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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 Sco
|
|
N10 |
N |
PERIOD |
MIN0 |
RA 2000 |
DE 2000 |
MAX |
MINP |
MINS |
|
|
| AL | p | 10 | 0 | 2 | 1.532249 | 25086.135 | 16:48:13.08 | -32:56:42.4 | 11.2 | 13.5 | 11.3 | P | predict |
| AO | p | 10 | 0 | 2 | 9.42669 | 40000.44 | 16:15:2.42 | -21:45:28 | 13.4 | 14.1 | 13.4 | P | predict |
| AO | s | 10 | 0 | 2 | 9.42669 | 40005.153 | 16:15:2.42 | -21:45:28 | 13.4 | 14.1 | 13.4 | P | predict |
| BS | p | 9 | 1 | 19 | 7.6223759 | 39301.468 | 17:55:4.42 | -31:38:34.9 | 11.5 | 13.2 | 11.5 | P | predict |
| FV | p | 10 | 0 | 2 | 5.7278964 | 48504.38 | 17:13:44.99 | -32:51:9.2 | 7.95 | 8.72 | 8.05 | V | predict |
| V 385 | p | 2 | 8 | 10 | 2.345127 | 24711.69 | 17:38:9.49 | -37:42:20 | 10.9 | 11.7 | 11.6 | P | predict |
| V 385 | s | 2 | 8 | 10 | 2.345127 | 54461.89457 | 17:38:9.49 | -37:42:20 | 10.9 | 11.7 | 11.6 | P | predict |
| V 387 | p | 9 | 1 | 2 | 1.3749173 | 26120.57 | 17:41:1.59 | -36:1:5.8 | 12.2 | 12.6 | 12.3 | V | predict |
| V 393 | p | 10 | 0 | 2 | 7.71259 | 48504.97 | 17:48:47.6 | -35:3:25.6 | 8.2 | 9 | 8.3 | P | predict |
| V 453 | p | 10 | 0 | 4 | 12.00597 | 48509.97 | 17:56:16.08 | -32:28:30 | 6.36 | 6.73 | 6.7 | V | predict |
| V 453 | s | 10 | 0 | 4 | 12.00597 | 42224.743 | 17:56:16.08 | -32:28:30 | 6.36 | 6.73 | 6.7 | V | predict |
| V 457 | p | 9 | 1 | 3 | 2.007379 | 51977.781 | 17:8:2.46 | -35:57:40.8 | 10.6 | 11.4 | 11.3 | V | predict |
| V 457 | s | 9 | 1 | 3 | 2.007379 | 52699.4299 | 17:8:2.46 | -35:57:40.8 | 10.6 | 11.4 | 11.3 | V | predict |
| V 468 | p | 9 | 1 | 2 | 11.099725 | 53644.57 | 17:15:46.47 | -36:52:1.4 | 12.15 | 12.58 | 12.15 | V | predict |
| V 472 | p | 9 | 1 | 2 | 208.771 | 52915.52 | 17:17:55.24 | -35:5:39.1 | 12.2 | 12.6 | 12.2 | P | predict |
| V 474 | p | 9 | 1 | 2 | 1.62004 | 52540.574 | 17:18:51.38 | -31:34:58.8 | 10.3 | 11 | 10.6 | V | predict |
| V 490 | p | 10 | 0 | 2 | 3.003757 | 28425.295 | 17:37:54.47 | -33:57:4 | 11.8 | 12.2 | 12.1 | V | predict |
| V 490 | s | 10 | 0 | 2 | 3.003757 | 52171.5 | 17:37:54.47 | -33:57:4 | 11.8 | 12.2 | 12.1 | V | predict |
| V 496 | p | 9 | 1 | 2 | 2.192551 | 52489.563 | 17:43:2.61 | -32:22:13.7 | 11.5 | 12.4 | 11.5 | V | predict |
| V 499 | p | 9 | 1 | 3 | 2.333291 | 55390.25 | 17:29:2.34 | -33:0:16.2 | 8.25 | 8.76 | 8.5 | V | predict |
| V 527 | p | 10 | 0 | 2 | 5.619533 | 52116.067 | 17:41:17.69 | -44:19:45.5 | 11.8 | 13.5 | 11.8 | P | predict |
| V 562 | p | 7 | 3 | 4 | 1.055051 | 52867.672 | 16:44:30.24 | -37:48:5.3 | 11.5 | 12 | 12 | V | predict |
