Note

Arb was merged into FLINT in 2023.

The documentation on arblib.org will no longer be updated.

See the FLINT documentation instead.

Technical conventions and potential issues

Integer types

Arb generally uses the int type for boolean values and status flags.

The char, short and int types are assumed to be two’s complement types with exactly 8, 16 and 32 bits. This is not technically guaranteed by the C standard, but there are no mainstream platforms where this assumption does not hold, and new ones are unlikely to appear in the near future (ignoring certain low-power DSPs and the like, which are out of scope for this software).

Since the C types long and unsigned long do not have a standardized size in practice, FLINT defines slong and ulong types which are guaranteed to be 32 bits on a 32-bit system and 64 bits on a 64-bit system. They are also guaranteed to have the same size as GMP’s mp_limb_t. GMP builds with a different limb size configuration are not supported at all. For convenience, the macro FLINT_BITS specifies the word length (32 or 64) of the system.

type slong

The slong type is used for precisions, bit counts, loop indices, array sizes, and the like, even when those values are known to be nonnegative. It is also used for small integer-valued coefficients. In method names, an slong parameter is denoted by si, for example arb_add_si().

The constants WORD_MIN and WORD_MAX give the range of this type. This type can be printed with flint_printf using the format string %wd.

type ulong

The ulong type is used for integer-valued coefficients that are known to be unsigned, and for values that require the full 32-bit or 64-bit range. In method names, a ulong parameter is denoted by ui, for example arb_add_ui().

The constant UWORD_MAX gives the range of this type. This type can be printed with flint_printf using the format string %wu.

The following GMP-defined types are used in methods that manipulate the internal representation of numbers (using limb arrays).

type mp_limb_t

A single limb.

type mp_ptr

Pointer to a writable array of limbs.

type mp_srcptr

Pointer to a read-only array of limbs.

type mp_size_t

A limb count (always nonnegative).

type flint_bitcnt_t

A bit offset within an array of limbs (always nonnegative).

Arb uses the following FLINT types for exact (integral and rational) arbitrary-size values. For details, refer to the FLINT documentation.

type fmpz

type fmpz_t

The FLINT multi-precision integer type uses an inline representation for small integers, specifically when the absolute value is at most \(2^{62}-1\) (on 64-bit machines) or \(2^{30}-1\) (on 32-bit machines). It switches automatically to a GMP integer for larger values. The fmpz_t type is functionally identical to the GMP mpz_t type, but faster for small values.

An fmpz_t is defined as an array of length one of type fmpz (which is just an alias for slong), permitting an fmpz_t to be passed by reference.

type fmpq_t

FLINT multi-precision rational number.

type fmpz_poly_t

type fmpq_poly_t

type fmpz_mat_t

type fmpq_mat_t

FLINT polynomials and matrices with integer and rational coefficients.

Integer overflow

When machine-size integers are used for precisions, sizes of integers in bits, lengths of polynomials, and similar quantities that relate to sizes in memory, very few internal checks are performed to verify that such quantities do not overflow.

Precisions and lengths exceeding a small fraction of LONG_MAX, say \(2^{24} \approx 10^7\) on 32-bit systems, should be regarded as resulting in undefined behavior. On 64-bit systems this should generally not be an issue, since most calculations will exhaust the available memory (or the user’s patience waiting for the computation to complete) long before running into integer overflows. However, the user needs to be wary of unintentionally passing input parameters of order LONG_MAX or negative parameters where positive parameters are expected, for example due to a runaway loop that repeatedly increases the precision.

Currently, no hard upper limit on the precision is defined, but \(2^{24} \approx 10^7\) bits on 32-bit system and \(2^{36} \approx 10^{11}\) bits on a 64-bit system can be considered safe for most purposes. The relatively low limit on 64-bit systems is due to the fact that GMP integers are used internally in some algorithms, and GMP integers are limited to \(2^{37}\) bits. The minimum allowed precision is 2 bits.

This caveat does not apply to exponents of floating-point numbers, which are represented as arbitrary-precision integers, nor to integers used as numerical scalars (e.g. arb_mul_si()). However, it still applies to conversions and operations where the result is requested exactly and sizes become an issue. For example, trying to convert the floating-point number \(2^{2^{100}}\) to an integer could result in anything from a silent wrong value to thrashing followed by a crash, and it is the user’s responsibility not to attempt such a thing.

Aliasing

As a rule, Arb allows aliasing of operands. For example, in the function call arb_add(z, x, y, prec), which performs \(z \gets x + y\), any two (or all three) of the variables x, y and z are allowed to be the same. Exceptions to this rule are documented explicitly.

The general rule that input and output variables can be aliased with each other only applies to variables of the same type (ignoring const qualifiers on input variables – a special case is that arb_srcptr is considered the const version of arb_ptr). This is a natural extension of the so-called strict aliasing rule in C.

For example, in arb_poly_evaluate() which evaluates \(y = f(x)\) for a polynomial f, the output variable y is not allowed to be a pointer to one of the coefficients of f (but aliasing between x and y or between x and the coefficients of f is allowed). This also applies to _arb_poly_evaluate(): for the purposes of aliasing, arb_srcptr (the type of the coefficient array within f) and arb_t (the type of x) are not considered to be the same type, and therefore must not be aliased with each other, even though an arb_ptr/arb_srcptr variable pointing to a length 1 array would otherwise be interchangeable with an arb_t/const arb_t.

