📄 fermi_dirac.c
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-1.3333e-15, 1.898e-16, 2.72e-17, -3.9e-18, -6.e-19, 1.e-19};static cheb_series fd_half_a_cs = { fd_half_a_data, 22, -1, 1, 11};/* Chebyshev fit for F_{1/2}(3/2(t+1) + 1); -1 < t < 1, 1 < x < 4 */static double fd_half_b_data[20] = { 7.651013792074984027, 2.475545606866155737, 0.218335982672476128, -0.007730591500584980, -0.000217443383867318, 0.000147663980681359, -0.000021586361321527, 8.07712735394e-7, 3.28858050706e-7, -7.9474330632e-8, 6.940207234e-9, 6.75594681e-10, -3.10200490e-10, 4.2677233e-11, -2.1696e-14, -1.170245e-12, 2.34757e-13, -1.4139e-14, -3.864e-15, 1.202e-15};static cheb_series fd_half_b_cs = { fd_half_b_data, 19, -1, 1, 12};/* Chebyshev fit for F_{1/2}(3(t+1) + 4); -1 < t < 1, 4 < x < 10 */static double fd_half_c_data[23] = { 29.584339348839816528, 8.808344283250615592, 0.503771641883577308, -0.021540694914550443, 0.002143341709406890, -0.000257365680646579, 0.000027933539372803, -1.678525030167e-6, -2.78100117693e-7, 1.35218065147e-7, -3.3740425009e-8, 6.474834942e-9, -1.009678978e-9, 1.20057555e-10, -6.636314e-12, -1.710566e-12, 7.75069e-13, -1.97973e-13, 3.9414e-14, -6.374e-15, 7.77e-16, -4.0e-17, -1.4e-17};static cheb_series fd_half_c_cs = { fd_half_c_data, 22, -1, 1, 13};/* Chebyshev fit for F_{1/2}(x) / x^(3/2) * 10 < x < 30 * -1 < t < 1 * t = 1/10 (x-10) - 1 = x/10 - 2 */static double fd_half_d_data[30] = { 1.5116909434145508537, -0.0036043405371630468, 0.0014207743256393359, -0.0005045399052400260, 0.0001690758006957347, -0.0000546305872688307, 0.0000172223228484571, -5.3352603788706e-6, 1.6315287543662e-6, -4.939021084898e-7, 1.482515450316e-7, -4.41552276226e-8, 1.30503160961e-8, -3.8262599802e-9, 1.1123226976e-9, -3.204765534e-10, 9.14870489e-11, -2.58778946e-11, 7.2550731e-12, -2.0172226e-12, 5.566891e-13, -1.526247e-13, 4.16121e-14, -1.12933e-14, 3.0537e-15, -8.234e-16, 2.215e-16, -5.95e-17, 1.59e-17, -4.0e-18};static cheb_series fd_half_d_cs = { fd_half_d_data, 29, -1, 1, 15};/* Chebyshev fit for F_{3/2}(t); -1 < t < 1, -1 < x < 1 */static double fd_3half_a_data[20] = { 2.0404775940601704976, 0.8122168298093491444, 0.1536371165644008069, 0.0156174323847845125, 0.0005943427879290297, -0.0000429609447738365, -3.8246452994606e-6, 3.802306180287e-7, 4.05746157593e-8, -4.5530360159e-9, -5.306873139e-10, 6.37297268e-11, 7.8403674e-12, -9.840241e-13, -1.255952e-13, 1.62617e-14, 2.1318e-15, -2.825e-16, -3.78e-17, 5.1e-18};static cheb_series fd_3half_a_cs = { fd_3half_a_data, 19, -1, 1, 11};/* Chebyshev fit for F_{3/2}(3/2(t+1) + 1); -1 < t < 1, 1 < x < 4 */static double fd_3half_b_data[22] = { 13.403206654624176674, 5.574508357051880924, 0.931228574387527769, 0.054638356514085862, -0.001477172902737439, -0.000029378553381869, 0.000018357033493246, -2.348059218454e-6, 8.3173787440e-8, 2.6826486956e-8, -6.011244398e-9, 4.94345981e-10, 3.9557340e-11, -1.7894930e-11, 2.348972e-12, -1.2823e-14, -5.4192e-14, 1.0527e-14, -6.39e-16, -1.47e-16, 4.5e-17, -5.e-18};static cheb_series fd_3half_b_cs = { fd_3half_b_data, 21, -1, 1, 12};/* Chebyshev fit for F_{3/2}(3(t+1) + 4); -1 < t < 1, 4 < x < 10 */static double fd_3half_c_data[21] = { 101.03685253378877642, 43.62085156043435883, 6.62241373362387453, 0.25081415008708521, -0.00798124846271395, 