Estimating Starburst Supernova Rates Using OSSE Observations of M82 and NGC 253

Similar documents
G.H. Share, W.N. Johnson, J.D. Kurfess, R.J. Murphy. A. Connors. B.L. Dingus, B.E. Schaefer. W. Collmar, V. Schonfelder

AN OPTICAL-IR COUNTERPART FOR SGR B1900+l4? and. 1. Introduction

Background and Sensitivity Simulation of a Space Based Germanium Compton Telescope

COMPTON OBSERVATORY OBSERVATIONS OF AGN

Report Documentation Page

Measurement of Accelerated Particles at the Sun

Use of Wijsman's Theorem for the Ratio of Maximal Invariant Densities in Signal Detection Applications

K. McNaron-Brown. George Mason University, Fairfax VA J.D. Kurfess, and M.S. Strickman

VLBA IMAGING OF SOURCES AT 24 AND 43 GHZ

Report Documentation Page

Report Documentation Page

Diagonal Representation of Certain Matrices

CGRO/OSSE Observations of the Cassiopeia A SNR

Quantitation and Ratio Determination of Uranium Isotopes in Water and Soil Using Inductively Coupled Plasma Mass Spectrometry (ICP-MS)

Analysis Comparison between CFD and FEA of an Idealized Concept V- Hull Floor Configuration in Two Dimensions. Dr. Bijan Khatib-Shahidi & Rob E.

2008 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies SPECTRAL ANALYSIS OF RADIOXENON

Closed-form and Numerical Reverberation and Propagation: Inclusion of Convergence Effects

P. Kestener and A. Arneodo. Laboratoire de Physique Ecole Normale Supérieure de Lyon 46, allée d Italie Lyon cedex 07, FRANCE

Discovery of Planetary Systems With SIM

REGENERATION OF SPENT ADSORBENTS USING ADVANCED OXIDATION (PREPRINT)

OBSERVATIONS OF DISCRETE GALACTIC SOURCES WITH OSSE

A report (dated September 20, 2011) on. scientific research carried out under Grant: FA

Astronomical Institute of the Romanian Academy, str. Cutitul de. Argint-5, Bucharest 28, Romania,

Thermo-Kinetic Model of Burning for Polymeric Materials

Attribution Concepts for Sub-meter Resolution Ground Physics Models

Report Documentation Page

Estimation of Vertical Distributions of Water Vapor and Aerosols from Spaceborne Observations of Scattered Sunlight

hard X-ray outbursts (Harmon et al. 1995). Its distance al. 1995a). 2. Observation viewing periods 336.5, 338, 405.5, 407 and respectively).

MODELING SOLAR UV/EUV IRRADIANCE AND IONOSPHERE VARIATIONS WITH MT. WILSON MAGNETIC INDICIES

USNO Analysis Center for Source Structure Report

Estimation of Vertical Distributions of Water Vapor from Spaceborne Observations of Scattered Sunlight

CRS Report for Congress

Spots and white light ares in an L dwarf

System Reliability Simulation and Optimization by Component Reliability Allocation

Marginal Sea - Open Ocean Exchange

The Navy Precision Optical Interferometer for SSA applications: an update

Crowd Behavior Modeling in COMBAT XXI

Rogue Wave Statistics and Dynamics Using Large-Scale Direct Simulations

Z-scan Measurement of Upconversion in Er:YAG

TIME SERIES ANALYSIS OF VLBI ASTROMETRIC SOURCE POSITIONS AT 24-GHZ

Metrology Experiment for Engineering Students: Platinum Resistance Temperature Detector

Understanding Near-Surface and In-cloud Turbulent Fluxes in the Coastal Stratocumulus-topped Boundary Layers

Erik L. Swanberg 1 and Steven G. Hoffert 2. Veridian Systems 1, Autometric 2. Sponsored by Defense Threat Reduction Agency

FRACTAL CONCEPTS AND THE ANALYSIS OF ATMOSPHERIC PROCESSES

Broadband matched-field source localization in the East China Sea*

SW06 Shallow Water Acoustics Experiment Data Analysis

Babylonian resistor networks

Predicting Tropical Cyclone Formation and Structure Change

Optimizing Robotic Team Performance with Probabilistic Model Checking

Dynamics of Droplet-Droplet and Droplet-Film Collision. C. K. Law Princeton University

