Createst a new CAcbPoly structure encapsulated in AcbPoly.

Use AcbPoly in f.

Use new AcbPoly ptr in f.

acb_poly_init poly

Initializes the polynomial for use, setting it to the zero polynomial.

acb_poly_clear poly

Clears the polynomial, deallocating all coefficients and the coefficient array.

acb_poly_fit_length poly len

Makes sure that the coefficient array of the polynomial contains at least len initialized coefficients.

_acb_poly_set_length poly len

Directly changes the length of the polynomial, without allocating or deallocating coefficients. The value should not exceed the allocation length.

_acb_poly_normalise poly

Strips any trailing coefficients which are identical to zero.

acb_poly_swap poly1 poly2

Swaps poly1 and poly2 efficiently.

acb_poly_allocated_bytes x

Returns the total number of bytes heap-allocated internally by this object. The count excludes the size of the structure itself. Add sizeof(acb_poly_struct) to get the size of the object as a whole.

acb_poly_length poly

Returns the length of poly, i.e. zero if poly is identically zero, and otherwise one more than the index of the highest term that is not identically zero.

acb_poly_degree poly

Returns the degree of poly, defined as one less than its length. Note that if one or several leading coefficients are balls containing zero, this value can be larger than the true degree of the exact polynomial represented by poly, so the return value of this function is effectively an upper bound.

acb_poly_is_x poly

Returns 1 if poly is exactly the polynomial 0, 1 or x respectively. Returns 0 otherwise.

acb_poly_zero poly

Sets poly to the zero polynomial.

acb_poly_one poly

Sets poly to the constant polynomial 1.

acb_poly_set dest src

Sets dest to a copy of src.

acb_poly_set_round dest src prec

Sets dest to a copy of src, rounded to prec bits.

acb_poly_set_trunc_round dest src n prec

Sets dest to a copy of src, truncated to length n and rounded to prec bits.

acb_poly_set_coeff_acb poly n c

Sets the coefficient with index n in poly to the value c. We require that n is nonnegative.

acb_poly_get_coeff_acb v poly n

Sets v to the value of the coefficient with index n in poly. We require that n is nonnegative.

acb_poly_shift_right res poly n

Sets res to poly divided by \(x^n\), throwing away the lower coefficients. We require that n is nonnegative.

acb_poly_shift_left res poly n

Sets res to poly multiplied by \(x^n\). We require that n is nonnegative.

acb_poly_truncate poly n

Truncates poly to have length at most n, i.e. degree strictly smaller than n. We require that n is nonnegative.

acb_poly_valuation poly

Returns the degree of the lowest term that is not exactly zero in poly. Returns -1 if poly is the zero polynomial.

acb_poly_printd poly digits

Prints the polynomial as an array of coefficients, printing each coefficient using acb_printd.

acb_poly_fprintd file poly digits

Prints the polynomial as an array of coefficients to the stream file, printing each coefficient using acb_fprintd.

acb_poly_randtest poly state len prec mag_bits

Creates a random polynomial with length at most len.

acb_poly_equal A B

Returns nonzero iff A and B are identical as interval polynomials.

acb_poly_contains_fmpq_poly poly1 poly2

Returns nonzero iff poly2 is contained in poly1.

acb_poly_overlaps poly1 poly2

Returns nonzero iff poly1 overlaps with poly2. The underscore function requires that len1 ist at least as large as len2.

acb_poly_get_unique_fmpz_poly z x

If x contains a unique integer polynomial, sets z to that value and returns nonzero. Otherwise (if x represents no integers or more than one integer), returns zero, possibly partially modifying z.

acb_poly_is_real poly

Returns nonzero iff all coefficients in poly have zero imaginary part.

acb_poly_set2_fmpq_poly poly re im prec

Sets poly to the given real part re plus the imaginary part im, both rounded to prec bits.

acb_poly_set_si poly src

Sets poly to src.

acb_poly_majorant res poly prec

Sets res to an exact real polynomial whose coefficients are upper bounds for the absolute values of the coefficients in poly, rounded to prec bits.

