implement K(X) & G(X) computation. Folding works

- implement G(X) & K(X) computation
- update e* and phi* usage of L_i(X)
- extend readme.md

with this commit, prover & verifier folding works, and outputed
instances satisfy the relation check.

README.md

@@ -5,3 +5,76 @@ Proof of concept implementation of ProtoGalaxy (https://eprint.iacr.org/2023/110
 > Do not use in production.
 
 Thanks to [Liam Eagen](https://twitter.com/LiamEagen) and [Ariel Gabizon](https://twitter.com/rel_zeta_tech) for their kind explanations.
+
+This code has been done in the context of the research on folding schemes in [0xPARC](https://0xparc.org).
+
+![protogalaxy img from Wikipedia](https://upload.wikimedia.org/wikipedia/commons/thumb/4/49/Stellar_Fireworks_Finale.jpg/303px-Stellar_Fireworks_Finale.jpg)
+
+(img: protogalaxies colliding, [from Wikipedia](https://en.wikipedia.org/wiki/File:Stellar_Fireworks_Finale.jpg))
+
+## Details
+Implementation of ProtoGalaxy's scheme described in section 4 of the paper.
+
+Current version implements the folding on prover & verifier and it works, but it is not optimized.
+Next steps in terms of implementation include: F(X) O(n) construction following Claim 4.4, compute K(X) in O(kd log(kd)M + ndkC) as described in Claim 4.5, add tests folding in multiple iterations and also in a tree approach, add the decider and integrate with some existing R1CS tooling for the R1CS & witness generation.
+
+### Usage
+
+Example of folding k+1 instances:
+```rust
+// assume we have:
+// an R1CS instance 'r1cs'
+// a valid witness 'w' from our running instance
+// k valid 'witnesses' to be fold
+
+// compute the committed instance for our running witness
+let phi = Pedersen::<G1Projective>::commit(&pedersen_params, &witness.w, &witness.r_w);
+let instance = CommittedInstance::<G1Projective> {
+    phi,
+    betas: betas.clone(),
+    e: Fr::zero(),
+};
+
+// compute the k committed instances to be fold
+let mut instances: Vec<CommittedInstance<G1Projective>> = Vec::new();
+for i in 0..k {
+    let phi_i =
+	Pedersen::<G1Projective>::commit(&pedersen_params, &witnesses[i].w, &witnesses[i].r_w);
+    let instance_i = CommittedInstance::<G1Projective> {
+	phi: phi_i,
+	betas: betas.clone(),
+	e: Fr::zero(),
+    };
+    witnesses.push(witness_i);
+    instances.push(instance_i);
+}
+
+// set the initial random betas
+let beta = Fr::rand(&mut rng);
+let betas = powers_of_beta(beta, t);
+
+// Prover folds the instances and witnesses
+let (F_coeffs, K_coeffs, folded_instance, folded_witness) = Folding::<G1Projective>::prover(
+    &mut transcript_p,
+    &r1cs,
+    instance.clone(),
+    witness,
+    instances.clone(),
+    witnesses,
+);
+
+// verifier folds the instances
+let folded_instance_v = Folding::<G1Projective>::verifier(
+    &mut transcript_v,
+    &r1cs,
+    instance,
+    instances,
+    F_coeffs,
+    K_coeffs,
+);
+
+// check that the folded instance satisfies the relation
+assert!(check_instance(&r2cs, folded_instance, folded_witness));
+
+```
+(see the actual code for more details)

src/lib.rs

@@ -1,7 +1,7 @@
 #![allow(non_snake_case)]
 #![allow(non_upper_case_globals)]
-#![allow(unused)] // TMP
-#![allow(dead_code)] // TMP
+// #![allow(unused)] // TMP
+// #![allow(dead_code)] // TMP
 
 pub mod pedersen;
 pub mod protogalaxy;

