Strategies to identify strongly lensed type Ia supernovae in Rubin LSST

Prajakta Mane

Final year, Integrated BS-MS,

Indian Institute of Science Education and Research (IISER) Mohali, India

Joint SLSC/DESC-SL Telcon

Anupreeta More, Surhud More

Inter-University Centre for Astronomy and Astrophysics (IUCAA), India

April 17, 2024

Time delay cosmography:

\frac{D_d D_s}{D_{ds}} = \frac{1}{H_0} f(z_s, z_l, \Omega_m, \Omega_\Lambda )

accurate time delays, surface mass distribution and redshift of lens

Hubble constant with strong lensing time delays

well-constrained Hubble Constant

Why are SNe Ia a better source for TDC?

  • well-studied light curves -> more accurate time delay measurements

  • transient source -> improved constraints on the lens galaxy model

  • standard candle nature -> help overcome degeneracies

How to find lensed SNe Ia?

DIA: run LSST Stack's difference imaging pipeline to identify multiply imaged SNe

CMA: study outliers in the colour-magnitude space for SNe to identify lensed SNe Ia

\Delta t = \frac{D_d D_s}{cD_{ds}}(1+z_l)\Delta\tau \text{+ constant}
  • Raw exposures from Subaru Hyper-Suprime Cam (HSC) -> Public Data Release 1
  • UltraDeep Survey's COSMOS region, Tract number 9813 (~1.7 deg wide)
  • 149 visits in grizy from 10 nights in 2014 and 2015: 16,688 CCD images
  • LSST Science Pipeline w_2022_12
  • Strong lensing positions, magnifications, and time delays simulated using a code adapted from More & More, 2022
  • SNe light curves: SALT2 (Guy et al., 2007, 2010) template built in SNCosmo (Barbary et al., 2017) manually incorporating strong lensing observables

SNe light curve simulations

Sky data for DIA

Difference imaging analysis

Template Image

Science Image

Difference Image

Difference imaging analysis

Preliminary results

Template Image

Science Image

Difference Image

Yellow circles of radius 1": injected lensed SNe

Red circles of radius 2": diaSources

\text{unresolved quads}
\text{resolved doubles}
\text{unresolved}\\\text{doubles}

Difference imaging analysis

  • Total recovery fraction ~70%​​
  • Slightly higher for quads
  • Decreases significantly for the y-band
Injected Detected % recovery
Total 74k 51.5k 70
Doubles 70k 48.3k 70
Quads 4.1k 3.2k 78
g 310 260 83
r 5.4k 4.7k 86
i 14k 11k 80
z 21k 16k 76
y 34k 20k 58

Lens system level analysis:

Is there a diaSource within the radius of 3" from each lens center in each epoch?

Difference imaging analysis

Preliminary results

Recovery fraction variation with injected unresolved magnitude for each band

  • Recovery fraction decreases for fainter systems -> cutoff brightness.
  • Cutoff brightness varies across bands.

Lens system level analysis

Difference imaging analysis

Preliminary results

Individual image level analysis:

How many unique diaSources were found corresponding to each lens system?

A single diaSource for entire system: Pipeline could not resolve the system (DUR): ~49k

Two or more diaSources for a system: Pipeline could resolve the system (DR): 1285

Doubles

Quads

vertical dashed line: median seeing

Difference imaging analysis

Preliminary results

Color-magnitude analysis

Quimby et al. 2014

         : Unlensed SNIa

         : Unlensed core collapse

         : Lensed SNIa
         : Lensed core collapse

 

The redder supernovae for given i-band magnitude are more likely to be lensed SNeIa when studied for unresolved photometry on rising phase of light curve.

The black bold curve separates the lensed SNeIa from unlensed both on the rising and the falling edge of light curve for z < 2.4

The criteria hold well for the observed unlensed and lensed SNeIa.

Contamination from unlensed SNe is neglegible.

Contamination from CC SNe

Color-magnitude analysis

Contamination from unlensed SNe is neglegible.

Contamination from CC SNe

Color-magnitude analysis

Primary contaminants are lensed SNe Ib and Ic.

Summary so far...

  • Employed difference imaging pipeline recovers ~70% of the injected data of lensed SNe Ia. The recovery fraction decreases for fainter injected systems. It is slightly higher for quads and decreases significantly for the HSC y-band. The resolved fraction is weakly correlated with the angular separation of system for the doubles.
  • Colour-magnitude effectively selects lensed SNe Ia for simulated and observed (un-)lensed SNe Ia till redshift 2.4, both on rising and falling edge. Contamination from unlensed CC SNe is low. Primary contaminants are lensed CC SNe Ib and Ic.

Ongoing work

  • Combine detections across epochs and study trends.
  • Study if extendedness can be used as a marker for a lensed system.
  • Next DI run: Incorporate LSST cadence.
  • Run it on DC2 data.

Yellow circles of radius 1": injected lensed SNe

Red circles of radius 2": diaSources

Quad system

Difference imaging analysis

Preliminary results

Template Image

Science Image

Difference Image

Quadruply-imaged SN Ia

Max. separation: 2.78"

Total UR magnitude: 18.23

Template Image

Science Image

Difference Image

Yellow circles of radius 1": injected lensed SNe

Red circles of radius 2": diaSources

double system

Difference imaging analysis

Preliminary results

Extra slides

Extra slides

Extra slides

Extra slides

Difference imaging analysis

Resolved fraction with respect to median seeing of each band

\theta_{max} < \text{median seeing}
\text{Pipeline could not resolve}
\theta_{max} > \text{median seeing}
\text{Pipeline could not resolve}

Individual image level analysis:

Difference imaging analysis

Resolved fraction with respect to median seeing of each band

\theta_{max} > \text{median seeing}
\text{Pipeline could resolve}
\theta_{max} > \text{median seeing}
\text{Pipeline could resolve: only doubles}

some trend

Individual image level analysis

Difference imaging analysis

Resolved fraction with respect to median seeing of each band

\theta_{max} > \text{median seeing}
\text{Pipeline could resolve}
\theta_{max} > \text{median seeing}
\text{Pipeline could resolve: only quads}

no trend

Individual image level analysis

Comaparison of unlensed CC SNe CMDs from low and high redshift

PRJ 501: Recap

Quimby et al. 2014

PRJ 502

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