| V 562 | s | 7 | 3 | 4 | 1.055051 | 29113.717 | 16:44:30.24 | -37:48:5.3 | 11.5 | 12 | 12 | V | predict |
| V 569 | p | 1 | 14 | 15 | 1.0472438 | 27923.6 | 16:50:2.4 | -42:36:8.4 | 10.75 | 11.54 | 11.45 | V | predict |
| V 569 | s | 1 | 14 | 15 | 1.0472438 | 27924.124 | 16:50:2.4 | -42:36:8.4 | 10.75 | 11.54 | 11.45 | V | predict |
| V 575 | p | 9 | 1 | 2 | 0.658934 | 29846.29 | 16:54:24.46 | -36:49:22.1 | 12.7 | 13.1 | 12.8 | V | predict |
| V 581 | p | 10 | 0 | 2 | 0.5110023 | 52180.498 | 16:56:18.71 | -37:57:55.2 | 11.4 | 12.1 | 11.5 | V | predict |
| V 583 | p | 9 | 1 | 2 | 0.994731 | 52826.714 | 16:57:1.45 | -37:17:38.4 | 12.3 | 13.2 | 12.6 | V | predict |
| V 586 | p | 9 | 1 | 2 | 0.955937 | 53135.773 | 16:57:32.22 | -41:18:35.5 | 12.7 | 13.1 | 12.8 | V | predict |
| V 590 | p | 9 | 1 | 2 | 2.472883 | 52794.65 | 16:58:50.8 | -42:22:13.6 | 10.68 | 11.3 | 10.68 | B | predict |
| V 594 | p | 10 | 0 | 2 | 3.632864 | 28720.41 | 17:0:24.64 | -41:42:39.2 | 10.4 | 11.3 | 10.6 | V | predict |
| V 607 | p | 10 | 0 | 2 | 4.516623 | 52184.55 | 17:6:16.91 | -35:57:58.2 | 10 | 10.4 | 10.1 | V | predict |
| V 612 | p | 9 | 1 | 2 | 1.062697 | 52734.788 | 17:9:52.98 | -42:38:54.6 | 10.6 | 10.7 | 10.6 | V | predict |
| V 616 | p | 10 | 0 | 2 | 0.844119 | 52137.524 | 17:13:13.32 | -42:59:3.2 | 11.5 | 12.1 | 11.9 | V | predict |
| V 619 | p | 9 | 1 | 2 | 0.7546255 | 52544.489 | 17:14:16.05 | -41:21:21 | 12.1 | 12.6 | 12.3 | V | predict |
| V 626 | p | 9 | 1 | 2 | 1.033685 | 53099.804 | 17:17:11.19 | -40:17:25.4 | 11.3 | 12 | 11.5 | V | predict |
| V 628 | p | 10 | 0 | 2 | 1.16957 | 29458.56 | 17:17:24.83 | -36:52:7.6 | 11.4 | 12.1 | 11.9 | V | predict |
| V 629 | p | 1 | 13 | 17 | 3.249119 | 27601.43 | 17:18:20.32 | -39:3:42.1 | 11.6 | 12 | 11.6 | V | predict |
| V 629 | s | 1 | 13 | 17 | 3.249119 | 54999.74491 | 17:18:20.32 | -39:3:42.1 | 11.6 | 12 | 11.6 | V | predict |
| V 714 | p | 9 | 1 | 2 | 0.6982113 | 28342.431 | 17:55:56.62 | -31:42:47.2 | 12.2 | 12.8 | 12.2 | P | predict |
| V 881 | p | 1 | 12 | 15 | 2.491582 | 54664.91417 | 16:42:8.09 | -33:46:0.5 | 9.2 | 9.7 | 9.2 | V | predict |
| V 881 | s | 1 | 12 | 15 | 2.491582 | 28773.516 | 16:42:8.09 | -33:46:0.5 | 9.2 | 9.7 | 9.2 | V | predict |
| V 884 | p | 10 | 0 | 2 | 3.41187 | 42476.68 | 17:3:56.77 | -37:50:38.9 | 6.51 | 6.6 | 6.51 | V | predict |
| V 889 | p | 9 | 1 | 2 | 12.51148 | 53057.88 | 16:51:37.18 | -44:57:45.6 | 10.8 | 11.5 | 10.9 | V | predict |
| V 906 | p | 10 | 0 | 6 | 2.78595 | 48500.78 | 17:53:54.77 | -34:45:9.8 | 5.96 | 6.23 | 5.96 | V | predict |
| V 906 | s | 10 | 0 | 6 | 2.78595 | 48362.8747 | 17:53:54.77 | -34:45:9.8 | 5.96 | 6.23 | 5.96 | V | predict |
