Arbitrary precision real balls

Arbitrary precision real ball arithmetic is supplied by Arb which provides a ball representation which tracks error bounds rigorously. Real numbers are represented in mid-rad interval form $[m \pm r] = [m-r, m+r]$.

The types of real balls in Nemo are given in the following table, along with the libraries that provide them and the associated types of the parent objects.

LibraryFieldElement typeParent type
Arb$\mathbb{R}$ (balls)RealFieldElemRealField

The real field types belong to the Field abstract type and the types of elements in this field, i.e. balls in this case, belong to the FieldElem abstract type.

Real ball functionality

Real balls in Nemo provide all the field functionality described in AbstractAlgebra:

https://nemocas.github.io/AbstractAlgebra.jl/stable/field

Below, we document the additional functionality provided for real balls.

Precision management

Precision for ball arithmetic and creation of elements can be controlled using the functions:

precisionMethod
precision(::Type{Balls})

Return the precision for ball arithmetic.

Examples

julia> set_precision!(Balls, 200); precision(Balls)
200
source
set_precision!Method
set_precision!(::Type{Balls}, n::Int)

Set the precision for all ball arithmetic to be n.

Examples

julia> const_pi(RealField())
[3.141592653589793239 +/- 5.96e-19]

julia> set_precision!(Balls, 200); const_pi(RealField())
[3.14159265358979323846264338327950288419716939937510582097494 +/- 5.73e-60]
source
set_precision!Method
set_precision!(f, ::Type{Balls}, n::Int)

Change ball arithmetic precision to n for the duration of f..

Examples

julia> set_precision!(Balls, 4) do
         const_pi(RealField())
       end
[3e+0 +/- 0.376]

julia> set_precision!(Balls, 200) do
         const_pi(RealField())
       end
[3.1415926535897932385 +/- 3.74e-20]
source
Info

This functions are not thread-safe.

Constructors

In order to construct real balls in Nemo, one must first construct the Arb real field itself. This is accomplished with the following constructor.

RealField()

Here is an example of creating the real field and using the resulting parent object to coerce values into the resulting field.

Examples

julia> RR = RealField()
Real field

julia> a = RR("0.25")
0.25000000000000000000

julia> b = RR("0.1 +/- 0.001")
[0.1 +/- 1.01e-3]

julia> c = RR(0.5)
0.50000000000000000000

julia> d = RR(12)
12.000000000000000000

Note that whilst one can coerce double precision floating point values into an Arb real 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 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.

Real ball constructors

Using coercion into the real field, new elements can be created.

Examples

julia> c = RR(1)
1.0000000000000000000

julia> d = RR(1//2)
0.50000000000000000000

Note that for the construction, also the precision can be supplied:

julia> c = RR(1//3, precision=100)
[0.33333333333333333333 +/- 3.34e-21]

julia> d = RR(1//3, precision=4)
[0.3 +/- 0.0438]

Conversions

julia> convert(Float64, RR(1//3))
0.3333333333333333

Basic manipulation

is_nonzeroMethod
is_nonzero(x::RealFieldElem)

Return true if $x$ is certainly not equal to zero, otherwise return false.

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isfiniteMethod
isfinite(x::RealFieldElem)

Return true if $x$ is finite, i.e. having finite midpoint and radius, otherwise return false.

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is_exactMethod
is_exact(x::RealFieldElem)

Return true if $x$ is exact, i.e. has zero radius, otherwise return false.

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isintegerMethod
isinteger(x::RealFieldElem)

Return true if $x$ is an exact integer, otherwise return false.

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is_positiveMethod
is_positive(x::RealFieldElem)

Return true if $x$ is certainly positive, otherwise return false.

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is_nonnegativeMethod
is_nonnegative(x::RealFieldElem)

Return true if $x$ is certainly non-negative, otherwise return false.

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is_negativeMethod
is_negative(x::RealFieldElem)

Return true if $x$ is certainly negative, otherwise return false.

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is_nonpositiveMethod
is_nonpositive(x::RealFieldElem)

Return true if $x$ is certainly nonpositive, otherwise return false.

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midpointMethod
midpoint(x::RealFieldElem)

Return the midpoint of the ball $x$ as an Arb ball.

