Discovering Strongly-lensed QSOs From Unresolved Light Curves

Shu, Yiping; Belokurov, Vasily; Evans, N. Wyn

doi:10.48550/arxiv.2011.04667

Cited by 3 publications

(4 citation statements)

References 106 publications

(136 reference statements)

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“…A combination of these two approaches and crosschecks between their results offer the potential to deal with a broad range of transients. (While we focus on transients, combined lightcurves from quasars have been studied by, e.g., [23][24][25][26][27].) Future work will seek to improve further our approaches to classify various lensed transients and estimate their time delays.…”

Section: Discussionmentioning

confidence: 99%

Out of One, Many: Distinguishing Time Delays from Lensed Supernovae

Denissenya,

Bag,

Kim

et al. 2021

Preprint

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Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images and their time delayed and magnified fluxes may be unresolved, however, blended into a single lightcurve. We demonstrate methods without a fixed source template matching for extracting the individual images, determining whether there are one (no lensing) or two or four (lensed) images, and measuring the time delays between them that are valuable cosmological probes. We find 100% success for determining the number of images for time delays greater than ∼ 10 days.

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Section: Discussionmentioning

confidence: 99%

Out of One, Many: Distinguishing Time Delays from Lensed Supernovae

Denissenya,

Bag,

Kim

et al. 2021

Preprint

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“…Our approach is different than the one outlined by Geiger & Schneider (1996), Pindor (2005), and Shu et al (2020) in several respects. First, we use the fact that we have a statistical model for the light curve of quasars.…”

Section: Introductionmentioning

confidence: 89%

“…As discussed by Pindor (2005) and explained here, this is not always possible and requires a statistical model for the quasar variability. Recently, Shu et al (2020) demonstrated that a modified version of the auto-correlation function can recover the time delays of real systems with a success rate of about 20%.…”

Section: Introductionmentioning

confidence: 99%

Measuring time delays: I. Using a flux time series that is a linear combination of time-shifted light curves

Springer,

Ofek

2021

Preprint

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Several phenomena in astrophysics generate light curves with time delays. Among these are reverberation mapping, and lensed quasars. In some of these systems, the measurement of the time-delay is complicated by the fact that the delayed components are unresolved and that the light curves are generated from a red-noise process. We derive the likelihood function of the observations given a model of either a combination of time-delayed light curves or a single light curve (i.e., the null hypothesis). This likelihood function is different from the auto-correlation function investigated by previous studies. We demonstrate that given a single-band light curve that is a linear combination of two (or more) time-shifted copies of an original light curve, generated from a red-noise probability distribution, it is possible to test if the total-flux light curve is a composition of time-delayed copies or, alternatively, is consistent with being a single copy of the original light curve. We also demonstrate that, in some realistic cases, it is possible to measure the time delays and flux ratios between these unresolved components even when the flux ratio is about 1/10. In the era of synoptic sky surveys, this method is useful for identifying lensed quasars and simultaneously measuring their time delays, and also for estimating the reverberation time scales of active galactic nuclei. In a companion paper, we build on these results to derive another method that uses the center-of-light astrometric position (e.g., of a lensed quasar) along with the combined flux. The combined flux and astrometry allow us to identify lensed quasars and supernovae and measure their time delays, with potentially higher fidelity compared to the flux-only method described in the current work. The astrometry + flux method, however, is not suitable for quasar reverberation mapping. We also comment on the commonly used method of fitting a power-law model to a power spectrum, and present the proper likelihood function for such a fit. We test the new method on simulations and provide Python and MATLAB implementations.

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“…For example, demonstrated that ignoring the correlations in quasar light curves results in significant underestimation of the time-delay uncertainties. Alternatively, Geiger & Schneider (1996), Pindor (2005) and Shu et al (2020) suggested using the auto-correlation (or related) function of the combined light curve of lensed quasars to measure their time delay. In Paper I (Springer & Ofek) we derive the likelihood function of the combined-flux of several time delayed light curves, given the free parameters (e.g., time delay, flux ratio).…”

Section: Introductionmentioning

confidence: 99%

Measuring time delays: II. Using observations of the unresolved flux and astrometry

Springer,

Ofek

2021

Preprint

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Lensed quasars and supernovae can be used to study galaxies' gravitational potential and measure cosmological parameters. The typical image separation of objects lensed by galaxies is of the order of 0.5 ′′ . Therefore, finding the ones with small separations, and measuring their time-delays using ground-based observations is challenging. We suggest a new method to identify lensed quasars and simultaneously measure their time-delays, using seeinglimited synoptic observations in which the lensed quasar images and the lensing galaxy are unresolved. We show that using the light curve of the combined flux, and the astrometric measurements of the center-of-light position of the lensed images, the lensed nature of a quasar can be identified, and its time-delay can be measured. We provide the analytic formalism to do so, taking into account the measurement errors and the fact that the power spectra of quasar light curves is red (i.e., the light curve is highly correlated). We demonstrate our method on simulated data, while its implementation to real data will be presented in future papers. Our simulations suggest that, under reasonable assumptions, the new method can detect unresolved lensed quasars and measure their time delays, even when the image separation is below 0.1 ′′ , or the flux ratio between the faintest and brightest images is as low as 0.03. Python and MATLAB implementations are provided. In a companion paper, we present a method for measuring the time delay using the combined flux observations. Although the flux-only method is less powerful, it may be useful in cases in which the astrometric information is not relevant (e.g., reverberation mapping).

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Discovering Strongly-lensed QSOs From Unresolved Light Curves

Cited by 3 publications

References 106 publications

Out of One, Many: Distinguishing Time Delays from Lensed Supernovae

Out of One, Many: Distinguishing Time Delays from Lensed Supernovae

Measuring time delays: I. Using a flux time series that is a linear combination of time-shifted light curves

Measuring time delays: II. Using observations of the unresolved flux and astrometry

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