Extragalactic Transients with SALT

Highlights of recent work looking at extragalactic transients with SALT. This includes a discussion of future instrumentation to help follow-up transient objects. Presented at https://salt2017.camk.edu.pl/

Transcript

1. Extragalactic Transients with SALT Steve Crawford SALT Science Data Manager SAAO
2. PySALT https://github.com/saltastro Tools for polarimetry, HRS, FP, LS, MOS, proposals, scripts Contributions welcome and needed! Big thanks to all that have contributed so far: And given feedback!
3. Outline • Reverberation mapping of AGN • Supernova follow-up • Cosmic chronometers • Next generation SALT?
4. Reverberation Mapping LCO reverberation mapping: Michael Hlabathe, Encarni Romero Colmenero, Keith Horne, LCOGT AGN Key project SALT/Korea reverberation Mapping: Songyoun Park, Encarni Romero Colmenero, Jong-Hak Woo
5. Reverberation Mapping Continuum variation from days to years Reflecting in emission lines in the broad line region Narrow line region can be used for calibration Kaspi Determine size of the board line region based on time lag
6. PG 0934+013 with SALT 4 PARK ET AL. Julian Date−2450000 B (mag) Flux (10−13 erg s−1 cm−2) 16.8 16.6 16.4 16.2 16.0 LCOGT LOAO 0.8 1.0 1.2 Hβ 0.2 0.4 0.6 He II 6300 6400 6500 6600 6700 6800 0.6 0.8 1.0 1.2 Fe II Figure 2. Light curves for the B band, the H , He II, and Fe II emission lines. curve of each emission line with respect to continuum sam- pling, then calculated the CCF (Gaskell & Peterson 1987; White & Peterson 1994; Peterson et al. 2004). The CCF was computed for time lags ranging from -20 to 60 days with in- of CCF was adopted for uncertainty. Figure 3 presents the results of CCF calculation between the continuum and H emission line. We measured the time lag ⌧peak = 8.52+2.23 -2.27 days, and ⌧cen = 8.46+2.08 -2.14 days in the observed
7. Calibrated the MgII RM for use at high-z Hβ MgII Hβ and MgII RM z=0.35 LCO imaging VLT/Gemini/ SALT monitoring
8. SALT Spectroscopy and Classification of Supernova Spectra Using 
 Bayesian Techniques SALT DES: Eli Kasai, Bruce Bassett, Matt Smith, and DES SN team
9. SALT/DES SN Nightly observations of the Dark Energy Survey Fields from Aug-Jan. DES is an LSST precursor observing 27 sq. degrees. Will find Need: Spectroscopic confirmation of type Ia supernova for cosmology DES
10. Supernova Follow-up Observe significant number of Ia supernova at z~0.3 near peak to: 1. Classify and determine redshift 2. Correlate EW with SN Ia light curve Challenges: 1. Can only observe for ~1 hr 2. Faint sources
11. SupernovaMC Bayesian classification of supernova spectra • The classification is performed in two steps • Model selection – optimization algorithm • Parameter estimation – Markov Chain Monte Carlo sampling • SNMC also • classifies heavily contaminated spectra • classifies low SNR spectra • fits type, contamination, redshift, epoch, AV CHAPTER 3. THE WORKING MECHANISM OF SUPERNOVAMC Figure 3.11: Corner plot of the SALT spectrum of ‘DES15S2ocv’, showing 1-D histograms and 1 -level contours of SNMC’s estimated posterior distributions of the four parameters: ↵, z, t and AV . SN templates5 and galaxy templates used in Crawford et al. (2006, 2009), which the authors originally adapted from Coleman et al. (1980) and Kinney et al. (1996). For computational reasons, only five of such total 14 galaxy templates are used by SNMC for classification. However, more than 5 galaxy templates can be included in the classification at the cost of increased computational time.
