Machine-learning Generated Catalog of Long Period Variables from Palomar Gattini-Infrared Lightcurves

<pre>A catalog of LPVs obtained from a decision tree classifier trained on features extracted from Palomar Gattini-IR J band <br>lightcurves as described in Suresh et. al. 2024 (https://arxiv.org/abs/2402.08000).<br><br>Description of columns<br><br>1. 'Name' - Unique identifier for each LPV; internal designation of the object<br>2. 'RA' - Right ascension<br>3. 'Dec' - Declination<br>4. 'num_detections' - number of detections<br><br>Calculated features:<br>5. 'von_neumann_score' - von-Neumann score <br>6. 'gp_score' - Gaussian process regression fit score<br>7. 'slope_min' - minimum slope of the lightcurve<br>8. 'slope_max' - maximum slope of the lightcurve<br>9. 'ptp' - peak-to-peak amplitude <br>10. 'nflips' - number of flips<br>11. 'max_rate' - maximum point-wise slope <br>12. 'min_rate' - minimum point-wise slope 13. 'lcdur' - observation baseline<br>14. 'per_diff_90_50' - difference between 90th and 50th percentiles of J band magnitude<br>15. 'per_diff_95_50' - difference between 95th and 50th percentiles of J band magnitude <br>16. 'J' - Stetson J index<br>17. 'K_s' - Stetson K index, calculated as single band data<br>18. 'K_m' - Stetson K index, calculated as multi-band data <br>19. 'L_s' - Stetson L index, calculated as single band data 20. 'L_m' - Stetson L index, calculated as multi-band data<br>21. 'phase_chisq' - chi sq of sinusiod fit to phase folded lightcurve<br>22. 'phase_redchi' - reduced chi sq of sinusiod fit to phase folded lightcurve <br>23. 'phase_aic' - akaike information criterion of sinusiod fit to phase folded lightcurve <br>24. 'phase_bic' - bayesian information criterion of sinusiod fit to phase folded lightcurve 25. 'bestperiod' - best fit Lomb-Scargle period <br>26. 'bestperiod_1' - second most likely Lomb-Scargle period<br>27. 'bestperiod_2' - third most likely Lomb-Scargle period<br>28. 'LSscore' - Lomb-Scargle score of best period <br>29. 'LSscore_2' - Lomb-Scargle score corresponding to second best period 30. 'LSscore_3' - Lomb-Scargle score corresponding to third best period <br>31. 'amplitude' - J band amplitude <br>32. 'meanF' - mean predicted value from Lomb-Scargle fit <br>33. 'chi2' - chi sq of sinusoidal fit to lightcurve<br>34. 'redchi2' - reduced chi square of sinusoidal fit to lightcurve<br>35. 'rednullchi2' - reduced chi square of linear fit to lightcurve 36. 'nullchi2' - chi square of linear fit to lightcurve<br>37. 'maxperiod' - maximum period from Lomb-Scargle fit <br>38. 'linear_slope' - slope of linear fit to lightcurve<br>39. 'linear_intercept' - y-intercept of linear fit to lightcurve<br>40. 'J_mag' - mean J band magnitude<br>41. 'LSratio' - ratio of Lomb-Scargle score of two most promiment peaks in <br> Lomb-Scargle periodogram<br>42. 'chi2ratio' - ratio of reduced chi square of sinusoidal fit and reduced <br> chi square of linear fit to lightcurve <br>43. 'period_ratio' - ratio of best fit Lomb-Scargle period and <br> maximum Lomb-Scargle period<br>44. 'prob_lpv_sum' - machine-learning classifier LPV score (obtained by summing probability of LPV and type II LPV)<br><br>Color information: 45. 'w1mpro' - WISE W1 mag<br>46. 'w1sigmpro' - WISE W1 error <br>47. 'w2mpro' - WISE W2 mag<br>48. 'w2sigmpro' - WISE W2 error <br>49. 'w3mpro' - WISE W3 mag<br>50. 'w3sigmpro' - WISE W3 error 51. 'w4mpro' - WISE W4 mag<br>52. 'w4sigmpro' - WISE W4 error<br>53. 'j_m' - 2MASS J mag <br>54. 'j_msigcom' - 2MASS J error<br>55. 'h_m' - 2MASS H mag <br>56. 'h_msigcom' - 2MASS H error<br>57. 'k_m' - 2MASS K mag 58. 'k_msigcom' - 2MASS K error<br>59. 'J-H' - 2MASS J-H<br>60. 'J-K' - 2MASS J-K 61. 'W1-W2' - WISE W1-W2 <br>62. 'W3-W4' - WISE W3-W4 <br>63. 'W1-W4' - WISE W1-W4</pre>