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER

INFRARED SPECTRAL MEASUREMENTS OF SHUTTLE ENGINE FIRINGS

Scattering of Internal Gravity Waves at Finite Topography

An Observational and Modeling Study of Air-Sea Fluxes at Very High Wind Speeds

Improvements in Modeling Radiant Emission from the Interaction Between Spacecraft Emanations and the Residual Atmosphere in LEO

Imaging compact supermassive binary black holes with Very Long Baseline Interferometry

On Applying Point-Interval Logic to Criminal Forensics

NAVGEM Platform Support

USMC Enlisted Endstrength Model

Extension of the BLT Equation to Incorporate Electromagnetic Field Propagation

Super-Parameterization of Boundary Layer Roll Vortices in Tropical Cyclone Models

Towards sub-microarsecond rigid Earth nutation series in. Abstract. The nonrigid Earth nutation series adopted by the IAU (International

Experimental and Theoretical Studies of Ice-Albedo Feedback Processes in the Arctic Basin

THE EULER FUNCTION OF FIBONACCI AND LUCAS NUMBERS AND FACTORIALS

High-Fidelity Computational Simulation of Nonlinear Fluid- Structure Interaction Problems

Improved Parameterizations Of Nonlinear Four Wave Interactions For Application In Operational Wave Prediction Models

DIRECTIONAL WAVE SPECTRA USING NORMAL SPREADING FUNCTION

Real-Time Environmental Information Network and Analysis System (REINAS)

Sensitivity of West Florida Shelf Simulations to Initial and Boundary Conditions Provided by HYCOM Data-Assimilative Ocean Hindcasts

Contract No. N C0123

Parametric Models of NIR Transmission and Reflectivity Spectra for Dyed Fabrics

uniform distribution theory

DISTRIBUTION A: Distribution approved for public release.

Award # N J-1716

REPORT DOCUMENTATION PAGE

Testing Turbulence Closure Models Against Oceanic Turbulence Measurements

Fleet Maintenance Simulation With Insufficient Data

PIPS 3.0. Pamela G. Posey NRL Code 7322 Stennis Space Center, MS Phone: Fax:

STUDY OF DETECTION LIMITS AND QUANTITATION ACCURACY USING 300 MHZ NMR

Sea Ice Model for Marginal Ice Zone

USER S GUIDE. ESTCP Project ER

Ocean Acoustics Turbulence Study

Modulation Instability of Spatially-Incoherent Light Beams and Pattern Formation in Incoherent Wave Systems

Vortex Rossby Waves and Hurricane Evolution in the Presence of Convection and Potential Vorticity and Hurricane Motion

DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited.

Understanding Near-Surface and In-Cloud Turbulent Fluxes in the Coastal Stratocumulus-Topped Boundary Layers

Predictive Model for Archaeological Resources. Marine Corps Base Quantico, Virginia John Haynes Jesse Bellavance

Experimental and Theoretical Studies of Ice-Albedo Feedback Processes in the Arctic Basin

ANALYSIS AND MODELING OF STRATOSPHERIC GRAVITY WAVE ACTIVITY ALONG ER-2 FLIGHT TRACKS

Investigation of the Air-Wave-Sea Interaction Modes Using an Airborne Doppler Wind Lidar: Analyses of the HRDL data taken during DYNAMO

REPORT DOCUMENTATION PAGE

High Resolution Surface Characterization from Marine Radar Measurements

REPORT DOCUMENTATION PAGE. Theoretical Study on Nano-Catalyst Burn Rate. Yoshiyuki Kawazoe (Tohoku Univ) N/A AOARD UNIT APO AP

HYCOM Caspian Sea Modeling. Part I: An Overview of the Model and Coastal Upwelling. Naval Research Laboratory, Stennis Space Center, USA

Mixture Distributions for Modeling Lead Time Demand in Coordinated Supply Chains. Barry Cobb. Alan Johnson

The FAME Mission: An Adventure in Celestial Astrometric Precision

Grupo demecanica Celeste, Facultad de Ciencias, Valladolid, Spain. Dept. Applied Mathematics, University of Alicante, Alicante, Spain

Exact Solution of a Constrained. Optimization Problem in Thermoelectric Cooling

Abyssal Current Steering of Upper Ocean Current Pathways in an Ocean Model with High Vertical Resolution

