eth2.0-specs/specs/eip4844/polynomial-commitments.md

16 KiB

EIP-4844 -- Polynomial Commitments

Table of contents

Introduction

This document specifies basic polynomial operations and KZG polynomial commitment operations as they are needed for the EIP-4844 specification. The implementations are not optimized for performance, but readability. All practical implementations should optimize the polynomial operations.

Functions flagged as "Public method" MUST be provided by the underlying KZG library as public functions. All other functions are private functions used internally by the KZG library.

Custom types

Name SSZ equivalent Description
G1Point Bytes48
G2Point Bytes96
BLSFieldElement uint256 x < BLS_MODULUS
KZGCommitment Bytes48 Same as BLS standard "is valid pubkey" check but also allows 0x00..00 for point-at-infinity
KZGProof Bytes48 Same as for KZGCommitment
Polynomial Vector[BLSFieldElement, FIELD_ELEMENTS_PER_BLOB] a polynomial in evaluation form
Blob ByteVector[BYTES_PER_FIELD_ELEMENT * FIELD_ELEMENTS_PER_BLOB] a basic blob data

Constants

Name Value Notes
BLS_MODULUS 52435875175126190479447740508185965837690552500527637822603658699938581184513 Scalar field modulus of BLS12-381
BYTES_PER_FIELD_ELEMENT uint64(32) Bytes used to encode a BLS scalar field element

Preset

Blob

Name Value
FIELD_ELEMENTS_PER_BLOB uint64(4096)
FIAT_SHAMIR_PROTOCOL_DOMAIN b'FSBLOBVERIFY_V1_'

Crypto

Name Value Notes
ROOTS_OF_UNITY Vector[BLSFieldElement, FIELD_ELEMENTS_PER_BLOB] Roots of unity of order FIELD_ELEMENTS_PER_BLOB over the BLS12-381 field

Trusted setup

The trusted setup is part of the preset: during testing a minimal insecure variant may be used, but reusing the mainnet settings in public networks is a critical security requirement.

Name Value
KZG_SETUP_G2_LENGTH 65
KZG_SETUP_G1 Vector[G1Point, FIELD_ELEMENTS_PER_BLOB], contents TBD
KZG_SETUP_G2 Vector[G2Point, KZG_SETUP_G2_LENGTH], contents TBD
KZG_SETUP_LAGRANGE Vector[KZGCommitment, FIELD_ELEMENTS_PER_BLOB], contents TBD

Helper functions

Bit-reversal permutation

All polynomials (which are always given in Lagrange form) should be interpreted as being in bit-reversal permutation. In practice, clients can implement this by storing the lists KZG_SETUP_LAGRANGE and ROOTS_OF_UNITY in bit-reversal permutation, so these functions only have to be called once at startup.

is_power_of_two

def is_power_of_two(value: int) -> bool:
    """
    Check if ``value`` is a power of two integer.
    """
    return (value > 0) and (value & (value - 1) == 0)

reverse_bits

def reverse_bits(n: int, order: int) -> int:
    """
    Reverse the bit order of an integer ``n``.
    """
    assert is_power_of_two(order)
    # Convert n to binary with the same number of bits as "order" - 1, then reverse its bit order
    return int(('{:0' + str(order.bit_length() - 1) + 'b}').format(n)[::-1], 2)

bit_reversal_permutation

def bit_reversal_permutation(sequence: Sequence[T]) -> Sequence[T]:
    """
    Return a copy with bit-reversed permutation. The permutation is an involution (inverts itself).

