# acb_hypgeom.h – hypergeometric functions of complex variables¶

The generalized hypergeometric function is formally defined by

${}_pF_q(a_1,\ldots,a_p;b_1,\ldots,b_q;z) = \sum_{k=0}^\infty \frac{(a_1)_k\dots(a_p)_k}{(b_1)_k\dots(b_q)_k} \frac {z^k} {k!}.$

It can be interpreted using analytic continuation or regularization when the sum does not converge. In a looser sense, we understand “hypergeometric functions” to be linear combinations of generalized hypergeometric functions with prefactors that are products of exponentials, powers, and gamma functions.

## Convergent series¶

In this section, we define

$T(k) = \frac{\prod_{i=0}^{p-1} (a_i)_k}{\prod_{i=0}^{q-1} (b_i)_k} z^k$

and

${}_pf_{q}(a_0,\ldots,a_{p-1}; b_0 \ldots b_{q-1}; z) = {}_{p+1}F_{q}(a_0,\ldots,a_{p-1},1; b_0 \ldots b_{q-1}; z) = \sum_{k=0}^{\infty} T(k)$

For the conventional generalized hypergeometric function $${}_pF_{q}$$, compute $${}_pf_{q+1}$$ with the explicit parameter $$b_q = 1$$, or remove a 1 from the $$a_i$$ parameters if there is one.

void acb_hypgeom_pfq_bound_factor(mag_t C, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, ulong n)

Computes a factor C such that $$\left|\sum_{k=n}^{\infty} T(k)\right| \le C |T(n)|$$. See Convergent series. As currently implemented, the bound becomes infinite when $$n$$ is too small, even if the series converges.

slong acb_hypgeom_pfq_choose_n(acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, slong prec)

Heuristically attempts to choose a number of terms n to sum of a hypergeometric series at a working precision of prec bits.

Uses double precision arithmetic internally. As currently implemented, it can fail to produce a good result if the parameters are extremely large or extremely close to nonpositive integers.

Numerical cancellation is assumed to be significant, so truncation is done when the current term is prec bits smaller than the largest encountered term.

This function will also attempt to pick a reasonable truncation point for divergent series.

void acb_hypgeom_pfq_sum_forward(acb_t s, acb_t t, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, slong n, slong prec)
void acb_hypgeom_pfq_sum_rs(acb_t s, acb_t t, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, slong n, slong prec)
void acb_hypgeom_pfq_sum_bs(acb_t s, acb_t t, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, slong n, slong prec)
void acb_hypgeom_pfq_sum_fme(acb_t s, acb_t t, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, slong n, slong prec)
void acb_hypgeom_pfq_sum(acb_t s, acb_t t, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, slong n, slong prec)

Computes $$s = \sum_{k=0}^{n-1} T(k)$$ and $$t = T(n)$$. Does not allow aliasing between input and output variables. We require $$n \ge 0$$.

The forward version computes the sum using forward recurrence.

The bs version computes the sum using binary splitting.

The rs version computes the sum in reverse order using rectangular splitting. It only computes a magnitude bound for the value of t.

The fme version uses fast multipoint evaluation.

The default version automatically chooses an algorithm depending on the inputs.

void acb_hypgeom_pfq_sum_bs_invz(acb_t s, acb_t t, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t w, slong n, slong prec)
void acb_hypgeom_pfq_sum_invz(acb_t s, acb_t t, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, const acb_t w, slong n, slong prec)

Like acb_hypgeom_pfq_sum(), but taking advantage of $$w = 1/z$$ possibly having few bits.

void acb_hypgeom_pfq_direct(acb_t res, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, slong n, slong prec)

Computes

${}_pf_{q}(z) = \sum_{k=0}^{\infty} T(k) = \sum_{k=0}^{n-1} T(k) + \varepsilon$

directly from the defining series, including a rigorous bound for the truncation error $$\varepsilon$$ in the output.

If $$n < 0$$, this function chooses a number of terms automatically using acb_hypgeom_pfq_choose_n().

void acb_hypgeom_pfq_series_sum_forward(acb_poly_t s, acb_poly_t t, const acb_poly_struct * a, slong p, const acb_poly_struct * b, slong q, const acb_poly_t z, int regularized, slong n, slong len, slong prec)
void acb_hypgeom_pfq_series_sum_bs(acb_poly_t s, acb_poly_t t, const acb_poly_struct * a, slong p, const acb_poly_struct * b, slong q, const acb_poly_t z, int regularized, slong n, slong len, slong prec)
void acb_hypgeom_pfq_series_sum_rs(acb_poly_t s, acb_poly_t t, const acb_poly_struct * a, slong p, const acb_poly_struct * b, slong q, const acb_poly_t z, int regularized, slong n, slong len, slong prec)
void acb_hypgeom_pfq_series_sum(acb_poly_t s, acb_poly_t t, const acb_poly_struct * a, slong p, const acb_poly_struct * b, slong q, const acb_poly_t z, int regularized, slong n, slong len, slong prec)

Computes $$s = \sum_{k=0}^{n-1} T(k)$$ and $$t = T(n)$$ given parameters and argument that are power series. Does not allow aliasing between input and output variables. We require $$n \ge 0$$ and that len is positive.

If regularized is set, the regularized sum is computed, avoiding division by zero at the poles of the gamma function.

The forward, bs, rs and default versions use forward recurrence, binary splitting, rectangular splitting, and an automatic algorithm choice.

void acb_hypgeom_pfq_series_direct(acb_poly_t res, const acb_poly_struct * a, slong p, const acb_poly_struct * b, slong q, const acb_poly_t z, int regularized, slong n, slong len, slong prec)

Computes $${}_pf_{q}(z)$$ directly using the defining series, given parameters and argument that are power series. The result is a power series of length len. We require that len is positive.

An error bound is computed automatically as a function of the number of terms n. If $$n < 0$$, the number of terms is chosen automatically.

If regularized is set, the regularized hypergeometric function is computed instead.