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radiusMethod
radius(x::RealFieldElem)

Return the radius of the ball $x$ as an Arb ball.

source
accuracy_bitsMethod
accuracy_bits(x::RealFieldElem)

Return the relative accuracy of $x$ measured in bits, capped between typemax(Int) and -typemax(Int).

source

Examples

julia> RR = RealField()
Real field

julia> a = RR("1.2 +/- 0.001")
[1.20 +/- 1.01e-3]

julia> b = RR(3)
3.0000000000000000000

julia> is_positive(a)
true

julia> isfinite(b)
true

julia> isinteger(b)
true

julia> is_negative(a)
false

julia> c = radius(a)
[0.0010000000038417056203 +/- 1.12e-23]

julia> d = midpoint(b)
3.0000000000000000000

julia> f = accuracy_bits(a)
9

Printing

Printing real balls can at first sight be confusing. Lets look at the following example:

julia> a = RR(1)
1.0000000000000000000

julia> b = RR(2)
2.0000000000000000000

julia> c = RR(12)
12.000000000000000000

julia> x = ball(a, b)
[+/- 3.01]

julia> y = ball(c, b)
[1e+1 +/- 4.01]

julia> mid = midpoint(x)
1.0000000000000000000

julia> rad = radius(x)
[2.0000000037252902985 +/- 3.81e-20]

julia> print(x, "\n", y, "\n", mid, "\n", rad)
[+/- 3.01]
[1e+1 +/- 4.01]
1.0000000000000000000
[2.0000000037252902985 +/- 3.81e-20]

The first reason that c is not printed as [1 +/- 2] is that the midpoint does not have a greater exponent than the radius in its scientific notation. For similar reasons y is not printed as [12 +/- 2].

The second reason is that we get an additional error term after our addition. As we see, radius(c) is not equal to $2$, which when printed rounds it up to a reasonable decimal place. This is because real balls keep track of rounding errors of basic arithmetic.

Containment

It is often necessary to determine whether a given exact value or ball is contained in a given real ball or whether two balls overlap. The following functions are provided for this purpose.

overlapsMethod
overlaps(x::RealFieldElem, y::RealFieldElem)

Returns true if any part of the ball $x$ overlaps any part of the ball $y$, otherwise return false.

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containsMethod
contains(x::RealFieldElem, y::RealFieldElem)

Returns true if the ball $x$ contains the ball $y$, otherwise return false.

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containsMethod
contains(x::RealFieldElem, y::Integer)

Returns true if the ball $x$ contains the given integer value, otherwise return false.

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containsMethod
contains(x::RealFieldElem, y::ZZRingElem)

Returns true if the ball $x$ contains the given integer value, otherwise return false.

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containsMethod
contains(x::RealFieldElem, y::QQFieldElem)

Returns true if the ball $x$ contains the given rational value, otherwise return false.

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containsMethod
contains(x::RealFieldElem, y::Rational{T}) where {T <: Integer}

Returns true if the ball $x$ contains the given rational value, otherwise return false.

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containsMethod
contains(x::RealFieldElem, y::BigFloat)

Returns true if the ball $x$ contains the given floating point value, otherwise return false.

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The following functions are also provided for determining if a ball intersects a certain part of the real number line.

contains_zeroMethod
contains_zero(x::RealFieldElem)

Returns true if the ball $x$ contains zero, otherwise return false.

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contains_negativeMethod
contains_negative(x::RealFieldElem)

Returns true if the ball $x$ contains any negative value, otherwise return false.

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contains_positiveMethod
contains_positive(x::RealFieldElem)

Returns true if the ball $x$ contains any positive value, otherwise return false.

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contains_nonnegativeMethod
contains_nonnegative(x::RealFieldElem)

Returns true if the ball $x$ contains any non-negative value, otherwise return false.

source
contains_nonpositiveMethod
contains_nonpositive(x::RealFieldElem)

Returns true if the ball $x$ contains any nonpositive value, otherwise return false.

source

Examples

julia> x = RR("1 +/- 0.001")
[1.00 +/- 1.01e-3]

julia> y = RR("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)
false

julia> contains_positive(y)
true

Comparison

Nemo provides a full range of comparison operations for Arb balls. Note that a ball is considered less than another ball if every value in the first ball is less than every value in the second ball, etc.

In addition to the standard comparison operators, 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.

isequalMethod
isequal(x::RealFieldElem, y::RealFieldElem)

Return true if the balls $x$ and $y$ are precisely equal, i.e. have the same midpoints and radii.

source

We also provide a full range of ad hoc comparison operators. These are implemented directly in Julia, but we document them as though isless and == were provided.

Function
==(x::RealFieldElem, y::Integer)
==(x::Integer, y::RealFieldElem)
==(x::RealFieldElem, y::ZZRingElem)
==(x::ZZRingElem, y::RealFieldElem)
==(x::RealFieldElem, y::Float64)
==(x::Float64, y::RealFieldElem)
isless(x::RealFieldElem, y::Integer)
isless(x::Integer, y::RealFieldElem)
isless(x::RealFieldElem, y::ZZRingElem)
isless(x::ZZRingElem, y::RealFieldElem)
isless(x::RealFieldElem, y::Float64)
isless(x::Float64, y::RealFieldElem)
isless(x::RealFieldElem, y::BigFloat)
isless(x::BigFloat, y::RealFieldElem)
isless(x::RealFieldElem, y::QQFieldElem)
isless(x::QQFieldElem, y::RealFieldElem)

Examples

julia> x = RR("1 +/- 0.001")
[1.00 +/- 1.01e-3]

julia> y = RR("3")
3.0000000000000000000

julia> z = RR("4")
4.0000000000000000000

julia> isequal(x, deepcopy(x))
true

julia> x == 3
false

julia> ZZ(3) < z
true

julia> x != 1.23
true

Absolute value

Examples

julia> x = RR("-1 +/- 0.001")
[-1.00 +/- 1.01e-3]

julia> a = abs(x)
[1.00 +/- 1.01e-3]

Shifting

Examples

julia> x = RR("-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

add_error!Method
add_error!(x::RealFieldElem, y::RealFieldElem)

Adds the absolute values of the midpoint and radius of $y$ to the radius of $x$.

source
trimMethod
trim(x::RealFieldElem)

Return an ArbFieldElem interval containing $x$ but which may be more economical, by rounding off insignificant bits from the midpoint.

source
unique_integerMethod
unique_integer(x::RealFieldElem)

Return a pair where the first value is a boolean and the second is an ZZRingElem integer. The boolean indicates whether the interval $x$ contains a unique integer. If this is the case, the second return value is set to this unique integer.

source
setunionMethod
setunion(x::RealFieldElem, y::RealFieldElem)

Return an ArbFieldElem containing the union of the intervals represented by $x$ and $y$.

source

Examples

julia> x = RR("-3 +/- 0.001")
[-3.00 +/- 1.01e-3]

julia> y = RR("2 +/- 0.5")
[2e+0 +/- 0.501]

julia> a = trim(x)
[-3.00 +/- 1.01e-3]

julia> b, c = unique_integer(x)
(true, -3)

julia> d = setunion(x, y)
[+/- 3.01]

Constants

const_piMethod
const_pi(r::RealField)

Return $\pi = 3.14159\ldots$ as an element of $r$.

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const_eMethod
const_e(r::RealField)

Return $e = 2.71828\ldots$ as an element of $r$.

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const_log2Method
const_log2(r::RealField)

Return $\log(2) = 0.69314\ldots$ as an element of $r$.

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const_log10Method
const_log10(r::RealField)

Return $\log(10) = 2.302585\ldots$ as an element of $r$.

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const_eulerMethod
const_euler(r::RealField)

Return Euler's constant $\gamma = 0.577215\ldots$ as an element of $r$.

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const_catalanMethod
const_catalan(r::RealField)

Return Catalan's constant $C = 0.915965\ldots$ as an element of $r$.

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const_khinchinMethod
const_khinchin(r::RealField)

Return Khinchin's constant $K = 2.685452\ldots$ as an element of $r$.

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const_glaisherMethod
const_glaisher(r::RealField)

Return Glaisher's constant $A = 1.282427\ldots$ as an element of $r$.

source

Examples

julia> a = const_pi(RR)
[3.141592653589793239 +/- 5.96e-19]

julia> b = const_e(RR)
[2.718281828459045235 +/- 4.29e-19]

julia> c = const_euler(RR)
[0.5772156649015328606 +/- 4.35e-20]

julia> d = const_glaisher(RR)
[1.282427129100622637 +/- 3.01e-19]

Mathematical and special functions

rsqrtMethod
rsqrt(x::RealFieldElem)

Return the reciprocal of the square root of $x$, i.e. $1/\sqrt{x}$.

source
sqrt1pm1Method
sqrt1pm1(x::RealFieldElem)

Return $\sqrt{1+x}-1$, evaluated accurately for small $x$.

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sqrtposMethod
sqrtpos(x::RealFieldElem)

Return the sqrt root of $x$, assuming that $x$ represents a non-negative number. Thus any negative number in the input interval is discarded.

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gammaMethod
gamma(x::RealFieldElem)

Return the Gamma function evaluated at $x$.

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lgammaMethod
lgamma(x::RealFieldElem)

Return the logarithm of the Gamma function evaluated at $x$.

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rgammaMethod
rgamma(x::RealFieldElem)

Return the reciprocal of the Gamma function evaluated at $x$.

