! Veto use outer layer to veto atmospheric muons " # - - PowerPoint PPT Presentation

Carlos Argüelles, Sergio Palomares-Ruiz, Austin Schneider, Logan Wille & Tianlu Yuan PANE Workshop Trieste, Italy • 29 May 2018

νeto: Atmospheric neutrino passing fractions and their

uncertainties for large-scale neutrino telescopes

Veto-based searches

Contained searches at high energies can use outer layer to veto atmospheric muons

Veto

!

✓ ✘

!

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High-energy, contained events in IceCube

Atmospheric neutrino passing frac2ons

Atmospheric neutrinos from the southern sky may be vetoed if accompanied by high-energy muon Veto probability correlated with energy and direc9on of neutrino Needed to understand how atmospheric neutrinos make it into our sample Proposed by SGRS [PRD 79, 043009 (2009)] Extended by GJKvS [PRD 90, 023009 (2014)]

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Zenith dependence

Passing fraction: probability of an atmospheric neutrino to not be vetoed

• !

• .//(1,,23)

Alters the zenith distribution of atmospheric neutrinos in the southern sky

• J. van Santen, ICRC2017

prompt

• conv. 56
• conv. 57

self-veto effect Southern sky Northern sky

HESE 6-year zenith distribution

Zenith distribu-on in southern-sky incompa2ble with background But this background suppression is calculated en2rely using the passing frac-on Assuming isotropic prompt, passing frac2on breaks degeneracy between prompt and diffuse astrophysical flux Drives current bound on prompt

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• N. Wandkowsky, TeVPA 2017

CA, SPR, and TY met at VietNus workshop on systematics for neutrino experiments Discrepancies in passing fraction calculation vs CORSIKA w/ SIBYLL 2.3 Unclear how to take systematic uncertainties into account at the time Idea: Use MCEq and calculate directly!

Start of this saga

Lines: GJKvS Crosses: CORSIKA MC Conventional !" + ̅ !" Prompt !" + ̅ !" Quy Nhon, Vietnam

Muon range

Veto is triggered by muons à Ask how likely an atmospheric muon is to reach the detector At high energies, muon is no longer minimum ionizing Stochastic energy losses become important

High-energy muon

Muon range pdfs

Need to evaluate !"#$%&(()

*|() ,, .ice), the pdf of the muon energy at depth, () *, as a

function of ()

, at surface and .ice the overburden

.ice ()

()

Detec%on probability

Simulate muons using MMC [arXiv:hep-ph/0407075] and build pdfs Convolute with detector response, !"#$%&(()

Detection probability

Previously, median muon range assumed [SGRS, PRD 79, 043009 (2009)]

• !"#$

• #"./0 − +,)

!

= 1 !

=

Uncorrelated muons

Atmospheric electron neutrinos may coincide with muons from other branches in shower

GJKvS, PRD 90, 023009 (2014)

• #"./0 − +,)

• f muons from
• proto. shower to

Assuming median muon-range

Correlated muons

Atmospheric muon neutrinos always have a sibling muon in addition to other branches

SGRS, PRD 79, 043009 (2009)

Assuming 2-body

Previous calculations

Single set of assumptions for primary flux, hadronic model, atmosphere density and muon range

• Correlated passing fraction analytically calculated
• Uncorrelated passing fraction obtained from fit to CORSIKA
• Equations were not formulated in the notation of previous slides

At low !", partner muon energy is too low to reach detector At higher !", partner muon energy increases and is more likely to trigger veto

Unified treatment

Muon-range from MMC [arXiv:hep-ph/0407075] n-body decays from Pythia 8.1 [CPC 178, 852-867] Fluxes and yields from MCEq [Fedynitch, hNps://github.com/afedynitch/MCEq] Coupling via !" subtracQon This work [arxiv:1805.11003]

Prompt νe

Prompt νµ

Conventional νe

Unified passing fractions

Conventional νµ

GJKvS uncorrelated, prompt calculations from fits to CORSIKA with DPMJET-2.55

Default settings

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detection threshold

GJKvS correlated calculaUon taken from SGRS analyUc formula Shoulder disappears (solid) due to muon stochasUcs GJKvS uncorrelated, conven0onal calculaUons from fits to CORSIKA with SIBYLL 2.1

Verifica(on against CORSIKA w. SIBYLL 2.3

103 104 105 106 107 Eν [GeV] 0.0 0.2 0.4 0.6 0.8 1.0 Passing Fraction

Conventional νµ/ ¯ νµ

CORSIKA set generated with

• H3a primary flux
• SIBYLL 2.3 hadronic model
• MSIS-90-E SP/July

atmosphere density

• 1.95 km depth in ice
• 1 TeV detection threshold

Excellent agreement for both neutrino and antineutrino No fitting performed!

νeto obviates need for high-

statistics CORSIKA!