0.00063462245101023, -0.00006392178890410, 6.04535131939e-6, -3.4007683037e-7, -4.072661545e-8, 1.931148453e-8, -4.46328355e-9, 7.9434717e-10, -1.1573569e-10, 1.304658e-11, -7.4114e-13, -1.4181e-13, 6.491e-14, -1.597e-14, 3.05e-15, -4.8e-16};static cheb_series fd_3half_c_cs = { fd_3half_c_data, 20, -1, 1, 12};/* Chebyshev fit for F_{3/2}(x) / x^(5/2) * 10 < x < 30 * -1 < t < 1 * t = 1/10 (x-10) - 1 = x/10 - 2 */static double fd_3half_d_data[25] = { 0.6160645215171852381, -0.0071239478492671463, 0.0027906866139659846, -0.0009829521424317718, 0.0003260229808519545, -0.0001040160912910890, 0.0000322931223232439, -9.8243506588102e-6, 2.9420132351277e-6, -8.699154670418e-7, 2.545460071999e-7, -7.38305056331e-8, 2.12545670310e-8, -6.0796532462e-9, 1.7294556741e-9, -4.896540687e-10, 1.380786037e-10, -3.88057305e-11, 1.08753212e-11, -3.0407308e-12, 8.485626e-13, -2.364275e-13, 6.57636e-14, -1.81807e-14, 4.6884e-15};static cheb_series fd_3half_d_cs = { fd_3half_d_data, 24, -1, 1, 16};/* Goano's modification of the Levin-u implementation. * This is a simplification of the original WHIZ algorithm. * See [Fessler et al., ACM Toms 9, 346 (1983)]. */staticintfd_whiz(const double term, const int iterm, double * qnum, double * qden, double * result, double * s){ if(iterm == 0) *s = 0.0; *s += term; qden[iterm] = 1.0/(term*(iterm+1.0)*(iterm+1.0)); qnum[iterm] = *s * qden[iterm]; if(iterm > 0) { double factor = 1.0; double ratio = iterm/(iterm+1.0); int j; for(j=iterm-1; j>=0; j--) { double c = factor * (j+1.0) / (iterm+1.0); factor *= ratio; qden[j] = qden[j+1] - c * qden[j]; qnum[j] = qnum[j+1] - c * qnum[j]; } } *result = qnum[0] / qden[0]; return GSL_SUCCESS;}/* Handle case of integer j <= -2. */staticintfd_nint(const int j, const double x, gsl_sf_result * result){/* const int nsize = 100 + 1; */ enum { nsize = 100+1 }; double qcoeff[nsize]; if(j >= -1) { result->val = 0.0; result->err = 0.0; GSL_ERROR ("error", GSL_ESANITY); } else if(j < -(nsize)) { result->val = 0.0; result->err = 0.0; GSL_ERROR ("error", GSL_EUNIMPL); } else { double a, p, f; int i, k; int n = -(j+1); qcoeff[1] = 1.0; for(k=2; k<=n; k++) { qcoeff[k] = -qcoeff[k-1]; for(i=k-1; i>=2; i--) { qcoeff[i] = i*qcoeff[i] - (k-(i-1))*qcoeff[i-1]; } } if(x >= 0.0) { a = exp(-x); f = qcoeff[1]; for(i=2; i<=n; i++) { f = f*a + qcoeff[i]; } } else { a = exp(x); f = qcoeff[n]; for(i=n-1; i>=1; i--) { f = f*a + qcoeff[i]; } } p = gsl_sf_pow_int(1.0+a, j); result->val = f*a*p; result->err = 3.0 * GSL_DBL_EPSILON * fabs(f*a*p); return GSL_SUCCESS; }}/* x < 0 */staticintfd_neg(const double j, const double x, gsl_sf_result * result){ enum { itmax = 100, qsize = 100+1 };/* const int itmax = 100; *//* const int qsize = 100 + 1; */ double qnum[qsize], qden[qsize]; if(x < GSL_LOG_DBL_MIN) { result->val = 0.0; result->err = 0.0; return GSL_SUCCESS; } else if(x < -1.0 && x < -fabs(j+1.0)) { /* Simple series implementation. Avoid the * complexity and extra work of the series * acceleration method below. */ double ex = exp(x); double term = ex; double sum = term; int n; for(n=2; n<100; n++) { double rat = (n-1.0)/n; double p = pow(rat, j+1.0); term *= -ex * p; sum += term; if(fabs(term/sum) < GSL_DBL_EPSILON) break; } result->val = sum; result->err = 2.0 * GSL_DBL_EPSILON * fabs(sum); return GSL_SUCCESS; } else { double s; double