Moreover, in functions that allow aliasing between an input array and an output array, the arrays must either be identical or completely disjoint, never partially overlapping.

There are natural exceptions to these aliasing restrictions, which may used internally without being documented explicitly. However, third party code should avoid relying on such exceptions.

An important caveat applies to aliasing of input variables. Identical pointers are understood to give permission for algebraic simplification. This assumption is made to improve performance. For example, the call arb_mul(z, x, x, prec) sets z to a ball enclosing the set

\[\{ t^2 \,:\, t \in x \}\]

and not the (generally larger) set

\[\{ t u \,:\, t \in x, u \in x \}.\]

If the user knows that two values x and y both lie in the interval \([-1,1]\) and wants to compute an enclosure for \(f(x,y)\), then it would be a mistake to create an arb_t variable x enclosing \([-1,1]\) and reusing the same variable for y, calling \(f(x,x)\). Instead, the user has to create a distinct variable y also enclosing \([-1,1]\).

Algebraic simplification is not guaranteed to occur. For example, arb_add(z, x, x, prec) and arb_sub(z, x, x, prec) currently do not implement this optimization. It is better to use arb_mul_2exp_si(z, x, 1) and arb_zero(z), respectively.

Thread safety and caches

Arb should be fully threadsafe, provided that both MPFR and FLINT have been built in threadsafe mode. Use flint_set_num_threads() to set the number of threads that Arb is allowed to use internally for single computations (this is currently only exploited by a handful of operations). Please note that thread safety is only tested minimally, and extra caution when developing multithreaded code is therefore recommended.

Arb may cache some data (such as the value of \(\pi\) and Bernoulli numbers) to speed up various computations. In threadsafe mode, caches use thread-local storage. There is currently no way to save memory and avoid recomputation by having several threads share the same cache. Caches can be freed by calling the flint_cleanup() function. To avoid memory leaks, the user should call flint_cleanup() when exiting a thread. It is also recommended to call flint_cleanup() when exiting the main program (this should result in a clean output when running Valgrind, and can help catching memory issues).

There does not seem to be an obvious way to make sure that flint_cleanup() is called when exiting a thread using OpenMP. A possible solution to this problem is to use OpenMP sections, or to use C++ and create a thread-local object whose destructor invokes flint_cleanup().

Use of hardware floating-point arithmetic

Arb uses hardware floating-point arithmetic (the double type in C) in two different ways.

First, double arithmetic as well as transcendental libm functions (such as exp, log) are used to select parameters heuristically in various algorithms. Such heuristic use of approximate arithmetic does not affect correctness: when any error bounds depend on the parameters, the error bounds are evaluated separately using rigorous methods. At worst, flaws in the floating-point arithmetic on a particular machine could cause an algorithm to become inefficient due to inefficient parameters being selected.

Second, double arithmetic is used internally for some rigorous error bound calculations. To guarantee correctness, we make the following assumptions. With the stated exceptions, these should hold on all commonly used platforms.

• A double uses the standard IEEE 754 format (with a 53-bit significand, 11-bit exponent, encoding of infinities and NaNs, etc.)

• We assume that the compiler does not perform “unsafe” floating-point optimizations, such as reordering of operations. Unsafe optimizations are disabled by default in most modern C compilers, including GCC and Clang. The exception appears to be the Intel C++ compiler, which does some unsafe optimizations by default. These must be disabled by the user.

• We do not assume that floating-point operations are correctly rounded (a counterexample is the x87 FPU), or that rounding is done in any particular direction (the rounding mode may have been changed by the user). We assume that any floating-point operation is done with at most 1.1 ulp error.

• We do not assume that underflow or overflow behaves in a particular way (we only use doubles that fit in the regular exponent range, or explicit infinities).

• We do not use transcendental libm functions, since these can have errors of several ulps, and there is unfortunately no way to get guaranteed bounds. However, we do use functions such as ldexp and sqrt, which we assume to be correctly implemented.

Interface changes

Most of the core API should be stable at this point, and significant compatibility-breaking changes will be specified in the release notes.

In general, Arb does not distinguish between “private” and “public” parts of the API. The implementation is meant to be transparent by design. All methods are intended to be fully documented and tested (exceptions to this are mainly due to lack of time on part of the author). The user should use common sense to determine whether a function is concerned with implementation details, making it likely to change as the implementation changes in the future. The interface of arb_add() is probably not going to change in the next version, but _arb_get_mpn_fixed_mod_pi4() just might.

General note on correctness

Except where otherwise specified, Arb is designed to produce provably correct error bounds. The code has been written carefully, and the library is extensively tested. However, like any complex mathematical software, Arb is virtually certain to contain bugs, so the usual precautions are advised:

• Do sanity checks. For example, check that the result satisfies an expected mathematical relation, or compute the same result in two different ways, with different settings, and with different levels of precision. Arb’s unit tests already do such checks, but they are not guaranteed to catch every possible bug, and they provide no protection against the user accidentally using the interface incorrectly.

• Compare results with other mathematical software.

• Read the source code to verify that it really does what it is supposed to do.

All bug reports are highly appreciated.