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//! This module implements Dlog-based polynomial commitment schema.
//! The following functionality is implemented
//!
//! 1. Commit to polynomial with its max degree
//! 2. Open polynomial commitment batch at the given evaluation point and
//! scaling factor scalar producing the batched opening proof
//! 3. Verify batch of batched opening proofs
use ark_ec::{
models::short_weierstrass::Affine as SWJAffine, short_weierstrass::SWCurveConfig, AffineRepr,
CurveGroup, VariableBaseMSM,
};
use ark_ff::{BigInteger, Field, One, PrimeField, Zero};
use ark_poly::univariate::DensePolynomial;
use ark_serialize::{CanonicalDeserialize, CanonicalSerialize};
use groupmap::{BWParameters, GroupMap};
use mina_poseidon::{sponge::ScalarChallenge, FqSponge};
use o1_utils::{field_helpers::product, ExtendedDensePolynomial as _};
use serde::{de::Visitor, Deserialize, Serialize};
use serde_with::{
de::DeserializeAsWrap, ser::SerializeAsWrap, serde_as, DeserializeAs, SerializeAs,
};
use std::{
iter::Iterator,
marker::PhantomData,
ops::{Add, AddAssign, Sub},
};
/// Represent a polynomial commitment when the type is instantiated with a
/// curve.
///
/// The structure also handles chunking, i.e. when we aim to handle polynomials
/// whose degree is higher than the SRS size. For this reason, we do use a
/// vector for the field `chunks`.
///
/// Note that the parameter `C` is not constrained to be a curve, therefore in
/// some places in the code, `C` can refer to a scalar field element. For
/// instance, `PolyComm<G::ScalarField>` is used to represent the evaluation of the
/// polynomial bound by a specific commitment, at a particular evaluation point.
#[serde_as]
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, Eq)]
#[serde(bound = "C: CanonicalDeserialize + CanonicalSerialize")]
pub struct PolyComm<C> {
#[serde_as(as = "Vec<o1_utils::serialization::SerdeAs>")]
pub chunks: Vec<C>,
}
impl<C> PolyComm<C>
where
C: CommitmentCurve,
{
/// Multiplies each commitment chunk of f with powers of zeta^n
pub fn chunk_commitment(&self, zeta_n: C::ScalarField) -> Self {
let mut res = C::Group::zero();
// use Horner's to compute chunk[0] + z^n chunk[1] + z^2n chunk[2] + ...
// as ( chunk[-1] * z^n + chunk[-2] ) * z^n + chunk[-3]
// (https://en.wikipedia.org/wiki/Horner%27s_method)
for chunk in self.chunks.iter().rev() {
res *= zeta_n;
res.add_assign(chunk);
}
PolyComm {
chunks: vec![res.into_affine()],
}
}
}
impl<F> PolyComm<F>
where
F: Field,
{
/// Multiplies each blinding chunk of f with powers of zeta^n
pub fn chunk_blinding(&self, zeta_n: F) -> F {
let mut res = F::zero();
// use Horner's to compute chunk[0] + z^n chunk[1] + z^2n chunk[2] + ...
// as ( chunk[-1] * z^n + chunk[-2] ) * z^n + chunk[-3]
// (https://en.wikipedia.org/wiki/Horner%27s_method)
for chunk in self.chunks.iter().rev() {
res *= zeta_n;
res += chunk
}
res
}
}
impl<'a, G> IntoIterator for &'a PolyComm<G> {
type Item = &'a G;
type IntoIter = std::slice::Iter<'a, G>;
fn into_iter(self) -> Self::IntoIter {
self.chunks.iter()
}
}
/// A commitment to a polynomial with some blinding factors.