## Asymptotic series¶

$$U(a,b,z)$$ is the confluent hypergeometric function of the second kind with the principal branch cut, and $$U^{*} = z^a U(a,b,z)$$. For details about how error bounds are computed, see Asymptotic series for the confluent hypergeometric function.

void acb_hypgeom_u_asymp(acb_t res, const acb_t a, const acb_t b, const acb_t z, slong n, slong prec)

Sets res to $$U^{*}(a,b,z)$$ computed using n terms of the asymptotic series, with a rigorous bound for the error included in the output. We require $$n \ge 0$$.

int acb_hypgeom_u_use_asymp(const acb_t z, slong prec)

Heuristically determines whether the asymptotic series can be used to evaluate $$U(a,b,z)$$ to prec accurate bits (assuming that a and b are small).

## Generalized hypergeometric function¶

void acb_hypgeom_pfq(acb_poly_t res, acb_srcptr a, slong p, acb_srcptr b, slong q, const acb_t z, int regularized, slong prec)

Computes the generalized hypergeometric function $${}_pF_{q}(z)$$, or the regularized version if regularized is set.

This function automatically delegates to a specialized implementation when the order (p, q) is one of (0,0), (1,0), (0,1), (1,1), (2,1). Otherwise, it falls back to direct summation.

While this is a top-level function meant to take care of special cases automatically, it does not generally perform the optimization of deleting parameters that appear in both a and b. This can be done ahead of time by the user in applications where duplicate parameters are likely to occur.

## Confluent hypergeometric functions¶

void acb_hypgeom_u_1f1_series(acb_poly_t res, const acb_poly_t a, const acb_poly_t b, const acb_poly_t z, slong len, slong prec)

Computes $$U(a,b,z)$$ as a power series truncated to length len, given $$a, b, z \in \mathbb{C}[[x]]$$. If $$b[0] \in \mathbb{Z}$$, it computes one extra derivative and removes the singularity (it is then assumed that $$b[1] \ne 0$$). As currently implemented, the output is indeterminate if $$b$$ is nonexact and contains an integer.

void acb_hypgeom_u_1f1(acb_t res, const acb_t a, const acb_t b, const acb_t z, slong prec)

Computes $$U(a,b,z)$$ as a sum of two convergent hypergeometric series. If $$b \in \mathbb{Z}$$, it computes the limit value via acb_hypgeom_u_1f1_series(). As currently implemented, the output is indeterminate if $$b$$ is nonexact and contains an integer.

void acb_hypgeom_u(acb_t res, const acb_t a, const acb_t b, const acb_t z, slong prec)

Computes $$U(a,b,z)$$ using an automatic algorithm choice. The function acb_hypgeom_u_asymp() is used if $$a$$ or $$a-b+1$$ is a nonpositive integer (in which case the asymptotic series terminates), or if z is sufficiently large. Otherwise acb_hypgeom_u_1f1() is used.

void acb_hypgeom_m_asymp(acb_t res, const acb_t a, const acb_t b, const acb_t z, int regularized, slong prec)
void acb_hypgeom_m_1f1(acb_t res, const acb_t a, const acb_t b, const acb_t z, int regularized, slong prec)
void acb_hypgeom_m(acb_t res, const acb_t a, const acb_t b, const acb_t z, int regularized, slong prec)

Computes the confluent hypergeometric function $$M(a,b,z) = {}_1F_1(a,b,z)$$, or $$\mathbf{M}(a,b,z) = \frac{1}{\Gamma(b)} {}_1F_1(a,b,z)$$ if regularized is set.

void acb_hypgeom_1f1(acb_t res, const acb_t a, const acb_t b, const acb_t z, int regularized, slong prec)

Alias for acb_hypgeom_m().

void acb_hypgeom_0f1_asymp(acb_t res, const acb_t a, const acb_t z, int regularized, slong prec)
void acb_hypgeom_0f1_direct(acb_t res, const acb_t a, const acb_t z, int regularized, slong prec)
void acb_hypgeom_0f1(acb_t res, const acb_t a, const acb_t z, int regularized, slong prec)

Computes the confluent hypergeometric function $${}_0F_1(a,z)$$, or $$\frac{1}{\Gamma(a)} {}_0F_1(a,z)$$ if regularized is set, using asymptotic expansions, direct summation, or an automatic algorithm choice. The asymp version uses the asymptotic expansions of Bessel functions, together with the connection formulas

$\frac{{}_0F_1(a,z)}{\Gamma(a)} = (-z)^{(1-a)/2} J_{a-1}(2 \sqrt{-z}) = z^{(1-a)/2} I_{a-1}(2 \sqrt{z}).$

The Bessel-J function is used in the left half-plane and the Bessel-I function is used in the right half-plane, to avoid loss of accuracy due to evaluating the square root on the branch cut.

## Error functions and Fresnel integrals¶

void acb_hypgeom_erf_propagated_error(mag_t re, mag_t im, const acb_t z)

Sets re and im to upper bounds for the error in the real and imaginary part resulting from approximating the error function of z by the error function evaluated at the midpoint of z. Uses the first derivative.

void acb_hypgeom_erf_1f1a(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_erf_1f1b(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_erf_asymp(acb_t res, const acb_t z, int complementary, slong prec, slong prec2)

Computes the error function respectively using

\begin{align}\begin{aligned}\operatorname{erf}(z) &= \frac{2z}{\sqrt{\pi}} {}_1F_1(\tfrac{1}{2}, \tfrac{3}{2}, -z^2)\\\operatorname{erf}(z) &= \frac{2z e^{-z^2}}{\sqrt{\pi}} {}_1F_1(1, \tfrac{3}{2}, z^2)\\\operatorname{erf}(z) &= \frac{z}{\sqrt{z^2}} \left(1 - \frac{e^{-z^2}}{\sqrt{\pi}} U(\tfrac{1}{2}, \tfrac{1}{2}, z^2)\right) = \frac{z}{\sqrt{z^2}} - \frac{e^{-z^2}}{z \sqrt{\pi}} U^{*}(\tfrac{1}{2}, \tfrac{1}{2}, z^2).\end{aligned}\end{align}

The asymp version takes a second precision to use for the U term. It also takes an extra flag complementary, computing the complementary error function if set.

void acb_hypgeom_erf(acb_t res, const acb_t z, slong prec)

