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Databáze známých zákrytových dvojhvěd podle O-C brány
V níže uvedeném seznamu jsou uvedeny všechny známé zákrytové dvojhvězdy, jejich souřadnice, elementy a míra sledovanosti v posledních 10ti letech
Data jsou převzata z O-C brány, administrátor databáze je Anton Paschke.
And, Ant, Aps, Aql, Aqr, Ara, Ari, Aur, Boo, Cae, Cam, Cap, Car, Cas, Cen, Cep, Cet, Cir, CMa, CMi, Cnc, Col, Com, CrA, CrB, Crt, Cru, Crv, CVn, Cyg, Del, Dor, Dra, Equ, Eri, For, Gem, Gru, Her, Hor, Hya, Hyi, Cha, Ind, Lac, Leo, LMi, Lep, Lib, Lup, Lyn, Lyr, Men, Mic, Mon, Mus, Nor, Oct, Oph, Ori, Pav, Peg, Per, Phe, Pic, Psc, PsA, Pup, Pyx, Ret, Sco, Scl, Sct, Ser, Sex, Sge, Sgr, Tau, Tel, Tri, TrA, Tuc, UMa, UMi, Vel, Vir, Vol, Vul,
| STAR Oph
|
|
N10 |
N |
PERIOD |
MIN0 |
RA 2000 |
DE 2000 |
MAX |
MINP |
MINS |
|
|
| U | p | 1 | 20 | 759 | 1.67734617 | 44416.3864 | 17:16:31.72 | +1:12:38 | 5.84 | 6.56 | 6.46 | V | predict |
| U | s | 1 | 20 | 759 | 1.67734617 | 44417.2251 | 17:16:31.72 | +1:12:38 | 5.84 | 6.56 | 6.46 | V | predict |
| RV | p | 7 | 3 | 144 | 3.687122 | 23997.38 | 17:34:34.95 | +7:14:49.2 | 9.42 | 11.44 | 11.44 | V | predict |
| RZ | p | 10 | 0 | 76 | 261.9277 | 42204.39 | 18:45:46.38 | +7:13:12.3 | 9.65 | 10.42 | 10.42 | V | predict |
| SW | p | 3 | 7 | 58 | 2.44607 | 55673.8374 | 16:16:28.05 | -6:58:43.7 | 10.6 | 11.7 | 11.7 | P | predict |
| SX | p | 1 | 11 | 55 | 2.0633038 | 33399.557 | 16:17:55.5 | -6:39:52.1 | 11.8 | 12.3 | 12.3 | P | predict |
| SZ | p | 9 | 1 | 29 | 3.70851 | 45485.48 | 17:15:2.76 | -8:3:27.3 | 10.7 | 12.2 | 12.2 | P | predict |
| UU | p | 6 | 4 | 5 | 4.396797 | 20750.489 | 16:57:22.64 | -25:47:58.5 | 10.2 | 12 | 10.3 | V | predict |
| WZ | p | 1 | 9 | 119 | 4.183506 | 53901.4151 | 17:6:39.04 | +7:46:57.8 | 9.14 | 9.82 | 9.82 | V | predict |
| WZ | s | 1 | 9 | 119 | 4.183506 | 53982.9931 | 17:6:39.04 | +7:46:57.8 | 9.14 | 9.82 | 9.82 | V | predict |
| AF | p | 9 | 1 | 2 | 8.8981 | 52768.73 | 17:17:38.95 | +4:14:53.1 | 12.9 | 13.6 | 13 | V | predict |
| AL | p | 6 | 4 | 17 | 0.992999 | 50243.43 | 17:26:45.33 | +12:57:57 | 14.1 | 15 | 15 | P | predict |
| AL | s | 6 | 4 | 17 | 0.992999 | 50321.3896 | 17:26:45.33 | +12:57:57 | 14.1 | 15 | 15 | P | predict |
| CY | p | 10 | 0 | 3 | 16.355 | 51931.924 | 16:56:5.9 | -28:21:48.5 | 10.59 | 11.09 | 11.01 | V | predict |
| CY | s | 10 | 0 | 3 | 16.355 | 51936.765 | 16:56:5.9 | -28:21:48.5 | 10.59 | 11.09 | 11.01 | V | predict |
| FG | p | 10 | 0 | 1 | 2.10375 | 51938.452 | 17:2:20.05 | -25:22:28.6 | 12.23 | 12.84 | 12.4 | V | predict |