Volume 6 Water Surface Profiles

Transcription:

Estimating Starburst Supernova Rates Using OSSE Observations of M82 and NGC 253 D. Bhattacharya 1, L.-S. The 2, J. D. Kurfess 3, D. D. Clayton 2, N. Gehrels 4, D. A. Grabelsky 5, W. N. Johnson 3, G. V. Jung 6, R. L. Kinzer 3, M. D. Leising 2, W. R. Purcell 5, M. S. Strickman 3, and M. P. Ulmer 5 1 Institute of Geophysics and Planetary Physics, University of California, Riverside, CA 92521 2 Dept. of Physics and Astronomy, Clemson University, Clemson, SC 29634-1911 3 E. O. Hulbert Center for Space Research Naval Research Laboratory, Mail Code 4150, Washington DC 20375-5352 4 Code 661, NASA/Goddard Space Flight Center, Greenbelt, MD 20771 5 Dept. of Physics and Astronomy, Northwestern University, Evanston, IL 60208 6 Universities Space Research Association, Washington, DC 20375-5320 Abstract We have used the OSSE observations of the starburst galaxies NGC 253 and M82 to obtain upper limits to the Type Ia and Ib supernova rates in these galaxies. Monte Carlo simulations of randomly occurring supernova events in NGC 253 and M82 were performed to evaluate the significance of our upper limit to the 0.847 and1.238 MeV 56 Co gamma-ray line fluxes on the supernova rate from these two galaxies. A set of observations of NGC 253 and M82 by OSSE is suggested in order to maximize the chances of gamma-ray line detection from these sources. 1. Introduction Intial observations of the starburst galaxies in radio and infra-red wavelengths suggested that these galaxies have a high supernova rate - on the order of 0.1-0.3 yr -1. This inference was deduced based on the radio observations of supernova remnants in M82 where some remnants apparently showed remarkable decrease in intensity within 6 months (Kronberg, Biermann and Schwabb 1985). However, recent radio observations of Ulvestad and Antonucci (1993) of M82 and NGC 253 suggest that the variability in the source intensity may result due to the differences in calibrations and measurements and hence, the rates in these galaxies may not be as high as claimed before. The radio rates are based only on the observations of Type II supernova remnants. Type Ia SNRs are not detected in radio, whereas Type Ib are detected only for a short time. Type Ib radio supernovae have a steeper spectra and rapid decay than Type IIs (Weiler and Sramek, 1988). Using the relative extragalactic supernova frequencies given by Van den Bergh and Tammann (1991) and a Hubble constant of 100 km s -1 Mpc -1 we find for NGC 253 (a type Sc galaxy) SN rates of 1, 1.5 and 7.5 per century for Types Ia, Ib and II, respectively (we should note that had we used a Hubble constant of 50 km s -1 Mpc -1 the

Report Documentation Page Form Approved OMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 1994 2. REPORT TYPE 3. DATES COVERED 00-00-1994 to 00-00-1994 4. TITLE AND SUBTITLE Estimating Starburst Supernova Rates Using OSSE Observations M82 and NGC 253 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Research Laboratory,E.O. Hulburt Center for Space Research,4555 Overlook Avenue, SW,Washington,DC,20375 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR S ACRONYM(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 11. SPONSOR/MONITOR S REPORT NUMBER(S) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT a. REPORT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified 18. NUMBER OF PAGES 6 19a. NAME OF RESPONSIBLE PERSON Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18

