/* specfunc/bessel_zero.c * * Copyright (C) 1996, 1997, 1998, 1999, 2000 Gerard Jungman * * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or (at * your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ /* Author: G. Jungman */ #include #include #include #include #include #include #include "error.h" #include "bessel_olver.h" /* For Chebyshev expansions of the roots as functions of nu, * see [G. Nemeth, Mathematical Approximation of Special Functions]. * This gives the fits for all nu and s <= 10. * I made the fits for other values of s myself [GJ]. */ /* Chebyshev expansion: j_{nu,1} = c_k T_k*(nu/2), nu <= 2 */ static const double coef_jnu1_a[] = { 3.801775243633476, 1.360704737511120, -0.030707710261106, 0.004526823746202, -0.000808682832134, 0.000159218792489, -0.000033225189761, 0.000007205599763, -0.000001606110397, 0.000000365439424, -0.000000084498039, 0.000000019793815, -0.000000004687054, 0.000000001120052, -0.000000000269767, 0.000000000065420, -0.000000000015961, 0.000000000003914, -0.000000000000965, 0.000000000000239, -0.000000000000059, 0.000000000000015, -0.000000000000004, 0.000000000000001 }; /* Chebyshev expansion: j_{nu,1} = nu c_k T_k*((2/nu)^(2/3)), nu >= 2 */ static const double coef_jnu1_b[] = { 1.735063412537096, 0.784478100951978, 0.048881473180370, -0.000578279783021, -0.000038984957864, 0.000005758297879, -0.000000327583229, -0.000000003853878, 0.000000002284653, -0.000000000153079, -0.000000000000895, 0.000000000000283, 0.000000000000043, 0.000000000000010, -0.000000000000003 }; /* Chebyshev expansion: j_{nu,2} = c_k T_k*(nu/2), nu <= 2 */ static const double coef_jnu2_a[] = { 6.992370244046161, 1.446379282056534, -0.023458616207293, 0.002172149448700, -0.000246262775620, 0.000030990180959, -0.000004154183047, 0.000000580766328, -0.000000083648175, 0.000000012317355, -0.000000001844887, 0.000000000280076, -0.000000000042986, 0.000000000006658, -0.000000000001039, 0.000000000000163, -0.000000000000026, 0.000000000000004, -0.000000000000001 }; /* Chebyshev expansion: j_{nu,2} = nu c_k T_k*((2/nu)^(2/3)), nu >= 2 */ static const double coef_jnu2_b[] = { 2.465611864263400, 1.607952988471069, 0.138758034431497, -0.003687791182054, -0.000051276007868, 0.000045113570749, -0.000007579172152, 0.000000736469208, -0.000000011118527, -0.000000011919884, 0.000000002696788, -0.000000000314488, 0.000000000008124, 0.000000000005211, -0.000000000001292, 0.000000000000158, -0.000000000000004, -0.000000000000003, 0.000000000000001 }; /* Chebyshev expansion: j_{nu,3} = c_k T_k*(nu/3), nu <= 3 */ static const double coef_jnu3_a[] = { 10.869647065239236, 2.177524286141710, -0.034822817125293, 0.003167249102413, -0.000353960349344, 0.000044039086085, -0.000005851380981, 0.000000812575483, -0.000000116463617, 0.000000017091246, -0.000000002554376, 0.000000000387335, -0.000000000059428, 0.000000000009207, -0.000000000001438, 0.000000000000226, -0.000000000000036, 0.000000000000006, -0.000000000000001 }; /* Chebyshev expansion: j_{nu,3} = nu c_k T_k*((3/nu)^(2/3)), nu >= 3 */ static const double coef_jnu3_b[] = { 2.522816775173244, 1.673199424973720, 0.146431617506314, -0.004049001763912, -0.000039517767244, 