Computes the error function using an automatic algorithm choice. If z is too small to use the asymptotic expansion, a working precision sufficient to circumvent cancellation in the hypergeometric series is determined automatically, and a bound for the propagated error is computed with acb_hypgeom_erf_propagated_error().

void _acb_hypgeom_erf_series(acb_ptr res, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_erf_series(acb_poly_t res, const acb_poly_t z, slong len, slong prec)

Computes the error function of the power series z, truncated to length len.

void acb_hypgeom_erfc(acb_t res, const acb_t z, slong prec)

Computes the complementary error function $$\operatorname{erfc}(z) = 1 - \operatorname{erf}(z)$$. This function avoids catastrophic cancellation for large positive z.

void _acb_hypgeom_erfc_series(acb_ptr res, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_erfc_series(acb_poly_t res, const acb_poly_t z, slong len, slong prec)

Computes the complementary error function of the power series z, truncated to length len.

void acb_hypgeom_erfi(acb_t res, const acb_t z, slong prec)

Computes the imaginary error function $$\operatorname{erfi}(z) = -i\operatorname{erf}(iz)$$. This is a trivial wrapper of acb_hypgeom_erf().

void _acb_hypgeom_erfi_series(acb_ptr res, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_erfi_series(acb_poly_t res, const acb_poly_t z, slong len, slong prec)

Computes the imaginary error function of the power series z, truncated to length len.

void acb_hypgeom_fresnel(acb_t res1, acb_t res2, const acb_t z, int normalized, slong prec)

Sets res1 to the Fresnel sine integral $$S(z)$$ and res2 to the Fresnel cosine integral $$C(z)$$. Optionally, just a single function can be computed by passing NULL as the other output variable. The definition $$S(z) = \int_0^z \sin(t^2) dt$$ is used if normalized is 0, and $$S(z) = \int_0^z \sin(\tfrac{1}{2} \pi t^2) dt$$ is used if normalized is 1 (the latter is the Abramowitz & Stegun convention). $$C(z)$$ is defined analogously.

void _acb_hypgeom_fresnel_series(acb_ptr res1, acb_ptr res2, acb_srcptr z, slong zlen, int normalized, slong len, slong prec)
void acb_hypgeom_fresnel_series(acb_poly_t res1, acb_poly_t res2, const acb_poly_t z, int normalized, slong len, slong prec)

Sets res1 to the Fresnel sine integral and res2 to the Fresnel cosine integral of the power series z, truncated to length len. Optionally, just a single function can be computed by passing NULL as the other output variable.

## Bessel functions¶

void acb_hypgeom_bessel_j_asymp(acb_t res, const acb_t nu, const acb_t z, slong prec)

Computes the Bessel function of the first kind via acb_hypgeom_u_asymp(). For all complex $$\nu, z$$, we have

$J_{\nu}(z) = \frac{z^{\nu}}{2^{\nu} e^{iz} \Gamma(\nu+1)} {}_1F_1(\nu+\tfrac{1}{2}, 2\nu+1, 2iz) = A_{+} B_{+} + A_{-} B_{-}$

where

$A_{\pm} = z^{\nu} (z^2)^{-\tfrac{1}{2}-\nu} (\mp i z)^{\tfrac{1}{2}+\nu} (2 \pi)^{-1/2} = (\pm iz)^{-1/2-\nu} z^{\nu} (2 \pi)^{-1/2}$
$B_{\pm} = e^{\pm i z} U^{*}(\nu+\tfrac{1}{2}, 2\nu+1, \mp 2iz).$

Nicer representations of the factors $$A_{\pm}$$ can be given depending conditionally on the parameters. If $$\nu + \tfrac{1}{2} = n \in \mathbb{Z}$$, we have $$A_{\pm} = (\pm i)^{n} (2 \pi z)^{-1/2}$$. And if $$\operatorname{Re}(z) > 0$$, we have $$A_{\pm} = \exp(\mp i [(2\nu+1)/4] \pi) (2 \pi z)^{-1/2}$$.

void acb_hypgeom_bessel_j_0f1(acb_t res, const acb_t nu, const acb_t z, slong prec)

Computes the Bessel function of the first kind from

$J_{\nu}(z) = \frac{1}{\Gamma(\nu+1)} \left(\frac{z}{2}\right)^{\nu} {}_0F_1\left(\nu+1, -\frac{z^2}{4}\right).$
void acb_hypgeom_bessel_j(acb_t res, const acb_t nu, const acb_t z, slong prec)

Computes the Bessel function of the first kind $$J_{\nu}(z)$$ using an automatic algorithm choice.

void acb_hypgeom_bessel_y(acb_t res, const acb_t nu, const acb_t z, slong prec)

Computes the Bessel function of the second kind $$Y_{\nu}(z)$$ from the formula

$Y_{\nu}(z) = \frac{\cos(\nu \pi) J_{\nu}(z) - J_{-\nu}(z)}{\sin(\nu \pi)}$

unless $$\nu = n$$ is an integer in which case the limit value

$Y_n(z) = -\frac{2}{\pi} \left( i^n K_n(iz) + \left[\log(iz)-\log(z)\right] J_n(z) \right)$

is computed. As currently implemented, the output is indeterminate if $$\nu$$ is nonexact and contains an integer.

void acb_hypgeom_bessel_jy(acb_t res1, acb_t res2, const acb_t nu, const acb_t z, slong prec)

Sets res1 to $$J_{\nu}(z)$$ and res2 to $$Y_{\nu}(z)$$, computed simultaneously. From these values, the user can easily construct the Bessel functions of the third kind (Hankel functions) $$H_{\nu}^{(1)}(z), H_{\nu}^{(2)}(z) = J_{\nu}(z) \pm i Y_{\nu}(z)$$.

## Modified Bessel functions¶

void acb_hypgeom_bessel_i_asymp(acb_t res, const acb_t nu, const acb_t z, int scaled, slong prec)
void acb_hypgeom_bessel_i_0f1(acb_t res, const acb_t nu, const acb_t z, int scaled, slong prec)
void acb_hypgeom_bessel_i(acb_t res, const acb_t nu, const acb_t z, slong prec)
void acb_hypgeom_bessel_i_scaled(acb_t res, const acb_t nu, const acb_t z, slong prec)

Computes the modified Bessel function of the first kind $$I_{\nu}(z) = z^{\nu} (iz)^{-\nu} J_{\nu}(iz)$$ respectively using asymptotic series (see acb_hypgeom_bessel_j_asymp()), the convergent series

$I_{\nu}(z) = \frac{1}{\Gamma(\nu+1)} \left(\frac{z}{2}\right)^{\nu} {}_0F_1\left(\nu+1, \frac{z^2}{4}\right),$

or an automatic algorithm choice.