xn = x; double ex = -exp(x); double enx = -ex; double f = 0.0; double f_previous; int jterm; for(jterm=0; jterm<=itmax; jterm++) { double p = pow(jterm+1.0, j+1.0); double term = enx/p; f_previous = f; fd_whiz(term, jterm, qnum, qden, &f, &s); xn += x; if(fabs(f-f_previous) < fabs(f)*2.0*GSL_DBL_EPSILON || xn < GSL_LOG_DBL_MIN) break; enx *= ex; } result->val = f; result->err = fabs(f-f_previous); result->err += 2.0 * GSL_DBL_EPSILON * fabs(f); if(jterm == itmax) GSL_ERROR ("error", GSL_EMAXITER); else return GSL_SUCCESS; }}/* asymptotic expansion * j + 2.0 > 0.0 */staticintfd_asymp(const double j, const double x, gsl_sf_result * result){ const int j_integer = ( fabs(j - floor(j+0.5)) < 100.0*GSL_DBL_EPSILON ); const int itmax = 200; gsl_sf_result lg; int stat_lg = gsl_sf_lngamma_e(j + 2.0, &lg); double seqn_val = 0.5; double seqn_err = 0.0; double xm2 = (1.0/x)/x; double xgam = 1.0; double add = GSL_DBL_MAX; double cos_term; double ln_x; double ex_term_1; double ex_term_2; gsl_sf_result fneg; gsl_sf_result ex_arg; gsl_sf_result ex; int stat_fneg; int stat_e; int n; for(n=1; n<=itmax; n++) { double add_previous = add; gsl_sf_result eta; gsl_sf_eta_int_e(2*n, &eta); xgam = xgam * xm2 * (j + 1.0 - (2*n-2)) * (j + 1.0 - (2*n-1)); add = eta.val * xgam; if(!j_integer && fabs(add) > fabs(add_previous)) break; if(fabs(add/seqn_val) < GSL_DBL_EPSILON) break; seqn_val += add; seqn_err += 2.0 * GSL_DBL_EPSILON * fabs(add); } seqn_err += fabs(add); stat_fneg = fd_neg(j, -x, &fneg); ln_x = log(x); ex_term_1 = (j+1.0)*ln_x; ex_term_2 = lg.val; ex_arg.val = ex_term_1 - ex_term_2; /*(j+1.0)*ln_x - lg.val; */ ex_arg.err = GSL_DBL_EPSILON*(fabs(ex_term_1) + fabs(ex_term_2)) + lg.err; stat_e = gsl_sf_exp_err_e(ex_arg.val, ex_arg.err, &ex); cos_term = cos(j*M_PI); result->val = cos_term * fneg.val + 2.0 * seqn_val * ex.val; result->err = fabs(2.0 * ex.err * seqn_val); result->err += fabs(2.0 * ex.val * seqn_err); result->err += fabs(cos_term) * fneg.err; result->err += 4.0 * GSL_DBL_EPSILON * fabs(result->val); return GSL_ERROR_SELECT_3(stat_e, stat_fneg, stat_lg);}/* Series evaluation for small x, generic j. * [Goano (8)] */#if 0staticintfd_series(const double j, const double x, double * result){ const int nmax = 1000; int n; double sum = 0.0; double prev; double pow_factor = 1.0; double eta_factor; gsl_sf_eta_e(j + 1.0, &eta_factor); prev = pow_factor * eta_factor; sum += prev; for(n=1; n<nmax; n++) { double term; gsl_sf_eta_e(j+1.0-n, &eta_factor); pow_factor *= x/n; term = pow_factor * eta_factor; sum += term; if(fabs(term/sum) < GSL_DBL_EPSILON && fabs(prev/sum) < GSL_DBL_EPSILON) break; prev = term; } *result = sum; return GSL_SUCCESS;}#endif /* 0 *//* Series evaluation for small x > 0, integer j > 0; x < Pi. * [Goano (8)] */staticintfd_series_int(const int j, const double x, gsl_sf_result * result){ int n; double sum = 0.0; double del; double pow_factor = 1.0; gsl_sf_result eta_factor; gsl_sf_eta_int_e(j + 1, &eta_factor); del = pow_factor * eta_factor.val; sum += del; /* Sum terms where the argument * of eta() is positive. */ for(n=1; n<=j+2; n++) { gsl_sf_eta_int_e(j+1-n, &eta_factor); pow_factor *= x/n; del = pow_factor * eta_factor.val; sum += del; if(fabs(del/sum) < GSL_DBL_EPSILON) break; }
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