    The input and output are a sequence of generic type ``T`` objects.
    """
    return [sequence[reverse_bits(i, len(sequence))] for i in range(len(sequence))]

BLS12-381 helpers

hash_to_bls_field

def hash_to_bls_field(data: bytes) -> BLSFieldElement:
    """
    Hash ``data`` and convert the output to a BLS scalar field element.
    The output is not uniform over the BLS field.
    """
    hashed_data = hash(data)
    return BLSFieldElement(int.from_bytes(hashed_data, ENDIANNESS) % BLS_MODULUS)

bytes_to_bls_field

def bytes_to_bls_field(b: Bytes32) -> BLSFieldElement:
    """
    Convert 32-byte value to a BLS scalar field element.
    This function does not accept inputs greater than the BLS modulus.
    """
    field_element = int.from_bytes(b, ENDIANNESS)
    assert field_element < BLS_MODULUS
    return BLSFieldElement(field_element)

blob_to_polynomial

def blob_to_polynomial(blob: Blob) -> Polynomial:
    """
    Convert a blob to list of BLS field scalars.
    """
    polynomial = Polynomial()
    for i in range(FIELD_ELEMENTS_PER_BLOB):
        value = bytes_to_bls_field(blob[i * BYTES_PER_FIELD_ELEMENT: (i + 1) * BYTES_PER_FIELD_ELEMENT])
        polynomial[i] = value
    return polynomial

compute_challenges

def compute_challenges(polynomials: Sequence[Polynomial],
                       commitments: Sequence[KZGCommitment]) -> Tuple[Sequence[BLSFieldElement], BLSFieldElement]:
    """
    Return the Fiat-Shamir challenges required by the rest of the protocol.
    The Fiat-Shamir logic works as per the following pseudocode:

       hashed_data = hash(DOMAIN_SEPARATOR, polynomials, commitments)
       r = hash(hashed_data, 0)
       r_powers = [1, r, r**2, r**3, ...]
       eval_challenge = hash(hashed_data, 1)

    Then return `r_powers` and `eval_challenge` after converting them to BLS field elements.
    The resulting field elements are not uniform over the BLS field.
    """
    # Append the number of polynomials and the degree of each polynomial as a domain separator
    num_polynomials = int.to_bytes(len(polynomials), 8, ENDIANNESS)
    degree_poly = int.to_bytes(FIELD_ELEMENTS_PER_BLOB, 8, ENDIANNESS)
    data = FIAT_SHAMIR_PROTOCOL_DOMAIN + degree_poly + num_polynomials

    # Append each polynomial which is composed by field elements
    for poly in polynomials:
        for field_element in poly:
            data += int.to_bytes(field_element, BYTES_PER_FIELD_ELEMENT, ENDIANNESS)

    # Append serialized G1 points
    for commitment in commitments:
        data += commitment

    # Transcript has been prepared: time to create the challenges
    hashed_data = hash(data)
    r = hash_to_bls_field(hashed_data + b'\x00')
    r_powers = compute_powers(r, len(commitments))
    eval_challenge = hash_to_bls_field(hashed_data + b'\x01')

    return r_powers, eval_challenge

bls_modular_inverse

def bls_modular_inverse(x: BLSFieldElement) -> BLSFieldElement:
    """
    Compute the modular inverse of x
    i.e. return y such that x * y % BLS_MODULUS == 1 and return 0 for x == 0
    """
    return BLSFieldElement(pow(x, -1, BLS_MODULUS)) if x != 0 else BLSFieldElement(0)

div

def div(x: BLSFieldElement, y: BLSFieldElement) -> BLSFieldElement:
    """
    Divide two field elements: ``x`` by `y``.
    """
    return BLSFieldElement((int(x) * int(bls_modular_inverse(y))) % BLS_MODULUS)

g1_lincomb

def g1_lincomb(points: Sequence[KZGCommitment], scalars: Sequence[BLSFieldElement]) -> KZGCommitment:
    """
    BLS multiscalar multiplication. This function can be optimized using Pippenger's algorithm and variants.
    """
    assert len(points) == len(scalars)
    result = bls.Z1
    for x, a in zip(points, scalars):
        result = bls.add(result, bls.multiply(bls.bytes48_to_G1(x), a))
    return KZGCommitment(bls.G1_to_bytes48(result))