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct BlindedCommitment<G>
where
G: CommitmentCurve,
{
pub commitment: PolyComm<G>,
pub blinders: PolyComm<G::ScalarField>,
}
impl<T> PolyComm<T> {
pub fn new(chunks: Vec<T>) -> Self {
Self { chunks }
}
}
impl<T, U> SerializeAs<PolyComm<T>> for PolyComm<U>
where
U: SerializeAs<T>,
{
fn serialize_as<S>(source: &PolyComm<T>, serializer: S) -> Result<S::Ok, S::Error>
where
S: serde::Serializer,
{
serializer.collect_seq(
source
.chunks
.iter()
.map(|e| SerializeAsWrap::<T, U>::new(e)),
)
}
}
impl<'de, T, U> DeserializeAs<'de, PolyComm<T>> for PolyComm<U>
where
U: DeserializeAs<'de, T>,
{
fn deserialize_as<D>(deserializer: D) -> Result<PolyComm<T>, D::Error>
where
D: serde::Deserializer<'de>,
{
struct SeqVisitor<T, U> {
marker: PhantomData<(T, U)>,
}
impl<'de, T, U> Visitor<'de> for SeqVisitor<T, U>
where
U: DeserializeAs<'de, T>,
{
type Value = PolyComm<T>;
fn expecting(&self, formatter: &mut core::fmt::Formatter<'_>) -> core::fmt::Result {
formatter.write_str("a sequence")
}
fn visit_seq<A>(self, mut seq: A) -> Result<Self::Value, A::Error>
where
A: serde::de::SeqAccess<'de>,
{
#[allow(clippy::redundant_closure_call)]
let mut chunks = vec![];
while let Some(value) = seq
.next_element()?
.map(|v: DeserializeAsWrap<T, U>| v.into_inner())
{
chunks.push(value);
}
Ok(PolyComm::new(chunks))
}
}
let visitor = SeqVisitor::<T, U> {
marker: PhantomData,
};
deserializer.deserialize_seq(visitor)
}
}
impl<A: Copy + Clone + CanonicalDeserialize + CanonicalSerialize> PolyComm<A> {
pub fn map<B, F>(&self, mut f: F) -> PolyComm<B>
where
F: FnMut(A) -> B,
B: CanonicalDeserialize + CanonicalSerialize,
{
let chunks = self.chunks.iter().map(|x| f(*x)).collect();
PolyComm::new(chunks)
}
/// Returns the number of chunks.
pub fn len(&self) -> usize {
self.chunks.len()
}
/// Returns `true` if the commitment is empty.
pub fn is_empty(&self) -> bool {
self.chunks.is_empty()
}
// TODO: if all callers end up calling unwrap, just call this zip_eq and
// panic here (and document the panic)
pub fn zip<B: Copy + CanonicalDeserialize + CanonicalSerialize>(
&self,
other: &PolyComm<B>,
) -> Option<PolyComm<(A, B)>> {
if self.chunks.len() != other.chunks.len() {
return None;
}
let chunks = self
.chunks
.iter()
.zip(other.chunks.iter())
.map(|(x, y)| (*x, *y))
.collect();
Some(PolyComm::new(chunks))
}
/// Return only the first chunk
/// Getting this single value is relatively common in the codebase, even
/// though we should not do this, and abstract the chunks in the structure.
pub fn get_first_chunk(&self) -> A {
self.chunks[0]
}
}
/// Inside the circuit, we have a specialized scalar multiplication which computes
/// either
///
/// ```ignore
/// |g: G, x: G::ScalarField| g.scale(x + 2^n)
/// ```
///
/// if the scalar field of G is greater than the size of the base field
/// and
///
/// ```ignore
/// |g: G, x: G::ScalarField| g.scale(2*x + 2^n)
/// ```
///
/// otherwise. So, if we want to actually scale by `x`, we need to apply the
/// inverse function of `|x| x + 2^n` (or of `|x| 2*x + 2^n` in the other case),
/// before supplying the scalar to our in-circuit scalar-multiplication
/// function. This computes that inverse function.