The scaled version computes the function $$e^{-z} I_{\nu}(z)$$. The asymp and 0f1 functions implement both variants and allow choosing with a flag.

void acb_hypgeom_bessel_k_asymp(acb_t res, const acb_t nu, const acb_t z, int scaled, slong prec)

Computes the modified Bessel function of the second kind via via acb_hypgeom_u_asymp(). For all $$\nu$$ and all $$z \ne 0$$, we have

$K_{\nu}(z) = \left(\frac{2z}{\pi}\right)^{-1/2} e^{-z} U^{*}(\nu+\tfrac{1}{2}, 2\nu+1, 2z).$

If scaled is set, computes the function $$e^{z} K_{\nu}(z)$$.

void acb_hypgeom_bessel_k_0f1_series(acb_poly_t res, const acb_poly_t nu, const acb_poly_t z, int scaled, slong len, slong prec)

Computes the modified Bessel function of the second kind $$K_{\nu}(z)$$ as a power series truncated to length len, given $$\nu, z \in \mathbb{C}[[x]]$$. Uses the formula

$K_{\nu}(z) = \frac{1}{2} \frac{\pi}{\sin(\pi \nu)} \left[ \left(\frac{z}{2}\right)^{-\nu} {}_0{\widetilde F}_1\left(1-\nu, \frac{z^2}{4}\right) - \left(\frac{z}{2}\right)^{\nu} {}_0{\widetilde F}_1\left(1+\nu, \frac{z^2}{4}\right) \right].$

If $$\nu[0] \in \mathbb{Z}$$, it computes one extra derivative and removes the singularity (it is then assumed that $$\nu[1] \ne 0$$). As currently implemented, the output is indeterminate if $$\nu[0]$$ is nonexact and contains an integer.

If scaled is set, computes the function $$e^{z} K_{\nu}(z)$$.

void acb_hypgeom_bessel_k_0f1(acb_t res, const acb_t nu, const acb_t z, int scaled, slong prec)

Computes the modified Bessel function of the second kind from

$K_{\nu}(z) = \frac{1}{2} \left[ \left(\frac{z}{2}\right)^{-\nu} \Gamma(\nu) {}_0F_1\left(1-\nu, \frac{z^2}{4}\right) - \left(\frac{z}{2}\right)^{\nu} \frac{\pi}{\nu \sin(\pi \nu) \Gamma(\nu)} {}_0F_1\left(\nu+1, \frac{z^2}{4}\right) \right]$

if $$\nu \notin \mathbb{Z}$$. If $$\nu \in \mathbb{Z}$$, it computes the limit value via acb_hypgeom_bessel_k_0f1_series(). As currently implemented, the output is indeterminate if $$\nu$$ is nonexact and contains an integer.

If scaled is set, computes the function $$e^{z} K_{\nu}(z)$$.

void acb_hypgeom_bessel_k(acb_t res, const acb_t nu, const acb_t z, slong prec)

Computes the modified Bessel function of the second kind $$K_{\nu}(z)$$ using an automatic algorithm choice.

void acb_hypgeom_bessel_k_scaled(acb_t res, const acb_t nu, const acb_t z, slong prec)

Computes the function $$e^{z} K_{\nu}(z)$$.

## Airy functions¶

The Airy functions are linearly independent solutions of the differential equation $$y'' - zy = 0$$. All solutions are entire functions. The standard solutions are denoted $$\operatorname{Ai}(z), \operatorname{Bi}(z)$$. For negative z, both functions are oscillatory. For positive z, the first function decreases exponentially while the second increases exponentially.

The Airy functions can be expressed in terms of Bessel functions of fractional order, but this is inconvenient since such formulas only hold piecewise (due to the Stokes phenomenon). Computation of the Airy functions can also be optimized more than Bessel functions in general. We therefore provide a dedicated interface for evaluating Airy functions.

The following methods optionally compute $$(\operatorname{Ai}(z), \operatorname{Ai}'(z), \operatorname{Bi}(z), \operatorname{Bi}'(z))$$ simultaneously. Any of the four function values can be omitted by passing NULL for the unwanted output variables, speeding up the evaluation.

void acb_hypgeom_airy_direct(acb_t ai, acb_t ai_prime, acb_t bi, acb_t bi_prime, const acb_t z, slong n, slong prec)

Computes the Airy functions using direct series expansions truncated at n terms. Error bounds are included in the output.

void acb_hypgeom_airy_asymp(acb_t ai, acb_t ai_prime, acb_t bi, acb_t bi_prime, const acb_t z, slong n, slong prec)

Computes the Airy functions using asymptotic expansions truncated at n terms. Error bounds are included in the output. For details about how the error bounds are computed, see Asymptotic series for Airy functions.

void acb_hypgeom_airy_bound(mag_t ai, mag_t ai_prime, mag_t bi, mag_t bi_prime, const acb_t z)

Computes bounds for the Airy functions using first-order asymptotic expansions together with error bounds. This function uses some shortcuts to make it slightly faster than calling acb_hypgeom_airy_asymp() with $$n = 1$$.

void acb_hypgeom_airy(acb_t ai, acb_t ai_prime, acb_t bi, acb_t bi_prime, const acb_t z, slong prec)

Computes Airy functions using an automatic algorithm choice.

