Core-Collapse Supernova Signal Detection with Borexino and Friends

CORE-COLLAPSE SUPERNOVA SIGNAL DETECTION WITH BOREXINO AND FRIENDS

Zara Bagdasarian1, Maxim Gromov2 , Claudio Casentini3, Odysse Halim4 on behalf of the Borexino collaboration(1,2) and GWNU working group

JULY 4 2018 I WORKSHOP ON CORE-COLLAPSE SUPERNOVA NEUTRINO DETECTION, ORSAY, FRANCE

1IKP Forschungszentrum Jülich; 2SINP Moscow State University, 3INFN Sezione Roma Tor Vergata, 4Gran Sasso Science Institute

[email protected] Say Hi to Borexino 3800 m.w.e shielding against cosmic rays

Laboratori Nazionali del Gran Sasso (LNGS)

Water tank Nylon Outer Vessel R = 9 m, 2.1 kt water R = 5.5 m Shielding Barrier for 222Rn Cherenkov muon veto from steel, PMTs etc.

Stainless Steel Sphere R = 6.85 m Buffer PMTs support Pseudocumene (PC) + Buffer + scint. container DMP quencher

208 Outer Detector Nylon Inner Vessel PMTs R = 4.25 m ~ 300 tons of liquid scintillator 2212 Inward-facing (PC/PPO solution) PMTs

Zara Bagdasarian, Supernova Workshop !2 Say Hi to Borexino: Detection Channels

Most radiopure scintillator core, lowest threshold on real-time measurements

Low-energy threshold High Light Yield Good energy and position resolution No directionality

Neutrinos detection: Antineutrinos detection: Elastic scattering on electrons Inverse Beta Decay (IBD)

e− − νe, ν μ ,ν τ νe e Z0 W !3

− e − e νe νe, ν μ , ντ

Zara Bagdasarian, Supernova Workshop Core Collapse Supernova Search Activities @ Borexino

SNEWS GWNU Analysis

SuperNova Early Gravitational Waves meet Warning System Neutrinos

Ofﬂine “archival data”

Online Low latency

Zara Bagdasarian, Supernova Workshop !4 Core Collapse Supernova Search Activities @ Borexino

SNEWS GWNU Analysis

SuperNova Early Gravitational Waves meet Warning System Neutrinos

Ofﬂine “archival data”

Online SNEWS 2.0 ? Low latency

Common Front of Supernova Hunt?

Zara Bagdasarian, Supernova Workshop !5 Borexino @ SNEWS

Current NU experiments in SNEWS: LVD IceCube KamLAND Borexino Super-K Daya Bay HALO

Prospective experiments in SNEWS: NOVA SNO+ Running in automated mode since 2005 KM3NeT? Borexino joined in July 2009

Zara Bagdasarian, Supernova Workshop !6 SNEWS & GWNU Current NU experiments in SNEWS: GW LVD LIGO IceCube GWNU VIRGO KamLAND Borexino Super-K Daya Bay HALO

Prospective experiments in SNEWS/GWNU: NOVA SNO+ KM3NeT? MicroBooNE XENON1T

Zara Bagdasarian, Supernova Workshop !7 GWNU Overview Current NU experiments in SNEWS: GW LVD LIGO IceCube GWNU VIRGO KamLAND Borexino

GWNU Global network

Proposed in 2010/2013, MoU since 2015

Main Goal: Search and Investigation of Core- Collapse Supernova signals from the Local Group

Conservative approach: t_coin = ± 10 s Galactic events -> Smaller time window

Zara Bagdasarian, Supernova Workshop !8 Borexino’s friends in GWNU

Italy Japan

0.4kton/PMT South Pole Italy

LIGO VIRGO

Hartford, Livinston, USA Italy Zara Bagdasarian, Supernova Workshop !9 Core Collapse Supernova Search Activities @ Borexino

SNEWS GWNU Analysis

SuperNova Early Gravitational Waves meet Warning System Neutrinos

Ofﬂine “archival data”

Online SNEWS 2.0 ? Low latency

Common Front of Supernova Hunt?

Zara Bagdasarian, Supernova Workshop !10 Methodology

Zara Bagdasarian, Supernova Workshop !11 Background and False Alarm Rate

- 10 years of simulated background per experiment - The number of triggers (m) in overlapped time window (w=20s) - Algorithm following LVD paper Astroparticle Physics 28 (2008) 516-522

∞ k −Rbkgw (Rbkgw) e R = 8640 FA ∑ k! k=mi Triggers produced Reconstructed R - false alarm rate with the rate of bursts with an associated FA experimental false alarm rate background Rbkg - rate of experimental background

Zara Bagdasarian, Supernova Workshop !12 Background and False Alarm Rate

∞ k −Rbkgw (Rbkgw) e R = 8640 FA ∑ k! k=mi

- RFA - False alarm rate, aka imitation frequency - Rbkg - background rate of the given detector - mi - multiplicity, the number of triggers in overlapped time window (w=20s) - 8640 - number of 20s windows in 1 day (overlapped every 10 sec)

RFA [ev/day] Lower multiplicity m -> higher false alarm rate RFA

100

0.01 The thresholds on false alarm rate RFA for the LVD detector 2 4 6 8 m

Zara Bagdasarian, Supernova Workshop !13 Signal Injection

- Injection of simulated signals at the given distance with a rate of 1/day inside previously produced unclustered background events time series - 3652 signals for each distance - Burst deﬁnition and reduction procedure -> detection efﬁciency η (D)

Simulated Experimental Reconstructed Detection signals Background Bursts (signals) efﬁciency η ( D )

