/* Logarithm of normalization factor, Log[N(ell,lambda)]. * N(ell,lambda) = Product[ lambda^2 + n^2, {n,0,ell} ] * = |Gamma(ell + 1 + I lambda)|^2 lambda sinh(Pi lambda) / Pi * Assumes ell >= 0. */ static int legendre_H3d_lnnorm(const int ell, const double lambda, double * result) { double abs_lam = fabs(lambda); if(abs_lam == 0.0) { *result = 0.0; GSL_ERROR ("error", GSL_EDOM); } else if(lambda > (ell + 1.0)/GSL_ROOT3_DBL_EPSILON) { /* There is a cancellation between the sinh(Pi lambda) * term and the log(gamma(ell + 1 + i lambda) in the * result below, so we show some care and save some digits. * Note that the above guarantees that lambda is large, * since ell >= 0. We use Stirling and a simple expansion * of sinh. */ double rat = (ell+1.0)/lambda; double ln_lam2ell2 = 2.0*log(lambda) + log(1.0 + rat*rat); double lg_corrected = -2.0*(ell+1.0) + M_LNPI + (ell+0.5)*ln_lam2ell2 + 1.0/(288.0*lambda*lambda); double angle_terms = lambda * 2.0 * rat * (1.0 - rat*rat/3.0); *result = log(abs_lam) + lg_corrected + angle_terms - M_LNPI; return GSL_SUCCESS; } else { gsl_sf_result lg_r; gsl_sf_result lg_theta; gsl_sf_result ln_sinh; gsl_sf_lngamma_complex_e(ell+1.0, lambda, &lg_r, &lg_theta); gsl_sf_lnsinh_e(M_PI * abs_lam, &ln_sinh); *result = log(abs_lam) + ln_sinh.val + 2.0*lg_r.val - M_LNPI; return GSL_SUCCESS; } }
/* Calculate series for small eta*lambda. * Assumes eta > 0, lambda != 0. * * This is just the defining hypergeometric for the Legendre function. * * P^{mu}_{-1/2 + I lam}(z) = 1/Gamma(l+3/2) ((z+1)/(z-1)^(mu/2) * 2F1(1/2 - I lam, 1/2 + I lam; l+3/2; (1-z)/2) * We use * z = cosh(eta) * (z-1)/2 = sinh^2(eta/2) * * And recall * H3d = sqrt(Pi Norm /(2 lam^2 sinh(eta))) P^{-l-1/2}_{-1/2 + I lam}(cosh(eta)) */ static int legendre_H3d_series(const int ell, const double lambda, const double eta, gsl_sf_result * result) { const int nmax = 5000; const double shheta = sinh(0.5*eta); const double ln_zp1 = M_LN2 + log(1.0 + shheta*shheta); const double ln_zm1 = M_LN2 + 2.0*log(shheta); const double zeta = -shheta*shheta; gsl_sf_result lg_lp32; double term = 1.0; double sum = 1.0; double sum_err = 0.0; gsl_sf_result lnsheta; double lnN; double lnpre_val, lnpre_err, lnprepow; int stat_e; int n; gsl_sf_lngamma_e(ell + 3.0/2.0, &lg_lp32); gsl_sf_lnsinh_e(eta, &lnsheta); legendre_H3d_lnnorm(ell, lambda, &lnN); lnprepow = 0.5*(ell + 0.5) * (ln_zm1 - ln_zp1); lnpre_val = lnprepow + 0.5*(lnN + M_LNPI - M_LN2 - lnsheta.val) - lg_lp32.val - log(fabs(lambda)); lnpre_err = lnsheta.err + lg_lp32.err + GSL_DBL_EPSILON * fabs(lnpre_val); lnpre_err += 2.0*GSL_DBL_EPSILON * (fabs(lnN) + M_LNPI + M_LN2); lnpre_err += 2.0*GSL_DBL_EPSILON * (0.5*(ell + 0.5) * (fabs(ln_zm1) + fabs(ln_zp1))); for(n=1; n<nmax; n++) { double aR = n - 0.5; term *= (aR*aR + lambda*lambda)*zeta/(ell + n + 0.5)/n; sum += term; sum_err += 2.0*GSL_DBL_EPSILON*fabs(term); if(fabs(term/sum) < 2.0 * GSL_DBL_EPSILON) break; } stat_e = gsl_sf_exp_mult_err_e(lnpre_val, lnpre_err, sum, fabs(term)+sum_err, result); return GSL_ERROR_SELECT_2(stat_e, (n==nmax ? GSL_EMAXITER : GSL_SUCCESS)); }
double gsl_sf_lnsinh(const double x) { EVAL_RESULT(gsl_sf_lnsinh_e(x, &result)); }