| LL | p | 10 | 0 | 1 | 2.7925 | 52468.615 | 16:55:34.88 | -27:54:47.1 | 12.8 | 13.6 | 12.9 | V | predict |
| V 378 | p | 10 | 0 | 28 | 70.46 | 49154.5 | 17:49:4.83 | +5:0:31.7 | 13.8 | 15.8 | 14.2 | P | predict |
| V 378 | s | 10 | 0 | 28 | 70.46 | 27699.25 | 17:49:4.83 | +5:0:31.7 | 13.8 | 15.8 | 14.2 | P | predict |
| V 391 | p | 6 | 4 | 25 | 2.895561 | 53171.523 | 17:58:9.13 | +4:39:27.6 | 11.5 | 15 | 11.5 | P | predict |
| V 415 | p | 8 | 2 | 21 | 2.537145 | 43199.585 | 18:1:3.98 | +1:11:23 | 14.6 | 15.4 | 15.4 | P | predict |
| V 423 | p | 7 | 3 | 21 | 1.2037875 | 27236.459 | 18:6:16.46 | +0:33:31.4 | 11 | 12 | 12 | P | predict |
| V 441 | p | 8 | 2 | 6 | 3.058525 | 53932.399 | 17:20:52.71 | -17:20:5.2 | 11.6 | 15.5 | 15.5 | P | predict |
| V 448 | p | 4 | 6 | 14 | 1.819698 | 53915.38 | 17:15:20.78 | -18:6:57.3 | 12.2 | 13.8 | 12.2 | P | predict |
| V 451 | p | 1 | 16 | 141 | 2.19659616 | 44834.365 | 18:29:14.04 | +10:53:31.4 | 7.86 | 8.46 | 8.23 | P | predict |
| V 451 | s | 1 | 16 | 141 | 2.19659616 | 53575.7235 | 18:29:14.04 | +10:53:31.4 | 7.86 | 8.46 | 8.23 | P | predict |
| V 456 | p | 1 | 29 | 85 | 1.016001 | 41897.532 | 18:43:5.82 | +8:50:23.3 | 10.2 | 10.7 | 10.5 | P | predict |
| V 456 | s | 1 | 29 | 85 | 1.016001 | 41898.04 | 18:43:5.82 | +8:50:23.3 | 10.2 | 10.7 | 10.5 | P | predict |
| V 487 | p | 8 | 2 | 13 | 3.13583516 | 44486.235 | 18:2:33.66 | +1:47:47.9 | 12.8 | 14.1 | 14.1 | P | predict |
| V 496 | p | 5 | 5 | 28 | 2.57587 | 55739.8123 | 18:10:14.63 | +3:8:42 | 14.3 | 15.7 | 15.7 | P | predict |
| V 501 | p | 4 | 6 | 173 | 0.96795 | 52836.4316 | 18:18:35.56 | +14:13:42.7 | 10.9 | 11.8 | 11.1 | V | predict |
| V 501 | s | 4 | 6 | 173 | 0.96795 | 30911.879 | 18:18:35.56 | +14:13:42.7 | 10.9 | 11.8 | 11.1 | V | predict |
| V 502 | p | 1 | 19 | 151 | 0.453387 | 48500.119 | 16:41:20.86 | +0:30:27.4 | 8.34 | 8.84 | 8.81 | V | predict |
| V 502 | s | 1 | 19 | 151 | 0.453387 | 48500.34569 | 16:41:20.86 | +0:30:27.4 | 8.34 | 8.84 | 8.81 | V | predict |
| V 506 | p | 1 | 79 | 144 | 1.0604275 | 54137.0212 | 17:41:4.19 | +7:47:4.3 | 11.2 | 12 | 12 | P | predict |
| V 506 | s | 1 | 79 | 144 | 1.0604275 | 54179.9684 | 17:41:4.19 | +7:47:4.3 | 11.2 | 12 | 12 | P | predict |
| V 509 | p | 10 | 0 | 0 | 1.223458 | 54284.48 | 18:0:3.2 | +3:27:20 | 12.6 | 13.8 | 13.8 | V | predict |
| V 511 | p | 7 | 3 | 32 | 1.0657 | 26413.605 | 18:8:19.25 | +2:25:30.8 | 13.4 | 15.2 | 13.7 | P | predict |
| V 524 | p | 9 | 1 | 2 | 0.308926 | 28778.347 | 17:29:48.74 | -28:57:31 | 13 | 13.8 | 13.8 | P | predict |