| V1041 | p | 10 | 0 | 2 | 2.18753 | 48500.55 | 16:1:51.54 | -28:22:26.2 | 8.937 | 9.258 | 8.937 | V | predict |
| V1044 | p | 8 | 2 | 3 | 0.914833 | 53064.836 | 16:4:2.85 | -21:55:40.2 | 8.6 | 9.07 | 8.92 | V | predict |
| V1046 | p | 10 | 0 | 1 | 11.11641 | 48528.387 | 16:6:39 | -26:25:1.6 | 9.25 | 9.66 | 9.63 | V | predict |
| V1055 | p | 4 | 6 | 7 | 0.3636835 | 48500.2734 | 16:27:26.2 | -37:28:37.3 | 8.65 | 8.919 | 8.65 | V | predict |
| V1055 | s | 4 | 6 | 7 | 0.3636835 | 48500.4552 | 16:27:26.2 | -37:28:37.3 | 8.65 | 8.919 | 8.65 | V | predict |
| V1067 | p | 10 | 0 | 2 | 12.0424 | 47926.15 | 16:50:59.1 | -26:46:52 | 10.55 | 10.94 | 10.83 | V | predict |
| V1067 | s | 10 | 0 | 2 | 12.0424 | 47931.328 | 16:50:59.1 | -26:46:52 | 10.55 | 10.94 | 10.83 | V | predict |
| V1069 | p | 10 | 0 | 1 | 5.347 | 48503.05 | 16:55:30.97 | -39:27:59.1 | 8.54 | 8.79 | 8.54 | V | predict |
| V1081 | p | 9 | 1 | 7 | 2.513741 | 47920.528 | 17:29:12.92 | -31:32:3.4 | 6.97 | 7.12 | 6.97 | V | predict |
| V1081 | s | 9 | 1 | 7 | 2.513741 | 47921.785 | 17:29:12.92 | -31:32:3.4 | 6.97 | 7.12 | 6.97 | V | predict |
| V1082 | p | 1 | 12 | 15 | 23.446 | 54651.99925 | 17:36:27.39 | -33:29:35.9 | 10 | 10.48 | 10.34 | V | predict |
| V1082 | s | 1 | 12 | 15 | 23.446 | 52105.023 | 17:36:27.39 | -33:29:35.9 | 10 | 10.48 | 10.34 | V | predict |
| V1195 | p | 10 | 0 | 1 | 4.00305 | 47963.349 | 16:19:23 | -40:56:39 | 8.86 | 9.04 | 9.01 | V | predict |
| V1216 | p | 10 | 0 | 1 | 3.9207 | 52481.518 | 16:54:57.7 | -43:56:27 | 10.09 | 10.52 | 10.35 | V | predict |
| V1219 | p | 10 | 0 | 1 | 1 | 52094.55 | 16:56:15.7 | -40:40:44 | 14.1 | 14.5 | 14.1 | B | predict |
| V1220 | p | 10 | 0 | 1 | 1 | 52096.6 | 16:56:19.6 | -40:34:41 | 14.2 | 15 | 14.2 | B | predict |
| V1223 | p | 10 | 0 | 1 | 1.9083 | 52468.5701 | 16:56:43.3 | -40:36:25 | 11 | 11.22 | 11 | V | predict |
| V1226 | p | 9 | 1 | 1 | 2.08355 | 52929.46 | 17:2:25 | -36:49:34 | 10.59 | 10.78 | 10.64 | V | predict |
| V1229 | p | 10 | 0 | 1 | 1.859839 | 47921.793 | 17:26:43.3 | -42:13:56 | 8.9 | 9.08 | 8.96 | V | predict |
| V1231 | p | 10 | 0 | 1 | 0.403586 | 50551.861 | 17:48:2.7 | -35:28:21 | 15.42 | 15.61 | 15.42 | I | predict |
| V1282 | p | 9 | 1 | 1 | 2.1315 | 52535.58 | 16:7:4.9 | -29:16:48 | 13.4 | 14.5 | 13.6 | V | predict |
| V1283 | p | 10 | 0 | 1 | 1.7587 | 48510.607 | 16:8:17 | -17:8:5 | 8.58 | 8.68 | 8.61 | V | predict |
| V1284 | p | 9 | 1 | 1 | 3.7297 | 52722.863 | 16:13:38.9 | -41:20:51 | 9.54 | 9.72 | 9.71 | V | predict |
| V1285 | p | 9 | 1 | 1 | 3.35345 | 52521.63 | 16:21:2.6 | -30:56:48 | 13.45 | 15 | 13.65 | V | predict |