src/pedersen.rs

@@ -1,4 +1,4 @@
-/// pedersen.rs file and adapted from https://github.com/arnaucube/nova-study
+/// pedersen.rs file adapted from https://github.com/arnaucube/nova-study
 use ark_ec::{CurveGroup, Group};
 use ark_std::{
     rand::{Rng, RngCore},

src/protogalaxy.rs

@@ -2,17 +2,16 @@ use ark_crypto_primitives::sponge::Absorb;
 use ark_ec::{CurveGroup, Group};
 use ark_ff::fields::PrimeField;
 use ark_std::log2;
-use ark_std::{cfg_into_iter, One, Zero};
+use ark_std::{cfg_into_iter, Zero};
 use std::marker::PhantomData;
-use std::ops::{Add, Mul};
+use std::ops::Add;
 
-use ark_ff::{batch_inversion, FftField};
 use ark_poly::{
     univariate::{DensePolynomial, SparsePolynomial},
     DenseUVPolynomial, EvaluationDomain, Evaluations, GeneralEvaluationDomain, Polynomial,
 };
 
-use crate::pedersen::{Commitment, Params as PedersenParams, Pedersen, Proof as PedersenProof};
+use crate::pedersen::Commitment;
 use crate::transcript::Transcript;
 use crate::utils::*;
 
@@ -40,8 +39,7 @@ where
 {
     // WIP naming of functions
     pub fn prover(
-        tr: &mut Transcript<C::ScalarField, C>,
-        pedersen_params: &PedersenParams<C>,
+        transcript: &mut Transcript<C::ScalarField, C>,
         r1cs: &R1CS<C::ScalarField>,
         // running instance
         instance: CommittedInstance<C>,
@@ -57,13 +55,14 @@ where
     ) {
         let t = instance.betas.len();
         let n = r1cs.A[0].len();
+        assert_eq!(w.w.len(), n);
+        assert_eq!(log2(n) as usize, t);
 
         // TODO initialize transcript
-        let delta = tr.get_challenge();
+        let delta = transcript.get_challenge();
         let deltas = powers_of_beta(delta, t);
 
-        let f_w = eval_f(&r1cs, &w.w);
-        // println!("is f(w) {:?}", f_w);
+        let f_w = eval_f(r1cs, &w.w);
 
         // F(X)
         let mut F_X: SparsePolynomial<C::ScalarField> = SparsePolynomial::zero();
@@ -74,9 +73,9 @@ where
         }
 
         let F_X_dense = DensePolynomial::from(F_X.clone());
-        tr.add_vec(&F_X_dense.coeffs);
+        transcript.add_vec(&F_X_dense.coeffs);
 
-        let alpha = tr.get_challenge();
+        let alpha = transcript.get_challenge();
 
         // eval F(alpha)
         let F_alpha = F_X.evaluate(&alpha);
@@ -106,31 +105,78 @@ where
             w.clone(),
         ));
 
-        let gamma = tr.get_challenge();
+        let gamma = transcript.get_challenge();
 