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digammaMethod
digamma(x::RealFieldElem)

Return the logarithmic derivative of the gamma function evaluated at $x$, i.e. $\psi(x)$.

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gammaMethod
gamma(s::RealFieldElem, x::RealFieldElem)

Return the upper incomplete gamma function $\Gamma(s,x)$.

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gamma_regularizedMethod
gamma_regularized(s::RealFieldElem, x::RealFieldElem)

Return the regularized upper incomplete gamma function $\Gamma(s,x) / \Gamma(s)$.

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gamma_lowerMethod
gamma_lower(s::RealFieldElem, x::RealFieldElem)

Return the lower incomplete gamma function $\gamma(s,x) / \Gamma(s)$.

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gamma_lower_regularizedMethod
gamma_lower_regularized(s::RealFieldElem, x::RealFieldElem)

Return the regularized lower incomplete gamma function $\gamma(s,x) / \Gamma(s)$.

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zetaMethod
zeta(x::RealFieldElem)

Return the Riemann zeta function evaluated at $x$.

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atan2Method
atan2(y::RealFieldElem, x::RealFieldElem)

Return $\operatorname{atan2}(y,x) = \arg(x+yi)$. Same as atan(y, x).

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agmMethod
agm(x::RealFieldElem, y::RealFieldElem)

Return the arithmetic-geometric mean of $x$ and $y$

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zetaMethod
zeta(s::RealFieldElem, a::RealFieldElem)

Return the Hurwitz zeta function $\zeta(s,a)$.

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rootMethod
root(x::RealFieldElem, n::Int)

Return the $n$-th root of $x$. We require $x \geq 0$.

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factorialMethod
factorial(x::RealFieldElem)

Return the factorial of $x$.

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factorialMethod
factorial(n::Int, r::RealField)

Return the factorial of $n$ in the given Arb field.

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binomialMethod
binomial(x::RealFieldElem, n::UInt)

Return the binomial coefficient ${x \choose n}$.

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binomialMethod
binomial(n::UInt, k::UInt, r::RealField)

Return the binomial coefficient ${n \choose k}$ in the given Arb field.

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fibonacciMethod
fibonacci(n::ZZRingElem, r::RealField)

Return the $n$-th Fibonacci number in the given Arb field.

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fibonacciMethod
fibonacci(n::Int, r::RealField)

Return the $n$-th Fibonacci number in the given Arb field.

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gammaMethod
gamma(x::ZZRingElem, r::RealField)

Return the Gamma function evaluated at $x$ in the given Arb field.

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gammaMethod
gamma(x::QQFieldElem, r::RealField)

Return the Gamma function evaluated at $x$ in the given Arb field.

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zetaMethod
zeta(n::Int, r::RealField)

Return the Riemann zeta function $\zeta(n)$ as an element of the given Arb field.

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bernoulliMethod
bernoulli(n::Int, r::RealField)

Return the $n$-th Bernoulli number as an element of the given Arb field.

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rising_factorialMethod
rising_factorial(x::RealFieldElem, n::Int)

Return the rising factorial $x(x + 1)\ldots (x + n - 1)$ as an Arb.

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rising_factorial(x::RingElement, n::Integer)

Return the rising factorial of $x$, i.e. $x(x + 1)(x + 2)\cdots (x + n - 1)$. If $n < 0$ we throw a DomainError().

Examples

julia> R, x = ZZ[:x];

julia> rising_factorial(x, 1)
x

julia> rising_factorial(x, 2)
x^2 + x

julia> rising_factorial(4, 2)
20
source
rising_factorialMethod
rising_factorial(x::QQFieldElem, n::Int, r::RealField)

Return the rising factorial $x(x + 1)\ldots (x + n - 1)$ as an element of the given Arb field.

source
rising_factorial2Method
rising_factorial2(x::RealFieldElem, n::Int)

Return a tuple containing the rising factorial $x(x + 1)\ldots (x + n - 1)$ and its derivative.

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rising_factorial2(x::RingElement, n::Integer)

Return a tuple containing the rising factorial $x(x + 1)\cdots (x + n - 1)$ and its derivative. If $n < 0$ we throw a DomainError().

Examples

julia> R, x = ZZ[:x];

julia> rising_factorial2(x, 1)
(x, 1)

julia> rising_factorial2(x, 2)
(x^2 + x, 2*x + 1)

julia> rising_factorial2(4, 2)
(20, 9)
source
polylogMethod
polylog(s::Union{RealFieldElem,Int}, a::RealFieldElem)

Return the polylogarithm Li$_s(a)$.

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chebyshev_tMethod
chebyshev_t(n::Int, x::RealFieldElem)

Return the value of the Chebyshev polynomial $T_n(x)$.

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chebyshev_uMethod
chebyshev_u(n::Int, x::RealFieldElem)

Return the value of the Chebyshev polynomial $U_n(x)$.

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chebyshev_t2Method
chebyshev_t2(n::Int, x::RealFieldElem)

Return the tuple $(T_{n}(x), T_{n-1}(x))$.

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chebyshev_u2Method
chebyshev_u2(n::Int, x::RealFieldElem)

Return the tuple $(U_{n}(x), U_{n-1}(x))$

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bellMethod
bell(n::ZZRingElem, r::RealField)

Return the Bell number $B_n$ as an element of $r$.

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bellMethod
bell(n::Int, r::RealField)

Return the Bell number $B_n$ as an element of $r$.

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numpartMethod
numpart(n::ZZRingElem, r::RealField)

Return the number of partitions $p(n)$ as an element of $r$.

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numpartMethod
numpart(n::Int, r::RealField)

Return the number of partitions $p(n)$ as an element of $r$.

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airy_aiMethod
airy_ai(x::RealFieldElem)

Return the Airy function $\operatorname{Ai}(x)$.

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airy_ai_primeMethod
airy_ai_prime(x::RealFieldElem)

Return the derivative of the Airy function $\operatorname{Ai}^\prime(x)$.

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airy_biMethod
airy_bi(x::RealFieldElem)

Return the Airy function $\operatorname{Bi}(x)$.

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airy_bi_primeMethod
airy_bi_prime(x::RealFieldElem)

Return the derivative of the Airy function $\operatorname{Bi}^\prime(x)$.

source

Examples

julia> a = floor(exp(RR(1)))
2.0000000000000000000

julia> b = sinpi(QQ(5,6), RR)
0.50000000000000000000

julia> c = gamma(QQ(1,3), RR)
[2.678938534707747634 +/- 7.13e-19]

julia> d = bernoulli(1000, RR)
[-5.318704469415522036e+1769 +/- 6.61e+1750]

julia> f = polylog(3, RR(-10))
[-5.92106480375697 +/- 6.68e-15]

Linear dependence

lindepMethod
lindep(A::Vector{RealFieldElem}, 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 to integers for use in LLL. This function can be used to find linear dependence between a list of real numbers. The algorithm is heuristic only and returns an array of Nemo integers representing the linear combination.

Examples

julia> RR = RealField()
Real field

julia> a = RR(-0.33198902958450931620250069492231652319)
[-0.33198902958450932088 +/- 4.15e-22]

julia> V = [RR(1), a, a^2, a^3, a^4, a^5]
6-element Vector{RealFieldElem}:
 1.0000000000000000000
 [-0.33198902958450932088 +/- 4.15e-22]
 [0.11021671576446420510 +/- 7.87e-21]
 [-0.03659074051063616184 +/- 4.17e-21]
 [0.012147724433904692427 +/- 4.99e-22]
 [-0.004032911246472051677 +/- 6.25e-22]

julia> W = lindep(V, 20)
6-element Vector{ZZRingElem}:
 1
 3
 0
 0
 0
 1
source
simplest_rational_insideMethod
  simplest_rational_inside(x::RealFieldElem)

Return the simplest fraction inside the ball $x$. A canonical fraction $a_1/b_1$ is defined to be simpler than $a_2/b_2$ iff $b_1 < b_2$ or $b_1 = b_2$ and $a_1 < a_2$.

Examples

julia> RR = RealField()
Real field

julia> simplest_rational_inside(const_pi(RR))
8717442233//2774848045
source

Random generation

randMethod
rand(r::RealField; randtype::Symbol=:urandom)

Return a random element in given Arb field.

The randtype default is :urandom which return an ArbFieldElem contained in $[0,1]$.

The rest of the methods return non-uniformly distributed values in order to exercise corner cases. The option :randtest will return a finite number, and :randtest_exact the same but with a zero radius. The option :randtest_precise return an ArbFieldElem with a radius around $2^{-\mathrm{prec}}$ the magnitude of the midpoint, while :randtest_wide return a radius that might be big relative to its midpoint. The :randtest_special-option might return a midpoint and radius whose values are NaN or inf.

source
rand([rng=GLOBAL_RNG,] G::SymmetricGroup)

Return a random permutation from G.

source

Examples

a = rand(RR)
b = rand(RR; randtype = :null_exact)
c = rand(RR; randtype = :exact)
d = rand(RR; randtype = :special)