| V1286 | p | 9 | 1 | 1 | 2.918 | 52924.412 | 16:28:59.7 | -32:7:34 | 12.88 | 14.2 | 13.07 | V | predict |
| V1288 | p | 9 | 1 | 2 | 1.108897 | 52040.789 | 16:37:0 | -45:19:7 | 8.17 | 8.51 | 8.26 | V | predict |
| V1290 | p | 10 | 0 | 1 | 4.49244 | 48704.307 | 16:50:1.4 | -41:37:16 | 7.96 | 8.07 | 8.01 | V | predict |
| V1291 | p | 10 | 0 | 1 | 50.007 | 51995.07 | 16:53:11.5 | -36:38:7 | 10.4 | 11.2 | 10.5 | V | predict |
| V1292 | p | 8 | 2 | 2 | 4.24038 | 53182.567 | 16:53:55.6 | -41:52:51 | 7.57 | 7.8 | 7.73 | V | predict |
| V1293 | p | 9 | 1 | 1 | 1.317716 | 53478.825 | 16:53:57.6 | -41:38:42 | 9.77 | 10.19 | 10.07 | V | predict |
| V1294 | p | 10 | 0 | 1 | 5.604 | 52468.62 | 16:54:0 | -41:42:53 | 7.58 | 7.67 | 7.59 | V | predict |
| V1295 | p | 10 | 0 | 1 | 2.15767 | 52439.649 | 16:54:35.8 | -41:25:23 | 7.96 | 8.19 | 8.11 | V | predict |
| V1296 | p | 10 | 0 | 1 | 5.8082 | 52071.677 | 16:54:44.6 | -43:16:53 | 12.18 | 12.77 | 12.72 | V | predict |
| V1297 | p | 9 | 1 | 1 | 4.48886 | 52893.699 | 16:56:5.2 | -40:20:58 | 8.4 | 8.47 | 8.46 | V | predict |
| V1299 | p | 9 | 1 | 1 | 7.6945 | 52501.474 | 17:4:26 | -39:16:4 | 11.73 | 12.2 | 12.1 | V | predict |
| V1300 | p | 10 | 0 | 1 | 29.3467 | 48005.71 | 17:4:58.4 | -38:37:6 | 8.87 | 9.03 | 9.02 | V | predict |
| V1301 | p | 8 | 2 | 2 | 1.9541 | 53634.555 | 17:5:18.7 | -34:56:0 | 13 | 13.5 | 13 | V | predict |
| V1301 | s | 8 | 2 | 2 | 1.9541 | 53635.58676 | 17:5:18.7 | -34:56:0 | 13 | 13.5 | 13 | V | predict |
| V1302 | p | 9 | 1 | 1 | 7.4158 | 53219.53 | 17:7:17.5 | -37:36:23 | 12.6 | 13.15 | 13.1 | V | predict |
| V1303 | p | 10 | 0 | 2 | 11.0943 | 51978.842 | 17:13:5.3 | -34:45:10 | 11.74 | 12.1 | 11.78 | V | predict |
| V1303 | s | 10 | 0 | 2 | 11.0943 | 51982.63625 | 17:13:5.3 | -34:45:10 | 11.74 | 12.1 | 11.78 | V | predict |
| V1304 | p | 10 | 0 | 1 | 3.3682 | 52030.779 | 17:28:21.8 | -38:41:48 | 8.28 | 8.6 | 8.59 | V | predict |
| V1305 | p | 10 | 0 | 1 | 1.29732 | 52452.597 | 17:28:40.1 | -33:34:58 | 8.74 | 9.07 | 8.74 | V | predict |
| V1306 | p | 10 | 0 | 1 | 5.54177 | 52117.565 | 17:31:34.2 | -38:51:40 | 11.21 | 11.6 | 11.52 | V | predict |
| V1308 | p | 9 | 1 | 1 | 9.1066 | 52549.519 | 17:49:16.4 | -38:11:35 | 10.4 | 11 | 10.92 | V | predict |
| mu. | p | 10 | 0 | 8 | 1.44627 | 49534.178 | 16:51:52.23 | -38:2:50.6 | 2.893 | 3.148 | 3.073 | V | predict |
| mu. | s | 10 | 0 | 8 | 1.44627 | 12374.434 | 16:51:52.23 | -38:2:50.6 | 2.893 | 3.148 | 3.073 | V | 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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