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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 Car
|
|
N10 |
N |
PERIOD |
MIN0 |
RA 2000 |
DE 2000 |
MAX |
MINP |
MINS |
|
|
| X | p | 8 | 2 | 8 | 1.08263 | 52705.324 | 8:31:16.8 | -59:13:37.4 | 7.9 | 8.65 | 8.6 | V | predict |
| X | s | 8 | 2 | 8 | 1.08263 | 52973.277 | 8:31:16.8 | -59:13:37.4 | 7.9 | 8.65 | 8.6 | V | predict |
| ST | p | 8 | 2 | 23 | 0.90164965 | 51868.144 | 10:15:54.27 | -60:11:57.1 | 9.6 | 10.75 | 9.87 | V | predict |
| ST | s | 8 | 2 | 23 | 0.90164965 | 44698.6785 | 10:15:54.27 | -60:11:57.1 | 9.6 | 10.75 | 9.87 | V | predict |
| SW | p | 8 | 2 | 31 | 8.165942 | 51918.446 | 10:26:57.67 | -58:16:17.3 | 10.5 | 11.7 | 10.55 | V | predict |
| AS | p | 6 | 4 | 7 | 2.765857 | 23921.655 | 10:24:23.51 | -60:14:57.2 | 11.5 | 12.5 | 11.5 | V | predict |
| CO | p | 9 | 1 | 4 | 8.30837 | 23877.983 | 10:17:56.57 | -63:22:30.1 | 11.1 | 12.7 | 11.1 | V | predict |
| DD | p | 9 | 1 | 3 | 1.442714 | 23904.27 | 11:5:52.81 | -63:29:55.9 | 13.2 | 14.1 | 13.2 | P | predict |
| DQ | p | 8 | 2 | 4 | 0.866837 | 53145.1508 | 10:21:56.71 | -57:14:41.1 | 11.1 | 11.5 | 11.1 | P | predict |
| DR | p | 9 | 1 | 4 | 3.99576 | 23849.5 | 10:24:41.41 | -60:29:55.4 | 11.3 | 12.7 | 11.3 | V | predict |
| DV | p | 8 | 2 | 3 | 1.68148 | 52659.213 | 10:40:4.57 | -60:12:16.2 | 10 | 10.3 | 10 | P | predict |
| EZ | p | 5 | 5 | 6 | 1.1886893 | 23995.421 | 10:42:53.87 | -62:23:32.8 | 9.9 | 10.3 | 10.2 | V | predict |
| EZ | s | 5 | 5 | 6 | 1.1886893 | 23996.015 | 10:42:53.87 | -62:23:32.8 | 9.9 | 10.3 | 10.2 | V | predict |
| GL | p | 7 | 3 | 6 | 2.422238 | 54099.2 | 11:14:39.84 | -60:39:36.4 | 9.73 | 10.33 | 10.31 | B | predict |
| GL | s | 7 | 3 | 6 | 2.422238 | 54100.18 | 11:14:39.84 | -60:39:36.4 | 9.73 | 10.33 | 10.31 | B | predict |
| GQ | p | 8 | 2 | 3 | 0.6837115 | 54253.405 | 10:36:20.79 | -60:35:41.5 | 13 | 13.7 | 13.5 | P | predict |
| HP | p | 5 | 5 | 7 | 1.600453 | 54183.0304 | 10:19:35.71 | -57:24:18.7 | 8.85 | 9.3 | 9.3 | V | predict |
| HP | s | 5 | 5 | 7 | 1.600453 | 53157.9383 | 10:19:35.71 | -57:24:18.7 | 8.85 | 9.3 | 9.3 | V | predict |
| PX | p | 10 | 0 | 48 | 0.795101 | 28656.275 | 6:21:0.35 | -54:32:27.3 | 9.65 | 10.45 | 10.1 | V | predict |
| PX | s | 10 | 0 | 48 | 0.795101 | 39178.285 | 6:21:0.35 | -54:32:27.3 | 9.65 | 10.45 | 10.1 | V | predict |
| PY | p | 9 | 1 | 32 | 3.340711 | 51867.949 | 7:34:58.31 | -63:43:41.4 | 10.3 | 11.2 | 10.3 | V | predict |
| PY | s | 9 | 1 | 32 | 3.340711 | 14941.39933 | 7:34:58.31 | -63:43:41.4 | 10.3 | 11.2 | 10.3 | V | predict |
| QQ | p | 9 | 1 | 14 | 11.01955 | 52553.72 | 8:46:44.8 | -58:5:2.4 | 11.8 | 13.6 | 11.8 | V | predict |