_acb_poly_add C A lenA B lenB prec

Sets {C, max(lenA, lenB)} to the sum of {A, lenA} and {B, lenB}. Allows aliasing of the input and output operands.

acb_poly_add_si C A B prec

Sets C to the sum of A and B.

_acb_poly_sub C A lenA B lenB prec

Sets {C, max(lenA, lenB)} to the difference of {A, lenA} and /{B, lenB}/. Allows aliasing of the input and output operands.

acb_poly_sub C A B prec

Sets C to the difference of A and B.

acb_poly_add_series C A B len prec

Sets C to the sum of A and B, truncated to length len.

acb_poly_sub_series C A B len prec

Sets C to the difference of A and B, truncated to length len.

acb_poly_neg C A

Sets C to the negation of A.

acb_poly_scalar_mul_2exp_si C A c

Sets C to A multiplied by \(2^c\).

acb_poly_scalar_mul C A c prec

Sets C to A multiplied by c.

acb_poly_scalar_div C A c prec

Sets C to A divided by c.

_acb_poly_mullow C A lenA B lenB n prec

Sets {C, n} to the product of {A, lenA} and {B, lenB}, truncated to length n. The output is not allowed to be aliased with either of the inputs. We require \(\mathrm{lenA} \ge \mathrm{lenB} > 0\), \(n > 0\), \(\mathrm{lenA} + \mathrm{lenB} - 1 \ge n\).

The classical version uses a plain loop.

The transpose version evaluates the product using four real polynomial multiplications (via _arb_poly_mullow).

The transpose_gauss version evaluates the product using three real polynomial multiplications. This is almost always faster than transpose, but has worse numerical stability when the coefficients vary in magnitude.

The default function _acb_poly_mullow automatically switches been classical and transpose multiplication.

If the input pointers are identical (and the lengths are the same), they are assumed to represent the same polynomial, and its square is computed.

acb_poly_mullow C A B n prec

Sets C to the product of A and B, truncated to length n. If the same variable is passed for A and B, sets C to the square of A truncated to length n.

_acb_poly_mul C A lenA B lenB prec

Sets {C, lenA + lenB - 1} to the product of {A, lenA} and /{B, lenB}/. The output is not allowed to be aliased with either of the inputs. We require \(\mathrm{lenA} \ge \mathrm{lenB} > 0\). This function is implemented as a simple wrapper for _acb_poly_mullow.

If the input pointers are identical (and the lengths are the same), they are assumed to represent the same polynomial, and its square is computed.

acb_poly_mul C A1 B2 prec

Sets C to the product of A and B. If the same variable is passed for A and B, sets C to the square of A.

_acb_poly_inv_series Qinv Q Qlen len prec

Sets {Qinv, len} to the power series inverse of {Q, Qlen}. Uses Newton iteration.

acb_poly_inv_series Qinv Q n prec

Sets Qinv to the power series inverse of Q.

_acb_poly_div_series Q A Alen B Blen n prec

Sets {Q, n} to the power series quotient of {A, Alen} by /{B, Blen}/. Uses Newton iteration followed by multiplication.

acb_poly_div_series Q A B n prec

Sets Q to the power series quotient A divided by B, truncated to length n.

acb_poly_divrem Q R A B prec

Performs polynomial division with remainder, computing a quotient \(Q\) and a remainder \(R\) such that \(A = BQ + R\). The implementation reverses the inputs and performs power series division.

If the leading coefficient of \(B\) contains zero (or if \(B\) is identically zero), returns 0 indicating failure without modifying the outputs. Otherwise returns nonzero.

_acb_poly_div_root Q R A len c prec

Divides \(A\) by the polynomial \(x - c\), computing the quotient \(Q\) as well as the remainder \(R = f(c)\).

