc) could be assessed by varying shape of spectra.
Had a preliminary look by not correcting for at all:
pME POT 1e19 2.5e19 5e19 7.5e19 1e20
shift in parLE 1.17 1.19 1.19 1.19 1.20
shift in parME 1.10 1.12 1.12 1.12 1.12
from -,K-)ME - ( from -,K-)LE
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Summary & Ongoing work
Almost no variation observed when reweighted from +
Have our 5 semi-independent methods for assessing ’s from +:
Fit method needs more work. Currently trying to converge on the best fit for antineutrinos in nubar group.
Need more pHE MC statistics to see if we can do something similar with the pHE data.
New idea of using the MC shapes to fit the (pME-LE) difference:
Allows to cancel many unknowns in ’s from -,K-
Preliminary study shows measurement is possible to ~20% with ~2.5e19 POT of pME data
pME data may be useful for other analyses
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Backup slides
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In Scale Method 5 C(E) was approximated with
Main idea of scaling methods is:
),()(),( KECK MCvv
Overall method:),(),,()( KK v
DATAvv
),,(),,(
KK
MCv
DATAv
Pol 4th deg
Why “Scaling method 5” was thrown away:
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Then we have: ),,()1(),(
),,()1(),(
KfK
KfKMCv
MCMCv
DATAv
DATADATAv
thus giving:
),,(
),,(
1
1
),(
),(
K
K
f
f
K
KMCv
DATAv
MC
DATA
MCv
DATAv
MCf
Let be the fraction of + in the spectrum (Data)
Let be the fraction of + in the spectrum (MC)
DATAfMCf
But if then MCDATA ff )(),(
),(
),,(
),,(EC
K
K
K
KMCv
DATAv
MCv
DATAv
This method implied assuming fDATA = fMC
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Antineutrino provenance: