Arbitrary precision complex balls
Arbitrary precision complex ball arithmetic is supplied by Arb which provides a ball representation which tracks error bounds rigorously. Complex numbers are represented in rectangular form $a+bi$ where $a,b$ are ArbFieldElem balls.
The corresponding field is constructed using the ComplexField constructor. This constructs the parent object for the Arb complex field.
The types of complex boxes in Nemo are given in the following table, along with the libraries that provide them and the associated types of the parent objects.
| Library | Field | Element type | Parent type |
|---|---|---|---|
| Arb | $\mathbb{C}$ (boxes) | ComplexFieldElem | ComplexField |
All the complex field types belong to the Field abstract type and the types of elements in this field, i.e. complex boxes in this case, belong to the FieldElem abstract type.
Complex ball functionality
The complex balls in Nemo provide all the field functionality defined by AbstractAlgebra:.
https://nemocas.github.io/AbstractAlgebra.jl/stable/field
Below, we document the additional functionality provided for complex balls.
Precision management
See Precision management.
Complex field constructors
In order to construct complex boxes in Nemo, one must first construct the Arb complex field itself. This is accomplished with the following constructor.
complex_field — Method
complex_field()Return the field of complex numbers modelled via complex balls.
See precision and set_precision! on how to control the precision.
Here is an example of creating an Arb complex field and using the resulting parent object to coerce values into the resulting field.
Examples
julia> CC = complex_field()
Complex field
julia> a = CC("0.25")
0.25000000000000000000
julia> b = CC("0.1")
[0.100000000000000000 +/- 1.22e-20]
julia> c = CC(0.5)
0.50000000000000000000
julia> d = CC(12)
12.000000000000000000Note that whilst one can coerce double precision floating point values into an Arb complex field, unless those values can be represented exactly in double precision the resulting ball can't be any more precise than the double precision supplied.
If instead, values can be represented precisely using decimal arithmetic then one can supply them to Arb using a string. In this case, Arb will store them to the precision specified when creating the Arb complex field.
If the values can be stored precisely as a binary floating point number, Arb will store the values exactly. See the function is_exact below for more information.
Constructors
Examples
julia> c = onei(CC)
1.0000000000000000000*imBasic functionality
The following basic functionality is provided by the default Arb complex field implementation in Nemo, to support construction of generic rings over complex fields. Any custom complex field implementation in Nemo should provide analogues of these functions along with the usual arithmetic operations.
parent_type(::Type{ComplexFieldElem})Gives the type of the parent object of an Arb complex field element.
elem_type(R::ComplexField)Given the parent object for an Arb complex field, return the type of elements of the field.
mul!(c::ComplexFieldElem, a::ComplexFieldElem, b::ComplexFieldElem)Multiply $a$ by $b$ and set the existing Arb complex field element $c$ to the result. This function is provided for performance reasons as it saves allocating a new object for the result and eliminates associated garbage collection.
deepcopy(a::ComplexFieldElem)Return a copy of the Arb complex field element $a$, recursively copying the internal data. Arb complex field elements are mutable in Nemo so a shallow copy is not sufficient.
Given the parent object R for an Arb complex field, the following coercion functions are provided to coerce various elements into the Arb complex field. Developers provide these by overloading the call operator for the complex field parent objects.
R()Coerce zero into the Arb complex field.
R(n::Integer)
R(f::ZZRingElem)
R(q::QQFieldElem)Coerce an integer or rational value into the Arb complex field.
R(f::Float64)
R(f::BigFloat)Coerce the given floating point number into the Arb complex field.
R(f::AbstractString)
R(f::AbstractString, g::AbstractString)Coerce the decimal number, given as a string, into the Arb complex field. In each case $f$ is the real part and $g$ is the imaginary part.
R(f::ArbFieldElem)Coerce the given Arb real ball into the Arb complex field.
R(f::ComplexFieldElem)Take an Arb complex field element that is already in an Arb field and simply return it. A copy of the original is not made.