| V 526 | p | 10 | 0 | 2 | 3.489561 | 51936.884 | 17:32:52.66 | -28:38:20.7 | 13.2 | 13.8 | 13.6 | P | predict |
| V 527 | p | 10 | 0 | 1 | 0.774704 | 28346.504 | 17:33:59.52 | -29:49:46.7 | 14.4 | 15.4 | 14.8 | P | predict |
| V 528 | p | 7 | 3 | 5 | 5.41098 | 53919.495 | 17:37:11.48 | -29:50:21.5 | 12.6 | 13.7 | 13.7 | P | predict |
| V 528 | s | 7 | 3 | 5 | 5.41098 | 28403.99666 | 17:37:11.48 | -29:50:21.5 | 12.6 | 13.7 | 13.7 | P | predict |
| V 529 | p | 10 | 0 | 1 | 27.8485 | 24732.8 | 17:41:56.62 | -28:18:9.8 | 13.2 | 16.5 | 16.5 | P | predict |
| V 535 | p | 10 | 0 | 2 | 6.05539 | 27959.505 | 17:32:10.18 | -29:26:0.3 | 11.3 | 13.6 | 13.6 | P | predict |
| V 537 | p | 9 | 1 | 3 | 1.147202 | 52053.717 | 17:33:36.94 | -28:20:9.7 | 12.1 | 12.7 | 12.4 | V | predict |
| V 572 | p | 10 | 0 | 18 | 2.4306039 | 49927.46 | 18:4:18.33 | +2:6:18.7 | 15.4 | 16.6 | 16.6 | P | predict |
| V 573 | p | 8 | 2 | 17 | 4.352269 | 51282.45 | 18:6:5.38 | +2:5:43.8 | 13.1 | 16.1 | 16.1 | P | predict |
| V 577 | p | 4 | 6 | 27 | 6.079096 | 52427.5226 | 18:16:45.85 | +6:54:18.2 | 11.36 | 12 | 11.9 | B | predict |
| V 577 | s | 4 | 6 | 27 | 6.079096 | 51385.4339 | 18:16:45.85 | +6:54:18.2 | 11.36 | 12 | 11.9 | B | predict |
| V 586 | p | 10 | 0 | 17 | 2.694116 | 51669.478 | 18:27:13.94 | +4:17:15.3 | 13.3 | 15.8 | 15.8 | P | predict |
| V 590 | p | 10 | 0 | 3 | 0.826876 | 29401.536 | 18:27:31.35 | +9:12:26.3 | 13.4 | 13.7 | 13.6 | P | predict |
| V 590 | s | 10 | 0 | 3 | 0.826876 | 52086.469 | 18:27:31.35 | +9:12:26.3 | 13.4 | 13.7 | 13.6 | P | predict |
| V 636 | p | 10 | 0 | 6 | 2.233265 | 51273.895 | 18:36:41.47 | +10:28:21.5 | 13.5 | 15.7 | 15.7 | P | predict |
| V 709 | p | 1 | 9 | 15 | 3.045175 | 48092.37 | 16:28:2.8 | -4:12:57 | 11.9 | 13.4 | 12 | P | predict |
| V 735 | p | 7 | 3 | 31 | 3.20521 | 26894.517 | 17:7:48.97 | +9:33:9.2 | 10.5 | 11.6 | 10.6 | P | predict |
| V 751 | p | 10 | 0 | 1 | 1.07285 | 51277.923 | 17:21:35.16 | +3:8:53.1 | 14 | 15 | 15 | P | predict |
| V 752 | p | 9 | 1 | 42 | 1.836643 | 51322.413 | 17:21:23.55 | +10:37:47.2 | 13.2 | 14.6 | 13.2 | P | predict |
| V 760 | p | 9 | 1 | 19 | 1.561533 | 49193.496 | 17:25:14.19 | +9:39:10.1 | 13.9 | 20.9 | 13.9 | P | predict |
| V 806 | p | 10 | 0 | 6 | 15.4065 | 48853.389 | 17:40:53.17 | -16:57:37.7 | 11.6 | 13 | 13 | V | predict |
| V 831 | p | 10 | 0 | 1 | 0.62616 | 51274.95 | 17:49:46.35 | +8:10:50.9 | 13.8 | 14.9 | 14.9 | P | predict |
| V 846 | p | 9 | 1 | 3 | 3.126721 | 52727.85 | 17:39:40.87 | -28:51:12.1 | 9.9 | 10.6 | 9.9 | V | predict |
| V 913 | p | 2 | 8 | 94 | 1.917387 | 55423.3714 | 17:55:3.59 | +14:10:39.2 | 11.5 | 14.5 | 14.5 | P | predict |