| QR | p | 10 | 0 | 20 | 0.749008 | 36691.256 | 9:51:7.31 | -67:26:5 | 10 | 10.5 | 10.4 | P | predict |
| QS | p | 8 | 2 | 23 | 4.6604 | 28656.245 | 10:34:17.66 | -71:9:53.7 | 9.3 | 10.1 | 9.6 | V | predict |
| QW | p | 9 | 1 | 23 | 2.853212 | 28904.505 | 9:32:59.66 | -74:16:22.2 | 11.7 | 13.5 | 11.7 | V | predict |
| QW | s | 9 | 1 | 23 | 2.853212 | 28905.93159 | 9:32:59.66 | -74:16:22.2 | 11.7 | 13.5 | 11.7 | V | predict |
| V 338 | p | 9 | 1 | 10 | 74.646 | 52215.438 | 11:13:52.04 | -58:36:19.8 | 9.2 | 10.1 | 9.2 | V | predict |
| V 466 | p | 8 | 2 | 10 | 3.4558 | 52940.765 | 8:18:5.03 | -60:18:50.1 | 7.25 | 7.55 | 7.25 | P | predict |
| V 466 | s | 8 | 2 | 10 | 3.455887 | 48038.284 | 8:18:5.03 | -60:18:50.1 | 7.25 | 7.55 | 7.25 | P | predict |
| V 493 | p | 1 | 9 | 23 | 3.22942 | 48501.21 | 9:57:40.26 | -59:42:51.7 | 8.84 | 9.19 | 8.84 | V | predict |
| V 493 | s | 1 | 9 | 23 | 3.22942 | 53450.638 | 9:57:40.26 | -59:42:51.7 | 8.84 | 9.19 | 8.84 | V | predict |
| V 529 | p | 2 | 8 | 15 | 4.74463 | 53480.686 | 11:3:12.85 | -63:3:59.9 | 8.19 | 8.58 | 8.19 | P | predict |
| V 529 | s | 2 | 8 | 15 | 4.74463 | 53454.799 | 11:3:12.85 | -63:3:59.9 | 8.19 | 8.58 | 8.19 | P | predict |
| V 604 | p | 10 | 0 | 1 | 0.472292 | 51878.748 | 7:14:50.6 | -59:16:4 | 9.16 | 9.64 | 9.6 | V | predict |
| V 605 | p | 9 | 1 | 1 | 0.688714 | 52989.797 | 7:39:50.2 | -53:38:28 | 9.5 | 10.18 | 9.91 | V | predict |
| V 606 | p | 9 | 1 | 1 | 12.3192 | 53042.68 | 7:44:38.7 | -56:42:32 | 8.31 | 8.68 | 8.6 | V | predict |
| V 608 | p | 10 | 0 | 1 | 0.967554 | 51884.718 | 8:7:34 | -55:19:37 | 8.87 | 9.55 | 9.55 | V | predict |
| V 609 | p | 9 | 1 | 1 | 3.13602 | 52690.713 | 9:10:25.5 | -57:30:22 | 10.96 | 11.82 | 11.35 | V | predict |
| V 610 | p | 9 | 1 | 1 | 4.84493 | 53383.85 | 9:22:59.8 | -59:44:56 | 10.2 | 10.75 | 10.6 | V | predict |
| V 613 | p | 9 | 1 | 1 | 11.8884 | 52954.874 | 9:35:16.6 | -60:27:28 | 12.3 | 13.15 | 12.35 | V | predict |
| V 625 | p | 9 | 1 | 1 | 0.2769435 | 52783.535 | 9:50:47.8 | -67:23:15 | 11.15 | 12 | 11.95 | V | predict |
| V 632 | p | 9 | 1 | 1 | 2 | 53018.82 | 9:57:50.3 | -58:15:33 | 12.16 | 12.66 | 12.54 | V | predict |
| V 635 | p | 9 | 1 | 1 | 0.79995 | 53018.786 | 10:0:30 | -69:58:21 | 12.6 | 13.3 | 12.8 | V | predict |
| V 654 | p | 10 | 0 | 1 | 2.87362 | 51919.73 | 10:29:24.7 | -60:5:16 | 12.5 | 13.3 | 13.1 | V | predict |
| V 655 | p | 10 | 0 | 1 | 16.933 | 48175.22 | 10:30:8.8 | -66:59:5 | 6.19 | 6.36 | 6.35 | V | predict |
| V 658 | p | 9 | 1 | 1 | 32.186 | 52786.54 | 10:38:47.2 | -58:43:32 | 9.08 | 9.37 | 9.23 | V | predict |
| V 661 | p | 8 | 2 | 2 | 23.944 | 53131.619 | 10:44:0.4 | -59:52:28 | 8.07 | 8.28 | 8.2 | V | predict |