_acb_poly_taylor_shift g c n prec

Sets g to the Taylor shift \(f(x+c)\). The underscore methods act in-place on g = f which has length n.

_acb_poly_compose res poly1 len1 poly2 len2 prec

Sets res to the composition \(h(x) = f(g(x))\) where \(f\) is given by poly1 and \(g\) is given by poly2. The underscore method does not support aliasing of the output with either input polynomial.

_acb_poly_compose_series res poly1 len1 poly2 len2 n prec

Sets res to the power series composition \(h(x) = f(g(x))\) truncated to order \(O(x^n)\) where \(f\) is given by poly1 and \(g\) is given by poly2. Wraps _gr_poly_compose_series which chooses automatically between various algorithms.

We require that the constant term in \(g(x)\) is exactly zero. The underscore method does not support aliasing of the output with either input polynomial.

acb_poly_revert_series h f n prec

Sets \(h\) to the power series reversion of \(f\), i.e. the expansion of the compositional inverse function \(f^{-1}(x)\), truncated to order \(O(x^n)\), using respectively Lagrange inversion, Newton iteration, fast Lagrange inversion, and a default algorithm choice.

We require that the constant term in \(f\) is exactly zero and that the linear term is nonzero. The underscore methods assume that flen is at least 2, and do not support aliasing.

acb_poly_evaluate y f x prec

Sets \(y = f(x)\), evaluated respectively using Horner's rule, rectangular splitting, and an automatic algorithm choice.

acb_poly_evaluate2 y z f x prec

Sets \(y = f(x), z = f'(x)\), evaluated respectively using Horner's rule, rectangular splitting, and an automatic algorithm choice.

When Horner's rule is used, the only advantage of evaluating the function and its derivative simultaneously is that one does not have to generate the derivative polynomial explicitly. With the rectangular splitting algorithm, the powers can be reused, making simultaneous evaluation slightly faster.

acb_poly_product_roots poly xs n prec

Generates the polynomial \((x-x_0)(x-x_1)\cdots(x-x_{n-1})\).

_acb_poly_tree_alloc len

Returns an initialized data structured capable of representing a remainder tree (product tree) of len roots.

_acb_poly_tree_free tree len

Deallocates a tree structure as allocated using _acb_poly_tree_alloc.

_acb_poly_tree_build tree roots len prec

Constructs a product tree from a given array of len roots. The tree structure must be pre-allocated to the specified length using _acb_poly_tree_alloc.

acb_poly_evaluate_vec_iter ys poly xs n prec

Evaluates the polynomial simultaneously at n given points, calling _acb_poly_evaluate repeatedly.

acb_poly_evaluate_vec_fast ys poly xs n prec

Evaluates the polynomial simultaneously at n given points, using fast multipoint evaluation.

acb_poly_interpolate_newton poly xs ys n prec

Recovers the unique polynomial of length at most n that interpolates the given x and y values. This implementation first interpolates in the Newton basis and then converts back to the monomial basis.

acb_poly_interpolate_barycentric poly xs ys n prec

Recovers the unique polynomial of length at most n that interpolates the given x and y values. This implementation uses the barycentric form of Lagrange interpolation.

acb_poly_interpolate_fast poly xs ys n prec

Recovers the unique polynomial of length at most n that interpolates the given x and y values, using fast Lagrange interpolation. The precomp function takes a precomputed product tree over the x values and a vector of interpolation weights as additional inputs.

_acb_poly_derivative res poly len prec

Sets {res, len - 1} to the derivative of {poly, len}. Allows aliasing of the input and output.

acb_poly_derivative res poly prec

Sets res to the derivative of poly.

_acb_poly_nth_derivative res poly n len prec

Sets {res, len - n} to the nth derivative of {poly, len}. Does nothing if len <= n. Allows aliasing of the input and output.

acb_poly_nth_derivative res poly n prec

Sets res to the nth derivative of poly.