Prompt νe/ ¯ νe

Prompt νµ/ ¯ νµ

Conventional νe/ ¯ νe

Verification against CORSIKA w. SIBYLL 2.3

Conventional νµ/ ¯ νµ

CORSIKA set generated with

• H3a primary flux
• SIBYLL 2.3 hadronic model
• MSIS-90-E SP/July atmosphere

density

• 1.95 km depth in ice
• 1 TeV detection threshold

Effect of !" subtrac.on

Default se,ngs

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detecQon threshold

Subtract parent energy from primary CR to calculate distribuQons for prototypical showers Affects higher energies; not enough CORSIKA staQsQc

103 104 105 106 107 Eν [GeV] 0.0 0.2 0.4 0.6 0.8 1.0 Passing Fraction

Conventional νe

cos θz = 0.25 cos θz = 0.45 cos θz = 0.85 CORSIKA Full Approximate

Importance of muon-range

Using the average muon- range treatment (dashed) results in large discrepancies with CORSIKA

Default settings

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detection threshold

103 104 105 106 107 Eν [GeV] 0.0 0.2 0.4 0.6 0.8 1.0 Passing Fraction

Conventional νe

cos θz = 0.25 cos θz = 0.45 cos θz = 0.85 Muon Range Dist. Average Treatment

103 104 105 106 107 Eν [GeV] 0.0 0.2 0.4 0.6 0.8 1.0 Correlated Passing Fraction

Conventional νµ

cos θz = 0.25 cos θz = 0.45 cos θz = 0.85 Muon Range Dist. Average Treatment

Importance of muon-range

For muon neutrinos, stochas-c losses smears out passing frac-on

Default se8ngs

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detec-on threshold

Prompt νe

Prompt νµ

Conventional νe

Uncertainties due to primary CR flux

Conventional νµ

GST: Gaisser, Stanev and Tilav (GST 4-gen) ZS: Zatsepin-Solkolskaya

Default settings

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detection threshold

Large variations for electron neutrino at high-energies ZS less accurate above 106 Muon neutrino suppression dominated by sibling muon Less affected by CR flux

Prompt νe

Prompt νµ

Conventional νe

Uncertain)es due to hadronic-interac)on models

Conventional νµ

Default settings

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detection threshold

Charm production only described by DPMJET and SIBYLL 2.3/c For conventional neutrinos, DPMJET-III similar to SIBYLL 2.3c

Prompt νe

Prompt νµ

Conventional νe

Uncertainties due to atmosphere-density models

Conventional νµ

Default se,ngs

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detecPon threshold

NRLMSIS-00 an update of MSIS-90-E SP: South-Pole KR: Karlsruhe Seasonal variaPons at South Pole bracket seasonal variaPons at Karlsruhe

Prompt νe

Prompt νµ

Conventional νe

Impact of detector depth and surrounding medium

Conventional νµ

Default settings

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detection threshold

KM3Net ~ 3.5 km in water IceCube ~ 1.95 km in ice Overburden dramatically affects passing fraction Surrounding medium also important Shallower detectors can reject atmospheric neutrinos more efficiently

Prompt νe

• 103

Prompt νµ

• 103

Conventional νe

• Impact of detector veto efficiency

Conventional νµ

• Default se,ngs
• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detecPon threshold

Three different !"#$%& 1 TeV Heaviside (solid) 0.75 TeV Heaviside (dashed) 0.75 TeV Sigmoid (dotted) Treat detector veto efficiency as function of muon energy at detector !"#$%&(()

Threshold is important and affects all flavors similarly

−1.0 −0.5 0.0 0.5 1.0 cos θz 10−6 10−5 10−4 10−3 10−2 10−1 E3

Eν = 10 TeV

−1.0 −0.5 0.0 0.5 1.0 cos θz 10−6 10−5 10−4 10−3 10−2 10−1 E3

Eν = 100 TeV

Summary fluxes vs zenith angle

Default se,ngs

• H3a primary flux
• SIBYLL 2.3c hadronic model
• MSIS-90-E SP/July atmosphere

density

• ALLM97 muon-range model
• 1.95 km depth in ice
• 1 TeV detecQon threshold

νeto

Earth-absorpQon

νeto

Earth-absorption

Conclusion

νeto is a framework for calculating the atmospheric neutrino background rate for

large-scale detectors Excellent agreement with CORSIKA and much less computationally intensive Systematic uncertainties can now be taken into account for wide range of detector configurations Already being applied in HESE-7.5yr analysis Code is publicly available @https://github.com/tianluyuan/nuVeto/ Paper online @https://arxiv.org/abs/1805.11003

Backups

Verification against previous calculation

Correlated-only comparison Identical assumptions as SGRS

• Gaisser-Honda primary flux
• Median muon-range

Excellent agreement with analytic formulation