0.000048781729288, -0.000008729705695, 0.000000928737310, -0.000000028388244, -0.000000012927432, 0.000000003441008, -0.000000000471695, 0.000000000025590, 0.000000000005502, -0.000000000001881, 0.000000000000295, -0.000000000000020, -0.000000000000003, 0.000000000000001 }; /* Chebyshev expansion: j_{nu,4} = c_k T_k*(nu/4), nu <= 4 */ static const double coef_jnu4_a[] = { 14.750310252773009, 2.908010932941708, -0.046093293420315, 0.004147172321412, -0.000459092310473, 0.000056646951906, -0.000007472351546, 0.000001031210065, -0.000000147008137, 0.000000021475218, -0.000000003197208, 0.000000000483249, -0.000000000073946, 0.000000000011431, -0.000000000001782, 0.000000000000280, -0.000000000000044, 0.000000000000007, -0.000000000000001 }; /* Chebyshev expansion: j_{nu,4} = nu c_k T_k*((4/nu)^(2/3)), nu >= 4 */ static const double coef_jnu4_b[] = { 2.551681323117914, 1.706177978336572, 0.150357658406131, -0.004234001378590, -0.000033854229898, 0.000050763551485, -0.000009337464057, 0.000001029717834, -0.000000037474196, -0.000000013450153, 0.000000003836180, -0.000000000557404, 0.000000000035748, 0.000000000005487, -0.000000000002187, 0.000000000000374, -0.000000000000031, -0.000000000000003, 0.000000000000001 }; /* Chebyshev expansion: j_{nu,5} = c_k T_k*(nu/5), nu <= 5 */ static const double coef_jnu5_a[] = { 18.632261081028211, 3.638249012596966, -0.057329705998828, 0.005121709126820, -0.000563325259487, 0.000069100826174, -0.000009066603030, 0.000001245181383, -0.000000176737282, 0.000000025716695, -0.000000003815184, 0.000000000574839, -0.000000000087715, 0.000000000013526, -0.000000000002104, 0.000000000000330, -0.000000000000052, 0.000000000000008, -0.000000000000001 }; /* Chebyshev expansion: j_{nu,5} = nu c_k T_k*((5/nu)^(2/3)), nu >= 5 */ /* FIXME: There is something wrong with this fit, in about the * 9th or 10th decimal place. */ static const double coef_jnu5_b[] = { 2.569079487591442, 1.726073360882134, 0.152740776809531, -0.004346449660148, -0.000030512461856, 0.000052000821080, -0.000009713343981, 0.000001091997863, -0.000000043061707, -0.000000013779413, 0.000000004082870, -0.000000000611259, 0.000000000042242, 0.000000000005448, -0.000000000002377, 0.000000000000424, -0.000000000000038, -0.000000000000002, 0.000000000000002 }; /* Chebyshev expansion: j_{nu,6} = c_k T_k*(nu/6), nu <= 6 */ static const double coef_jnu6_a[] = { 22.514836143374042, 4.368367257557198, -0.068550155285562, 0.006093776505822, -0.000667152784957, 0.000081486022398, -0.000010649011647, 0.000001457089679, -0.000000206105082, 0.000000029894724, -0.000000004422012, 0.000000000664471, -0.000000000101140, 0.000000000015561, -0.000000000002416, 0.000000000000378, -0.000000000000060, 0.000000000000009, -0.000000000000002 }; /* Chebyshev expansion: j_{nu,6} = nu c_k T_k*((6/nu)^(2/3)), nu >= 6 */ static const double coef_jnu6_b[] = { 2.580710285494837, 1.739380728566154, 0.154340696401691, -0.004422028860168, -0.000028305272624, 0.000052845975269, -0.000009968794373, 0.000001134252926, -0.000000046841241, -0.000000014007555, 0.000000004251816, -0.000000000648213, 0.000000000046728, 0.000000000005414, -0.000000000002508, 