sonobe/folding-schemes/src/folding/hypernova/lcccs.rs

use ark_crypto_primitives::{
    crh::{poseidon::CRH, CRHScheme},
    sponge::{poseidon::PoseidonConfig, Absorb},
};
use ark_ec::{CurveGroup, Group};
use ark_ff::PrimeField;
use ark_poly::DenseMultilinearExtension;
use ark_poly::MultilinearExtension;
use ark_std::rand::Rng;
use ark_std::Zero;

use super::Witness;
use crate::arith::ccs::CCS;
use crate::commitment::CommitmentScheme;
use crate::folding::circuits::nonnative::affine::nonnative_affine_to_field_elements;
use crate::utils::mle::dense_vec_to_dense_mle;
use crate::utils::vec::mat_vec_mul;
use crate::Error;

/// Linearized Committed CCS instance
#[derive(Debug, Clone, Eq, PartialEq)]
pub struct LCCCS<C: CurveGroup> {
    // Commitment to witness
    pub C: C,
    // Relaxation factor of z for folded LCCCS
    pub u: C::ScalarField,
    // Public input/output
    pub x: Vec<C::ScalarField>,
    // Random evaluation point for the v_i
    pub r_x: Vec<C::ScalarField>,
    // Vector of v_i
    pub v: Vec<C::ScalarField>,
}

impl<F: PrimeField> CCS<F> {
    pub fn to_lcccs<R: Rng, C: CurveGroup, CS: CommitmentScheme<C>>(
        &self,
        rng: &mut R,
        cs_params: &CS::ProverParams,
        z: &[C::ScalarField],
    ) -> Result<(LCCCS<C>, Witness<C::ScalarField>), Error>
    where
        // enforce that CCS's F is the C::ScalarField
        C: CurveGroup<ScalarField = F>,
    {
        let w: Vec<C::ScalarField> = z[(1 + self.l)..].to_vec();
        // if the commitment scheme is set to be hiding, set the random blinding parameter
        let r_w = if CS::is_hiding() {
            C::ScalarField::rand(rng)
        } else {
            C::ScalarField::zero()
        };
        let C = CS::commit(cs_params, &w, &r_w)?;

        let r_x: Vec<C::ScalarField> = (0..self.s).map(|_| C::ScalarField::rand(rng)).collect();

        let Mzs: Vec<DenseMultilinearExtension<F>> = self
            .M
            .iter()
            .map(|M_j| Ok(dense_vec_to_dense_mle(self.s, &mat_vec_mul(M_j, z)?)))
            .collect::<Result<_, Error>>()?;

        // compute v_j
        let v: Vec<F> = Mzs
            .iter()
            .map(|Mz| Mz.evaluate(&r_x).ok_or(Error::EvaluationFail))
            .collect::<Result<_, Error>>()?;

        Ok((
            LCCCS::<C> {
                C,
                u: C::ScalarField::one(),
                x: z[1..(1 + self.l)].to_vec(),
                r_x,
                v,
            },
            Witness::<C::ScalarField> { w, r_w },
        ))
    }
}

impl<C: CurveGroup> LCCCS<C> {
    pub fn dummy(l: usize, t: usize, s: usize) -> LCCCS<C>
    where
        C::ScalarField: PrimeField,
    {
        LCCCS::<C> {
            C: C::zero(),
            u: C::ScalarField::zero(),
            x: vec![C::ScalarField::zero(); l],
            r_x: vec![C::ScalarField::zero(); s],
            v: vec![C::ScalarField::zero(); t],
        }
    }

    /// Perform the check of the LCCCS instance described at section 4.2,
    /// notice that this method does not check the commitment correctness
    pub fn check_relation(
        &self,
        ccs: &CCS<C::ScalarField>,
        w: &Witness<C::ScalarField>,
    ) -> Result<(), Error> {
        // check CCS relation
        let z: Vec<C::ScalarField> = [vec![self.u], self.x.clone(), w.w.to_vec()].concat();

        let computed_v: Vec<C::ScalarField> = ccs
            .M
            .iter()
            .map(|M_j| {
                let Mz_mle = dense_vec_to_dense_mle(ccs.s, &mat_vec_mul(M_j, &z)?);
                Mz_mle.evaluate(&self.r_x).ok_or(Error::EvaluationFail)
            })
            .collect::<Result<_, Error>>()?;
        if computed_v != self.v {
            return Err(Error::NotSatisfied);
        }
        Ok(())
    }
}

impl<C: CurveGroup> LCCCS<C>
where
    <C as Group>::ScalarField: Absorb,
    <C as ark_ec::CurveGroup>::BaseField: ark_ff::PrimeField,
{
    /// [`LCCCS`].hash implements the committed instance hash compatible with the gadget
    /// implemented in nova/circuits.rs::CommittedInstanceVar.hash.
    /// Returns `H(i, z_0, z_i, U_i)`, where `i` can be `i` but also `i+1`, and `U_i` is the LCCCS.
    pub fn hash(
        &self,
        poseidon_config: &PoseidonConfig<C::ScalarField>,
        pp_hash: C::ScalarField,
        i: C::ScalarField,
        z_0: Vec<C::ScalarField>,
        z_i: Vec<C::ScalarField>,
    ) -> Result<C::ScalarField, Error> {
        let (C_x, C_y) = nonnative_affine_to_field_elements::<C>(self.C)?;