12. >35 Ia spectra observed
13. 8 Cartier et al. arXiv:1609.04465v2 [astro-ph.SR] 14 Oct 2016 MNRAS 000, 1–17 (2016) Preprint 17 October 2016 Compiled using MNRAS L ATEX style file v3.0 Early observations of the nearby type Ia supernova SN 2015F R. Cartier1⋆, M. Sullivan1, R. Firth1, G. Pignata2,3, P. Mazzali4,5, K. Maguire6, M. J. Childress1, I. Arcavi7,8, C. Ashall4, B. Bassett9,10,11, S. M. Crawford9, C. Frohmaier1, L. Galbany12,13, A. Gal-Yam14, G. Hosseinzadeh7,8, D. A. Howell7,8, C. Inserra6, J. Johansson14, E. K. Kasai9,10,11,15, C. McCully7,8, S. Prajs1, S. Prentice4, S. Schulze3,16, S. J. Smartt6, K. W. Smith6, M. Smith1, S. Valenti7,8, and D. R. Young6 1Department of Physics and Astronomy, University of Southampton, Southampton, Hampshire, SO17 1BJ, UK 2Departamento de Ciencias Fisicas, Universidad Andres Bello, Avda. Republica 252, Santiago, Chile 3Millennium Institute of Astrophysics, Santiago, Chile 4Astrophysics Research Institute, Liverpool John Moores University, IC2, Liverpool Science Park, 146 Brownlow Hill, Liverpool L3 5RF, UK 5Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, D-85748 Garching, Germany 6Astrophysics Research Centre, School of Mathematics and Physics, Queens University Belfast, Belfast BT7 1NN, UK 7Las Cumbres Observatory Global Telescope Network, 6740 Cortona Dr., Suite 102 Goleta, Ca 93117 8Department of Physics, University of California, Santa Barbara, CA 93106-9530, USA 9South African Astronomical Observatory, P.O.Box 9, Observatory 7935, South Africa 10African Institute for Mathematical Sciences, 6-8 Melrose Road, Muizenberg 7945, South Africa 11Department of Mathematics and Applied Mathematics, University of Cape Town, Rondebosch, 7700, South Africa 12Pittsburgh Particle Physics, Astrophysics, and Cosmology Center (PITT PACC). 13Physics and Astronomy Department, University of Pittsburgh, Pittsburgh, PA 15260, USA. 14Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot 76100, Israel 15Department of Physics, University of Namibia, 340 Mandume Ndemufayo Avenue, Pioneerspark, Windhoek, Namibia 16Instituto de Astrofísica, Facultad de Física, Pontificia Universidad Católica de Chile, Vicuña Mackena 4860, 7820436 Macul, Santiago, Chile Accepted 2016 October 14. Received 2016 October 11; in original form 2016 May 25 ABSTRACT We present photometry and time-series spectroscopy of the nearby type Ia supernova (SN Ia) SN 2015F over −16 days to +80 days relative to maximum light, obtained as part of the Public ESO Spectroscopic Survey of Transient Objects (PESSTO). SN 2015F is a slightly sub-luminous SN Ia with a decline rate of ∆m15(B) = 1.35 ± 0.03 mag, placing it in the region between normal and SN 1991bg-like events. Our densely-sampled photometric data place tight constraints on the epoch of first light and form of the early-time light curve. The spectra exhibit photospheric C ii λ6580 absorption until −4 days, and high-velocity Ca ii is particularly strong at < −10 days at expansion velocities of ≃23000 km s−1. At early times, our spectral modelling with syn++ shows strong evidence for iron-peak elements (Fe ii, Cr ii, Ti ii, and V ii) expanding at velocities > 14000km s−1, suggesting mixing in the outermost layers of the SN ejecta. Although unusual in SN Ia spectra, including V ii in the modelling significantly improves the spectral fits. Intriguingly,we detect an absorption feature at ∼6800 Å that persists until maximum light. Our favoured explanation for this line is photospheric Al ii, which has never been claimed before in SNe Ia, although detached high-velocity C ii material could also be responsible. In both cases the absorbing material seems to be confined to a relatively narrow region in velocity space. The nucleosynthesis of detectable amounts of Al ii would argue against a low-metallicity white dwarf progenitor. We also show that this 6800 Å feature is weakly present in other normal SN Ia events, and common in the SN 1991bg-like sub-class. Key words: supernovae: general – supernovae: individual (SN 2015F) ArXiv:1609.04465 SALT
14. Cosmic Chronometers SCALPEL: Ando Ratsimbazafy, Ilani Loubser, Catherine Cress, Bruce Bassett, Petri Väisänen, Bob Nicol