0.000000000000459, -0.000000000000043, -0.000000000000002, 0.000000000000002 }; /* Chebyshev expansion: j_{nu,7} = c_k T_k*(nu/7), nu <= 7 */ static const double coef_jnu7_a[] = { 26.397760539730869, 5.098418721711790, -0.079761896398948, 0.007064521280487, -0.000770766522482, 0.000093835449636, -0.000012225308542, 0.000001667939800, -0.000000235288157, 0.000000034040347, -0.000000005023142, 0.000000000753101, -0.000000000114389, 0.000000000017564, -0.000000000002722, 0.000000000000425, -0.000000000000067, 0.000000000000011, -0.000000000000002 }; /* Chebyshev expansion: j_{nu,7} = nu c_k T_k*((7/nu)^(2/3)), nu >= 7 */ static const double coef_jnu7_b[] = { 2.589033335856773, 1.748907007612678, 0.155488900387653, -0.004476317805688, -0.000026737952924, 0.000053459680946, -0.000010153699240, 0.000001164804272, -0.000000049566917, -0.000000014175403, 0.000000004374840, -0.000000000675135, 0.000000000050004, 0.000000000005387, -0.000000000002603, 0.000000000000485, -0.000000000000047, -0.000000000000002, 0.000000000000002 }; /* Chebyshev expansion: j_{nu,8} = c_k T_k*(nu/8), nu <= 8 */ static const double coef_jnu8_a[] = { 30.280900001606662, 5.828429205461221, -0.090968381181069, 0.008034479731033, -0.000874254899080, 0.000106164151611, -0.000013798098749, 0.000001878187386, -0.000000264366627, 0.000000038167685, -0.000000005621060, 0.000000000841165, -0.000000000127538, 0.000000000019550, -0.000000000003025, 0.000000000000472, -0.000000000000074, 0.000000000000012, -0.000000000000002 }; /* Chebyshev expansion: j_{nu,8} = nu c_k T_k*((8/nu)^(2/3)), nu >= 8 */ static const double coef_jnu8_b[] = { 2.595283877150078, 1.756063044986928, 0.156352972371030, -0.004517201896761, -0.000025567187878, 0.000053925472558, -0.000010293734486, 0.000001187923085, -0.000000051625122, -0.000000014304212, 0.000000004468450, -0.000000000695620, 0.000000000052500, 0.000000000005367, -0.000000000002676, 0.000000000000505, -0.000000000000050, -0.000000000000002, 0.000000000000002 }; /* Chebyshev expansion: j_{nu,9} = c_k T_k*(nu/9), nu <= 9 */ static const double coef_jnu9_a[] = { 34.164181213238386, 6.558412747925228, -0.102171455365016, 0.009003934361201, -0.000977663914535, 0.000118479876579, -0.000015368714220, 0.000002088064285, -0.000000293381154, 0.000000042283900, -0.000000006217033, 0.000000000928887, -0.000000000140627, 0.000000000021526, -0.000000000003326, 0.000000000000518, -0.000000000000081, 0.000000000000013, -0.000000000000002 }; /* Chebyshev expansion: j_{nu,9} = nu c_k T_k*((9/nu)^(2/3)), nu >= 9 */ static const double coef_jnu9_b[] = { 2.600150240905079, 1.761635491694032, 0.157026743724010, -0.004549100368716, -0.000024659248617, 0.000054291035068, -0.000010403464334, 0.000001206027524, -0.000000053234089, -0.000000014406241, 0.000000004542078, -0.000000000711728, 0.000000000054464, 0.000000000005350, -0.000000000002733, 0.000000000000521, -0.000000000000052, -0.000000000000002, 0.000000000000002 }; /* Chebyshev expansion: j_{nu,10} = c_k T_k*(nu/10), nu <= 10 */ static const double coef_jnu10_a[] = { 38.047560766184647, 7.288377637926008, -0.113372193277897, 0.009973047509098, -0.001081019701335, 0.000130786983847, -0.000016937898538, 