UNPKG

@noble/curves

Version:

Audited & minimal JS implementation of elliptic curve cryptography

439 lines 16.3 kB
/** * Experimental implementation of NTT / FFT (Fast Fourier Transform) over finite fields. * API may change at any time. The code has not been audited. Feature requests are welcome. * @module */ import type { TArg } from '../utils.ts'; import type { IField } from './modular.ts'; /** Array-like coefficient storage that can be mutated in place. */ export interface MutableArrayLike<T> { /** Element access by numeric index. */ [index: number]: T; /** Current amount of stored coefficients. */ length: number; /** * Return a sliced copy using the same storage shape. * @param start - Inclusive start index. * @param end - Exclusive end index. * @returns Sliced copy. */ slice(start?: number, end?: number): this; /** * Iterate over stored coefficients in order. * @returns Coefficient iterator. */ [Symbol.iterator](): Iterator<T>; } /** * Concrete polynomial containers accepted by the high-level `poly(...)` helpers. * Lower-level FFT helpers can work with structural `MutableArrayLike`, but `poly(...)` * intentionally keeps runtime dispatch on plain arrays and typed-array views. */ export type PolyStorage<T> = T[] | (MutableArrayLike<T> & ArrayBufferView); /** * Checks if integer is in form of `1 << X`. * @param x - Integer to inspect. * @returns `true` when the value is a power of two. * @throws If `x` is not a valid unsigned 32-bit integer. {@link Error} * @example * Validate that an FFT size is a power of two. * * ```ts * isPowerOfTwo(8); * ``` */ export declare function isPowerOfTwo(x: number): boolean; /** * @param n - Input value. * @returns Next power of two within the u32/array-length domain. * @throws If `n` is not a valid unsigned 32-bit integer. {@link Error} * @example * Round an integer up to the FFT size it needs. * * ```ts * nextPowerOfTwo(9); * ``` */ export declare function nextPowerOfTwo(n: number): number; /** * @param n - Value to reverse. * @param bits - Number of bits to use. * @returns Bit-reversed integer. * @throws If `n` is not a valid unsigned 32-bit integer. {@link Error} * @example * Reverse the low `bits` bits of one index. * * ```ts * reverseBits(3, 3); * ``` */ export declare function reverseBits(n: number, bits: number): number; /** * Similar to `bitLen(x)-1` but much faster for small integers, like indices. * @param n - Input value. * @returns Base-2 logarithm. For `n = 0`, the current implementation returns `-1`. * @throws If `n` is not a valid unsigned 32-bit integer. {@link Error} * @example * Compute the radix-2 stage count for one transform size. * * ```ts * log2(8); * ``` */ export declare function log2(n: number): number; /** * Moves lowest bit to highest position, which at first step splits * array on even and odd indices, then it applied again to each part, * which is core of fft * @param values - Mutable coefficient array. * @returns Mutated input array. * @throws If the array length is not a positive power of two. {@link Error} * @example * Reorder coefficients into bit-reversed order in place. * * ```ts * const values = Uint8Array.from([0, 1, 2, 3]); * bitReversalInplace(values); * ``` */ export declare function bitReversalInplace<T extends MutableArrayLike<any>>(values: T): T; /** * @param values - Input values. * @returns Reordered copy. * @throws If the array length is not a positive power of two. {@link Error} * @example * Return a reordered copy instead of mutating the input in place. * * ```ts * const reordered = bitReversalPermutation([0, 1, 2, 3]); * ``` */ export declare function bitReversalPermutation<T>(values: T[]): T[]; /** Cached roots-of-unity tables derived from one finite field. */ export type RootsOfUnity = { /** Generator and 2-adicity metadata for the cached field. */ info: { G: bigint; oddFactor: bigint; powerOfTwo: number; }; /** * Return the natural-order roots of unity for one radix-2 size. * @param bits - Transform size as `log2(N)`. * @returns Natural-order roots for that size. */ roots: (bits: number) => bigint[]; /** * Return the bit-reversal permutation of the roots for one radix-2 size. * @param bits - Transform size as `log2(N)`. * @returns Bit-reversed roots. */ brp(bits: number): bigint[]; /** * Return the inverse roots of unity for one radix-2 size. * @param bits - Transform size as `log2(N)`. * @returns Inverse roots. */ inverse(bits: number): bigint[]; /** * Return one primitive root used by a radix-2 stage. * @param bits - Transform size as `log2(N)`. * @returns Primitive root for that stage. */ omega: (bits: number) => bigint; /** * Drop all cached root tables. * @returns Nothing. */ clear: () => void; }; /** * We limit roots up to 2**31, which is a lot: 2-billion polynomimal should be rare. * @param field - Field implementation. * @param generator - Optional generator override. * @returns Roots-of-unity cache. * @example * Cache roots once, then ask for the omega table of one FFT size. * * ```ts * import { rootsOfUnity } from '@noble/curves/abstract/fft.js'; * import { Field } from '@noble/curves/abstract/modular.js'; * const roots = rootsOfUnity(Field(17n)); * const omega = roots.omega(4); * ``` */ export declare function rootsOfUnity(field: TArg<IField<bigint>>, generator?: bigint): RootsOfUnity; /** Polynomial coefficient container used by the FFT helpers. */ export type Polynomial<T> = MutableArrayLike<T>; /** * Arithmetic operations used by the generic FFT implementation. * * Maps great to Field<bigint>, but not to Group (EC points): * - inv from scalar field * - we need multiplyUnsafe here, instead of multiply for speed * - multiplyUnsafe is safe in the context: we do mul(rootsOfUnity), which are public and sparse */ export type FFTOpts<T, R> = { /** * Add two coefficients. * @param a - Left coefficient. * @param b - Right coefficient. * @returns Sum coefficient. */ add: (a: T, b: T) => T; /** * Subtract two coefficients. * @param a - Left coefficient. * @param b - Right coefficient. * @returns Difference coefficient. */ sub: (a: T, b: T) => T; /** * Multiply one coefficient by a scalar/root factor. * @param a - Coefficient value. * @param scalar - Scalar/root factor. * @returns Scaled coefficient. */ mul: (a: T, scalar: R) => T; /** * Invert one scalar/root factor. * @param a - Scalar/root factor. * @returns Inverse factor. */ inv: (a: R) => R; }; /** Configuration for one low-level FFT loop. */ export type FFTCoreOpts<R> = { /** Transform size. Must be a power of two. */ N: number; /** Stage roots for the selected transform size. */ roots: Polynomial<R>; /** Whether to run the DIT variant instead of DIF. */ dit: boolean; /** Whether to invert butterfly placement for decode-oriented layouts. */ invertButterflies?: boolean; /** Number of initial stages to skip. */ skipStages?: number; /** Whether to apply bit-reversal permutation at the boundary. */ brp?: boolean; }; /** * Callable low-level FFT loop over one polynomial storage shape. * @param values - Polynomial coefficients to transform in place. * @returns The mutated input polynomial. */ export type FFTCoreLoop<T> = <P extends Polynomial<T>>(values: P) => P; /** * Constructs different flavors of FFT. radix2 implementation of low level mutating API. Flavors: * * - DIT (Decimation-in-Time): Bottom-Up (leaves to root), Cool-Turkey * - DIF (Decimation-in-Frequency): Top-Down (root to leaves), Gentleman-Sande * * DIT takes brp input, returns natural output. * DIF takes natural input, returns brp output. * * The output is actually identical. Time / frequence distinction is not meaningful * for Polynomial multiplication in fields. * Which means if protocol