rates would drop by a factor of 4). The total supernova rate 10 per century is consistent with the rate deduced by Ulvestad and Antonucci, although our estimation does not take into account the starburst nature of NGC 253. A rate of < 0.1 sn yr-1 results in agreement with one of the starburst models (D) of Rieke et al. (1980) which correctly predicts the bolometric luminosity, but underpredicts the radio intensity by an order of magnitude. Most of the supernovae in starburst galaxies will not be detectable in optical wavelengths due to the presence of dust in the starburst cores. Hence, it is not clear whether for an infra-red bright galaxy such as NGC 253, the ratio N(Type II)/N(Type Ia + Type Ib) ~ 3 would hold. It is generally believed that only population II stars produce Type Ia SNe so that such events are unlikely to occur in starburst cores. However, due to the present insufficient knowledge of the Type Ia progenitors we do not preclude the possibility that Type Ia may come from a wide variety of population. Indeed, the observations that SN Type Ia rate per unit infra-red luminosity is an order of magnitude higher in Sc spirals than it is in E and So type galaxies may indicate that not all SN Ia are associated with a very old stellar population (Van den Bergh 1990). In this respect gamma-ray observations of starburst galaxies may serve a promising role with its potential to detect supernovae signatures through the dense starburst nuclear regions and complement the radio observations. Such observations could be used as a direct estimator of supernova rates and discern between different types of SNe occuring in the starburst cores. Some of the starburst galaxies are sufficiently nearby so that supernovae lines of Type Ia, Ib and Ic may be detected at a significant level. The recent detection of supernova continuum from SN 1993J from M81 (which is a companion galaxy of M82) by OSSE proves that it is not unreasonable to expect detectable Type I supernovae in gamma-rays from these nearby infrared luminous galaxies. 2. Observations and Results OSSE observed NGC 253 during 4 viewing periods and M82 during 5. The target for the last three M82 VP's was actually M81, but due to the close proximity of these two galaxies (~1_) OSSE field-of-view could not distiguish between them. The VPs are given in Table 1. Upper limits to the NGC 253 and M82 847 kev lines are given in Table 2. The detailed results are presented elsewhere (Bhattacharya 1993, Lihsin 1993, Leising 1993). During the first three VPs NGC 253 was detected up to 200 kev with a total significance of 4.2σ and an estimated luminosity of 3 10 40 ergs s-1. The spectrum is best fit by a photon power law index of ~ 2.5. A search for gamma-ray lines from the decay of the most abundant radioactive element produced in the supernovae( 56 Ni 56 Co 56 Fe) yielded no significant detection: the 3σ upper limits at 0.158, 0.847 and 1.238 MeV are 4 10-5, 8 10-5 and 9 10-5 cm -2 s -1, respectively. The last VP of NGC 253 showed no significant continuum emission. No significant continuum flux was observed from from M82. The 3σ upper limits of 0.847 MeV 56 Co gamma-line fluxes are 2.2 10-4 and 1.2 10-4 cm -2 s -1, respectively.

3. Supernova Rates Based on the non-detection of supernovae lines and Monte Carlo simulations we have ascertained upper limits to the supernova rates in these galaxies. Monte Carlo simulations of randomly occurring supernova events in NGC 253 and M82 were performed to evaluate the significance of our upper limit to the 0.847 and1.238 MeV 56 Co gamma-ray line fluxes on the supernova rate from these two galaxies. For this purpose we take the 3σ upper limit to be the best-fit value plus three standard deviations from that value, even though this confidence limit may differ slightly from the expected 3σ sensitivity of OSSE to lines. The 3σ upper limits to the 0.847 MeV gamma-line fluxes from first two viewing periods of M82 and the first three viewing periods of NGC 253 were compared with the line flux generated by the Monte Carlo histories. The fraction of galaxies in the simulations that would be fainter than both Fig. 1 The probability for the 847 kev gamma-line fluxes from stohastically occuring Type Ia, Type Ib, and Type II supernovae to be less than both 3σ upper limits a) for the three NGC 253 observations, and b) for the two M82 observations. 3σ OSSE limits at 847 kev is shown in figure 1. It therefore represents the probability that that particular astrophysical simulation would not have been detected. Different types of supernova models are used in the simulation but are considered independently of each other. Model W7 is a Type Ia supernova deflagration model of carbon-oxygen white dwarf thermonuclear explosion (Nomoto, Thielemann and Yokoi 1984).WR6C is a Type Ib supernova model of Wolf-Rayet progenitor (Ensman and Woosley 1988). For Type II supernova we take the SN87A model that produces 0.075 solar mass 56 Ni (Pinto and Woosley 1988b). Based on the non-detection of gamm-lines during the first two observations of M82 and the first three of NGC 253, and Monte Carlo simulations we can exclude a recurrence time of less than 0.5.yr for a Type Ia (SN rate of 2 yr -1 ) and 0.15 yr for Type Ib supernova (SN rate of 7 yr -1 ) models in starburst galaxies. To further constrain the limit on supernova rates we have added the last VP of NGC 253 and three viewing periods on SN1993J in M81. M81 and M82 are indistiguishable in the OSSE field of view, hence these three VPs can be considered as M82 observations. We further assumed that the supernova rates are the same in all