We use acb_hypgeom_airy_asymp() whenever this gives full accuracy and acb_hypgeom_airy_direct() otherwise. In the latter case, we first use hardware double precision arithmetic to determine an accurate estimate of the working precision needed to compute the Airy functions accurately for given z. This estimate is obtained by comparing the leading-order asymptotic estimate of the Airy functions with the magnitude of the largest term in the power series. The estimate is generic in the sense that it does not take into account vanishing near the roots of the functions. We subsequently evaluate the power series at the midpoint of z and bound the propagated error using derivatives. Derivatives are bounded using acb_hypgeom_airy_bound().

void acb_hypgeom_airy_jet(acb_ptr ai, acb_ptr bi, const acb_t z, slong len, slong prec)

Writes to ai and bi the respective Taylor expansions of the Airy functions at the point z, truncated to length len. Either of the outputs can be NULL to avoid computing that function. The variable z is not allowed to be aliased with the outputs. To simplify the implementation, this method does not compute the series expansions of the primed versions directly; these are easily obtained by computing one extra coefficient and differentiating the output with _acb_poly_derivative().

void _acb_hypgeom_airy_series(acb_ptr ai, acb_ptr ai_prime, acb_ptr bi, acb_ptr bi_prime, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_airy_series(acb_poly_t ai, acb_poly_t ai_prime, acb_poly_t bi, acb_poly_t bi_prime, const acb_poly_t z, slong len, slong prec)

Computes the Airy functions evaluated at the power series z, truncated to length len. As with the other Airy methods, any of the outputs can be NULL.

## Incomplete gamma and beta functions¶

void acb_hypgeom_gamma_upper_asymp(acb_t res, const acb_t s, const acb_t z, int regularized, slong prec)
void acb_hypgeom_gamma_upper_1f1a(acb_t res, const acb_t s, const acb_t z, int regularized, slong prec)
void acb_hypgeom_gamma_upper_1f1b(acb_t res, const acb_t s, const acb_t z, int regularized, slong prec)
void acb_hypgeom_gamma_upper_singular(acb_t res, slong s, const acb_t z, int regularized, slong prec)
void acb_hypgeom_gamma_upper(acb_t res, const acb_t s, const acb_t z, int regularized, slong prec)

If regularized is 0, computes the upper incomplete gamma function $$\Gamma(s,z)$$.

If regularized is 1, computes the regularized upper incomplete gamma function $$Q(s,z) = \Gamma(s,z) / \Gamma(s)$$.

If regularized is 2, computes the generalized exponential integral $$z^{-s} \Gamma(s,z) = E_{1-s}(z)$$ instead (this option is mainly intended for internal use; acb_hypgeom_expint() is the intended interface for computing the exponential integral).

The different methods respectively implement the formulas

$\Gamma(s,z) = e^{-z} U(1-s,1-s,z)$
$\Gamma(s,z) = \Gamma(s) - \frac{z^s}{s} {}_1F_1(s, s+1, -z)$
$\Gamma(s,z) = \Gamma(s) - \frac{z^s e^{-z}}{s} {}_1F_1(1, s+1, z)$
$\Gamma(s,z) = \frac{(-1)^n}{n!} (\psi(n+1) - \log(z)) + \frac{(-1)^n}{(n+1)!} z \, {}_2F_2(1,1,2,2+n,-z) - z^{-n} \sum_{k=0}^{n-1} \frac{(-z)^k}{(k-n) k!}, \quad n = -s \in \mathbb{Z}_{\ge 0}$

and an automatic algorithm choice. The automatic version also handles other special input such as $$z = 0$$ and $$s = 1, 2, 3$$. The singular version evaluates the finite sum directly and therefore assumes that s is not too large.

void _acb_hypgeom_gamma_upper_series(acb_ptr res, const acb_t s, acb_srcptr z, slong zlen, int regularized, slong n, slong prec)
void acb_hypgeom_gamma_upper_series(acb_poly_t res, const acb_t s, const acb_poly_t z, int regularized, slong n, slong prec)

Sets res to an upper incomplete gamma function where s is a constant and z is a power series, truncated to length n. The regularized argument has the same interpretation as in acb_hypgeom_gamma_upper().

void acb_hypgeom_gamma_lower(acb_t res, const acb_t s, const acb_t z, int regularized, slong prec)

If regularized is 0, computes the lower incomplete gamma function $$\gamma(s,z) = \frac{z^s}{s} {}_1F_1(s, s+1, -z)$$.

If regularized is 1, computes the regularized lower incomplete gamma function $$P(s,z) = \gamma(s,z) / \Gamma(s)$$.

If regularized is 2, computes a further regularized lower incomplete gamma function $$\gamma^{*}(s,z) = z^{-s} P(s,z)$$.

void _acb_hypgeom_gamma_lower_series(acb_ptr res, const acb_t s, acb_srcptr z, slong zlen, int regularized, slong n, slong prec)
void acb_hypgeom_gamma_lower_series(acb_poly_t res, const acb_t s, const acb_poly_t z, int regularized, slong n, slong prec)

Sets res to an lower incomplete gamma function where s is a constant and z is a power series, truncated to length n. The regularized argument has the same interpretation as in acb_hypgeom_gamma_lower().

void acb_hypgeom_beta_lower(acb_t res, const acb_t a, const acb_t b, const acb_t z, int regularized, slong prec)

Computes the (lower) incomplete beta function, defined by $$B(a,b;z) = \int_0^z t^{a-1} (1-t)^{b-1}$$, optionally the regularized incomplete beta function $$I(a,b;z) = B(a,b;z) / B(a,b;1)$$.

In general, the integral must be interpreted using analytic continuation. The precise definitions for all parameter values are

$B(a,b;z) = \frac{z^a}{a} {}_2F_1(a, 1-b, a+1, z)$
$I(a,b;z) = \frac{\Gamma(a+b)}{\Gamma(b)} z^a {}_2{\widetilde F}_1(a, 1-b, a+1, z).$

Note that both functions with this definition are undefined for nonpositive integer a, and I is undefined for nonpositive integer $$a + b$$.

void _acb_hypgeom_beta_lower_series(acb_ptr res, const acb_t a, const acb_t b, acb_srcptr z, slong zlen, int regularized, slong n, slong prec)
void acb_hypgeom_beta_lower_series(acb_poly_t res, const acb_t a, const acb_t b, const acb_poly_t z, int regularized, slong n, slong prec)

Sets res to the lower incomplete beta function $$B(a,b;z)$$ (optionally the regularized version $$I(a,b;z)$$) where a and b are constants and z is a power series, truncating the result to length n. The underscore method requires positive lengths and does not support aliasing.