/// Namely,
///
/// ```ignore
/// |x: G::ScalarField| x - 2^n
/// ```
///
/// when the scalar field is larger than the base field and
///
/// ```ignore
/// |x: G::ScalarField| (x - 2^n) / 2
/// ```
///
/// in the other case.
pub fn shift_scalar<G: AffineRepr>(x: G::ScalarField) -> G::ScalarField
where
G::BaseField: PrimeField,
{
let n1 = <G::ScalarField as PrimeField>::MODULUS;
let n2 = <G::ScalarField as PrimeField>::BigInt::from_bits_le(
&<G::BaseField as PrimeField>::MODULUS.to_bits_le()[..],
);
let two: G::ScalarField = (2u64).into();
let two_pow = two.pow([<G::ScalarField as PrimeField>::MODULUS_BIT_SIZE as u64]);
if n1 < n2 {
(x - (two_pow + G::ScalarField::one())) / two
} else {
x - two_pow
}
}
impl<'a, 'b, C: AffineRepr> Add<&'a PolyComm<C>> for &'b PolyComm<C> {
type Output = PolyComm<C>;
fn add(self, other: &'a PolyComm<C>) -> PolyComm<C> {
let mut chunks = vec![];
let n1 = self.chunks.len();
let n2 = other.chunks.len();
for i in 0..std::cmp::max(n1, n2) {
let pt = if i < n1 && i < n2 {
(self.chunks[i] + other.chunks[i]).into_affine()
} else if i < n1 {
self.chunks[i]
} else {
other.chunks[i]
};
chunks.push(pt);
}
PolyComm::new(chunks)
}
}
impl<'a, 'b, C: AffineRepr + Sub<Output = C::Group>> Sub<&'a PolyComm<C>> for &'b PolyComm<C> {
type Output = PolyComm<C>;
fn sub(self, other: &'a PolyComm<C>) -> PolyComm<C> {
let mut chunks = vec![];
let n1 = self.chunks.len();
let n2 = other.chunks.len();
for i in 0..std::cmp::max(n1, n2) {
let pt = if i < n1 && i < n2 {
(self.chunks[i] - other.chunks[i]).into_affine()
} else if i < n1 {
self.chunks[i]
} else {
other.chunks[i]
};
chunks.push(pt);
}
PolyComm::new(chunks)
}
}
impl<C: AffineRepr> PolyComm<C> {
pub fn scale(&self, c: C::ScalarField) -> PolyComm<C> {
PolyComm {
chunks: self.chunks.iter().map(|g| g.mul(c).into_affine()).collect(),
}
}
/// Performs a multi-scalar multiplication between scalars `elm` and commitments `com`.
/// If both are empty, returns a commitment of length 1 containing the point at infinity.
///
/// ## Panics
///
/// Panics if `com` and `elm` are not of the same size.
pub fn multi_scalar_mul(com: &[&PolyComm<C>], elm: &[C::ScalarField]) -> Self {
assert_eq!(com.len(), elm.len());
if com.is_empty() || elm.is_empty() {
return Self::new(vec![C::zero()]);
}
let all_scalars: Vec<_> = elm.iter().map(|s| s.into_bigint()).collect();
let elems_size = Iterator::max(com.iter().map(|c| c.chunks.len())).unwrap();
let mut chunks = Vec::with_capacity(elems_size);
for chunk in 0..elems_size {
let (points, scalars): (Vec<_>, Vec<_>) = com
.iter()
.zip(&all_scalars)
// get rid of scalars that don't have an associated chunk
.filter_map(|(com, scalar)| com.chunks.get(chunk).map(|c| (c, scalar)))
.unzip();
let chunk_msm = C::Group::msm_bigint(&points, &scalars);
chunks.push(chunk_msm.into_affine());
}
Self::new(chunks)
}
}
/// Returns (1 + chal[-1] x)(1 + chal[-2] x^2)(1 + chal[-3] x^4) ...
