Slideshow Presentation

Upload
halstonjason 
Category
Education

view
69 
download
0
Embed Size (px)
description
Transcript of Slideshow Presentation
Detectability of Neutrinos from Failed Supernovae and Black HoleNeutron Star Mergers
Halston Lim and Jason LiangNorth Carolina School of Science and Mathematics
1
Neutrinos and their Detection• Fundamental particles
– Three flavors (νe, νμ, ντ)
– Mainly interact through weak force
• Can propagate through matter
– Useful when astrophysical phenomena are opaque to light
– Detectors use secondary particles to determine if event has occurred
• Detectors
– Water Cherenkov (SuperKamiokande)
– Liquid argon (LBNE)
The fundamental particles of the Standard Model
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 20132
Neutrino Emission• Neutrinos emitted by
astrophysical phenomena
• Core collapse supernova (SN) –stellar collapse and explosion
• Emits neutrinos (99% of binding energy)
• Analyzed important events different from typical SN
 Failed supernovae (fSN)
 Black holeneutron star mergers (BHNSM)
Supernova 1987A
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 20133
fSN and BHNSM• fSN
 Very highmass star
 Site of nucleosynthesis
 Would allow for first observation of BH formation
• BHNSM
 Thought to be linked with shortperiod gammaray bursts
 Very luminous events
 Can be used to study the evolution of early universe
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Artist’s conception of a BHNSM
Artist’s conception of a fSN
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 20134
Research Goals1. Determine observability of neutrinos from fSNand BHNSM in current and proposed detectors
2. Compare detector signals from our events with signals from typical SN
3. Investigate how well the parameters of the original flux distribution can be determined from interaction rates Schematic of SuperKamiokande
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 20135
General Methods
Use theoretical models of fSN and BHNSM to calculate the
neutrino emission
After finding the neutrinos emitted, use SNOwGLoBES to calculate the
what detectors on Earth observe
Determine the observability of
neutrinos
Consider existing astrophysical models of
fSN and BHNSM and how observations will confirm/reject these
models
6
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino event generated with Superscan event display program
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 2013
SNOwGLoBES(SuperNova Observatories with General Long Baseline Experiment Simulator)1
• Interaction rates calculator that we used to simulate neutrino events on Earth
• We calculated the neutrino flux from fSN and BHNSM and integrated real detectors parameters (cross sections, smearing, efficiencies)
[1] K. Scholberg, in APS April Meeting 2011 (2011), p. 1.
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 20137
Fluence Calculation
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
[4] O. L. Caballero and G. C. McLaughlin, Physical Review D 80, 123004 (2009).
[3] K. Sumiyoshi, S. Yamada, and H. Suzuki, The Astrophysical Journal 667, 32 (2007).
[2] H. Minakata et al., Journal of Cosmology and Astroparticle Physics 2008, 006 (2008).
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 20138
Examples of Flux ParameterizationsFermiDirac Parameterization3Garching Parameterization3
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 20139
Best to model fSN (nonthermal emission)
Best to model BHNSM(thermal emission)
Flux Comparisons with Typical SN
• fSN and BHNSM have higher neutrino energies
45
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
SH fSN BHNSM
[5] G. Shen, arXiv Preprint arXiv:1202.5791 1–20 (2012).
5
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201310
Event Rate Calculation4
Flux Interaction Cross Section x
Secondary Particle Distribution
Threshold Response xEnergy Resolution
• Calculated the flux– Applied intrinsic interaction and detection inputs for various
detectors in SNOwGLoBES6
• Main focus on liquid argon (LBNE) and water Cherenkov (SuperK) detectors
[6] K. Scholberg, arXiv Preprint arXiv:1205.6003 1–19 (2012).
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201311
b.a.
LEFT: The total number of events as a function of threshold energy is plotted for typical SN, fSN, and BHNSM models.
RIGHT: The total number of events is shown as a function of time for typical SN (Livermore, Basel) and fSN models (SH and LS nuclear equation of states. All events are calculated in SuperKamiokande at 10 kpc.
Neutrino Detector Signal
7
[7] J. M. Lattimer and F. D. Swesty, Nuclear Physics A 535, 331 (1991).
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201312
a. b.
The total number of events in various current (SuperKamiokande, HALO, LVD, Borexino) and proposed (HyperKamiokande, LENA, GLACIER, LBNE) detectors as a function of distance. Water Cherenkov (blue), liquid scintillator (red), and liquid argon (green) detectors are shown.
Viewing neutrinos from our neighbor Andromeda (700 kpc) is feasible with new detectors.
Observability
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
SH fSN BHNSM
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201313
Observed Neutrino Events
Center of Milky Way (10 kpc) Andromeda (700 kpc)
fSN (32 kt SuperK) 37400 events 8 events
fSN (560 kt HyperK) 654000 events 134 events
BHNSM (32 kt SuperK) 9300 events 2 events
BHNSM (560 kt HyperK) 162000 events 33 events
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
• Supernova 1987A, which exploded in the Large MagellanicCloud 50 kpc away, only produced 20 neutrinos that were detected
• Only confirmed observation of astrophysical neutrinos to date • The next supernova event would give many more neutrinos!
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201314
Neutronization Burst
fSN neutrino luminosities3
Neutronization burst
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201315
Neutronization Burst Visibility
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Water Cherenkov (SuperK) Liquid Argon (LBNE)
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201316
Nucleosynthesis
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201317
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201318
Nucleosynthesis Potential
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
FD parameterization for BHNSMGR parameterization for fSN
Temperature
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201319
Results• Showed differences between typical SN
detector signal and fSN/BHNSM detector signals
• Calculated the number of observed events from fSN and BHNSM in current and proposed detectors
• Determined the potential for nucleosynthesisto occur in fSN and BHNSM
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201320
Future Work
• Incorporate systematic uncertainties in parameter determinations
• Apply flavor dependent flux parameterizations to improve fits
• Use timedependent models of BHNSM
• Incorporate neutrino oscillation
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201321
Credits
Dr. Kate Scholberg, Duke University
Dr. Josh Albert, Duke University
Dr. Alex Himmel, Duke University
Dr. Jonathan Bennett, NCSSM
Poison Bear
Introduction SNOwGLoBES Time EvolutionObserved Signal Parameter Determination Conclusion
Neutrino Detection Halston Lim and Jason Liang, North Carolina School of Science and Mathematics, Sigma Xi 201322