0.000002297699179, -0.000000322354218, 0.000000046392941, -0.000000006811759, 0.000000001016395, -0.000000000153677, 0.000000000023486, -0.000000000003616, 0.000000000000561, -0.000000000000095, 0.000000000000027, -0.000000000000013, 0.000000000000005 }; /* Chebyshev expansion: j_{nu,10} = nu c_k T_k*((10/nu)^(2/3)), nu >= 10 */ static const double coef_jnu10_b[] = { 2.604046346867949, 1.766097596481182, 0.157566834446511, -0.004574682244089, -0.000023934500688, 0.000054585558231, -0.000010491765415, 0.000001220589364, -0.000000054526331, -0.000000014489078, 0.000000004601510, -0.000000000724727, 0.000000000056049, 0.000000000005337, -0.000000000002779, 0.000000000000533, -0.000000000000054, -0.000000000000002, 0.000000000000002 }; /* Chebyshev expansion: j_{nu,11} = c_k T_k*(nu/22), nu <= 22 */ static const double coef_jnu11_a[] = { 49.5054081076848637, 15.33692279367165101, -0.33677234163517130, 0.04623235772920729, -0.00781084960665093, 0.00147217395434708, -0.00029695043846867, 0.00006273356860235, -0.00001370575125628, 3.07171282012e-6, -7.0235041249e-7, 1.6320559339e-7, -3.843117306e-8, 9.15083800e-9, -2.19957642e-9, 5.3301703e-10, -1.3007541e-10, 3.193827e-11, -7.88605e-12, 1.95918e-12, -4.9020e-13, 1.2207e-13, -2.820e-14, 5.25e-15, -1.88e-15, 2.80e-15, -2.45e-15 }; /* Chebyshev expansion: j_{nu,12} = c_k T_k*(nu/24), nu <= 24 */ static const double coef_jnu12_a[] = { 54.0787833216641519, 16.7336367772863598, -0.36718411124537953, 0.05035523375053820, -0.00849884978867533, 0.00160027692813434, -0.00032248114889921, 0.00006806354127199, -0.00001485665901339, 3.32668783672e-6, -7.5998952729e-7, 1.7644939709e-7, -4.151538210e-8, 9.87722772e-9, -2.37230133e-9, 5.7442875e-10, -1.4007767e-10, 3.437166e-11, -8.48215e-12, 2.10554e-12, -5.2623e-13, 1.3189e-13, -3.175e-14, 5.73e-15, 5.6e-16, -8.7e-16, -6.5e-16 }; /* Chebyshev expansion: j_{nu,13} = c_k T_k*(nu/26), nu <= 26 */ static const double coef_jnu13_a[] = { 58.6521941921708890, 18.1303398137970284, -0.39759381380126650, 0.05447765240465494, -0.00918674227679980, 0.00172835361420579, -0.00034800528297612, 0.00007339183835188, -0.00001600713368099, 3.58154960392e-6, -8.1759873497e-7, 1.8968523220e-7, -4.459745253e-8, 1.060304419e-8, -2.54487624e-9, 6.1580214e-10, -1.5006751e-10, 3.679707e-11, -9.07159e-12, 2.24713e-12, -5.5943e-13, 1.4069e-13, -3.679e-14, 1.119e-14, -4.99e-15, 3.43e-15, -2.85e-15, 2.3e-15, -1.7e-15, 8.7e-16 }; /* Chebyshev expansion: j_{nu,14} = c_k T_k*(nu/28), nu <= 28 */ static const double coef_jnu14_a[] = { 63.2256329577315566, 19.5270342832914901, -0.42800190567884337, 0.05859971627729398, -0.00987455163523582, 0.00185641011402081, -0.00037352439419968, 0.00007871886257265, -0.00001715728110045, 3.83632624437e-6, -8.7518558668e-7, 2.0291515353e-7, -4.767795233e-8, 1.132844415e-8, -2.71734219e-9, 6.5714886e-10, -1.6005342e-10, 3.922557e-11, -9.66637e-12, 2.39379e-12, -5.9541e-13, 1.4868e-13, -3.726e-14, 9.37e-15, -2.36e-15, 6.0e-16 }; /* Chebyshev expansion: j_{nu,15} = c_k T_k*(nu/30), nu <= 30 */ static const double coef_jnu15_a[] = { 67.7990939565631635, 20.9237219226859859, -0.45840871823085836, 0.06272149946755639, -0.01056229551143042, 