## Exponential and trigonometric integrals¶

The branch cut conventions of the following functions match Mathematica.

void acb_hypgeom_expint(acb_t res, const acb_t s, const acb_t z, slong prec)

Computes the generalized exponential integral $$E_s(z)$$. This is a trivial wrapper of acb_hypgeom_gamma_upper().

void acb_hypgeom_ei_asymp(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_ei_2f2(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_ei(acb_t res, const acb_t z, slong prec)

Computes the exponential integral $$\operatorname{Ei}(z)$$, respectively using

$\operatorname{Ei}(z) = -e^z U(1,1,-z) - \log(-z) + \frac{1}{2} \left(\log(z) - \log\left(\frac{1}{z}\right) \right)$
$\operatorname{Ei}(z) = z {}_2F_2(1, 1; 2, 2; z) + \gamma + \frac{1}{2} \left(\log(z) - \log\left(\frac{1}{z}\right) \right)$

and an automatic algorithm choice.

void _acb_hypgeom_ei_series(acb_ptr res, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_ei_series(acb_poly_t res, const acb_poly_t z, slong len, slong prec)

Computes the exponential integral of the power series z, truncated to length len.

void acb_hypgeom_si_asymp(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_si_1f2(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_si(acb_t res, const acb_t z, slong prec)

Computes the sine integral $$\operatorname{Si}(z)$$, respectively using

$\operatorname{Si}(z) = \frac{i}{2} \left[ e^{iz} U(1,1,-iz) - e^{-iz} U(1,1,iz) + \log(-iz) - \log(iz) \right]$
$\operatorname{Si}(z) = z {}_1F_2(\tfrac{1}{2}; \tfrac{3}{2}, \tfrac{3}{2}; -\tfrac{z^2}{4})$

and an automatic algorithm choice.

void _acb_hypgeom_si_series(acb_ptr res, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_si_series(acb_poly_t res, const acb_poly_t z, slong len, slong prec)

Computes the sine integral of the power series z, truncated to length len.

void acb_hypgeom_ci_asymp(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_ci_2f3(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_ci(acb_t res, const acb_t z, slong prec)

Computes the cosine integral $$\operatorname{Ci}(z)$$, respectively using

$\operatorname{Ci}(z) = \log(z) - \frac{1}{2} \left[ e^{iz} U(1,1,-iz) + e^{-iz} U(1,1,iz) + \log(-iz) + \log(iz) \right]$
$\operatorname{Ci}(z) = -\tfrac{z^2}{4} {}_2F_3(1, 1; 2, 2, \tfrac{3}{2}; -\tfrac{z^2}{4}) + \log(z) + \gamma$

and an automatic algorithm choice.

void _acb_hypgeom_ci_series(acb_ptr res, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_ci_series(acb_poly_t res, const acb_poly_t z, slong len, slong prec)

Computes the cosine integral of the power series z, truncated to length len.

void acb_hypgeom_shi(acb_t res, const acb_t z, slong prec)

Computes the hyperbolic sine integral $$\operatorname{Shi}(z) = -i \operatorname{Si}(iz)$$. This is a trivial wrapper of acb_hypgeom_si().

void _acb_hypgeom_shi_series(acb_ptr res, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_shi_series(acb_poly_t res, const acb_poly_t z, slong len, slong prec)

Computes the hyperbolic sine integral of the power series z, truncated to length len.

void acb_hypgeom_chi_asymp(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_chi_2f3(acb_t res, const acb_t z, slong prec)
void acb_hypgeom_chi(acb_t res, const acb_t z, slong prec)

Computes the hyperbolic cosine integral $$\operatorname{Chi}(z)$$, respectively using

$\operatorname{Chi}(z) = -\frac{1}{2} \left[ e^{z} U(1,1,-z) + e^{-z} U(1,1,z) + \log(-z) - \log(z) \right]$
$\operatorname{Chi}(z) = \tfrac{z^2}{4} {}_2F_3(1, 1; 2, 2, \tfrac{3}{2}; \tfrac{z^2}{4}) + \log(z) + \gamma$

and an automatic algorithm choice.

void _acb_hypgeom_chi_series(acb_ptr res, acb_srcptr z, slong zlen, slong len, slong prec)
void acb_hypgeom_chi_series(acb_poly_t res, const acb_poly_t z, slong len, slong prec)

Computes the hyperbolic cosine integral of the power series z, truncated to length len.

void acb_hypgeom_li(acb_t res, const acb_t z, int offset, slong prec)

If offset is zero, computes the logarithmic integral $$\operatorname{li}(z) = \operatorname{Ei}(\log(z))$$.

If offset is nonzero, computes the offset logarithmic integral $$\operatorname{Li}(z) = \operatorname{li}(z) - \operatorname{li}(2)$$.

void _acb_hypgeom_li_series(acb_ptr res, acb_srcptr z, slong zlen, int offset, slong len, slong prec)
void acb_hypgeom_li_series(acb_poly_t res, const acb_poly_t z, int offset, slong len, slong prec)

Computes the logarithmic integral (optionally the offset version) of the power series z, truncated to length len.

## Gauss hypergeometric function¶

The following methods compute the Gauss hypergeometric function

$F(z) = {}_2F_1(a,b,c,z) = \sum_{k=0}^{\infty} \frac{(a)_k (b)_k}{(c)_k} \frac{z^k}{k!}$

or the regularized version $$\operatorname{\mathbf{F}}(z) = \operatorname{\mathbf{F}}(a,b,c,z) = {}_2F_1(a,b,c,z) / \Gamma(c)$$ if the flag regularized is set.

void acb_hypgeom_2f1_continuation(acb_t res0, acb_t res1, const acb_t a, const acb_t b, const acb_t c, const acb_t z0, const acb_t z1, const acb_t f0, const acb_t f1, slong prec)

Given $$F(z_0), F'(z_0)$$ in f0, f1, sets res0 and res1 to $$F(z_1), F'(z_1)$$ by integrating the hypergeometric differential equation along a straight-line path. The evaluation points should be well-isolated from the singular points 0 and 1.

void acb_hypgeom_2f1_series_direct(acb_poly_t res, const acb_poly_t a, const acb_poly_t b, const acb_poly_t c, const acb_poly_t z, int regularized, slong len, slong prec)