poly_lincomb

def poly_lincomb(polys: Sequence[Polynomial],
                 scalars: Sequence[BLSFieldElement]) -> Polynomial:
    """
    Given a list of ``polynomials``, interpret it as a 2D matrix and compute the linear combination
    of each column with `scalars`: return the resulting polynomials.
    """
    assert len(polys) == len(scalars)
    result = [0] * FIELD_ELEMENTS_PER_BLOB
    for v, s in zip(polys, scalars):
        for i, x in enumerate(v):
            result[i] = (result[i] + int(s) * int(x)) % BLS_MODULUS
    return Polynomial([BLSFieldElement(x) for x in result])

compute_powers

def compute_powers(x: BLSFieldElement, n: uint64) -> Sequence[BLSFieldElement]:
    """
    Return ``x`` to power of [0, n-1], if n > 0. When n==0, an empty array is returned.
    """
    current_power = 1
    powers = []
    for _ in range(n):
        powers.append(BLSFieldElement(current_power))
        current_power = current_power * int(x) % BLS_MODULUS
    return powers

Polynomials

evaluate_polynomial_in_evaluation_form

def evaluate_polynomial_in_evaluation_form(polynomial: Polynomial,
                                           z: BLSFieldElement) -> BLSFieldElement:
    """
    Evaluate a polynomial (in evaluation form) at an arbitrary point ``z`` that is not in the domain.
    Uses the barycentric formula:
       f(z) = (z**WIDTH - 1) / WIDTH  *  sum_(i=0)^WIDTH  (f(DOMAIN[i]) * DOMAIN[i]) / (z - DOMAIN[i])
    """
    width = len(polynomial)
    assert width == FIELD_ELEMENTS_PER_BLOB
    inverse_width = bls_modular_inverse(BLSFieldElement(width))

    # Make sure we won't divide by zero during division
    assert z not in ROOTS_OF_UNITY

    roots_of_unity_brp = bit_reversal_permutation(ROOTS_OF_UNITY)

    result = 0
    for i in range(width):
        a = BLSFieldElement(int(polynomial[i]) * int(roots_of_unity_brp[i]) % BLS_MODULUS)
        b = BLSFieldElement((int(BLS_MODULUS) + int(z) - int(roots_of_unity_brp[i])) % BLS_MODULUS)
        result += int(div(a, b) % BLS_MODULUS)
    result = result * int(pow(z, width, BLS_MODULUS) - 1) * int(inverse_width)
    return BLSFieldElement(result % BLS_MODULUS)

KZG

KZG core functions. These are also defined in EIP-4844 execution specs.

blob_to_kzg_commitment

def blob_to_kzg_commitment(blob: Blob) -> KZGCommitment:
    """
    Public method.
    """
    return g1_lincomb(bit_reversal_permutation(KZG_SETUP_LAGRANGE), blob_to_polynomial(blob))

verify_kzg_proof

def verify_kzg_proof(polynomial_kzg: KZGCommitment,
                     z: Bytes32,
                     y: Bytes32,
                     kzg_proof: KZGProof) -> bool:
    """
    Verify KZG proof that ``p(z) == y`` where ``p(z)`` is the polynomial represented by ``polynomial_kzg``.
    Receives inputs as bytes.
    Public method.
    """
    return verify_kzg_proof_impl(polynomial_kzg, bytes_to_bls_field(z), bytes_to_bls_field(y), kzg_proof)

verify_kzg_proof_impl

def verify_kzg_proof_impl(polynomial_kzg: KZGCommitment,
                          z: BLSFieldElement,
                          y: BLSFieldElement,
                          kzg_proof: KZGProof) -> bool:
    """
    Verify KZG proof that ``p(z) == y`` where ``p(z)`` is the polynomial represented by ``polynomial_kzg``.
    """
    # Verify: P - y = Q * (X - z)
    X_minus_z = bls.add(bls.bytes96_to_G2(KZG_SETUP_G2[1]), bls.multiply(bls.G2, BLS_MODULUS - z))
    P_minus_y = bls.add(bls.bytes48_to_G1(polynomial_kzg), bls.multiply(bls.G1, BLS_MODULUS - y))
    return bls.pairing_check([
        [P_minus_y, bls.neg(bls.G2)],
        [bls.bytes48_to_G1(kzg_proof), X_minus_z]
    ])