15. Luminous Red Galaxies as timekeepers 6 Ratsimbazafy et al. Figure 1. This shows an example of full–spectrum fitting. The fitting of 2SLAQ J100825.72−002443.3 spectrum (smoothed with a 5 pixel boxcar) which is in black and the best fit in blue line. The red regions were excluded and masked in the fit: the outliers which correspond to the regions of the telluric lines and the residuals form the sky emission lines. The green lines in the residuals of the fit are the estimated 1 − σ deviation. Fluxes are expressed in erg cm−2 s−1 Å−1. Table 3. Results of SSP fit with BC03 models showing the SSP equivalent ages. Errors of each parameter are from the covariance matrix. S/N ratio per resolution element of the observed spectra is also given. The first 9 galaxies are all belong to one redshift bin which is at z ≃ 0.40, and the last 5 galaxies are in the redshift bin of z ≃ 0.55. Name Redshift Age [Fe/H] χ2 S/N ratio⋆ Assume LRGs are standard ages Fit the ages of LRGs at different redshifts Use to determine H(z) ses the age difference between two redshifts for a passively evolving o calculate the expansion rate of the Universe. Our measurement is gh quality spectra of Luminous Red Galaxies (LRGs) obtained with arge Telescope (SALT) in two narrow redshift ranges of z ≃ 0.40 and tial pilot study. Ages were estimated by fitting single stellar population spectra. This measurement presents one of the best estimates of H(z) .5 to date. volution– cosmology: cosmological parameters–cosmology: observa- een ers. ck- 07; CK ous- t al. t al. gier xies an- redshift, rather than a quantity which gives an integrated measure- ment of H(z) out to redshift z. This technique is independent of the cosmological model and allows a determination of the expansion rate at a given redshift without relying on the nature of the metric between the chronometers and observers, and therefore can provide tighter constraints on cosmological parameters of the model. The expansion rate H(z) at redshifts z > 0 can be obtained by H(z) = − 1 (1 + z) dz dt . (1) In the CC method, dz/dt is approximated by determining the time interval ∆t corresponding to a given ∆z, where ∆z is centered at redshift z. If one assumes that most stars in Lu-
16. Age Dating LRGs 017 MNRAS 000, 1–11 (2016) Preprint 3 February 2017 Compiled using MNRAS L A TEX style file v3.0 Age–dating Luminous Red Galaxies observed with the Southern African Large Telescope∗ A. L. Ratsimbazafy1,2†, S. I. Loubser1, S. M. Crawford3, C. M. Cress4,2, B. A. Bassett5,3,6, R. C. Nichol7, and P. Väisänen3,8 1Centre for Space Research, North-West University, Potchefstroom 2520, South Africa 2Physics Department, University of the Western Cape, Private Bag X17 Cape Town 7535, South Africa 3South African Astronomical Observatory, P.O. Box 9 Observatory 7935, Cape Town, South Africa 4Centre of High Performance Computing, CSIR, 15 Lower hope St., Rosebank, Cape Town 7700, South Africa ArXiv:1702.00418 8 Ratsimbazafy et al. Figure 4. Our estimate H(z ≃ 0.47) measured using SALT LRG spectra is represented by the red filled rectangle. It has a value of H(z) = 89 ± 34 (stat) km s−1 Mpc−1. Our result is plotted with all available H(z) in the literature up to redshift z ∼ 2 (Simon, Verde, & Jimenez 2005; Stern et al. 2010; Moresco et al. 2012; Moresco 2015; Moresco et al. 2016; Zhang et al. 2014). The dashed line and the shaded regions are not a best fit to the data but the theoretical H(z) of a flat ΛCDM model with its 1σ uncertainty obtained by Planck Collaboration et al. (2016) (with Ωm = 0.308 ± 0.012, and H0 = 67.8 ± 0.9 km s−1 Mpc−1). The black point at z =0 is the Hubble Space Telescope measurement of the Hubble parameter today H0 = 73.8 ± 2.4 km s−1 Mpc−1 (Riess et al. 2011). This can explain the SSP equivalent age of 1.02±0.03 Gyr as the light–dominant epoch of star formation.
17. Next Generation SALT Transient Spectroscopy Factory?
18. Short Term Projects • RSS upgrade (20% more throughput) • Slit IFU • Rapid follow-up (API for submitting single blocks) • High throughput spectrograph?
19. Rise of the Machines Instead of a single monolithic tracker Multiple-mini single object robotic trackers
20. Fields of View SALT FOV-8’ LSST-3.5o SALT Visibility—12o Spherical primary— always on axis Why not have two (or more) independent trackers Not to scale
21. How many transients? LSST 10k transients per minute -> 1M per night. However, only a few per sq degree require immediate follow-up -> only tens per LSST FOV. Still ~1000s per night of interesting transients So large number of low density, all sky events (SALT is great at that!), how to follow-up as many as you can? SALT visibility window contains ~100 interesting sources at any one time. So 100 robotic arms (or 2 SALTs with 50 robotic arms) observing each visibility window for 1 hour could observe 800 interesting transients a night. How good would other telescopes do? Maximum 1o FOV typically which means 15-30 interesting transients a night.
22. Summary SALT is fantastic at: • Quickly following up events • Providing regularly monitoring • Large aperture allows faint objects Can SALT be even better? • Improved RSS performance • high throughput spectrograph • Make maximum use of SALT visibility window