supports/needs brp output/inputs, then we can skip this step. * * Cyclic NTT: Rq = Zq[x]/(x^n-1). butterfly_DIT+loop_DIT OR butterfly_DIF+loop_DIT, roots are omega * Negacyclic NTT: Rq = Zq[x]/(x^n+1). butterfly_DIT+loop_DIF, at least for mlkem / mldsa * @param F - Field operations. * @param coreOpts - FFT configuration: * - `N`: Transform size. Must be a power of two. * - `roots`: Stage roots for the selected transform size. * - `dit`: Whether to run the DIT variant instead of DIF. * - `invertButterflies` (optional): Whether to invert butterfly placement. * - `skipStages` (optional): Number of initial stages to skip. * - `brp` (optional): Whether to apply bit-reversal permutation at the boundary. * @returns Low-level FFT loop. * @throws If the FFT options or cached roots are invalid for the requested size. {@link Error} * @example * Constructs different flavors of FFT. * * ```ts * import { FFTCore, rootsOfUnity } from '@noble/curves/abstract/fft.js'; * import { Field } from '@noble/curves/abstract/modular.js'; * const Fp = Field(17n); * const roots = rootsOfUnity(Fp).roots(2); * const loop = FFTCore(Fp, { N: 4, roots, dit: true }); * const values = loop([1n, 2n, 3n, 4n]); * ``` */ export declare const FFTCore: <T, R>(F: FFTOpts<T, R>, coreOpts: FFTCoreOpts<R>) => FFTCoreLoop<T>; /** Forward and inverse FFT helpers for one coefficient domain. */ export type FFTMethods<T> = { /** * Apply the forward transform. * @param values - Polynomial coefficients to transform. * @param brpInput - Whether the input is already bit-reversed. * @param brpOutput - Whether to keep the output bit-reversed. * @returns Transformed copy. */ direct<P extends Polynomial<T>>(values: P, brpInput?: boolean, brpOutput?: boolean): P; /** * Apply the inverse transform. * @param values - Polynomial coefficients to transform. * @param brpInput - Whether the input is already bit-reversed. * @param brpOutput - Whether to keep the output bit-reversed. * @returns Inverse-transformed copy. */ inverse<P extends Polynomial<T>>(values: P, brpInput?: boolean, brpOutput?: boolean): P; }; /** * NTT aka FFT over finite field (NOT over complex numbers). * Naming mirrors other libraries. * @param roots - Roots-of-unity cache. * @param opts - Field operations. See {@link FFTOpts}. * @returns Forward and inverse FFT helpers. * @example * NTT aka FFT over finite field (NOT over complex numbers). * * ```ts * import { FFT, rootsOfUnity } from '@noble/curves/abstract/fft.js'; * import { Field } from '@noble/curves/abstract/modular.js'; * const Fp = Field(17n); * const fft = FFT(rootsOfUnity(Fp), Fp); * const values = fft.direct([1n, 2n, 3n, 4n]); * ``` */ export declare function FFT<T>(roots: RootsOfUnity, opts: FFTOpts<T, bigint>): FFTMethods<T>; /** * Factory that allocates one polynomial storage container. * Callers must ensure `_create(len)` returns field-zero-filled storage when `elm` is omitted, * because the quadratic `mul()` / `convolve()` paths and the Kronecker-δ shortcut in * `lagrange.basis()` rely on that default instead of always passing `field.ZERO` explicitly. * @param len - Requested amount of coefficients. * @param elm - Optional fill value. * @returns Newly allocated polynomial container. */ export type CreatePolyFn<P extends PolyStorage<T>, T> = (len: number, elm?: T) => P; /** High-level polynomial helpers layered on top of FFT and field arithmetic. */ export type PolyFn<P extends PolyStorage<T>, T> = { /** Roots-of-unity cache used by the helper namespace. */ roots: RootsOfUnity; /** Factory used to allocate new polynomial containers. */ create: CreatePolyFn<P, T>; /** Optional enforced polynomial length. */ length?: number; /** * Compute the polynomial degree. * @param a - Polynomial coefficients. * @returns Polynomial degree. */ degree: (a: P) => number; /** * Extend or truncate one