| V 916 | p | 9 | 1 | 34 | 3.11481 | 52839.533 | 18:22:49.5 | +4:7:55.4 | 11.4 | 13.3 | 13.3 | P | predict |
| V 920 | p | 10 | 0 | 7 | 1.5505 | 29114.415 | 18:28:20.23 | +8:30:5.6 | 15.1 | 15.9 | 15.9 | P | predict |
| V 920 | s | 10 | 0 | 7 | 1.5505 | 29115.19 | 18:28:20.23 | +8:30:5.6 | 15.1 | 15.9 | 15.9 | P | predict |
| V 924 | p | 10 | 0 | 5 | 0.359554 | 29135.354 | 18:33:28.29 | +7:57:50.8 | 15.7 | 16.4 | 16.4 | P | predict |
| V 924 | s | 10 | 0 | 5 | 0.359554 | 30200.535 | 18:33:28.29 | +7:57:50.8 | 15.7 | 16.4 | 16.4 | P | predict |
| V 929 | p | 10 | 0 | 4 | 2.3401 | 30207.451 | 18:40:56.4 | +8:17:51 | 15.5 | 16.1 | 15.5 | c | predict |
| V 930 | p | 10 | 0 | 4 | 1.397553 | 30146.478 | 18:41:45.66 | +12:2:11.1 | 14.2 | 14.8 | 14.8 | P | predict |
| V 940 | p | 10 | 0 | 11 | 0.433226 | 29785.408 | 17:53:6.21 | +7:41:20.2 | 14.8 | 15.8 | 15.6 | P | predict |
| V 940 | s | 10 | 0 | 11 | 0.433226 | 29845.413 | 17:53:6.21 | +7:41:20.2 | 14.8 | 15.8 | 15.6 | P | predict |
| V 941 | p | 8 | 2 | 21 | 1.2497107 | 48801.486 | 17:53:30.88 | +7:41:27.4 | 16 | 16.6 | 16.5 | P | predict |
| V 941 | s | 8 | 2 | 21 | 1.2497107 | 48802.111 | 17:53:30.88 | +7:41:27.4 | 16 | 16.6 | 16.5 | P | predict |
| V 947 | p | 6 | 4 | 25 | 0.7977454 | 53583.659 | 18:2:5.33 | +5:52:45.7 | 15.25 | 15.6 | 15.45 | P | predict |
| V 954 | p | 9 | 1 | 8 | 0.2252705 | 55014.807 | 18:9:23.02 | +1:23:4.3 | 14.3 | 14.9 | 14.9 | P | predict |
| V 954 | s | 9 | 1 | 8 | 0.2252705 | 29785.524 | 18:9:23.02 | +1:23:4.3 | 14.3 | 14.9 | 14.9 | P | predict |
| V 963 | p | 10 | 0 | 11 | 0.264743 | 29785.523 | 18:15:18.39 | +6:47:12.8 | 14.6 | 15.1 | 15.1 | P | predict |
| V 968 | p | 10 | 0 | 30 | 0.7232656 | 49215.413 | 18:19:21.64 | +3:22:11.3 | 14.3 | 15.2 | 15.2 | P | predict |
| V 968 | s | 10 | 0 | 30 | 0.7232656 | 49215.8 | 18:19:21.64 | +3:22:11.3 | 14.3 | 15.2 | 15.2 | P | predict |
| V 969 | p | 9 | 1 | 23 | 0.60146118 | 55045.4115 | 18:20:17.85 | +3:30:31.6 | 13.5 | 13.9 | 13.8 | B | predict |
| V 981 | p | 6 | 4 | 28 | 1.428512 | 36069.259 | 17:48:50.43 | +11:24:27.5 | 13.1 | 14.2 | 13.5 | P | predict |
| V 983 | p | 10 | 0 | 7 | 8.4449 | 52092.359 | 17:55:38 | +2:28:41.4 | 10.06 | 10.45 | 10.43 | V | predict |
| V 983 | s | 10 | 0 | 7 | 8.4449 | 52098.532 | 17:55:38 | +2:28:41.4 | 10.06 | 10.45 | 10.43 | V | predict |
| V 987 | p | 10 | 0 | 7 | 2.20285 | 47736.447 | 18:14:36.93 | +2:23:0.8 | 14.45 | 15.05 | 14.65 | B | predict |
| V1001 | p | 8 | 2 | 4 | 1.789753 | 52787.85 | 16:32:33.76 | -15:25:14 | 14.5 | 16.1 | 16.1 | P | predict |
| V1010 | p | 1 | 27 | 442 | 0.66143 | 55758.3547 | 16:49:27.67 | -15:40:4.7 | 6.1 | 7 | 6.46 | V | predict |
| V1010 | s | 1 | 27 | 442 | 0.66143 | 55757.3644 | 16:49:27.67 | -15:40:4.7 | 6.1 | 7 | 6.46 | V | predict |
| V1016 | p | 1 | 10 | 42 | 0.407161 | 54984.8212 | 16:16:38.39 | -5:21:17.8 | 13.1 | 14.1 | 14.1 | P | predict |
| V1016 | s | 1 | 10 | 42 | 0.407161 | 53552.6465 | 16:16:38.39 | -5:21:17.8 | 13.1 | 14.1 | 14.1 | P | predict |
| V1022 | p | 4 | 6 | 7 | 0.2394017 | 44441.5624 | 16:21:21.32 | -4:3:10 | 15.1 | 16.12 | 15.95 | B | predict |
| V1022 | s | 4 | 6 | 7 | 0.2394017 | 54984.6958 | 16:21:21.32 | -4:3:10 | 15.1 | 16.12 | 15.95 | B | predict |
| V1065 | p | 4 | 6 | 21 | 9.85745 | 51274.591 | 17:38:53.1 | +10:23:31.9 | 11.99 | 12.84 | 12.32 | V | predict |
| V1076 | p | 10 | 0 | 9 | 1.874345 | 43195.598 | 17:51:2.09 | +6:27:39.6 | 15.7 | 18 | 18 | B | predict |
| V1080 | p | 10 | 0 | 14 | 4.873579 | 48862.362 | 17:56:48.44 | +6:26:12.7 | 15.4 | 17.8 | 15.4 | P | predict |
| V1087 | p | 10 | 0 | 1 | 0.5872985 | 48100.367 | 18:3:36.33 | +3:4:18.9 | 15.1 | 16.2 | 15.1 | p | predict |
| V1102 | p | 10 | 0 | 12 | 2.2155274 | 38553.49 | 18:17:41.7 | +5:31:11 | 16 | 17 | 17 | P | predict |
| V1120 | p | 6 | 4 | 6 | 0.33675319 | 29298.575 | 16:9:59.64 | -6:34:12.7 | 13.9 | 14.4 | 14.3 | P | predict |
| V1120 | s | 6 | 4 | 6 | 0.33675319 | 29298.407 | 16:9:59.64 | -6:34:12.7 | 13.9 | 14.4 | 14.3 | P | predict |
| V1125 | p | 1 | 9 | 50 | 0.911629 | 55283.933 | 16:55:6 | +11:33:2 | 11 | 11.5 | 11.5 | P | predict |
| V1125 | s | 1 | 9 | 50 | 0.911629 | 38901.5 | 16:55:6 | +11:33:2 | 11 | 11.5 | 11.5 | P | predict |
| V1171 | p | 10 | 0 | 1 | 0.91165 | 52389.433 | 16:59:15.64 | -18:12:43.9 | 14.2 | 14.7 | 14.7 | P | predict |
| V1879 | p | 9 | 1 | 1 | 4.8167 | 53606.615 | 17:20:2.86 | -20:58:13.1 | 13.4 | 14 | 14 | V | predict |
| V1927 | p | 10 | 0 | 2 | 4.08851 | 35960.916 | 17:21:13.58 | -18:25:12.8 | 13.8 | 15 | 15 | P | predict |
| V2036 | p | 10 | 0 | 18 | 6.787649 | 47770.344 | 18:8:39.38 | +6:15:38.2 | 14.1 | 16.2 | 16.2 | P | predict |
| V2051 | p | 10 | 0 | 4 | 0.06242786 | 45115.75448 | 17:8:19.11 | -25:48:30.3 | 13 | 17.5 | 17 | V | predict |
| V2056 | p | 10 | 0 | 6 | 4.2549086 | 47368.474 | 17:41:34.83 | -0:35:40.5 | 13.7 | 15.9 | 13.9 | P | predict |
| V2056 | s | 10 | 0 | 6 | 4.2549086 | 51276.601 | 17:41:34.83 | -0:35:40.5 | 13.7 | 15.9 | 13.9 | P | predict |
| V2117 | p | 10 | 0 | 4 | 2.34375 | 52157.403 | 17:59:24.32 | -9:54:41.8 | 12.4 | 13.3 | 13.3 | P | predict |
| V2201 | p | 10 | 0 | 50 | 0.345017599 | 49127.495 | 17:44:4.44 | +3:44:16.8 | 14.51 | 14.82 | 14.82 | B | predict |