Computes $$F(z)$$ of the given power series truncated to length len, using direct summation of the hypergeometric series.

void acb_hypgeom_2f1_direct(acb_t res, const acb_t a, const acb_t b, const acb_t c, const acb_t z, int regularized, slong prec)

Computes $$F(z)$$ using direct summation of the hypergeometric series.

void acb_hypgeom_2f1_transform(acb_t res, const acb_t a, const acb_t b, const acb_t c, const acb_t z, int flags, int which, slong prec)
void acb_hypgeom_2f1_transform_limit(acb_t res, const acb_t a, const acb_t b, const acb_t c, const acb_t z, int regularized, int which, slong prec)

Computes $$F(z)$$ using an argument transformation determined by the flag which. Legal values are 1 for $$z/(z-1)$$, 2 for $$1/z$$, 3 for $$1/(1-z)$$, 4 for $$1-z$$, and 5 for $$1-1/z$$.

The transform_limit version assumes that which is not 1. If which is 2 or 3, it assumes that $$b-a$$ represents an exact integer. If which is 4 or 5, it assumes that $$c-a-b$$ represents an exact integer. In these cases, it computes the correct limit value.

See acb_hypgeom_2f1() for the meaning of flags.

void acb_hypgeom_2f1_corner(acb_t res, const acb_t a, const acb_t b, const acb_t c, const acb_t z, int regularized, slong prec)

Computes $$F(z)$$ near the corner cases $$\exp(\pm \pi i \sqrt{3})$$ by analytic continuation.

int acb_hypgeom_2f1_choose(const acb_t z)

Chooses a method to compute the function based on the location of z in the complex plane. If the return value is 0, direct summation should be used. If the return value is 1 to 5, the transformation with this index in acb_hypgeom_2f1_transform() should be used. If the return value is 6, the corner case algorithm should be used.

void acb_hypgeom_2f1(acb_t res, const acb_t a, const acb_t b, const acb_t c, const acb_t z, int flags, slong prec)

Computes $$F(z)$$ or $$\operatorname{\mathbf{F}}(z)$$ using an automatic algorithm choice.

The following bit fields can be set in flags:

• ACB_HYPGEOM_2F1_REGULARIZED - computes the regularized hypergeometric function $$\operatorname{\mathbf{F}}(z)$$. Setting flags to 1 is the same as just toggling this option.
• ACB_HYPGEOM_2F1_AB - $$a-b$$ is an integer.
• ACB_HYPGEOM_2F1_ABC - $$a+b-c$$ is an integer.
• ACB_HYPGEOM_2F1_AC - $$a-c$$ is an integer.
• ACB_HYPGEOM_2F1_BC - $$b-c$$ is an integer.

The last four flags can be set to indicate that the respective parameter differences are known to represent exact integers, even if the input intervals are inexact. This allows the correct limits to be evaluated when applying transformation formulas. For example, to evaluate $${}_2F_1(\sqrt{2}, 1/2, \sqrt{2}+3/2, 9/10)$$, the ABC flag should be set. If not set, the result will be an indeterminate interval due to internally dividing by an interval containing zero. If the parameters are exact floating-point numbers (including exact integers or half-integers), then the limits are computed automatically, and setting these flags is unnecessary.

Currently, only the AB and ABC flags are used this way; the AC and BC flags might be used in the future.

## Orthogonal polynomials and functions¶

void acb_hypgeom_chebyshev_t(acb_t res, const acb_t n, const acb_t z, slong prec)
void acb_hypgeom_chebyshev_u(acb_t res, const acb_t n, const acb_t z, slong prec)

Computes the Chebyshev polynomial (or Chebyshev function) of first or second kind

$T_n(z) = {}_2F_1\left(-n,n,\frac{1}{2},\frac{1-z}{2}\right)$
$U_n(z) = (n+1) {}_2F_1\left(-n,n+2,\frac{3}{2},\frac{1-z}{2}\right).$

The hypergeometric series definitions are only used for computation near the point 1. In general, trigonometric representations are used. For word-size integer n, acb_chebyshev_t_ui() and acb_chebyshev_u_ui() are called.

void acb_hypgeom_jacobi_p(acb_t res, const acb_t n, const acb_t a, const acb_t b, const acb_t z, slong prec)

Computes the Jacobi polynomial (or Jacobi function)

$P_n^{(a,b)}(z)=\frac{(a+1)_n}{\Gamma(n+1)} {}_2F_1\left(-n,n+a+b+1,a+1,\frac{1-z}{2}\right).$

For nonnegative integer n, this is a polynomial in a, b and z, even when the parameters are such that the hypergeometric series is undefined. In such cases, the polynomial is evaluated using direct methods.

void acb_hypgeom_gegenbauer_c(acb_t res, const acb_t n, const acb_t m, const acb_t z, slong prec)

Computes the Gegenbauer polynomial (or Gegenbauer function)

$C_n^{m}(z)=\frac{(2m)_n}{\Gamma(n+1)} {}_2F_1\left(-n,2m+n,m+\frac{1}{2},\frac{1-z}{2}\right).$

For nonnegative integer n, this is a polynomial in m and z, even when the parameters are such that the hypergeometric series is undefined. In such cases, the polynomial is evaluated using direct methods.

void acb_hypgeom_laguerre_l(acb_t res, const acb_t n, const acb_t m, const acb_t z, slong prec)

Computes the Laguerre polynomial (or Laguerre function)

$L_n^{m}(z)=\frac{(m+1)_n}{\Gamma(n+1)} {}_1F_1\left(-n,m+1,z\right).$

For nonnegative integer n, this is a polynomial in m and z, even when the parameters are such that the hypergeometric series is undefined. In such cases, the polynomial is evaluated using direct methods.