polynomial to a requested length. * @param a - Polynomial coefficients. * @param len - Target length. * @returns Resized polynomial. */ extend: (a: P, len: number) => P; /** * Add two polynomials coefficient-wise. * @param a - Left polynomial. * @param b - Right polynomial. * @returns Sum polynomial. */ add: (a: P, b: P) => P; /** * Subtract two polynomials coefficient-wise. * @param a - Left polynomial. * @param b - Right polynomial. * @returns Difference polynomial. */ sub: (a: P, b: P) => P; /** * Multiply by another polynomial or by one scalar. * @param a - Left polynomial. * @param b - Right polynomial or scalar. * @returns Product polynomial. */ mul: (a: P, b: P | T) => P; /** * Multiply coefficients point-wise. * @param a - Left polynomial. * @param b - Right polynomial. * @returns Point-wise product polynomial. */ dot: (a: P, b: P) => P; /** * Multiply two polynomials with convolution. * @param a - Left polynomial. * @param b - Right polynomial. * @returns Convolution product. */ convolve: (a: P, b: P) => P; /** * Apply a point-wise coefficient shift by powers of one factor. * @param p - Polynomial coefficients. * @param factor - Shift factor. * @returns Shifted polynomial. */ shift: (p: P, factor: bigint) => P; /** * Clone one polynomial container. * @param a - Polynomial coefficients. * @returns Cloned polynomial. */ clone: (a: P) => P; /** * Evaluate one polynomial on a basis vector. * @param a - Polynomial coefficients. * @param basis - Basis vector. * @returns Evaluated field element. */ eval: (a: P, basis: P) => T; /** Helpers for monomial-basis polynomials. */ monomial: { /** Build the monomial basis vector for one evaluation point. */ basis: (x: T, n: number) => P; /** Evaluate a polynomial in the monomial basis. */ eval: (a: P, x: T) => T; }; /** Helpers for Lagrange-basis polynomials. */ lagrange: { /** Build the Lagrange basis vector for one evaluation point. */ basis: (x: T, n: number, brp?: boolean) => P; /** Evaluate a polynomial in the Lagrange basis. */ eval: (a: P, x: T, brp?: boolean) => T; }; /** * Build the vanishing polynomial for a root set. * @param roots - Root set. * @returns Vanishing polynomial. */ vanishing: (roots: P) => P; }; /** * Poly wants a cracker. * * Polynomials are functions like `y=f(x)`, which means when we multiply two polynomials, result is * function `f3(x) = f1(x) * f2(x)`, we don't multiply values. Key takeaways: * * - **Polynomial** is an array of coefficients: `f(x) = sum(coeff[i] * basis[i](x))` * - **Basis** is array of functions * - **Monominal** is Polynomial where `basis[i](x) == x**i` (powers) * - **Array size** is domain size * - **Lattice** is matrix (Polynomial of Polynomials) * @param field - Field implementation. * @param roots - Roots-of-unity cache. * @param create - Optional polynomial factory. Runtime input validation accepts only plain `Array` * and typed-array polynomial containers; arbitrary structural wrappers are intentionally rejected. * @param fft - Optional FFT implementation. * @param length - Optional fixed polynomial length. * @returns Polynomial helper namespace. * @example * Build polynomial helpers, then convolve two coefficient arrays. * * ```ts * import { poly, rootsOfUnity } from '@noble/curves/abstract/fft.js'; * import { Field } from '@noble/curves/abstract/modular.js'; * const Fp = Field(17n); * const poly17 = poly(Fp, rootsOfUnity(Fp)); * const product = poly17.convolve([1n, 2n], [3n, 4n]); * ``` */ export declare function poly<T>(field: TArg<IField<T>>, roots: RootsOfUnity, create?: undefined, fft?: FFTMethods<T>, length?: number): PolyFn<T[], T>; export declare function poly<T, P extends PolyStorage<T>>(field: TArg<IField<T>>, roots: RootsOfUnity, create: CreatePolyFn<P, T>, fft?: FFTMethods<T>, length?: number): PolyFn<P, T>; //# sourceMappingURL=fft.d.ts.map