0.00198445078693100, -0.00039903958650729, 0.00008404489865469, -0.00001830717574922, 4.09103745566e-6, -9.3275533309e-7, 2.1614056403e-7, -5.075725222e-8, 1.205352081e-8, -2.88971837e-9, 6.9846848e-10, -1.7002946e-10, 4.164941e-11, -1.025859e-11, 2.53921e-12, -6.3128e-13, 1.5757e-13, -3.947e-14, 9.92e-15, -2.50e-15, 6.3e-16 }; /* Chebyshev expansion: j_{nu,16} = c_k T_k*(nu/32), nu <= 32 */ static const double coef_jnu16_a[] = { 72.3725729616724770, 22.32040402918608585, -0.48881449782358690, 0.06684305681828766, -0.01124998690363398, 0.00211247882775445, -0.00042455166484632, 0.00008937015316346, -0.00001945687139551, 4.34569739281e-6, -9.9031173548e-7, 2.2936247195e-7, -5.383562595e-8, 1.277835103e-8, -3.06202860e-9, 7.3977037e-10, -1.8000071e-10, 4.407196e-11, -1.085046e-11, 2.68453e-12, -6.6712e-13, 1.6644e-13, -4.168e-14, 1.047e-14, -2.64e-15, 6.7e-16 }; /* Chebyshev expansion: j_{nu,17} = c_k T_k*(nu/34), nu <= 34 */ static const double coef_jnu17_a[] = { 76.9460667535209549, 23.71708159112252670, -0.51921943142405352, 0.07096442978067622, -0.01193763559341369, 0.00224049662974902, -0.00045006122941781, 0.00009469477941684, -0.00002060640777107, 4.60031647195e-6, -1.04785755046e-6, 2.4258161247e-7, -5.691327087e-8, 1.350298805e-8, -3.23428733e-9, 7.8105847e-10, -1.8996825e-10, 4.649350e-11, -1.144205e-11, 2.82979e-12, -7.0294e-13, 1.7531e-13, -4.388e-14, 1.102e-14, -2.78e-15, 7.0e-16 }; /* Chebyshev expansion: j_{nu,18} = c_k T_k*(nu/36), nu <= 36 */ static const double coef_jnu18_a[] = { 81.5195728368096659, 25.11375537470259305, -0.54962366347317668, 0.07508565026117689, -0.01262524908033818, 0.00236850602019778, -0.00047556873651929, 0.00010001889347161, -0.00002175581482429, 4.85490251239e-6, -1.10539483940e-6, 2.5579853343e-7, -5.999033352e-8, 1.422747129e-8, -3.40650521e-9, 8.2233565e-10, -1.9993286e-10, 4.891426e-11, -1.203343e-11, 2.97498e-12, -7.3875e-13, 1.8418e-13, -4.608e-14, 1.157e-14, -2.91e-15, 7.4e-16 }; /* Chebyshev expansion: j_{nu,19} = c_k T_k*(nu/38), nu <= 38 */ static const double coef_jnu19_a[] = { 86.0930892477047512, 26.51042598308271729, -0.58002730731948358, 0.07920674321589394, -0.01331283320930301, 0.00249650841778073, -0.00050107453900793, 0.00010534258471335, -0.00002290511552874, 5.10946148897e-6, -1.16292517157e-6, 2.6901365037e-7, -6.306692473e-8, 1.495183048e-8, -3.57869025e-9, 8.6360410e-10, -2.0989514e-10, 5.133439e-11, -1.262465e-11, 3.12013e-12, -7.7455e-13, 1.9304e-13, -4.829e-14, 1.212e-14, -3.05e-15, 7.7e-16 }; /* Chebyshev expansion: j_{nu,20} = c_k T_k*(nu/40), nu <= 40 */ static const double coef_jnu20_a[] = { 90.6666144195163770, 27.9070938975436823, -0.61043045315390591, 0.08332772844325554, -0.01400039260208282, 0.00262450494035660, -0.00052657891389470, 0.00011066592304919, -0.00002405432778364, 5.36399803946e-6, -1.22044976064e-6, 2.8222728362e-7, -6.614312964e-8, 1.567608839e-8, -3.75084856e-9, 9.0486546e-10, -2.1985553e-10, 5.375401e-11, -1.321572e-11, 3.26524e-12, -8.1033e-13, 2.0190e-13, -5.049e-14, 1.267e-14, -3.19e-15, 8.0e-16, -2.0e-16 }; static const double * coef_jnu_a[] = { 