| V 661 | s | 8 | 2 | 2 | 23.944 | 53147.186 | 10:44:0.4 | -59:52:28 | 8.07 | 8.28 | 8.2 | V | predict |
| V 662 | p | 9 | 1 | 1 | 1.41355 | 53490.609 | 10:45:36.32 | -59:48:23.2 | 12.09 | 12.7 | 12.45 | V | predict |
| V 665 | p | 10 | 0 | 1 | 15.509 | 51888.78 | 10:51:52 | -66:20:7 | 10.9 | 11.3 | 10.9 | V | predict |
| V 674 | p | 9 | 1 | 1 | 19.811 | 52973.77 | 11:6:50.2 | -59:50:48 | 9.94 | 10.47 | 10.24 | V | predict |
| V 681 | p | 10 | 0 | 1 | 1.2209619 | 51978.6871 | 7:39:3.7 | -60:37:9 | 10.04 | 10.22 | 10.04 | V | predict |
| V 684 | p | 9 | 1 | 1 | 3.33751 | 52619.731 | 8:57:29.6 | -62:53:50 | 8.76 | 8.94 | 8.76 | V | predict |
| V 686 | p | 9 | 1 | 1 | 2.08489 | 53851.646 | 9:33:38.82 | -57:42:8.4 | 8.92 | 9.05 | 9.01 | V | predict |
| V 712 | p | 9 | 1 | 1 | 3.686 | 53124.569 | 10:23:58 | -57:45:49 | 10.64 | 11.07 | 10.64 | I | predict |
| V 713 | p | 9 | 1 | 1 | 3.12881 | 52703.7 | 10:27:35.85 | -58:23:26.5 | 9.45 | 9.64 | 9.62 | V | predict |
| V 714 | p | 10 | 0 | 1 | 2.0453 | 51958.636 | 10:28:15.75 | -57:41:38.5 | 9.68 | 9.85 | 9.77 | V | predict |
| V 717 | p | 9 | 1 | 1 | 0.9533071 | 54540.7963 | 10:32:9.8 | -59:5:42 | 10.44 | 10.94 | 10.44 | V | predict |
| V 718 | p | 9 | 1 | 1 | 0.81619 | 53773.7961 | 10:33:8.1 | -71:33:45 | 10.55 | 10.87 | 10.55 | V | predict |
| V 725 | p | 8 | 2 | 2 | 9.4109 | 52979.82 | 10:43:30.84 | -59:29:23.9 | 9.95 | 10.16 | 9.95 | V | predict |
| V 725 | s | 8 | 2 | 2 | 9.4109 | 52981.326 | 10:43:30.84 | -59:29:23.9 | 9.95 | 10.16 | 9.95 | V | predict |
| V 731 | p | 9 | 1 | 1 | 2.29995 | 52652.8 | 10:45:12.71 | -59:44:46.2 | 9.27 | 9.78 | 9.27 | V | predict |
| V 733 | p | 10 | 0 | 1 | 2.95697 | 51920.833 | 10:46:38.85 | -59:23:46.3 | 10.76 | 11.03 | 10.76 | V | predict |
| V 734 | p | 8 | 2 | 2 | 3.10746 | 52662.788 | 10:47:27.83 | -59:37:46.7 | 11.2 | 11.58 | 11.2 | V | predict |
| V 734 | s | 8 | 2 | 2 | 3.10746 | 52664.155 | 10:47:27.83 | -59:37:46.7 | 11.2 | 11.58 | 11.2 | V | predict |
| V 736 | p | 8 | 2 | 2 | 17.7997 | 52700.64 | 10:47:38.97 | -60:37:3.7 | 7.91 | 8.18 | 7.91 | V | predict |
| V 736 | s | 8 | 2 | 2 | 17.7997 | 52712.2988 | 10:47:38.97 | -60:37:3.7 | 7.91 | 8.18 | 7.91 | V | predict |
| V 738 | p | 9 | 1 | 1 | 4.778 | 53015.8 | 10:48:46.52 | -60:35:39.9 | 9.08 | 9.17 | 9.08 | V | predict |
| V 740 | p | 10 | 0 | 1 | 8.3467 | 52329.94514 | 10:50:20.5 | -61:28:35 | 16.66 | 16.72 | 16.66 | I | predict |
| V 741 | p | 10 | 0 | 1 | 6.0643 | 52324.21555 | 10:50:24.7 | -61:26:12 | 14.9 | 14.98 | 14.9 | I | 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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