There are at least two incompatible ways to define the Laguerre function when n is a negative integer. One possibility when $$m = 0$$ is to define $$L_{-n}^0(z) = e^z L_{n-1}^0(-z)$$. Another possibility is to cover this case with the recurrence relation $$L_{n-1}^m(z) + L_n^{m-1}(z) = L_n^m(z)$$. Currently, we leave this case undefined (returning indeterminate).

void acb_hypgeom_hermite_h(acb_t res, const acb_t n, const acb_t z, slong prec)

Computes the Hermite polynomial (or Hermite function)

$H_n(z) = 2^n \sqrt{\pi} \left( \frac{1}{\Gamma((1-n)/2)} {}_1F_1\left(-\frac{n}{2},\frac{1}{2},z^2\right) - \frac{2z}{\Gamma(-n/2)} {}_1F_1\left(\frac{1-n}{2},\frac{3}{2},z^2\right)\right).$
void acb_hypgeom_legendre_p(acb_t res, const acb_t n, const acb_t m, const acb_t z, int type, slong prec)

Sets res to the associated Legendre function of the first kind evaluated for degree n, order m, and argument z. When m is zero, this reduces to the Legendre polynomial $$P_n(z)$$.

Many different branch cut conventions appear in the literature. If type is 0, the version

$P_n^m(z) = \frac{(1+z)^{m/2}}{(1-z)^{m/2}} \mathbf{F}\left(-n, n+1, 1-m, \frac{1-z}{2}\right)$

is computed, and if type is 1, the alternative version

${\mathcal P}_n^m(z) = \frac{(z+1)^{m/2}}{(z-1)^{m/2}} \mathbf{F}\left(-n, n+1, 1-m, \frac{1-z}{2}\right).$

is computed. Type 0 and type 1 respectively correspond to type 2 and type 3 in Mathematica and mpmath.

void acb_hypgeom_legendre_q(acb_t res, const acb_t n, const acb_t m, const acb_t z, int type, slong prec)

Sets res to the associated Legendre function of the second kind evaluated for degree n, order m, and argument z. When m is zero, this reduces to the Legendre function $$Q_n(z)$$.

Many different branch cut conventions appear in the literature. If type is 0, the version

$Q_n^m(z) = \frac{\pi}{2 \sin(\pi m)} \left( \cos(\pi m) P_n^m(z) - \frac{\Gamma(1+m+n)}{\Gamma(1-m+n)} P_n^{-m}(z)\right)$

is computed, and if type is 1, the alternative version

$\mathcal{Q}_n^m(z) = \frac{\pi}{2 \sin(\pi m)} e^{\pi i m} \left( \mathcal{P}_n^m(z) - \frac{\Gamma(1+m+n)}{\Gamma(1-m+n)} \mathcal{P}_n^{-m}(z)\right)$

is computed. Type 0 and type 1 respectively correspond to type 2 and type 3 in Mathematica and mpmath.

When m is an integer, either expression is interpreted as a limit. We make use of the connection formulas [WQ3a], [WQ3b] and [WQ3c] to allow computing the function even in the limiting case. (The formula [WQ3d] would be useful, but is incorrect in the lower half plane.)

void acb_hypgeom_legendre_p_uiui_rec(acb_t res, ulong n, ulong m, const acb_t z, slong prec)

For nonnegative integer n and m, uses recurrence relations to evaluate $$(1-z^2)^{-m/2} P_n^m(z)$$ which is a polynomial in z.

void acb_hypgeom_spherical_y(acb_t res, slong n, slong m, const acb_t theta, const acb_t phi, slong prec)

Computes the spherical harmonic of degree n, order m, latitude angle theta, and longitude angle phi, normalized such that

$Y_n^m(\theta, \phi) = \sqrt{\frac{2n+1}{4\pi} \frac{(n-m)!}{(n+m)!}} e^{im\phi} P_n^m(\cos(\theta)).$

The definition is extended to negative m and n by symmetry. This function is a polynomial in $$\cos(\theta)$$ and $$\sin(\theta)$$. We evaluate it using acb_hypgeom_legendre_p_uiui_rec().

## Dilogarithm¶

The dilogarithm function is given by $$\operatorname{Li}_2(z) = -\int_0^z \frac{\log(1-t)}{t} dt = z {}_3F_2(1,1,1,2,2,z)$$.

void acb_hypgeom_dilog_bernoulli(acb_t res, const acb_t z, slong prec)

Computes the dilogarithm using a series expansion in $$w = \log(z)$$, with rate of convergence $$|w/(2\pi)|^n$$. This provides good convergence near $$z = e^{\pm i \pi / 3}$$, where hypergeometric series expansions fail. Since the coefficients involve Bernoulli numbers, this method should only be used at moderate precision.

void acb_hypgeom_dilog_zero_taylor(acb_t res, const acb_t z, slong prec)

Computes the dilogarithm for z close to 0 using the hypergeometric series (effective only when $$|z| \ll 1$$).

void acb_hypgeom_dilog_zero(acb_t res, const acb_t z, slong prec)

Computes the dilogarithm for z close to 0, using the bit-burst algorithm instead of the hypergeometric series directly at very high precision.

void acb_hypgeom_dilog_transform(acb_t res, const acb_t z, int algorithm, slong prec)

Computes the dilogarithm by applying one of the transformations $$1/z$$, $$1-z$$, $$z/(z-1)$$, $$1/(1-z)$$, indexed by algorithm from 1 to 4, and calling acb_hypgeom_dilog_zero() with the reduced variable. Alternatively, for algorithm between 5 and 7, starts from the respective point $$\pm i$$, $$(1\pm i)/2$$, $$(1\pm i)/2$$ (with the sign chosen according to the midpoint of z) and computes the dilogarithm by the bit-burst method.

void acb_hypgeom_dilog_continuation(acb_t res, const acb_t a, const acb_t z, slong prec)

Computes $$\operatorname{Li}_2(z) - \operatorname{Li}_2(a)$$ using Taylor expansion at a. Binary splitting is used. Both a and z should be well isolated from the points 0 and 1, except that a may be exactly 0. If the straight line path from a to b crosses the branch cut, this method provides continuous analytic continuation instead of computing the principal branch.

void acb_hypgeom_dilog_bitburst(acb_t res, acb_t z0, const acb_t z, slong prec)

Sets z0 to a point with short bit expansion close to z and sets res to $$\operatorname{Li}_2(z) - \operatorname{Li}_2(z_0)$$, computed using the bit-burst algorithm.

void acb_hypgeom_dilog(acb_t res, const acb_t z, slong prec)

Computes the dilogarithm using a default algorithm choice.