license: gpl-3.0
Simulated Light Curves for Strong Gravitational Lensing
This mock dataset simulates light curves for strong gravitational lensing (optical data). Each file contains pairs of light curves with a time delay of five days (DS-5).
Table: Simulated Large Scale Data Sets
| Noise | Gap Size 0 | Gap Size 1 | Gap Size 2 | Gap Size 3 | Gap Size 4 | Gap Size 5 |
|---|---|---|---|---|---|---|
| 0% | 1 | 10 | 10 | 10 | 10 | 10 |
| 0.036% | 50 | 50 | 50 | 50 | 50 | 50 |
| 0.106% | 50 | 50 | 50 | 50 | 50 | 50 |
| 0.466% | 50 | 50 | 50 | 50 | 50 | 50 |
| Sub-Total | 151 | 1510 | 1510 | 1510 | 1510 | 1510 |
Total = 7,701 data sets per underlying function.
5 underlying functions yield 38,505 data sets.
File Naming Convention
Files follow this notation:
DS-5-<Function>-GAP-<GapSize>-<Realization>-N-<NoiseLevel>
Explanation of Components:
- DS-5: Indicates that the true time delay is five days.
- Function (
<Function>): Represents the underlying function number (ranges from1to10). - GAP (
<GapSize>): Indicates the number of removed points:0: No gap.1-5: Different gap sizes.
- Realization (
<Realization>): Represents different random gap realizations (ranges from1to10). - N (
<NoiseLevel>): Represents the noise level:0: No noise.1-3: Different noise levels.
Example
DS-5-1-GAP-0-1-N-0
DS-5: True time delay of five days.1: First underlying function.GAP-0: No gaps.1: First realization.N-0: No noise.
Each pair of light curves is divided into five blocks before applying the gap procedure.
Plots
Noise level 2 = 0.106%

Noise level 3 = 0.466%

Underlying fuction 1

Underlying fuction 2

Underlying fuction 3

Underlying fuction 4

Underlying fuction 5

Underlying fuction 6

Underlying fuction 7

Underlying fuction 8

Underlying fuction 9

Underlying fuction 10

If you use this dataset, please cite the following paper:
Cuevas-Tello, J. C., Tiňo, P., Raychaudhury, S., Yao, X., & Harva, M.
Uncovering delayed patterns in noisy and irregularly sampled time series: An astronomy application.
Pattern Recognition, 43(3), 1165-1179 (2010).
DOI: 10.1016/j.patcog.2009.07.016
BibTeX Citation
@article{CUEVASTELLO20101165,
title = {Uncovering delayed patterns in noisy and irregularly sampled time series: An astronomy application},
author = {Juan C. Cuevas-Tello and Peter Tiňo and Somak Raychaudhury and Xin Yao and Markus Harva},
journal = {Pattern Recognition},
volume = {43},
number = {3},
pages = {1165-1179},
year = {2010},
issn = {0031-3203},
doi = {10.1016/j.patcog.2009.07.016}
}