Here are some examples of coercing elements into the Arb complex field.
julia> RR = real_field()
Real field
julia> CC = complex_field()
Complex field
julia> a = CC(3)
3.0000000000000000000
julia> b = CC(QQ(2,3))
[0.6666666666666666666 +/- 8.48e-20]
julia> c = CC("3 +/- 0.0001")
[3.000 +/- 1.01e-4]
julia> d = CC("-1.24e+12345")
[-1.240000000000000000e+12345 +/- 1.16e+12326]
julia> f = CC("nan +/- inf")
nan
julia> g = CC(RR(3))
3.0000000000000000000In addition to the above, developers of custom complex field types must ensure that they provide the equivalent of the function base_ring(R::ComplexField) which should return Union{}. In addition to this they should ensure that each complex field element contains a field parent specifying the parent object of the complex field element, or at least supply the equivalent of the function parent(a::ComplexFieldElem) to return the parent object of a complex field element.
Basic manipulation
accuracy_bits — Method
accuracy_bits(x::ComplexFieldElem)Return the relative accuracy of $x$ measured in bits, capped between typemax(Int) and -typemax(Int).
Examples
julia> a = CC("1.2 +/- 0.001")
[1.20 +/- 1.01e-3]
julia> b = CC(3)
3.0000000000000000000
julia> isreal(a)
true
julia> isfinite(b)
true
julia> isinteger(b)
true
julia> c = real(a)
[1.20 +/- 1.01e-3]
julia> d = imag(b)
0
julia> f = accuracy_bits(a)
9Containment
It is often necessary to determine whether a given exact value or box is contained in a given complex box or whether two boxes overlap. The following functions are provided for this purpose.
The following functions are also provided for determining if a box intersects a certain part of the complex number plane.
contains_zero — Method
contains_zero(x::ComplexFieldElem)Returns true if the box $x$ contains zero, otherwise return false.
Examples
julia> x = CC("1 +/- 0.001")
[1.00 +/- 1.01e-3]
julia> y = CC("3")
3.0000000000000000000
julia> overlaps(x, y)
false
julia> contains(x, y)
false
julia> contains(y, 3)
true
julia> contains(x, ZZ(1)//2)
false
julia> contains_zero(x)
falseComparison
Nemo provides a full range of comparison operations for Arb complex boxes.
In addition to the standard comparisons, we introduce an exact equality. This is distinct from arithmetic equality implemented by ==, which merely compares up to the minimum of the precisions of its operands.
A full range of ad hoc comparison operators is provided. These are implemented directly in Julia, but we document them as though only == were provided.
| Function |
|---|
==(x::ComplexFieldElem, y::Integer) |
==(x::Integer, y::ComplexFieldElem) |
==(x::ComplexFieldElem, y::ZZRingElem) |
==(x::ZZRingElem, y::ComplexFieldElem) |
==(x::ArbFieldElem, y::ZZRingElem) |
==(x::ZZRingElem, y::ArbFieldElem) |
==(x::ComplexFieldElem, y::Float64) |
==(x::Float64, y::ComplexFieldElem) |
Examples
julia> x = CC("1 +/- 0.001")
[1.00 +/- 1.01e-3]
julia> y = CC("3")
3.0000000000000000000
julia> z = CC("4")
4.0000000000000000000
julia> isequal(x, deepcopy(x))
true
julia> x == 3
false
julia> ZZ(3) == y
true
julia> z != 1.23
trueAbsolute value
Examples
julia> x = CC("-1 +/- 0.001")
[-1.00 +/- 1.01e-3]
julia> a = abs(x)
[1.00 +/- 1.01e-3]Shifting
Examples
julia> x = CC("-3 +/- 0.001")
[-3.00 +/- 1.01e-3]
julia> a = ldexp(x, 23)
[-2.52e+7 +/- 4.26e+4]
julia> b = ldexp(x, -ZZ(15))
[-9.16e-5 +/- 7.78e-8]Miscellaneous operations
unique_integer — Method
unique_integer(x::ComplexFieldElem)Return a pair where the first value is a boolean and the second is an ZZRingElem integer. The boolean indicates whether the box $x$ contains a unique integer. If this is the case, the second return value is set to this unique integer.