Zara Bagdasarian, Supernova Workshop !14 Detection efficiency & Misidentification probability

Simulated Experimental Reconstructed Detection signals Background Bursts (signals) efﬁciency

Detection efﬁciency

Nrec,s η(D) = Ninj,s

Zara Bagdasarian, Supernova Workshop !15 Detection efficiency & Misidentification probability

Simulated Experimental Reconstructed Detection signals Background Bursts (signals) efﬁciency

Reconstructed Simulated Experimental Misidentiﬁcation signals Background Bursts (sig. and bkg) probability

Detection efﬁciency Misidentiﬁcation probability

Nrec,s Nrec,b η(D) = ζ(D) = Ninj,s Nrec,b + Nrec,s

Zara Bagdasarian, Supernova Workshop !16 Detection efficiency & Misidentification probability

Detection efﬁciency Misidentiﬁcation probability

Nrec,s Nrec,b η(D) = ζ(D) = Ninj,s Nrec,b + Nrec,s

Borexino

Claudio Casentini PhD Thesis 2017

Borexino detector working alone at a background level RFA = 1 ev/day.

Zara Bagdasarian, Supernova Workshop !17 Detection efficiency & Misidentification probability

LVD

Each detector working alone at a background level RFA = 1 ev/day.

KamLAND

Claudio Casentini PhD Thesis 2017

Zara Bagdasarian, Supernova Workshop !18 Burst discrimination - � parameter m ξ = Δt m - burst (aka cluster) multiplicity, i.e. number of events in the coincidence window Δ t - burst duration (time difference between the last and ﬁrst trigger of each burst )

Distributions of pure background and background plus signal clusters in terms of Probability Density Functions (PDFs)

Closer source -> increased multiplicity -> better separation of signals and backgrounds

Casentini et. al (2017) arXiv:1801.09062

Zara Bagdasarian, Supernova Workshop !19 Improvements due to � parameter cut

No big loss in detection efﬁciencies η Big improvement in misidentiﬁcation probability ζ at galactic distances (Large Magelanic Cloud)

Claudio Casentini PhD Thesis 2017

Zara Bagdasarian, Supernova Workshop !20 Improvements due to � parameter cut

Detector M[kton] Ethr[MeV] � cut [Hz] Gain D [kpc]

Borexino 0.3 1 0.65 6.9 20

LVD 1 10 0.72 14.0 40

KamLAND 1 1 0.77 13.4 50

Claudio Casentini PhD Thesis 2017

Zara Bagdasarian, Supernova Workshop !21 IceCube Sensitivity

Trigger efﬁciency

IceCube in the network of 3 100 % IceCube alone

10 %

Lutz Köpke, Alexander Fritz

Zara Bagdasarian, Supernova Workshop !22 Network Sensitivity

Zara Bagdasarian, Supernova Workshop !23 False Alarm Rate for detector networks

N N−1 Rjoint = ∏Ri(2tcoin) i=1

Rjoint - the joint False Alarm Rate , a number of accidental coincidence of detector signals in the network

GW ν Rjoint = Rjoint × Rjoint × (2tcoin)

1 ev 1 ev Guidelines: 1000 years 1 ev day month

GW ν 3 Rjoint = RLG × RVG × 2tcoin Rjoint = RBX × RIC × RLVD × RKL × (2tcoin)

Zara Bagdasarian, Supernova Workshop !24 False Alarm Rate for neutrino detector networks

N N−1 Rjoint = ∏Ri(2tcoin) i=1

GW ν Rjoint = Rjoint × Rjoint × (2tcoin) ν 3 Rjoint = RBX × RIC × RLVD × RKL × (2tcoin)

1 ev day

False Alarm Rate requirement on the individual detector in the neutrino network:

ν a) Network of 1 detector: R i = 1 ev/day b) Network of 2 detectors: ν = 66 ev/day 1 ev Ri Rν ≈ c) Network of 3 detectors: ν = 265 ev/day joint Ri day d) Network of 4 detectors: ν = 525 ev/day Ri More detectors -> lower detection threshold

Zara Bagdasarian, Supernova Workshop !25 Data overlap: What data may we have in general?

More experiments

Zara Bagdasarian, Supernova Workshop !26 Shared Data: What data have we analysed?

Zara Bagdasarian, Supernova Workshop !27 Background analysis

~ 4000 Time shifts allow to simulate 100-1000 years of background

Expected number of coincidences:

The results obtained agree with the expectation->the goodness of the procedure

Zara Bagdasarian, Supernova Workshop !28 Coincidence search in networks

Expected number of coincidences:

Zara Bagdasarian, Supernova Workshop !29 Coincidence search (GW +NU)

GW network + LVD: Background study coincidences as expected No real coincidences as expected GW network + Borexino: Background study coincidences as expected No real coincidences as expected

GW network + IceCube: Background study coincidences as expected One real coincidence (due to a noisy behaviour in Virgo detector)

To further improve the sensitivity:

Lower the threshold Increase the common lifetime

Zara Bagdasarian, Supernova Workshop !30 CONCLUSIONS AND OUTLOOK

•Proof of Principle and methodology of the ofﬂine analysis - Done ✅ •Successful exchange of data and its analysis - Done ✅ •Redo the analysis with lower thresholds and more common life time in the new data format - Coming up •Low latency analysis - Coming up •Get ready for the new scientiﬁc run of GW detectors

Zara Bagdasarian, Supernova Workshop !31 CONCLUSIONS AND OUTLOOK

Open community: The more the merrier!

Zara Bagdasarian, Supernova Workshop !32