0, coef_jnu1_a, coef_jnu2_a, coef_jnu3_a, coef_jnu4_a, coef_jnu5_a, coef_jnu6_a, coef_jnu7_a, coef_jnu8_a, coef_jnu9_a, coef_jnu10_a, coef_jnu11_a, coef_jnu12_a, coef_jnu13_a, coef_jnu14_a, coef_jnu15_a, coef_jnu16_a, coef_jnu17_a, coef_jnu18_a, coef_jnu19_a, coef_jnu20_a }; static const size_t size_jnu_a[] = { 0, sizeof(coef_jnu1_a)/sizeof(double), sizeof(coef_jnu2_a)/sizeof(double), sizeof(coef_jnu3_a)/sizeof(double), sizeof(coef_jnu4_a)/sizeof(double), sizeof(coef_jnu5_a)/sizeof(double), sizeof(coef_jnu6_a)/sizeof(double), sizeof(coef_jnu7_a)/sizeof(double), sizeof(coef_jnu8_a)/sizeof(double), sizeof(coef_jnu9_a)/sizeof(double), sizeof(coef_jnu10_a)/sizeof(double), sizeof(coef_jnu11_a)/sizeof(double), sizeof(coef_jnu12_a)/sizeof(double), sizeof(coef_jnu13_a)/sizeof(double), sizeof(coef_jnu14_a)/sizeof(double), sizeof(coef_jnu15_a)/sizeof(double), sizeof(coef_jnu16_a)/sizeof(double), sizeof(coef_jnu17_a)/sizeof(double), sizeof(coef_jnu18_a)/sizeof(double), sizeof(coef_jnu19_a)/sizeof(double), sizeof(coef_jnu20_a)/sizeof(double) }; static const double * coef_jnu_b[] = { 0, coef_jnu1_b, coef_jnu2_b, coef_jnu3_b, coef_jnu4_b, coef_jnu5_b, coef_jnu6_b, coef_jnu7_b, coef_jnu8_b, coef_jnu9_b, coef_jnu10_b }; static const size_t size_jnu_b[] = { 0, sizeof(coef_jnu1_b)/sizeof(double), sizeof(coef_jnu2_b)/sizeof(double), sizeof(coef_jnu3_b)/sizeof(double), sizeof(coef_jnu4_b)/sizeof(double), sizeof(coef_jnu5_b)/sizeof(double), sizeof(coef_jnu6_b)/sizeof(double), sizeof(coef_jnu7_b)/sizeof(double), sizeof(coef_jnu8_b)/sizeof(double), sizeof(coef_jnu9_b)/sizeof(double), sizeof(coef_jnu10_b)/sizeof(double) }; /* Evaluate Clenshaw recurrence for * a T* Chebyshev series. * sizeof(c) = N+1 */ static double clenshaw(const double * c, int N, double u) { double B_np1 = 0.0; double B_n = c[N]; double B_nm1; int n; for(n=N; n>0; n--) { B_nm1 = 2.0*(2.0*u-1.0) * B_n - B_np1 + c[n-1]; B_np1 = B_n; B_n = B_nm1; } return B_n - (2.0*u-1.0)*B_np1; } /* correction terms to leading McMahon expansion * [Abramowitz+Stegun 9.5.12] * [Olver, Royal Society Math. Tables, v. 7] * We factor out a beta, so that this is a multiplicative * correction: * j_{nu,s} = beta(s,nu) * mcmahon_correction(nu, beta(s,nu)) * macmahon_correction --> 1 as s --> Inf */ static double mcmahon_correction(const double mu, const double beta) { const double eb = 8.0*beta; const double ebsq = eb*eb; if(mu < GSL_DBL_EPSILON) { /* Prevent division by zero below. */ const double term1 = 1.0/ebsq; const double term2 = -4.0*31.0/(3*ebsq*ebsq); const double term3 = 32.0*3779.0/(15.0*ebsq*ebsq*ebsq); const double term4 = -64.0*6277237.0/(105.0*ebsq*ebsq*ebsq*ebsq); const double term5 = 512.0*2092163573.0/(315.0*ebsq*ebsq*ebsq*ebsq*ebsq); return 1.0 + 8.0*(term1 + term2 + term3 + term4 + term5); } else { /* Here we do things in terms of 1/mu, which * is purely to prevent overflow in the very * unlikely case that mu is really big. */ const double mi = 1.0/mu; const double r = mu/ebsq; const double n2 = 4.0/3.0 * (7.0 - 31.0*mi); const double n3 = 32.0/15.0 * (83.0 + (-982.0 + 3779.0*mi)*mi); const double n4 = 64.0/105.0 * (6949.0 + (-153855.0 + (1585743.0 - 6277237.0*mi)*mi)*mi); const double n5 = 512.0/315.0 * (70197.0 + (-2479316.0 + (48010494.0 + (-512062548.0 + 2092163573.0*mi)*mi)*mi)*mi); const double n6 = 2048.0/3465.0 * (5592657.0 + (-287149133.0 + (8903961290.0 + (-179289628602.0 + (1982611456181.0 - 8249725736393.0*mi)*mi)*mi)*mi)*mi); const double term1 = (1.0 - mi) * r; const double term2 = term1 * n2 * r; const double term3 = term1 * n3 * r*r; const double term4 = term1 * n4 * r*r*r; const double term5 = term1 * n5 * r*r*r*r; const double term6 = term1 * n6 * r*r*r*r*r; return 1.0 - 8.0*(term1 + term2 + term3 + term4 + term5 + term6); } } /* Assumes z >= 1.0 */ static double olver_b0(double z, double minus_zeta) { if(z < 1.02) { const double a = 1.0-z; const double c0 = 0.0179988721413553309252458658183; const double c1 = 0.0111992982212877614645974276203; const double c2 = 0.0059404069786014304317781160605; const double c3 = 0.0028676724516390040844556450173; const double c4 = 0.0012339189052567271708525111185; const double c5 = 0.0004169250674535178764734660248; const double c6 = 0.0000330173385085949806952777365; const double c7 = -0.0001318076238578203009990106425; const double c8 = -0.0001906870370050847239813945647; return c0 + a*(c1 + a*(c2 + a*(c3 + a*(c4 + a*(c5 + a*(c6 + a*(c7 + a*c8))))))); } else { const double abs_zeta = minus_zeta; const double t = 1.0/(z*sqrt(1.0 - 1.0/(z*z))); return -5.0/(48.0*abs_zeta*abs_zeta) + t*(3.0 + 5.0*t*t)/(24.0*sqrt(abs_zeta)); } } inline static double olver_f1(double z, double minus_zeta) { const double b0 = olver_b0(z, minus_zeta); const double h2 = sqrt(4.0*minus_zeta/(z*z-1.0)); /* FIXME */ return 0.5 * z * h2 * b0; } int gsl_sf_bessel_zero_J0_e(unsigned int s, gsl_sf_result * result) { /* CHECK_POINTER(result) */ if(s == 0){ result->val = 0.0; result->err = 0.0; GSL_ERROR ("error", GSL_EINVAL); } else { /* See [F. Lether, J. Comp. Appl .Math. 67, 167 (1996)]. */ static const double P[] = { 1567450796.0/12539606369.0, 8903660.0/2365861.0, 10747040.0/536751.0, 17590991.0/1696654.0 }; static const double Q[] = { 1.0, 29354255.0/954518.0, 76900001.0/431847.0, 67237052.0/442411.0 }; const double beta = (s - 0.25) * M_PI; const double bi2 = 1.0/(beta*beta); const double R33num = P[0] + bi2 * (P[1] + bi2 * (P[2] + P[3] * bi2)); const double R33den = Q[0] + bi2 * (Q[1] + bi2 * (Q[2] + Q[3] * bi2)); const double R33 = R33num/R33den; result->val = beta + R33/beta; result->err = fabs(3.0e-15 * result->val); return GSL_SUCCESS; } } int gsl_sf_bessel_zero_J1_e(unsigned int s, gsl_sf_result * result) { /* CHECK_POINTER(result) */ if(s == 0) { result->val = 0.0; result->err = 0.0; return GSL_SUCCESS; } else { /* See [M. Branders et al., J. Comp. Phys. 42, 403 (1981)]. */ static const double a[] = { -0.362804405737084, 0.120341279038597, 0.439454547101171e-01, 0.159340088474713e-02 }; static const double b[] = { 1.0, -0.325641790801361, -0.117453445968927, -0.424906902601794e-02 }; const double beta = (s + 0.25) * M_PI; const double bi2 = 1.0/(beta*beta); const double Rnum = a[3] + bi2 * (a[2] + bi2 * (a[1] + bi2 * a[0])); const double Rden = b[3] + bi2 * (b[2] + bi2 * (b[1] + bi2 * b[0])); const double R = Rnum/Rden; result->val = beta * (1.0 + R*bi2); result->err = fabs(2.0e-14 * result->val); return