_acb_poly_integral res poly len prec

Sets {res, len} to the integral of {poly, len - 1}. Allows aliasing of the input and output.

acb_poly_integral res poly prec

Sets res to the integral of poly.

acb_poly_borel_transform res poly prec

Computes the Borel transform of the input polynomial, mapping \(\sum_k a_k x^k\) to \(\sum_k (a_k / k!) x^k\). The underscore method allows aliasing.

acb_poly_inv_borel_transform res poly prec

Computes the inverse Borel transform of the input polynomial, mapping \(\sum_k a_k x^k\) to \(\sum_k a_k k! x^k\). The underscore method allows aliasing.

acb_poly_binomial_transform b a len prec

Computes the binomial transform of the input polynomial, truncating the output to length len. See arb_poly_binomial_transform for details.

The underscore methods do not support aliasing, and assume that the lengths are nonzero.

acb_poly_graeffe_transform b a prec

Computes the Graeffe transform of input polynomial, which is of length len. See arb_poly_graeffe_transform for details.

The underscore method assumes that a and b are initialized, a is of length len, and b is of length at least len. Both methods allow aliasing.

_acb_poly_pow_ui_trunc_binexp res f flen exp len prec

Sets {res, len} to {f, flen} raised to the power exp, truncated to length len. Requires that len is no longer than the length of the power as computed without truncation (i.e. no zero-padding is performed). Does not support aliasing of the input and output, and requires that flen and len are positive. Uses binary exponentiation.

acb_poly_pow_ui_trunc_binexp res poly exp len prec

Sets res to poly raised to the power exp, truncated to length len. Uses binary exponentiation.

_acb_poly_pow_ui res f flen exp prec

Sets res to {f, flen} raised to the power exp. Does not support aliasing of the input and output, and requires that flen is positive.

acb_poly_pow_ui res poly exp prec

Sets res to poly raised to the power exp.

_acb_poly_pow_series h f flen g glen len prec

Sets {h, len} to the power series \(f(x)^{g(x)} = \exp(g(x) \log f(x))\) truncated to length len. This function detects special cases such as g being an exact small integer or \(\pm 1/2\), and computes such powers more efficiently. This function does not support aliasing of the output with either of the input operands. It requires that all lengths are positive, and assumes that flen and glen do not exceed len.

acb_poly_pow_series h f g len prec

Sets h to the power series \(f(x)^{g(x)} = \exp(g(x) \log f(x))\) truncated to length len. This function detects special cases such as g being an exact small integer or \(\pm 1/2\), and computes such powers more efficiently.

_acb_poly_pow_acb_series h f flen g len prec

Sets {h, len} to the power series \(f(x)^g = \exp(g \log f(x))\) truncated to length len. This function detects special cases such as g being an exact small integer or \(\pm 1/2\), and computes such powers more efficiently. This function does not support aliasing of the output with either of the input operands. It requires that all lengths are positive, and assumes that flen does not exceed len.

acb_poly_pow_acb_series h f g len prec

Sets h to the power series \(f(x)^g = \exp(g \log f(x))\) truncated to length len.

acb_poly_sqrt_series g h n prec

Sets g to the power series square root of h, truncated to length n. Uses division-free Newton iteration for the reciprocal square root, followed by a multiplication.

The underscore method does not support aliasing of the input and output arrays. It requires that hlen and n are greater than zero.

acb_poly_rsqrt_series g h n prec

Sets g to the reciprocal power series square root of h, truncated to length n. Uses division-free Newton iteration.

The underscore method does not support aliasing of the input and output arrays. It requires that hlen and n are greater than zero.

acb_poly_log_series res f n prec

Sets res to the power series logarithm of f, truncated to length n. Uses the formula \(\log(f(x)) = \int f'(x) / f(x) dx\), adding the logarithm of the constant term in f as the constant of integration.