| V2201 | s | 10 | 0 | 50 | 0.345017599 | 49127.66751 | 17:44:4.44 | +3:44:16.8 | 14.51 | 14.82 | 14.82 | B | predict |
| V2203 | p | 1 | 9 | 78 | 0.455001 | 42812.645 | 17:49:43.28 | +4:28:24.3 | 11.56 | 11.94 | 11.94 | V | predict |
| V2203 | s | 1 | 9 | 78 | 0.455001 | 42812.867 | 17:49:43.28 | +4:28:24.3 | 11.56 | 11.94 | 11.94 | V | predict |
| V2288 | p | 1 | 20 | 20 | 21.6661 | 53901.43 | 17:41:53.63 | +5:16:30.8 | 12.6 | 13.1 | 13.1 | P | predict |
| V2288 | s | 1 | 20 | 20 | 21.6661 | 53906.78 | 17:41:53.63 | +5:16:30.8 | 12.6 | 13.1 | 13.1 | P | predict |
| V2332 | p | 7 | 3 | 4 | 0.54458 | 55327.7702 | 18:1:48.91 | +8:35:45.3 | 13.8 | 14.9 | 14.9 | B | predict |
| V2355 | p | 10 | 0 | 1 | 2.10773 | 48502.006 | 16:50:55.48 | -16:32:48.9 | 7.107 | 7.244 | 7.244 | V | predict |
| V2357 | p | 6 | 4 | 6 | 0.415565 | 51277.916 | 16:57:16.76 | +10:59:51.4 | 10.66 | 10.79 | 10.7 | V | predict |
| V2357 | s | 6 | 4 | 6 | 0.415565 | 53137.7985 | 16:57:16.76 | +10:59:51.4 | 10.66 | 10.79 | 10.7 | V | predict |
| V2368 | p | 9 | 1 | 2 | 38.32712 | 54294.67 | 17:16:14.26 | +2:11:10.3 | 6.22 | 6.42 | 6.42 | V | predict |
| V2373 | p | 7 | 3 | 4 | 1.086282 | 55697.56539 | 17:32:2.87 | +2:49:25.3 | 7.389 | 7.464 | 7.464 | V | predict |
| V2373 | s | 7 | 3 | 4 | 1.086282 | 48501.4803 | 17:32:2.87 | +2:49:25.3 | 7.389 | 7.464 | 7.464 | V | predict |
| V2377 | p | 7 | 3 | 5 | 0.4254035 | 54599.46783 | 17:33:56.05 | +8:9:57.8 | 8.595 | 8.727 | 8.727 | V | predict |
| V2377 | s | 7 | 3 | 5 | 0.4254035 | 55698.49786 | 17:33:56.05 | +8:9:57.8 | 8.595 | 8.727 | 8.727 | V | predict |
| V2383 | p | 4 | 6 | 8 | 0.5022043 | 53484.7905 | 17:40:43.78 | -7:46:12.9 | 10.23 | 11.09 | 10.48 | V | predict |
| V2383 | s | 4 | 6 | 8 | 0.5022043 | 52083.891 | 17:40:43.78 | -7:46:12.9 | 10.23 | 11.09 | 10.48 | V | predict |
| V2388 | p | 1 | 24 | 26 | 0.802299 | 49890.5045 | 17:54:14.17 | +11:7:50 | 6.253 | 6.553 | 6.553 | V | predict |
| V2388 | s | 1 | 24 | 26 | 0.802299 | 54365.3269 | 17:54:14.17 | +11:7:50 | 6.253 | 6.553 | 6.553 | V | predict |
| V2394 | p | 8 | 2 | 14 | 0.589356 | 50275.2101 | 16:31:40.67 | -24:25:16.3 | 11.25 | 11.95 | 11.9 | U | predict |
| V2394 | s | 8 | 2 | 14 | 0.589356 | 53511.6615 | 16:31:40.67 | -24:25:16.3 | 11.25 | 11.95 | 11.9 | U | predict |
| V2425 | p | 9 | 1 | 5 | 1.763055 | 50265.452 | 17:19:18.49 | -0:10:17.9 | 10.6 | 11.43 | 11.4 | P | predict |
| V2425 | s | 9 | 1 | 5 | 1.763055 | 51278.339 | 17:19:18.49 | -0:10:17.9 | 10.6 | 11.43 | 11.4 | P | predict |