int gsl_sf_legendre_H3d_e(const int ell, const double lambda, const double eta, gsl_sf_result * result) { const double abs_lam = fabs(lambda); const double lsq = abs_lam*abs_lam; const double xi = abs_lam * eta; const double cosh_eta = cosh(eta); /* CHECK_POINTER(result) */ if(eta < 0.0) { DOMAIN_ERROR(result); } else if(eta > GSL_LOG_DBL_MAX) { /* cosh(eta) is too big. */ OVERFLOW_ERROR(result); } else if(ell == 0) { return gsl_sf_legendre_H3d_0_e(lambda, eta, result); } else if(ell == 1) { return gsl_sf_legendre_H3d_1_e(lambda, eta, result); } else if(eta == 0.0) { result->val = 0.0; result->err = 0.0; return GSL_SUCCESS; } else if(xi < 1.0) { return legendre_H3d_series(ell, lambda, eta, result); } else if((ell*ell+lsq)/sqrt(1.0+lsq)/(cosh_eta*cosh_eta) < 5.0*GSL_ROOT3_DBL_EPSILON) { /* Large argument. */ gsl_sf_result P; double lm; int stat_P = gsl_sf_conicalP_large_x_e(-ell-0.5, lambda, cosh_eta, &P, &lm); if(P.val == 0.0) { result->val = 0.0; result->err = 0.0; return stat_P; } else { double lnN; gsl_sf_result lnsh; double ln_abslam; double lnpre_val, lnpre_err; int stat_e; gsl_sf_lnsinh_e(eta, &lnsh); legendre_H3d_lnnorm(ell, lambda, &lnN); ln_abslam = log(abs_lam); lnpre_val = 0.5*(M_LNPI + lnN - M_LN2 - lnsh.val) - ln_abslam; lnpre_err = lnsh.err; lnpre_err += 2.0 * GSL_DBL_EPSILON * (0.5*(M_LNPI + M_LN2 + fabs(lnN)) + fabs(ln_abslam)); lnpre_err += 2.0 * GSL_DBL_EPSILON * fabs(lnpre_val); stat_e = gsl_sf_exp_mult_err_e(lnpre_val + lm, lnpre_err, P.val, P.err, result); return GSL_ERROR_SELECT_2(stat_e, stat_P); } } else if(abs_lam > 1000.0*ell*ell) { /* Large degree. */ gsl_sf_result P; double lm; int stat_P = gsl_sf_conicalP_xgt1_neg_mu_largetau_e(ell+0.5, lambda, cosh_eta, eta, &P, &lm); if(P.val == 0.0) { result->val = 0.0; result->err = 0.0; return stat_P; } else { double lnN; gsl_sf_result lnsh; double ln_abslam; double lnpre_val, lnpre_err; int stat_e; gsl_sf_lnsinh_e(eta, &lnsh); legendre_H3d_lnnorm(ell, lambda, &lnN); ln_abslam = log(abs_lam); lnpre_val = 0.5*(M_LNPI + lnN - M_LN2 - lnsh.val) - ln_abslam; lnpre_err = lnsh.err; lnpre_err += GSL_DBL_EPSILON * (0.5*(M_LNPI + M_LN2 + fabs(lnN)) + fabs(ln_abslam)); lnpre_err += 2.0 * GSL_DBL_EPSILON * fabs(lnpre_val); stat_e = gsl_sf_exp_mult_err_e(lnpre_val + lm, lnpre_err, P.val, P.err, result); return GSL_ERROR_SELECT_2(stat_e, stat_P); } } else { /* Backward recurrence. */ const double coth_eta = 1.0/tanh(eta); const double coth_err_mult = fabs(eta) + 1.0; gsl_sf_result rH; int stat_CF1 = legendre_H3d_CF1_ser(ell, lambda, coth_eta, &rH); double Hlm1; double Hl = GSL_SQRT_DBL_MIN; double Hlp1 = rH.val * Hl; int lp; for(lp=ell; lp>0; lp--) { double root_term_0 = sqrt(lambda*lambda + (double)lp*lp); double root_term_1 = sqrt(lambda*lambda + (lp+1.0)*(lp+1.0)); Hlm1 = ((2.0*lp + 1.0)*coth_eta*Hl - root_term_1 * Hlp1)/root_term_0; Hlp1 = Hl; Hl = Hlm1; } if(fabs(Hl) > fabs(Hlp1)) { gsl_sf_result H0; int stat_H0 = gsl_sf_legendre_H3d_0_e(lambda, eta, &H0); result->val = GSL_SQRT_DBL_MIN/Hl * H0.val; result->err = GSL_SQRT_DBL_MIN/fabs(Hl) * H0.err; result->err += fabs(rH.err/rH.val) * (ell+1.0) * coth_err_mult * fabs(result->val); result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); return GSL_ERROR_SELECT_2(stat_H0, stat_CF1); } else { gsl_sf_result H1; int stat_H1 = gsl_sf_legendre_H3d_1_e(lambda, eta, &H1); result->val = GSL_SQRT_DBL_MIN/Hlp1 * H1.val; result->err = GSL_SQRT_DBL_MIN/fabs(Hlp1) * H1.err; result->err += fabs(rH.err/rH.val) * (ell+1.0) * coth_err_mult * fabs(result->val); result->err += 2.0 * GSL_DBL_EPSILON * fabs(result->val); return GSL_ERROR_SELECT_2(stat_H1, stat_CF1); } } }