The underscore method supports aliasing of the input and output arrays. It requires that flen and n are greater than zero.

acb_poly_log1p_series res f n prec

Computes the power series \(\log(1+f)\), with better accuracy when the constant term of f is small.

acb_poly_atan_series res f n prec

Sets res the power series inverse tangent of f, truncated to length n.

Uses the formula

\[`\] \[\tan^{-1}(f(x)) = \int f'(x) / (1+f(x)^2) dx,\]

adding the function of the constant term in f as the constant of integration.

The underscore method supports aliasing of the input and output arrays. It requires that flen and n are greater than zero.

acb_poly_exp_series f h n prec

Sets \(f\) to the power series exponential of \(h\), truncated to length \(n\).

The basecase version uses a simple recurrence for the coefficients, requiring \(O(nm)\) operations where \(m\) is the length of \(h\).

The main implementation uses Newton iteration, starting from a small number of terms given by the basecase algorithm. The complexity is \(O(M(n))\). Redundant operations in the Newton iteration are avoided by using the scheme described in [HZ2004].

The underscore methods support aliasing and allow the input to be shorter than the output, but require the lengths to be nonzero.

acb_poly_exp_pi_i_series f h n prec

Sets f to the power series \(\exp(\pi i h)\) truncated to length n. The underscore method supports aliasing and allows the input to be shorter than the output, but requires the lengths to be nonzero.

_acb_poly_sin_cos_series s c h hlen n prec

Sets s and c to the power series sine and cosine of h, computed simultaneously. The underscore method supports aliasing and requires the lengths to be nonzero.

acb_poly_cos_series c h n prec

Respectively evaluates the power series sine or cosine. These functions simply wrap _acb_poly_sin_cos_series. The underscore methods support aliasing and require the lengths to be nonzero.

acb_poly_tan_series g h n prec

Sets g to the power series tangent of h.

For small n takes the quotient of the sine and cosine as computed using the basecase algorithm. For large n, uses Newton iteration to invert the inverse tangent series. The complexity is \(O(M(n))\).

The underscore version does not support aliasing, and requires the lengths to be nonzero.

acb_poly_cot_pi_series c h n prec

Compute the respective trigonometric functions of the input multiplied by \(\pi\).

acb_poly_cosh_series c h n prec

Sets s and c respectively to the hyperbolic sine and cosine of the power series h, truncated to length n.

The implementations mirror those for sine and cosine, except that the exponential version computes both functions using the exponential function instead of the hyperbolic tangent.

acb_poly_sinc_series s h n prec

Sets s to the sinc function of the power series h, truncated to length n.

acb_poly_lambertw_series res z k flags len prec

Sets res to branch k of the Lambert W function of the power series z. The argument flags is reserved for future use. The underscore method allows aliasing, but assumes that the lengths are nonzero.

acb_poly_digamma_series res h n prec

Sets res to the series expansion of \(\Gamma(h(x))\), \(1/\Gamma(h(x))\), or \(\log \Gamma(h(x))\), \(\psi(h(x))\), truncated to length n.

These functions first generate the Taylor series at the constant term of h, and then call _acb_poly_compose_series. The Taylor coefficients are generated using Stirling's series.

The underscore methods support aliasing of the input and output arrays, and require that hlen and n are greater than zero.

acb_poly_rising_ui_series res f r trunc prec

Sets res to the rising factorial \((f) (f+1) (f+2) \cdots (f+r-1)\), truncated to length trunc. The underscore method assumes that flen, r and trunc are at least 1, and does not support aliasing. Uses binary splitting.

_acb_poly_powsum_series_naive_threaded z s a q n len prec

Computes

\[`\] \[z = S(s,a,n) = \sum_{k=0}^{n-1} \frac{q^k}{(k+a)^{s+t}}\]

as a power series in \(t\) truncated to length len. This function evaluates the sum naively term by term. The threaded version splits the computation over the number of threads returned by flint_get_num_threads().