-        // TODO WIP compute G(X) & K(X)
-        let G_evals: Vec<C::ScalarField> = vec![C::ScalarField::zero(); n];
-        let G_X: DensePolynomial<C::ScalarField> =
-            Evaluations::<C::ScalarField>::from_vec_and_domain(G_evals.clone(), H).interpolate();
-        // dbg!(&G_X);
-        let (K_X, remainder) = G_X.divide_by_vanishing_poly(H).unwrap();
-        // dbg!(&K_X);
-        assert!(remainder.is_zero());
+        let mut ws: Vec<Vec<C::ScalarField>> = Vec::new();
+        ws.push(w.w.clone());
+        for wj in vec_w.iter() {
+            assert_eq!(wj.w.len(), n);
+            ws.push(wj.w.clone());
+        }
+
+        let k = vec_instances.len();
+        let H = GeneralEvaluationDomain::<C::ScalarField>::new(k + 1).unwrap();
+        let EH = GeneralEvaluationDomain::<C::ScalarField>::new(t * k + 1).unwrap();
+        let L_X: Vec<DensePolynomial<C::ScalarField>> = lagrange_polys(H);
+
+        // K(X) computation in a naive way, next iterations will compute K(X) as described in Claim
+        // 4.5 of the paper.
+        let mut G_evals: Vec<C::ScalarField> = vec![C::ScalarField::zero(); EH.size()];
+        for (hi, h) in EH.elements().enumerate() {
+            // each iteration evaluates G(h)
+            // inner = L_0(x) * w + \sum_k L_i(x) * w_j
+            let mut inner: Vec<C::ScalarField> = vec![C::ScalarField::zero(); ws[0].len()];
+            for (i, w) in ws.iter().enumerate() {
+                // Li_w = Li(X) * wj
+                let mut Li_w: Vec<DensePolynomial<C::ScalarField>> =
+                    vec![DensePolynomial::<C::ScalarField>::zero(); w.len()];
+                for (j, wj) in w.iter().enumerate() {
+                    let Li_wj = &L_X[i] * *wj;
+                    Li_w[j] = Li_wj;
+                }
+                // Li_w_h = Li_w(h) = Li(h) * wj
+                let mut Liw_h: Vec<C::ScalarField> = vec![C::ScalarField::zero(); w.len()];
+                for (j, _) in Li_w.iter().enumerate() {
+                    Liw_h[j] = Li_w[j].evaluate(&h);
+                }
+
+                for j in 0..inner.len() {
+                    inner[j] += Liw_h[j];
+                }
+            }
+            let f_ev = eval_f(r1cs, &inner);
 
+            let mut Gsum = C::ScalarField::zero();
+            for i in 0..n {
+                let pow_i_betas = pow_i(i, &betas_star);
+                let curr = pow_i_betas * f_ev[i];
+                Gsum += curr;
+            }
+            // G_evals[hi] = Gsum / Z_X.evaluate(&h); // WIP
+            G_evals[hi] = Gsum;
+        }
+        let G_X: DensePolynomial<C::ScalarField> =
+            Evaluations::<C::ScalarField>::from_vec_and_domain(G_evals.clone(), EH).interpolate();
         let Z_X: DensePolynomial<C::ScalarField> = H.vanishing_polynomial().into();
+        // K(X) = (G(X)- F(alpha)*L_0(X)) / Z(X)
+        let L0_e = &L_X[0] * F_alpha; // L0(X)*F(a) will be 0 in the native case
+        let G_L0e = &G_X - &L0_e;
+        // TODO move division by Z_X to the prev loop
+        let (K_X, remainder) = G_L0e.divide_by_vanishing_poly(H).unwrap();
+        assert!(remainder.is_zero());
 
         let e_star =
             F_alpha * L_X[0].evaluate(&gamma) + Z_X.evaluate(&gamma) * K_X.evaluate(&gamma);
 
         let mut phi_star: C = instance.phi.0 * L_X[0].evaluate(&gamma);
         for i in 0..k {
-            phi_star += vec_instances[i].phi.0 * L_X[i].evaluate(&gamma);
+            phi_star += vec_instances[i].phi.0 * L_X[i + 1].evaluate(&gamma);
         }
         let mut w_star: Vec<C::ScalarField> = vec_scalar_mul(&w.w, &L_X[0].evaluate(&gamma));
         for i in 0..k {
             w_star = vec_add(
                 &w_star,
-                &vec_scalar_mul(&vec_w[i].w, &L_X[i].evaluate(&gamma)),
+                &vec_scalar_mul(&vec_w[i].w, &L_X[i + 1].evaluate(&gamma)),
             );
         }
 