/// It's "step 8: Define the univariate polynomial" of
/// appendix A.2 of <https://eprint.iacr.org/2020/499>
pub fn b_poly<F: Field>(chals: &[F], x: F) -> F {
let k = chals.len();
let mut pow_twos = vec![x];
for i in 1..k {
pow_twos.push(pow_twos[i - 1].square());
}
product((0..k).map(|i| (F::one() + (chals[i] * pow_twos[k - 1 - i]))))
}
pub fn b_poly_coefficients<F: Field>(chals: &[F]) -> Vec<F> {
let rounds = chals.len();
let s_length = 1 << rounds;
let mut s = vec![F::one(); s_length];
let mut k: usize = 0;
let mut pow: usize = 1;
for i in 1..s_length {
k += if i == pow { 1 } else { 0 };
pow <<= if i == pow { 1 } else { 0 };
s[i] = s[i - (pow >> 1)] * chals[rounds - 1 - (k - 1)];
}
s
}
pub fn squeeze_prechallenge<Fq: Field, G, Fr: Field, EFqSponge: FqSponge<Fq, G, Fr>>(
sponge: &mut EFqSponge,
) -> ScalarChallenge<Fr> {
ScalarChallenge(sponge.challenge())
}
pub fn squeeze_challenge<Fq: Field, G, Fr: PrimeField, EFqSponge: FqSponge<Fq, G, Fr>>(
endo_r: &Fr,
sponge: &mut EFqSponge,
) -> Fr {
squeeze_prechallenge(sponge).to_field(endo_r)
}
pub fn absorb_commitment<Fq: Field, G: Clone, Fr: PrimeField, EFqSponge: FqSponge<Fq, G, Fr>>(
sponge: &mut EFqSponge,
commitment: &PolyComm<G>,
) {
sponge.absorb_g(&commitment.chunks);
}
/// A useful trait extending AffineRepr for commitments.
/// Unfortunately, we can't specify that `AffineRepr<BaseField : PrimeField>`,
/// so usage of this traits must manually bind `G::BaseField: PrimeField`.
pub trait CommitmentCurve: AffineRepr + Sub<Output = Self::Group> {
type Params: SWCurveConfig;
type Map: GroupMap<Self::BaseField>;
fn to_coordinates(&self) -> Option<(Self::BaseField, Self::BaseField)>;
fn of_coordinates(x: Self::BaseField, y: Self::BaseField) -> Self;
}
/// A trait extending CommitmentCurve for endomorphisms.
/// Unfortunately, we can't specify that `AffineRepr<BaseField : PrimeField>`,
/// so usage of this traits must manually bind `G::BaseField: PrimeField`.
pub trait EndoCurve: CommitmentCurve {
/// Combine where x1 = one
fn combine_one(g1: &[Self], g2: &[Self], x2: Self::ScalarField) -> Vec<Self> {
crate::combine::window_combine(g1, g2, Self::ScalarField::one(), x2)
}
/// Combine where x1 = one
fn combine_one_endo(
endo_r: Self::ScalarField,
_endo_q: Self::BaseField,
g1: &[Self],
g2: &[Self],
x2: ScalarChallenge<Self::ScalarField>,
) -> Vec<Self> {
crate::combine::window_combine(g1, g2, Self::ScalarField::one(), x2.to_field(&endo_r))
}
fn combine(
g1: &[Self],
g2: &[Self],
x1: Self::ScalarField,
x2: Self::ScalarField,
) -> Vec<Self> {
crate::combine::window_combine(g1, g2, x1, x2)
}
}
impl<P: SWCurveConfig + Clone> CommitmentCurve for SWJAffine<P> {
type Params = P;
type Map = BWParameters<P>;
fn to_coordinates(&self) -> Option<(Self::BaseField, Self::BaseField)> {
if self.infinity {
None
} else {
Some((self.x, self.y))
}
}
fn of_coordinates(x: P::BaseField, y: P::BaseField) -> SWJAffine<P> {
SWJAffine::<P>::new_unchecked(x, y)
}
}
impl<P: SWCurveConfig + Clone> EndoCurve for SWJAffine<P> {
fn combine_one(g1: &[Self], g2: &[Self], x2: Self::ScalarField) -> Vec<Self> {
crate::combine::affine_window_combine_one(g1, g2, x2)
}
fn combine_one_endo(
_endo_r: Self::ScalarField,
endo_q: Self::BaseField,
g1: &[Self],
g2: &[Self],
x2: ScalarChallenge<Self::ScalarField>,
) -> Vec<Self> {
crate::combine::affine_window_combine_one_endo(endo_q, g1, g2, x2)
}
fn combine(
g1: &[Self],
g2: &[Self],
x1: Self::ScalarField,
x2: Self::ScalarField,
) -> Vec<Self> {
crate::combine::affine_window_combine(g1, g2, x1, x2)
}
}
/// Computes the linearization of the evaluations of a (potentially
/// split) polynomial.