_acb_poly_powsum_one_series_sieved z s n len prec

Computes

\[`\] \[z = S(s,1,n) \sum_{k=1}^n \frac{1}{k^{s+t}}\]

as a power series in \(t\) truncated to length len. This function stores a table of powers that have already been calculated, computing \((ij)^r\) as \(i^r j^r\) whenever \(k = ij\) is composite. As a further optimization, it groups all even \(k\) and evaluates the sum as a polynomial in \(2^{-(s+t)}\). This scheme requires about \(n / \log n\) powers, \(n / 2\) multiplications, and temporary storage of \(n / 6\) power series. Due to the extra power series multiplications, it is only faster than the naive algorithm when len is small.

_acb_poly_zeta_em_choose_param bound N M s a d target prec

Chooses N and M for Euler-Maclaurin summation of the Hurwitz zeta function, using a default algorithm.

_acb_poly_zeta_em_bound vec s a N M d wp

Compute bounds for Euler-Maclaurin evaluation of the Hurwitz zeta function or its power series, using the formulas in [Joh2013].

_acb_poly_zeta_em_tail_bsplit z s Na Nasx M len prec

Evaluates the tail in the Euler-Maclaurin sum for the Hurwitz zeta function, respectively using the naive recurrence and binary splitting.

_acb_poly_zeta_em_sum z s a deflate N M d prec

Evaluates the truncated Euler-Maclaurin sum of order \(N, M\) for the length-d truncated Taylor series of the Hurwitz zeta function \(\zeta(s,a)\) at \(s\), using a working precision of prec bits. With \(a = 1\), this gives the usual Riemann zeta function.

If deflate is nonzero, \(\zeta(s,a) - 1/(s-1)\) is evaluated (which permits series expansion at \(s = 1\)).

_acb_poly_zeta_cpx_series z s a deflate d prec

Computes the series expansion of \(\zeta(s+x,a)\) (or \(\zeta(s+x,a) - 1/(s+x-1)\) if deflate is nonzero) to order d.

This function wraps _acb_poly_zeta_em_sum, automatically choosing default values for \(N, M\) using _acb_poly_zeta_em_choose_param to target an absolute truncation error of \(2^{-\operatorname{prec}}\).

acb_poly_zeta_series res f a deflate n prec

Sets res to the Hurwitz zeta function \(\zeta(s,a)\) where \(s\) a power series and \(a\) is a constant, truncated to length n. To evaluate the usual Riemann zeta function, set \(a = 1\).

If deflate is nonzero, evaluates \(\zeta(s,a) + 1/(1-s)\), which is well-defined as a limit when the constant term of \(s\) is 1. In particular, expanding \(\zeta(s,a) + 1/(1-s)\) with \(s = 1+x\) gives the Stieltjes constants

\[`\] \[\sum_{k=0}^{n-1} \frac{(-1)^k}{k!} \gamma_k(a) x^k`.\]

If \(a = 1\), this implementation uses the reflection formula if the midpoint of the constant term of \(s\) is negative.

_acb_poly_polylog_cpx w s z len prec

Sets w to the Taylor series with respect to x of the polylogarithm \(\operatorname{Li}_{s+x}(z)\), where s and z are given complex constants. The output is computed to length len which must be positive. Aliasing between w and s or z is not permitted.

The small version uses the standard power series expansion with respect to z, convergent when \(|z| < 1\). The zeta version evaluates the polylogarithm as a sum of two Hurwitz zeta functions. The default version automatically delegates to the small version when z is close to zero, and the zeta version otherwise. For further details, see algorithms_polylogarithms.

acb_poly_polylog_series w s z len prec

Sets w to the polylogarithm \(\operatorname{Li}_{s}(z)\) where s is a given power series, truncating the output to length len. The underscore method requires all lengths to be positive and supports aliasing between all inputs and outputs.

acb_poly_erf_series res z n prec

Sets res to the error function of the power series z, truncated to length n. These methods are provided for backwards compatibility. See acb_hypgeom_erf_series, acb_hypgeom_erfc_series, acb_hypgeom_erfi_series.