@@ -144,15 +190,14 @@ where
             },
             Witness {
                 w: w_star,
-                r_w: w.r_w,
+                r_w: w.r_w, // wip, fold also r_w (blinding used for the w commitment)
             },
         )
     }
 
     pub fn verifier(
-        tr: &mut Transcript<C::ScalarField, C>,
-        pedersen_params: &PedersenParams<C>,
-        r1cs: R1CS<C::ScalarField>,
+        transcript: &mut Transcript<C::ScalarField, C>,
+        r1cs: &R1CS<C::ScalarField>,
         // running instance
         instance: CommittedInstance<C>,
         // incomming instances
@@ -164,17 +209,14 @@ where
         let t = instance.betas.len();
         let n = r1cs.A[0].len();
 
-        let delta = tr.get_challenge();
+        let delta = transcript.get_challenge();
         let deltas = powers_of_beta(delta, t);
 
-        tr.add_vec(&F_coeffs);
+        transcript.add_vec(&F_coeffs);
 
-        let alpha = tr.get_challenge();
+        let alpha = transcript.get_challenge();
         let alphas = all_powers(alpha, n);
 
-        // dbg!(instance.e);
-        // dbg!(F_coeffs[0]);
-
         // F(alpha) = e + \sum_t F_i * alpha^i
         let mut F_alpha = instance.e;
         for (i, F_i) in F_coeffs.iter().enumerate() {
@@ -193,20 +235,21 @@ where
             .map(|(beta_i, delta_i_alpha)| *beta_i + delta_i_alpha)
             .collect();
 
-        let gamma = tr.get_challenge();
+        let gamma = transcript.get_challenge();
 
         let k = vec_instances.len();
-        let domain_k = GeneralEvaluationDomain::<C::ScalarField>::new(k).unwrap();
-        let L_X: Vec<DensePolynomial<C::ScalarField>> = lagrange_polys(domain_k);
-        let Z_X: DensePolynomial<C::ScalarField> = domain_k.vanishing_polynomial().into();
+        let H = GeneralEvaluationDomain::<C::ScalarField>::new(k + 1).unwrap();
+        let L_X: Vec<DensePolynomial<C::ScalarField>> = lagrange_polys(H);
+        let Z_X: DensePolynomial<C::ScalarField> = H.vanishing_polynomial().into();
         let K_X: DensePolynomial<C::ScalarField> =
             DensePolynomial::<C::ScalarField>::from_coefficients_vec(K_coeffs);
+
         let e_star =
             F_alpha * L_X[0].evaluate(&gamma) + Z_X.evaluate(&gamma) * K_X.evaluate(&gamma);
 
         let mut phi_star: C = instance.phi.0 * L_X[0].evaluate(&gamma);
         for i in 0..k {
-            phi_star += vec_instances[i].phi.0 * L_X[i].evaluate(&gamma);
+            phi_star += vec_instances[i].phi.0 * L_X[i + 1].evaluate(&gamma);
         }
 
         // return the folded instance
@@ -226,12 +269,12 @@ fn pow_i(i: usize, betas: &Vec) -> F {
     let b = bit_decompose(i as u64, n as usize);
 
     let mut r: F = F::one();
-    for (j, beta_i) in betas.iter().enumerate() {
+    for (j, beta_j) in betas.iter().enumerate() {
         let mut b_j = F::zero();
         if b[j] {
             b_j = F::one();
         }
-        r *= (F::one() - b_j) + b_j * betas[j];
+        r *= (F::one() - b_j) + b_j * beta_j;
     }
     r
 }
@@ -244,20 +287,19 @@ fn pow_i_over_x(i: usize, betas: &Vec, deltas: &Vec) -> Spa
 
     let mut r: SparsePolynomial<F> =
         SparsePolynomial::<F>::from_coefficients_vec(vec![(0, F::one())]); // start with r(x) = 1
-    for (j, beta_i) in betas.iter().enumerate() {
+    for (j, beta_j) in betas.iter().enumerate() {
         if b[j] {
             let curr: SparsePolynomial<F> =
-                SparsePolynomial::<F>::from_coefficients_vec(vec![(0, betas[j]), (1, deltas[j])]);
+                SparsePolynomial::<F>::from_coefficients_vec(vec![(0, *beta_j), (1, deltas[j])]);
             r = r.mul(&curr);
         }
     }
     r
 }
 
