Servicios Básicos

The nightly photometry from the LT and LCO comes reduced (e.g., bias subtraction, flat fielding) through their own pipelines. This leaves photometric calibration down to the user. I developed a short pipeline to align and the calibrate the images in order to

process light curves of the objects observed. This pipeline utilises PYRAF as part of

theUREKApackage.

Standard star lists are obtained from the Sloan Digital Sky Survey data releases 4 – 9 and the American Association of Variable Star Observers Photometric All-sky Survey (APASS). The latter are observed in ugriz and the former in BV gri. Use of the SDSS stars is preferential as the fields are well observed, with sources to ∼ 24 mag, whereas the APASS fields can be sparse, with few stars in the field and a limit of ∼ 17 mag.

Host subtraction is desirable for some SNe, particularly if they explode in a bright

HII region. Without host subtraction the late time light curves (∼ hundred days) are

flattened as the host flux begins to dominate over the SN flux. At maximum light the host-flux is negligible compared to that of the SN. Unfortunately suitable frames for host subtraction require very good seeing conditions < 1.1 arcsec, a total of 15 – 20 minutes of exposure time per band, and be taken at least three years after the SN explodes. Hence, given that telescope time is limited, observations of new objects were prioritised over host-subtraction exposures for the two pre-2014 SNe.

Image preparation

The pipeline flow is shown in Figure 4.1 and was based upon the method described in Ashall et al. (2014). The pipeline starts aligning the nightly exposures to a reference

image (usually r) usingIRAF.DAOFINDto obtain the physical coordinates of sources

within the reference image and thenIRAF.IMALIGN to align the remaining exposures

to it. If there are multiple exposures in the same band these are then stacked using

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.fits images

iraf.imalign iraf.imcombine iraf.daofind

iraf.phot Match stars iraf.fitparams iraf.invertfit SN magnitude list Calibrated magnitudes FWHM-PSF choice FWHM-PSF loop iraf.daofind/

Figure 4.1: Flow diagram of the photometry pipeline. The “FWHM-PSF loop” is shown in blue, this loop is repeated for varying FWHM-PSF values between 1 and 20 pixels.

Finding instrumental magnitudes

The pipeline begins the “FWHM-PSF loop” – an iteration through a list of Full-width half-maximum (FWHM) values that define the point spread function (PSF) used, nor- mally 10 values in the range 1 – 20 pixels. This method evolved because measured FWHM of the SN did not always return well behaved photometry. Hence the range of FWHM values allows a variety of possibilities to be tested. Its value is seen further when, on rare occasions, just one FWHM-PSF value works.

The aligned frames and FWHM-PSF are passed to the main pipeline which usesIRAF.DAOFIND

to find all the sources in the frames. These sources are then passed toIRAF.PHOTwhich

performs aperture photometry using the FWHM-PSF to find the instrumental magni- tudes. These sources are then cross-correlated with the RA and DEC of the standard

stars and the supernova via a customPYTHONscript namedMATCH STARS which re-

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Photometric equations and calibration

This list is passed toIRAF.FITPARAMS which fits a simple linear equation in the form

of

minst= mstandard+ Zp (4.1)

where minstis the instrumental magnitude, mstandardthe magnitude of the standard star,

and Zp is the zero point, in order to compare the standard stars with the instrumental magnitudes and hence calibrate the photometry for a particular band. Note the absence of a colour term and an airmass term. The exposures are all at approximately the same airmass, so an airmass term would be effectively zero. On the other hand, a colour term based on the standard stars was originally used in Equation 4.1 in the form

minst= mstandard+ A + B × C (4.2)

where A and B are constants and C is a colour term based upon the calibrate magni- tudes of the standard stars (e.g., g − r or B − V ). A consistency check found that the form of the equation without the colour term returned calibrated magnitudes of the standard stars that were closer to measured magnitudes of those stars, or no worse. This is because, if one exposure of one of the reference bands in the colour term was poor, it would then affect the photometry for any other band where this term was used.

The photometric equations and instrumental magnitudes are then passed toIRAF.INVERTFIT

which applies the equations to the sources in the field and returns the calibrated magni- tudes. The calibrated magnitudes of the SN is extracted from the output and appended to a list

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Final output

The code then either repeats the “FWHM-PSF loop” with the next FWHM-PSF value or ends if this process is complete. If complete, the pipeline takes the median magni- tude for each band from the SN magnitude list as the calibrated photometry of the SN. Uncertainties on this value are either the standard deviation on the distribution of cal- ibrated magnitudes or the mean error from the fit to the photometric equations (these are the errors derived from the least-squares fit applied to find the parameters of the photometric equations)

Testing

The pipeline developed over the course of 2016 to 2017 and underwent a series of con- sistency checks during its development in order to determine its reliability. The key test was to ensure that the calibrated photometry was accurate. To do this, the magnitudes of the standard stars were compared with those output by the pipeline, as demonstrated in Figure 4.2. Typically, the pipeline output was found to return the magnitudes of the standard stars with a median percentage difference of < 2 percent. The best calibrated stars were those that were bright and unsaturated, while the scatter increased towards the magnitude limit defined by the exposure time and weather conditions of the night.

The final test is on the actual light curves themselves. If the pipeline is sensitive to systematics that result in significant (> a few percent) deviations in calibration then this would show as random scatter in the light curves, or offsets in the case of photometric observations taken at different latitudes. This is not seen, the light curves are well behaved when the standard stars are well behaved, the SN has a good S/N, and when the weather conditions are fine.

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Percentage difference

Number

Figure 4.2: Histogram of the percentage difference between r-band standard star magnitudes and calibrated magnitudes. The absolute mean of the distribution is 0.08 percent, the absolute median is 0.09 percent (magenta dotted line), and the standard deviation on the distribution is 2 percent.