GSL_SUCCESS; } } int gsl_sf_bessel_zero_Jnu_e(double nu, unsigned int s, gsl_sf_result * result) { /* CHECK_POINTER(result) */ if(nu <= -1.0) { DOMAIN_ERROR(result); } else if(s == 0) { result->val = 0.0; result->err = 0.0; if (nu == 0.0) { GSL_ERROR ("no zero-th root for nu = 0.0", GSL_EINVAL); } return GSL_SUCCESS; } else if(nu < 0.0) { /* This can be done, I'm just lazy now. */ result->val = 0.0; result->err = 0.0; GSL_ERROR("unimplemented", GSL_EUNIMPL); } else if(s == 1) { /* Chebyshev fits for the first positive zero. * For some reason Nemeth made this different from the others. */ if(nu < 2.0) { const double * c = coef_jnu_a[s]; const size_t L = size_jnu_a[s]; const double arg = nu/2.0; const double chb = clenshaw(c, L-1, arg); result->val = chb; result->err = 2.0e-15 * result->val; } else { const double * c = coef_jnu_b[s]; const size_t L = size_jnu_b[s]; const double arg = pow(2.0/nu, 2.0/3.0); const double chb = clenshaw(c, L-1, arg); result->val = nu * chb; result->err = 2.0e-15 * result->val; } return GSL_SUCCESS; } else if(s <= 10) { /* Chebyshev fits for the first 10 positive zeros. */ if(nu < s) { const double * c = coef_jnu_a[s]; const size_t L = size_jnu_a[s]; const double arg = nu/s; const double chb = clenshaw(c, L-1, arg); result->val = chb; result->err = 2.0e-15 * result->val; } else { const double * c = coef_jnu_b[s]; const size_t L = size_jnu_b[s]; const double arg = pow(s/nu, 2.0/3.0); const double chb = clenshaw(c, L-1, arg); result->val = nu * chb; result->err = 2.0e-15 * result->val; /* FIXME: truth in advertising for the screwed up * s = 5 fit. Need to fix that. */ if(s == 5) { result->err *= 5.0e+06; } } return GSL_SUCCESS; } else if(s > 0.5*nu && s <= 20) { /* Chebyshev fits for 10 < s <= 20. */ const double * c = coef_jnu_a[s]; const size_t L = size_jnu_a[s]; const double arg = nu/(2.0*s); const double chb = clenshaw(c, L-1, arg); result->val = chb; result->err = 4.0e-15 * chb; return GSL_SUCCESS; } else if(s > 2.0 * nu) { /* McMahon expansion if s is large compared to nu. */ const double beta = (s + 0.5*nu - 0.25) * M_PI; const double mc = mcmahon_correction(4.0*nu*nu, beta); gsl_sf_result rat12; gsl_sf_pow_int_e(nu/beta, 14, &rat12); result->val = beta * mc; result->err = 4.0 * fabs(beta) * rat12.val; result->err += 4.0 * fabs(GSL_DBL_EPSILON * result->val); return GSL_SUCCESS; } else { /* Olver uniform asymptotic. */ gsl_sf_result as; const int stat_as = gsl_sf_airy_zero_Ai_e(s, &as); const double minus_zeta = -pow(nu,-2.0/3.0) * as.val; const double z = gsl_sf_bessel_Olver_zofmzeta(minus_zeta); const double f1 = olver_f1(z, minus_zeta); result->val = nu * (z + f1/(nu*nu)); result->err = 0.001/(nu*nu*nu); result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); return stat_as; } } /*-*-*-*-*-*-*-*-*-* Functions w/ Natural Prototypes *-*-*-*-*-*-*-*-*-*-*/ #include "eval.h" double gsl_sf_bessel_zero_J0(unsigned int s) { EVAL_RESULT(gsl_sf_bessel_zero_J0_e(s, &result)); } double gsl_sf_bessel_zero_J1(unsigned int s) { EVAL_RESULT(gsl_sf_bessel_zero_J1_e(s, &result)); } double gsl_sf_bessel_zero_Jnu(double nu, unsigned int s) { EVAL_RESULT(gsl_sf_bessel_zero_Jnu_e(nu, s, &result)); }