///
/// Each polynomial in `polys` is represented by a matrix where the
/// rows correspond to evaluated points, and the columns represent
/// potential segments (if a polynomial was split in several parts).
///
/// Elements in `evaluation_points` are several discrete points on which
/// we evaluate polynomials, e.g. `[zeta,zeta*w]`. See `PointEvaluations`.
///
/// Note that if one of the polynomial comes specified with a degree
/// bound, the evaluation for the last segment is potentially shifted
/// to meet the proof.
///
/// Returns
/// ```text
/// |polys| |segments[k]|
/// Σ Σ polyscale^{k*n+i} (Σ polys[k][j][i] * evalscale^j)
/// k = 1 i = 1 j
/// ```
#[allow(clippy::type_complexity)]
pub fn combined_inner_product<F: PrimeField>(
polyscale: &F,
evalscale: &F,
// TODO(mimoo): needs a type that can get you evaluations or segments
polys: &[Vec<Vec<F>>],
) -> F {
// final combined evaluation result
let mut res = F::zero();
// polyscale^i
let mut xi_i = F::one();
for evals_tr in polys.iter().filter(|evals_tr| !evals_tr[0].is_empty()) {
// Transpose the evaluations.
// evals[i] = {evals_tr[j][i]}_j now corresponds to a column in evals_tr,
// representing a segment.
let evals: Vec<_> = (0..evals_tr[0].len())
.map(|i| evals_tr.iter().map(|v| v[i]).collect::<Vec<_>>())
.collect();
// Iterating over the polynomial segments.
// Each segment gets its own polyscale^i, each segment element j is multiplied by evalscale^j.
// Given that xi_i = polyscale^i0 at this point, after this loop we have:
//
// res += Σ polyscale^{i0+i} ( Σ evals_tr[j][i] * evalscale^j )
// i j
//
for eval in &evals {
// p_i(evalscale)
let term = DensePolynomial::<F>::eval_polynomial(eval, *evalscale);
res += &(xi_i * term);
xi_i *= polyscale;
}
}
res
}
/// Contains the evaluation of a polynomial commitment at a set of points.
pub struct Evaluation<G>
where
G: AffineRepr,
{
/// The commitment of the polynomial being evaluated.
/// Note that PolyComm contains a vector of commitments, which handles the
/// case when chunking is used, i.e. when the polynomial degree is higher
/// than the SRS size.
pub commitment: PolyComm<G>,
/// Contains an evaluation table. For instance, for vanilla PlonK, it
/// would be a vector of (chunked) evaluations at ζ and ζω.
/// The outer vector would be the evaluations at the different points (e.g.
/// ζ and ζω for vanilla PlonK) and the inner vector would be the chunks of
/// the polynomial.
pub evaluations: Vec<Vec<G::ScalarField>>,
}
/// Contains the batch evaluation
pub struct BatchEvaluationProof<'a, G, EFqSponge, OpeningProof>
where
G: AffineRepr,
EFqSponge: FqSponge<G::BaseField, G, G::ScalarField>,
{
/// Sponge used to coin and absorb values and simulate
/// non-interactivity using the Fiat-Shamir transformation.
pub sponge: EFqSponge,
/// A list of evaluations, each supposed to correspond to a different
/// polynomial.
pub evaluations: Vec<Evaluation<G>>,
/// The actual evaluation points. Each field `evaluations` of each structure
/// of `Evaluation` should have the same (outer) length.
pub evaluation_points: Vec<G::ScalarField>,
/// A challenge to combine polynomials. Powers of this point will be used,
/// hence the name.
pub polyscale: G::ScalarField,
/// A challenge to aggregate multiple evaluation points.
pub evalscale: G::ScalarField,
/// The opening proof.
pub opening: &'a OpeningProof,
pub combined_inner_product: G::ScalarField,
}
/// This function populates the parameters `scalars` and `points`.