starbursts. Generating Monte Carlo histories of these 9 viewing periods over a starburst time of 10 6 years we have obtained a 3σ upper limit of 1 SN yr -1 for Type Ia (Fig 2). A set of observations of NGC 253 and M82 are suggested to maximize 1 0.8 the chances of gammaray line detection from Type Ia 0.6 these sources-this will 0.4 also ensure better sensitivity for detecting 0.2 diffuse emission. We 0 have tried to maximize 10-3 10-2 10-1 the probability using Supernova Rate (yr -1 ) two observation periods 10 0 where the source is detected at least during one. Fig. 3 shows how Fig. 2 Probability of a SN Type Ia line detection as a function of the supernova rate for the 9 viewing periods used in the analysis. The 3σ upper limit to the Type Ia rate is ~1 yr -1. the separation between two periods change the probability of detection. For example, the probability of detection for Type 1b model WR6Cfm with a 1 yr recurrence time is ~40% if the separation between the observations is ~20 days. The probability increases reaching a plateau at around ~180 days after which it remains constant. Probability of detection If the cosmic ray electrons are supplied by supernova explosions, then making use of the minimum energy requirements (to deduce the cosmic ray density) given by Longair (1981) and Miley (1980), and an average supernova energy release, we can estimate the recurrence time of supernovae, t SN, from the following relation: ε= t elec t SN E SN V where telec is the electron lifetime or the characteristic escape time from the confinement volume V, E SN is the average energy release in cosmic rays per SN, and ε is the cosmic ray energy density. V is the infra-red emitting volume used in the diffuse emission estimation for NGC 253 (~2.5 10 64 cm 3 ). t elec is assumed to be ~ 10 6 yrs. One of the unknowns in this calculation is k, the ratio of proton energy density to that of electron's. For a value of k ~ 100 (which is valid at the top of the atmosphere), the minimum energy in cosmic rays increases by an order of magnitude. In the following calculation, we have taken k to be 1; the energy density increases by a factor of ~ 1.5. In this case E SN is assumed to be 2 10 49 ergs, where the average electron energy yield of a supernova is 10 49 ergs. Using the observed radio intensities for NGC 253 given in Klien et al. (1983)

we estimate the minimum energy in the starburst nuclei following Miley (1980). Assuming the size of the emitting region to be 2.5' 0.35' and the path length through the source in the line of sight to be 500 pc, we derive an energy density, ε of 10-10 ergs cm -3. Hence, from the equation we get t SN to be 4 yrs. On the other hand, our initial observational t SN of 0.5 yr (for Type Ia) and 0.15 yr (for Type Ib) provide an upper limit to the cosmic ray electron density in starbursts to be 4 10-9 ergs cm -3. Further observation can give a proper estimation of t SN and consequently a better understanding of the energy density in starburst environment. References Bhattacharya, D. et al. 1993, Compton Observatory Symposium, St. Louis, AIP Conf. Proc., 280, 498. Colina, L. and Perez-Olea, D. 1992, MNRAS, 259, 709. Ensman, L. and Woosley, S. E. 1988, ApJ, 333, 754. Kroenberg, P. P., Biermann, P., and Schwab, F. R. 1985, ApJ, 291, 693. Leising, M. et al. 1993, this proceeding. Lih-sin, T. et al. 1993, Compton Observatory Symposium, St. Louis, AIP Conf. Proc., 280, 503. Longair, M.S. 1981, High Energy Astrophysics, (Cambridge:University Press) Nomoto, K., Thielemann, F.K. \& Yokoi, K. 1984, ApJ, 286, 644. Pinto, P.A. and Woosley, S.E. 1988b, ApJ, 329, 820. Ulvestad, J. S. and Antonucci, R. R. J. 1992, submitted to ApJ van den Bergh, S. and Tammann, G. A. 1991, Ann Rev Astron Astrophys, 29, 363. Volk, H.J., Klein, U., and Wielbinski, R. 1989, AA, L12 Weiler, K. W. and Sramek, R. A. 1988, Ann. Rev. Astron Astrophys, 26, 295.

Fig.3 Gamma-Ray line (847 kev) detection probability at least in one of the two observations.