acb_poly_agm1_series res z n prec

Sets res to the arithmetic-geometric mean of 1 and the power series z, truncated to length n.

acb_poly_root_bound_fujiwara bound poly

Sets bound to an upper bound for the magnitude of all the complex roots of poly. Uses Fujiwara's bound

\[`\] \[2 \max \left\{\left|\frac{a_{n-1}}{a_n}\right|, \left|\frac{a_{n-2}}{a_n}\right|^{1/2}, \cdots, \left|\frac{a_1}{a_n}\right|^{1/(n-1)}, \left|\frac{a_0}{2a_n}\right|^{1/n} \right\}\]

where \(a_0, \ldots, a_n\) are the coefficients of poly.

_acb_poly_root_inclusion r m poly polyder len prec

Given any complex number \(m\), and a nonconstant polynomial \(f\) and its derivative \(f'\), sets r to a complex interval centered on \(m\) that is guaranteed to contain at least one root of \(f\). Such an interval is obtained by taking a ball of radius \(|f(m)/f'(m)| n\) where \(n\) is the degree of \(f\). Proof: assume that the distance to the nearest root exceeds \(r = |f(m)/f'(m)| n\). Then

\[`\] \[\left|\frac{f'(m)}{f(m)}\right| = \left|\sum_i \frac{1}{m-\zeta_i}\right| \le \sum_i \frac{1}{|m-\zeta_i|} < \frac{n}{r} = \left|\frac{f'(m)}{f(m)}\right|\]

which is a contradiction (see [Kob2010]).

_acb_poly_validate_roots roots poly len prec

Given a list of approximate roots of the input polynomial, this function sets a rigorous bounding interval for each root, and determines which roots are isolated from all the other roots. It then rearranges the list of roots so that the isolated roots are at the front of the list, and returns the count of isolated roots.

If the return value equals the degree of the polynomial, then all roots have been found. If the return value is smaller, all the remaining output intervals are guaranteed to contain roots, but it is possible that not all of the polynomial's roots are contained among them.

_acb_poly_refine_roots_durand_kerner roots poly len prec

Refines the given roots simultaneously using a single iteration of the Durand-Kerner method. The radius of each root is set to an approximation of the correction, giving a rough estimate of its error (not a rigorous bound).

acb_poly_find_roots roots poly initial maxiter prec

Attempts to compute all the roots of the given nonzero polynomial poly using a working precision of prec bits. If n denotes the degree of poly, the function writes n approximate roots with rigorous error bounds to the preallocated array roots, and returns the number of roots that are isolated.

If the return value equals the degree of the polynomial, then all roots have been found. If the return value is smaller, all the output intervals are guaranteed to contain roots, but it is possible that not all of the polynomial's roots are contained among them.

The roots are computed numerically by performing several steps with the Durand-Kerner method and terminating if the estimated accuracy of the roots approaches the working precision or if the number of steps exceeds maxiter, which can be set to zero in order to use a default value. Finally, the approximate roots are validated rigorously.

Initial values for the iteration can be provided as the array initial. If initial is set to NULL, default values \((0.4+0.9i)^k\) are used.

The polynomial is assumed to be squarefree. If there are repeated roots, the iteration is likely to find them (with low numerical accuracy), but the error bounds will not converge as the precision increases.

acb_poly_validate_real_roots roots poly prec

Given a strictly real polynomial poly (of length len) and isolating intervals for all its complex roots, determines if all the real roots are separated from the non-real roots. If this function returns nonzero, every root enclosure that touches the real axis (as tested by applying arb_contains_zero to the imaginary part) corresponds to a real root (its imaginary part can be set to zero), and every other root enclosure corresponds to a non-real root (with known sign for the imaginary part).

If this function returns zero, then the signs of the imaginary parts are not known for certain, based on the accuracy of the inputs and the working precision prec.