/// It iterates over the evaluations and adds each commitment to the
/// vector `points`.
/// The parameter `scalars` is populated with the values:
/// `rand_base * polyscale^i` for each commitment.
/// For instance, if we have 3 commitments, the `scalars` vector will
/// contain the values
/// ```text
/// [rand_base, rand_base * polyscale, rand_base * polyscale^2]`
/// ```
/// and the vector `points` will contain the commitments.
///
/// Note that the function skips the commitments that are empty.
///
/// If more than one commitment is present in a single evaluation (i.e. if
/// `elems` is larger than one), it means that probably chunking was used (i.e.
/// it is a commitment to a polynomial larger than the SRS).
pub fn combine_commitments<G: CommitmentCurve>(
evaluations: &[Evaluation<G>],
scalars: &mut Vec<G::ScalarField>,
points: &mut Vec<G>,
polyscale: G::ScalarField,
rand_base: G::ScalarField,
) {
// will contain the power of polyscale
let mut xi_i = G::ScalarField::one();
for Evaluation { commitment, .. } in evaluations.iter().filter(|x| !x.commitment.is_empty()) {
// iterating over the polynomial segments
for comm_ch in &commitment.chunks {
scalars.push(rand_base * xi_i);
points.push(*comm_ch);
// compute next power of polyscale
xi_i *= polyscale;
}
}
}
#[cfg(feature = "ocaml_types")]
pub mod caml {
// polynomial commitment
use super::PolyComm;
use ark_ec::AffineRepr;
#[derive(Clone, Debug, ocaml::IntoValue, ocaml::FromValue, ocaml_gen::Struct)]
pub struct CamlPolyComm<CamlG> {
pub unshifted: Vec<CamlG>,
pub shifted: Option<CamlG>,
}
// handy conversions
impl<G, CamlG> From<PolyComm<G>> for CamlPolyComm<CamlG>
where
G: AffineRepr,
CamlG: From<G>,
{
fn from(polycomm: PolyComm<G>) -> Self {
Self {
unshifted: polycomm.chunks.into_iter().map(CamlG::from).collect(),
shifted: None,
}
}
}
impl<'a, G, CamlG> From<&'a PolyComm<G>> for CamlPolyComm<CamlG>
where
G: AffineRepr,
CamlG: From<G> + From<&'a G>,
{
fn from(polycomm: &'a PolyComm<G>) -> Self {
Self {
unshifted: polycomm.chunks.iter().map(Into::<CamlG>::into).collect(),
shifted: None,
}
}
}
impl<G, CamlG> From<CamlPolyComm<CamlG>> for PolyComm<G>
where
G: AffineRepr + From<CamlG>,
{
fn from(camlpolycomm: CamlPolyComm<CamlG>) -> PolyComm<G> {
assert!(
camlpolycomm.shifted.is_none(),
"mina#14628: Shifted commitments are deprecated and must not be used"
);
PolyComm {
chunks: camlpolycomm
.unshifted
.into_iter()
.map(Into::<G>::into)
.collect(),
}
}
}
impl<'a, G, CamlG> From<&'a CamlPolyComm<CamlG>> for PolyComm<G>
where
G: AffineRepr + From<&'a CamlG> + From<CamlG>,
{
fn from(camlpolycomm: &'a CamlPolyComm<CamlG>) -> PolyComm<G> {
assert!(
camlpolycomm.shifted.is_none(),
"mina#14628: Shifted commitments are deprecated and must not be used"
);
PolyComm {
//FIXME something with as_ref()
chunks: camlpolycomm.unshifted.iter().map(Into::into).collect(),
}
}
}
}