compute_kzg_proof

def compute_kzg_proof(polynomial: Polynomial, z: BLSFieldElement) -> KZGProof:
    """
    Compute KZG proof at point `z` with `polynomial` being in evaluation form.
    Do this by computing the quotient polynomial in evaluation form: q(x) = (p(x) - p(z)) / (x - z).
    Public method.
    """
    y = evaluate_polynomial_in_evaluation_form(polynomial, z)
    polynomial_shifted = [BLSFieldElement((int(p) - int(y)) % BLS_MODULUS) for p in polynomial]

    # Make sure we won't divide by zero during division
    assert z not in ROOTS_OF_UNITY
    denominator_poly = [BLSFieldElement((int(x) - int(z)) % BLS_MODULUS)
                        for x in bit_reversal_permutation(ROOTS_OF_UNITY)]

    # Calculate quotient polynomial by doing point-by-point division
    quotient_polynomial = [div(a, b) for a, b in zip(polynomial_shifted, denominator_poly)]
    return KZGProof(g1_lincomb(bit_reversal_permutation(KZG_SETUP_LAGRANGE), quotient_polynomial))

compute_aggregated_poly_and_commitment

def compute_aggregated_poly_and_commitment(
        blobs: Sequence[Blob],
        kzg_commitments: Sequence[KZGCommitment]) -> Tuple[Polynomial, KZGCommitment, BLSFieldElement]:
    """
    Return (1) the aggregated polynomial, (2) the aggregated KZG commitment,
    and (3) the polynomial evaluation random challenge.
    This function should also work with blobs == [] and kzg_commitments == []
    """
    assert len(blobs) == len(kzg_commitments)

    # Convert blobs to polynomials
    polynomials = [blob_to_polynomial(blob) for blob in blobs]

    # Generate random linear combination and evaluation challenges
    r_powers, evaluation_challenge = compute_challenges(polynomials, kzg_commitments)

    # Create aggregated polynomial in evaluation form
    aggregated_poly = poly_lincomb(polynomials, r_powers)

    # Compute commitment to aggregated polynomial
    aggregated_poly_commitment = KZGCommitment(g1_lincomb(kzg_commitments, r_powers))

    return aggregated_poly, aggregated_poly_commitment, evaluation_challenge

compute_aggregate_kzg_proof

def compute_aggregate_kzg_proof(blobs: Sequence[Blob]) -> KZGProof:
    """
    Given a list of blobs, return the aggregated KZG proof that is used to verify them against their commitments.
    Public method.
    """
    commitments = [blob_to_kzg_commitment(blob) for blob in blobs]
    aggregated_poly, aggregated_poly_commitment, evaluation_challenge = compute_aggregated_poly_and_commitment(
        blobs,
        commitments
    )
    return compute_kzg_proof(aggregated_poly, evaluation_challenge)

verify_aggregate_kzg_proof

def verify_aggregate_kzg_proof(blobs: Sequence[Blob],
                               expected_kzg_commitments: Sequence[KZGCommitment],
                               kzg_aggregated_proof: KZGProof) -> bool:
    """
    Given a list of blobs and an aggregated KZG proof, verify that they correspond to the provided commitments.

    Public method.
    """
    aggregated_poly, aggregated_poly_commitment, evaluation_challenge = compute_aggregated_poly_and_commitment(
        blobs,
        expected_kzg_commitments,
    )

    # Evaluate aggregated polynomial at `evaluation_challenge` (evaluation function checks for div-by-zero)
    y = evaluate_polynomial_in_evaluation_form(aggregated_poly, evaluation_challenge)

    # Verify aggregated proof
    return verify_kzg_proof_impl(aggregated_poly_commitment, evaluation_challenge, y, kzg_aggregated_proof)