# Presentation: 551100

## SDSS-II Supernova Survey

- Josh Frieman
- Leopoldina Dark Energy Conference
- October 8, 2008

- See also: poster by Hubert Lampeitl, talk by Bob Nichol

## SN Models and Observations

- SN cosmology based on a purely empirical approach (Phillips)
- SN observations over the last decade have strengthened evidence for cosmic
-       acceleration, but dark energy constraints now dominated by systematic errors
- SNe will be one of 3 dark energy probes pursued by JDEM
- Reaching JDEM level of precision for SNe will require improved control
-       of systematics
- Improved SN modeling, better empirical approaches to estimating SN distances,
-       and better data are all important weapons in the arsenal to reduce systematics
- Current empirical distance estimators are limited by the paucity of high-quality
-       input/training data. The situation is improving (CfA, CSP, KAIT, SNF, SDSS),
-       but we need better, homogeneous data at low/intermediate redshifts and a
-       systematic approach to ingesting them to build better empirical estimators.
-       Will current ground-based SN surveys deliver what we need for JDEM?

- Published Light Curves for Nearby Supernovae

- Nearby SNe used to train distance estimators and
- anchor Hubble
- diagram
- Heterogeneous published sample, subject to various
- selection biases

## Cosmic Acceleration

- Discovery from
- High-redshift
- SNe Ia
- SNe at *z*~0.5 are 25% fainter than in an open Universe with same value of
- m

-  = 0.7
-  = 0.
- m = 1.

- Technological Redshift Desert:
- Possible photometric offsets between low- and high-redshift data

- Desert still there 10 years later

## SDSS II Supernova Survey Goals

- Obtain few hundred *high-quality* SNe Ia light curves in the `redshift desert’ *z*~0.05-0.4 for continuous Hubble diagram
- Spectroscopic follow-up for redshifts, SN typing, and to study diversity of SN features
- Probe Dark Energy and systematics in redshift range complementary to other surveys
- Well-observed, homogeneous sample to anchor Hubble diagram & train distance estimators
- Large survey volume: rare & peculiar SNe, probe outliers of population to test SN models

- Frieman, et al (2008); Sako, et al (2008)

- Spectroscopic follow-up telescopes

- R. Miquel, M. Molla

_**CfA team**_

## Searching For Supernovae

*g*
*r*
*i*

- 2005
- 118,693 objects scanned
- 10,937 unique candidates
- 130 confirmed Ia
- 2006
- 14,430 scanned
- 3,694 candidates
- 193 confirmed Ia
- 2007
- 13,613 scanned
- 3,962 candidates
- 175 confirmed Ia

- Positional match to remove movers
- Insert fake SNe to monitor efficiency

- B. Dilday

## Redshift Distribution for SNe Ia

- and counting

- Well-sampled, multi-band light curves, including measurements before peak light

- SDSS
- SN
- Light-
- curves
- Holtzman
- et al (2008)

## Spectroscopic Target Selection

- _2 Epochs_
- _SN Ia Fit_
- _SN Ibc Fit_
- _SN II Fit_

- Sako etal 2008

**Notes:**
Talk by Masao
Poster by Ben

chi2 high because there is no model uncertianty
and no zpt (systematic) contribution to data pts

## Spectroscopic Target Selection

- _2 Epochs_
- _SN Ia Fit_
- _SN Ibc Fit_
- _SN II Fit_

- _31 Epochs_
- _SN Ia Fit_
- _SN Ibc Fit_
- _SN II Fit_

- Fit with
- template
- library
- Classification
- >90%
- accurate after
- 2-3 epochs
- Redshifts
- 5-10%
- accurate
- Sako etal 2008

**Notes:**
Talk by Masao
Poster by Ben

chi2 high because there is no model uncertianty
and no zpt (systematic) contribution to data pts

## SN and Host Spectroscopy

- MDM 2.4m
- NOT 2.6m
- APO 3.5m
- NTT 3.6m
- KPNO 4m
- WHT 4.2m
- Subaru 8.2m
- HET 9.2m
- Keck 10m
- Magellan 6m
- TNG 3.5m
- SALT 10m

- 2005+2006

**Notes:**
Until we have photo-z for supernovae, need spec followup.

## SDSS SN Ia Spectra

- ~1000 spectra taken over 3 seasons

- Zheng et al (2008)

## Fitting SN light curves I: MLCS2k2

- Multicolor Light Curve Shape *(Riess et al '98; Jha et al '07)*
- Model SN light curves as a single parameter family, trained on low-*z* UBVRI data from the literature* *
- Assumes SN color variations are due to dust extinction, _subject to prior_

*fit parameters*

*time-dependent model “vectors”*

- Time of maximum     _distance modulus_         dust law   extinction    stretch/decline rate

- P(Av)

## MLCS2k2 model templates

- ∆ =  -0.3: bright, broad
- ∆ = +1.2:  faint, narrow

*Jha et al, 2007*

## Fitting SN Light curves II: SALT2

-  Fit each light curve using rest-frame *spectral* surfaces*:
-  Transform to observer frame:
-  Light curves fit individually, but distances only estimated globally:
- *Not trained just on low-redshift data; distances are cosmology-dependent,  flat priors on model parameters

- Global fit parameters, determined along with cosmological parameters

- color term

*Guy et al*

- light-curve shape

- Light Curve Fitting with MLCS2k2 and SALT2

## Monte Carlo Simulations match data distributions

- Use actual observing conditions (local sky, zero-points, PSF, etc)

## Model Spectroscopic & Photometric Efficiency

- Redshift distribution for all SNe passing photometric selection cuts (spectroscopically complete sample)
- Data
- Need to model biases due to what’s missing
- Difficult to model spectroscopic selection

## Extract AV Distribution from SDSS

- Extract *A**V* Distribution from SDSS

- (no prior)

## Extract RV distribution from SDSS SN data

- MLCS previously used Milky Way avg *R**V*=3.1
- Lower *R**V* more consistent with SALT2 color law
- Not conventional dust

## Preliminary Cosmology Results

- Kessler, Becker, et al. 2008

-   *w*
- open

## Issues with rest-frame U band

- Data vs. SALT2 Model Residuals
- Similar Low-z vs. High-z discrepancy seen in MLCS
- MLCS trained only on Low-z, SALT2 model dominated by SNLS
- Similar differences seen in rest-frame UV spectra (Foley et al)

- epoch

- SN Ia vs. Host Galaxy Properties: I

- Smith et al

- Bright                        SN Luminosity/Decline Rate                         Faint

- SN Ia vs. Host Galaxy Properties: II

- Smith et al

- Color/reddening

- Is reddening
- local to the
- SN environment?

## SN Ia vs. Host Galaxy Properties: III

- Smith et al

- Preliminary

- Two SN Ia
- Populations?
- Implications
- for SN
- cosmology:
- host-galaxy
- population
- evolution

## Future: Improved SN Ia Distances

- Train
- Fitters

- Fit Cosmology