Examples
julia> x = CC("-3 +/- 0.001", "0.1")
[-3.00 +/- 1.01e-3] + [0.100000000000000000 +/- 1.22e-20]*im
julia> a = trim(x)
[-3.00 +/- 1.01e-3] + [0.100000000000000000 +/- 1.22e-20]*im
julia> b, c = unique_integer(x)
(false, 0)
julia> d = conj(x)
[-3.00 +/- 1.01e-3] + [-0.100000000000000000 +/- 1.22e-20]*im
julia> f = angle(x)
[3.1083 +/- 3.95e-5]Constants
Examples
CC = complex_field()
set_precision!(ComplexField, 200) do
a = const_pi(CC)
endMathematical and special functions
root_of_unity — Method
log_barnes_g — Method
log_barnes_g(x::ComplexFieldElem)Return the logarithm of the Barnes $G$-function, evaluated at $x$.
sourceexp_integral_ei — Method
sin_integral — Method
cos_integral — Method
sinh_integral — Method
cosh_integral — Method
dedekind_eta — Method
modular_weber_f — Method
modular_weber_f(x::ComplexFieldElem)Return the modular Weber function $\mathfrak{f}(\tau) = \frac{\eta^2(\tau)}{\eta(\tau/2)\eta(2\tau)},$ at $x$ in the complex upper half plane.
sourcemodular_weber_f1 — Method
modular_weber_f1(x::ComplexFieldElem)Return the modular Weber function $\mathfrak{f}_1(\tau) = \frac{\eta(\tau/2)}{\eta(\tau)},$ at $x$ in the complex upper half plane.
sourcemodular_weber_f2 — Method
modular_weber_f2(x::ComplexFieldElem)Return the modular Weber function $\mathfrak{f}_2(\tau) = \frac{\sqrt{2}\eta(2\tau)}{\eta(\tau)}$ at $x$ in the complex upper half plane.
sourcej_invariant — Method
modular_lambda — Method
modular_lambda(x::ComplexFieldElem)Return the modular lambda function $\lambda(\tau)$ at $\tau = x$.
sourcemodular_delta — Method
modular_delta(x::ComplexFieldElem)Return the modular delta function $\Delta(\tau)$ at $\tau = x$.
sourceeisenstein_g — Method
eisenstein_g(k::Int, x::ComplexFieldElem)Return the non-normalized Eisenstein series $G_k(\tau)$ of $\mathrm{SL}_2(\mathbb{Z})$. Also defined for $\tau = i \infty$.
sourcehilbert_class_polynomial — Method
hilbert_class_polynomial(D::Int, R::ZZPolyRing)Return in the ring $R$ the Hilbert class polynomial of discriminant $D$, which is only defined for $D < 0$ and $D \equiv 0, 1 \pmod 4$.
sourceelliptic_k — Method
elliptic_e — Method
rising_factorial — Method
rising_factorial(x::ComplexFieldElem, n::Int)Return the rising factorial $x(x + 1)\ldots (x + n - 1)$.
sourcerising_factorial2 — Method
rising_factorial2(x::ComplexFieldElem, n::Int)Return a tuple containing the rising factorial $x(x + 1)\ldots (x + n - 1)$ and its derivative.
sourcelog_integral — Method
log_integral_offset — Method
log_integral_offset(x::ComplexFieldElem)Return the offset logarithmic integral, evaluated at $x$.
sourceexp_integral_e — Method
exp_integral_e(s::ComplexFieldElem, x::ComplexFieldElem)Return the generalised exponential integral $E_s(x)$.
sourcegamma_regularized — Method
gamma_regularized(s::ComplexFieldElem, x::ComplexFieldElem)Return the regularized upper incomplete gamma function $\Gamma(s,x) / \Gamma(s)$.
sourcegamma_lower — Method
gamma_lower(s::ComplexFieldElem, x::ComplexFieldElem)Return the lower incomplete gamma function $\gamma(s,x) / \Gamma(s)$.
sourcegamma_lower_regularized — Method
gamma_lower_regularized(s::ComplexFieldElem, x::ComplexFieldElem)Return the regularized lower incomplete gamma function $\gamma(s,x) / \Gamma(s)$.
sourceairy_ai_prime — Method
airy_ai_prime(x::ComplexFieldElem)Return the derivative of the Airy function $\operatorname{Ai}^\prime(x)$.
sourceairy_bi_prime — Method
airy_bi_prime(x::ComplexFieldElem)Return the derivative of the Airy function $\operatorname{Bi}^\prime(x)$.