| V2536 | p | 9 | 1 | 2 | 2.1635 | 52792.4862 | 18:9:57.29 | +8:50:26.2 | 11.55 | 12.08 | 11.55 | c | predict |
| V2553 | p | 1 | 11 | 14 | 0.457615 | 51274.866 | 17:24:41.57 | +13:53:58 | 11.3 | 11.8 | 11.7 | V | predict |
| V2553 | s | 1 | 11 | 14 | 0.457615 | 54239.525 | 17:24:41.57 | +13:53:58 | 11.3 | 11.8 | 11.7 | V | predict |
| V2563 | p | 8 | 2 | 2 | 0.372302 | 54316.694 | 18:4:21.5 | +0:36:23 | 10 | 10 | 10 | c | predict |
| V2563 | s | 8 | 2 | 2 | 0.372302 | 55739.8293 | 18:4:21.5 | +0:36:23 | 10 | 10 | 10 | c | predict |
| V2610 | p | 1 | 18 | 19 | 0.426512 | 52369.95 | 17:53:32.3 | -3:54:55 | 9.2 | 9.45 | 9.45 | V | predict |
| V2610 | s | 1 | 18 | 19 | 0.426512 | 54681.0096 | 17:53:32.3 | -3:54:55 | 9.2 | 9.45 | 9.45 | V | predict |
| V2612 | p | 1 | 13 | 22 | 0.375308 | 52798.494 | 18:29:13.02 | +6:47:13.8 | 9.35 | 9.72 | 9.7 | V | predict |
| V2612 | s | 1 | 13 | 22 | 0.375308 | 55729.4632 | 18:29:13.02 | +6:47:13.8 | 9.35 | 9.72 | 9.7 | V | predict |
| V2617 | p | 9 | 1 | 1 | 0.424074 | 52749.804 | 16:27:7.2 | -8:51:0 | 13.15 | 13.75 | 13.35 | V | predict |
| V2619 | p | 10 | 0 | 1 | 0.479238 | 51352.79 | 16:43:27.4 | -12:10:47 | 13.75 | 14.35 | 14.35 | V | predict |
| V2626 | p | 5 | 5 | 5 | 10.8743 | 52787.824 | 17:5:32 | +10:32:47 | 8.26 | 8.43 | 8.36 | V | predict |
| V2626 | s | 5 | 5 | 5 | 10.8743 | 52793.261 | 17:5:32 | +10:32:47 | 8.26 | 8.43 | 8.36 | V | predict |
| V2632 | p | 9 | 1 | 1 | 2.69691 | 53491.81 | 17:11:52.7 | -23:54:35 | 12.98 | 13.6 | 12.98 | V | predict |
| V2635 | p | 7 | 3 | 3 | 0.430961 | 54250.759 | 17:16:29.8 | -0:29:17 | 12.15 | 12.6 | 12.6 | V | predict |
| V2635 | s | 7 | 3 | 3 | 0.430961 | 52721.053 | 17:16:29.8 | -0:29:17 | 12.15 | 12.6 | 12.6 | V | predict |
| V2636 | p | 9 | 1 | 1 | 3.3337 | 53544.686 | 17:18:10.1 | -17:15:48 | 12.75 | 13.5 | 12.75 | V | predict |
| V2637 | p | 7 | 3 | 4 | 0.386176 | 51325.797 | 17:18:29.7 | +5:16:31 | 11.8 | 12.27 | 12.21 | V | predict |
| V2637 | s | 7 | 3 | 4 | 0.386176 | 51325.99 | 17:18:29.7 | +5:16:31 | 11.8 | 12.27 | 12.21 | V | predict |
| V2638 | p | 9 | 1 | 1 | 1.87423 | 52841.67 | 17:18:44.6 | -18:56:15 | 13.2 | 14 | 13.9 | V | predict |
| V2640 | p | 7 | 3 | 3 | 0.419892 | 52860.694 | 17:28:1.5 | +5:7:15 | 12.5 | 13.2 | 13.2 | V | predict |
| V2640 | s | 7 | 3 | 3 | 0.419892 | 52860.904 | 17:28:1.5 | +5:7:15 | 12.5 | 13.2 | 13.2 | V | predict |
| V2642 | p | 9 | 1 | 1 | 3.46464 | 53122.835 | 17:35:57.1 | +11:50:41 | 11.4 | 12 | 11.4 | V | predict |
| V2644 | p | 9 | 1 | 1 | 1.27748 | 53194.705 | 17:36:44.9 | -29:14:27 | 12.8 | 13.25 | 13 | V | predict |