        CRH::<C::ScalarField>::evaluate(
            poseidon_config,
            vec![
                vec![pp_hash, i],
                z_0,
                z_i,
                C_x,
                C_y,
                vec![self.u],
                self.x.clone(),
                self.r_x.clone(),
                self.v.clone(),
            ]
            .concat(),
        )
        .map_err(|e| Error::Other(e.to_string()))
    }
}

#[cfg(test)]
pub mod tests {
    use ark_pallas::{Fr, Projective};
    use ark_std::test_rng;
    use ark_std::One;
    use ark_std::UniformRand;
    use ark_std::Zero;
    use std::sync::Arc;

    use super::*;
    use crate::arith::{
        ccs::tests::{get_test_ccs, get_test_z},
        r1cs::R1CS,
        Arith,
    };
    use crate::commitment::pedersen::Pedersen;
    use crate::utils::hypercube::BooleanHypercube;
    use crate::utils::virtual_polynomial::{build_eq_x_r_vec, VirtualPolynomial};

    // method for testing
    pub fn compute_Ls<C: CurveGroup>(
        ccs: &CCS<C::ScalarField>,
        lcccs: &LCCCS<C>,
        z: &[C::ScalarField],
    ) -> Vec<VirtualPolynomial<C::ScalarField>> {
        let eq_rx = build_eq_x_r_vec(&lcccs.r_x).unwrap();
        let eq_rx_mle = dense_vec_to_dense_mle(ccs.s, &eq_rx);

        let mut Ls = Vec::with_capacity(ccs.t);
        for M_j in ccs.M.iter() {
            let mut L = VirtualPolynomial::<C::ScalarField>::new(ccs.s);
            let mut Mz = vec![dense_vec_to_dense_mle(ccs.s, &mat_vec_mul(M_j, z).unwrap())];
            Mz.push(eq_rx_mle.clone());
            L.add_mle_list(
                Mz.iter().map(|v| Arc::new(v.clone())),
                C::ScalarField::one(),
            )
            .unwrap();
            Ls.push(L);
        }
        Ls
    }

    #[test]
    /// Test linearized CCCS v_j against the L_j(x)
    fn test_lcccs_v_j() {
        let mut rng = test_rng();

        let n_rows = 2_u32.pow(5) as usize;
        let n_cols = 2_u32.pow(5) as usize;
        let r1cs = R1CS::<Fr>::rand(&mut rng, n_rows, n_cols);
        let ccs = CCS::from_r1cs(r1cs);
        let z: Vec<Fr> = (0..n_cols).map(|_| Fr::rand(&mut rng)).collect();

        let (pedersen_params, _) =
            Pedersen::<Projective>::setup(&mut rng, ccs.n - ccs.l - 1).unwrap();

        let (lcccs, _) = ccs
            .to_lcccs::<_, Projective, Pedersen<Projective>>(&mut rng, &pedersen_params, &z)
            .unwrap();
        // with our test vector coming from R1CS, v should have length 3
        assert_eq!(lcccs.v.len(), 3);

        let vec_L_j_x = compute_Ls(&ccs, &lcccs, &z);
        assert_eq!(vec_L_j_x.len(), lcccs.v.len());

        for (v_i, L_j_x) in lcccs.v.into_iter().zip(vec_L_j_x) {
            let sum_L_j_x = BooleanHypercube::new(ccs.s)
                .map(|y| L_j_x.evaluate(&y).unwrap())
                .fold(Fr::zero(), |acc, result| acc + result);
            assert_eq!(v_i, sum_L_j_x);
        }
    }

    /// Given a bad z, check that the v_j should not match with the L_j(x)
    #[test]
    fn test_bad_v_j() {
        let mut rng = test_rng();

        let ccs = get_test_ccs();
        let z = get_test_z(3);
        ccs.check_relation(&z.clone()).unwrap();

        // Mutate z so that the relation does not hold
        let mut bad_z = z.clone();
        bad_z[3] = Fr::zero();
        assert!(ccs.check_relation(&bad_z.clone()).is_err());

        let (pedersen_params, _) =
            Pedersen::<Projective>::setup(&mut rng, ccs.n - ccs.l - 1).unwrap();
        // Compute v_j with the right z
        let (lcccs, _) = ccs
            .to_lcccs::<_, Projective, Pedersen<Projective>>(&mut rng, &pedersen_params, &z)
            .unwrap();
        // with our test vector coming from R1CS, v should have length 3
        assert_eq!(lcccs.v.len(), 3);

        // Bad compute L_j(x) with the bad z
        let vec_L_j_x = compute_Ls(&ccs, &lcccs, &bad_z);
        assert_eq!(vec_L_j_x.len(), lcccs.v.len());

        // Make sure that the LCCCS is not satisfied given these L_j(x)
        // i.e. summing L_j(x) over the hypercube should not give v_j for all j
        let mut satisfied = true;
        for (v_i, L_j_x) in lcccs.v.into_iter().zip(vec_L_j_x) {
            let sum_L_j_x = BooleanHypercube::new(ccs.s)
                .map(|y| L_j_x.evaluate(&y).unwrap())
                .fold(Fr::zero(), |acc, result| acc + result);
            if v_i != sum_L_j_x {
                satisfied = false;
            }
        }
        assert!(!satisfied);
    }
}