sourcehypergeometric_1f1 — Method
hypergeometric_1f1(a::ComplexFieldElem, b::ComplexFieldElem, x::ComplexFieldElem)Return the confluent hypergeometric function ${}_1F_1(a,b,x)$.
sourcehypergeometric_1f1_regularized — Method
hypergeometric_1f1_regularized(a::ComplexFieldElem, b::ComplexFieldElem, x::ComplexFieldElem)Return the regularized confluent hypergeometric function ${}_1F_1(a,b,x) / \Gamma(b)$.
sourcehypergeometric_u — Method
hypergeometric_u(a::ComplexFieldElem, b::ComplexFieldElem, x::ComplexFieldElem)Return the confluent hypergeometric function $U(a,b,x)$.
sourcehypergeometric_2f1 — Method
hypergeometric_2f1(a::ComplexFieldElem, b::ComplexFieldElem, c::ComplexFieldElem, x::ComplexFieldElem; flags=0)Return the Gauss hypergeometric function ${}_2F_1(a,b,c,x)$.
sourcejacobi_theta — Method
jacobi_theta(z::ComplexFieldElem, tau::ComplexFieldElem)Return a tuple of four elements containing the Jacobi theta function values $\theta_1, \theta_2, \theta_3, \theta_4$ evaluated at $z, \tau$.
sourceweierstrass_p — Method
weierstrass_p(z::ComplexFieldElem, tau::ComplexFieldElem)Return the Weierstrass elliptic function $\wp(z,\tau)$.
sourceExamples
julia> s = CC(1, 2)
1.0000000000000000000 + 2.0000000000000000000*im
julia> z = CC("1.23", "3.45")
[1.230000000000000000 +/- 2.00e-19] + [3.450000000000000000 +/- 3.91e-19]*im
julia> a = sin(z)^2 + cos(z)^2
[1.000000000000000 +/- 4.92e-16] + [+/- 4.12e-16]*im
julia> b = zeta(z)
[0.685803329024164062 +/- 6.30e-19] + [-0.038574782404586856 +/- 7.54e-19]*im
julia> c = bessel_j(s, z)
[0.63189634741402481 +/- 4.85e-18] + [0.00970090757446076 +/- 4.66e-18]*im
julia> d = hypergeometric_1f1(s, s+1, z)
[-1.3355297330012291 +/- 5.83e-17] + [-0.1715020340928697 +/- 4.97e-17]*imLinear dependence
lindep — Method
lindep(A::Vector{ComplexFieldElem}, bits::Int)Find a small linear combination of the entries of the array $A$ that is small (using LLL). The entries are first scaled by the given number of bits before truncating the real and imaginary parts to integers for use in LLL. This function can be used to find linear dependence between a list of complex numbers. The algorithm is heuristic only and returns an array of Nemo integers representing the linear combination.
sourcelindep — Method
lindep(A::Matrix{ComplexFieldElem}, bits::Int)Find a (common) small linear combination of the entries in each row of the array $A$, that is small (using LLL). It is assumed that the complex numbers in each row of the array share the same linear combination. The entries are first scaled by the given number of bits before truncating the real and imaginary parts to integers for use in LLL. This function can be used to find a common linear dependence shared across a number of lists of complex numbers. The algorithm is heuristic only and returns an array of Nemo integers representing the common linear combination.
sourceExamples
julia> # These are two of the roots of x^5 + 3x + 1
julia> a = CC(1.0050669478588622428791051888364775253, -0.93725915669289182697903585868761513585)
[1.0050669478588623029 +/- 2.25e-20] - [0.93725915669289183718 +/- 1.50e-21]*im
julia> b = CC(-0.33198902958450931620250069492231652319)
-[0.33198902958450932088 +/- 4.15e-22]
julia> V1 = [CC(1), a, a^2, a^3, a^4, a^5]; # We recover the polynomial from one root....
julia> W = lindep(V1, 20)
6-element Vector{ZZRingElem}:
1
3
0
0
0
1
julia> V2 = [CC(1), b, b^2, b^3, b^4, b^5]; # ...or from two
julia> Vs = [transpose(V1); transpose(V2)];
julia> X = lindep(Vs, 20)
6-element Vector{ZZRingElem}:
1
3
0
0
0
1