| V2647 | p | 8 | 2 | 2 | 3.3515 | 53077.904 | 17:42:20.3 | +10:20:4 | 12.3 | 12.85 | 12.4 | V | predict |
| V2650 | p | 8 | 2 | 3 | 0.384055 | 51453.688 | 17:45:20.7 | +8:10:39 | 12.57 | 13.2 | 13 | V | predict |
| V2653 | p | 10 | 0 | 2 | 4.39433 | 48744.81 | 17:52:47.3 | +3:47:39 | 9.5 | 9.78 | 9.74 | V | predict |
| V2657 | p | 10 | 0 | 17 | 1.710533 | 49215.413 | 17:57:42.7 | +2:31:20 | 13.7 | 15.2 | 13.7 | P | predict |
| V2659 | p | 9 | 1 | 1 | 0.776761 | 53448.899 | 17:58:13.8 | +3:0:14 | 12.83 | 13.85 | 12.97 | V | predict |
| V2660 | p | 10 | 0 | 13 | 1.2061988 | 47380.399 | 18:1:24 | +0:0:8 | 14.15 | 14.45 | 14.15 | B | predict |
| V2663 | p | 10 | 0 | 13 | 1.4057497 | 48839.392 | 18:2:47.7 | +7:54:1 | 15 | 15.9 | 15 | B | predict |
| NSV 08733 | p | 7 | 3 | 21 | 0.357189 | 55321.8094 | 17:25:2 | +8:46:12 | 13.7 | 14 | 13.8 | p | predict |
| NSV 08733 | s | 7 | 3 | 21 | 0.357189 | 46704.444 | 17:25:2 | +8:46:12 | 13.7 | 14 | 13.8 | p | predict |
| NSV 08869 | p | 10 | 0 | 15 | 1.4340859 | 49133.45 | 17:28:50 | +12:21:57 | 13.9 | 15 | 13.9 | P | predict |
| NSV 08970 | p | 10 | 0 | 14 | 2.504273 | 49213.364 | 17:30:1 | +10:3:26 | 14.9 | 15.7 | 15.2 | P | predict |
| G0995.1646 | p | 2 | 8 | 10 | 0.444631 | 53250.3326 | 17:21:56.7 | +9:56:54 | 13 | 14 | 14 | c | predict |
| G0995.1646 | s | 2 | 8 | 10 | 0.444631 | 54364.3625 | 17:21:56.7 | +9:56:54 | 13 | 14 | 14 | c | predict |
VYSVĚTLIVKY K TABULCE:
Star - název proměnné, 2. sloupec - primární / sekundární minima, 3. sloupec - "kanadské bodování" za posledních 10 let, N10 - počet pozorování za posledních 10 let, N - celkový počet pozorování, CCD, viz i pg minima mají stejnou hodnotu 1 bodu, PERIOD - perioda ve dnech, MIN0 - základní minimum, RA 2000 - rektascenze, DE 2000 - deklinace, MAX - hvězdná velikost v maximu, MINP - hvězdná velikost v primárním minimu, MINS - hvězdná velikost v sekundárním minimu, spektrální obor, pro který jsou údaje o hvězdné velikosti.
VÝPOČET KANADSKÉHO BODOVÁNÍ:
Pro každý objekt byla spočítána dostupná pozorování za posledních 10 let.
1 CCD minimu byla dána hodnota 1, 1 vizuálnímu / pg minimu byla dána hodnota 0,1.
Např. 1 CCD minimum + 1 vizuální minimum = hodnota N10 1.1
Pro takto získanou hodnotu N10 (počet CCD pozorování za posledních 10 let) byl proveden rozdíl 10 - N10 a zaokrouhlen na celé číslo. To pak představuje výsledné kanadské bodování sledovanosti systému.
Příklad: Pokud budeme mít za posledních 10 let 1 pozorování, bude mít objekt 9 bodů. 2 pozorování odpovídají 8 bodům, atd. až 10 a více pozorování odpovída 1 bodu stupnice.
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