-// method from caulk: https://github.com/caulk-crypto/caulk/tree/8210b51fb8a9eef4335505d1695c44ddc7bf8170/src/multi/setup.rs#L300
+// lagrange_polys method from caulk: https://github.com/caulk-crypto/caulk/tree/8210b51fb8a9eef4335505d1695c44ddc7bf8170/src/multi/setup.rs#L300
 fn lagrange_polys<F: PrimeField>(domain_n: GeneralEvaluationDomain<F>) -> Vec<DensePolynomial<F>> {
     let mut lagrange_polynomials: Vec<DensePolynomial<F>> = Vec::new();
-
     for i in 0..domain_n.size() {
         let evals: Vec<F> = cfg_into_iter!(0..domain_n.size())
             .map(|k| if k == i { F::one() } else { F::zero() })
@@ -275,11 +317,10 @@ pub struct R1CS {
 }
 
 // f(w) in R1CS context
-fn eval_f<F: PrimeField>(r1cs: &R1CS<F>, w: &Vec<F>) -> Vec<F> {
-    let AzBz = hadamard(&mat_vec_mul(&r1cs.A, &w), &mat_vec_mul(&r1cs.B, &w));
-    let Cz = mat_vec_mul(&r1cs.C, &w);
-    let f_w = vec_sub(&AzBz, &Cz);
-    f_w
+fn eval_f<F: PrimeField>(r1cs: &R1CS<F>, w: &[F]) -> Vec<F> {
+    let AzBz = hadamard(&mat_vec_mul(&r1cs.A, w), &mat_vec_mul(&r1cs.B, w));
+    let Cz = mat_vec_mul(&r1cs.C, w);
+    vec_sub(&AzBz, &Cz)
 }
 
 fn check_instance<C: CurveGroup>(
@@ -288,11 +329,8 @@ fn check_instance(
     w: Witness<C>,
 ) -> bool {
     let n = 2_u64.pow(instance.betas.len() as u32) as usize;
-    dbg!(n);
-    dbg!(w.w.len());
 
-    let f_w = eval_f(&r1cs, &w.w); // f(w)
-    dbg!(f_w.len());
+    let f_w = eval_f(r1cs, &w.w); // f(w)
 
     let mut r = C::ScalarField::zero();
     for i in 0..n {
@@ -310,7 +348,6 @@ mod tests {
     use crate::pedersen::Pedersen;
     use crate::transcript::poseidon_test_config;
     use ark_bls12_381::{Fr, G1Projective};
-    use ark_std::One;
     use ark_std::UniformRand;
 
     pub fn to_F_matrix<F: PrimeField>(M: Vec<Vec<usize>>) -> Vec<Vec<F>> {
@@ -405,16 +442,22 @@ mod tests {
         let mut rng = ark_std::test_rng();
         let t = 3;
         let n = 8;
-        // let beta = Fr::rand(&mut rng);
-        // let delta = Fr::rand(&mut rng);
-        let beta = Fr::from(3);
-        let delta = Fr::from(5);
+        let beta = Fr::rand(&mut rng);
+        let delta = Fr::rand(&mut rng);
         let betas = powers_of_beta(beta, t);
         let deltas = powers_of_beta(delta, t);
 
-        // for i in 0..n {
-        //     dbg!(pow_i_over_x(i, &betas, &deltas));
-        // }
+        // compute b + X*d, with X=rand
+        let x = Fr::rand(&mut rng);
+        let bxd = vec_add(&betas, &vec_scalar_mul(&deltas, &x));
+
+        // assert that computing pow_over_x of betas,deltas, is equivalent to first computing the
+        // vector [betas+X*deltas] and then computing pow_i over it
+        for i in 0..n {
+            let pow_i1 = pow_i_over_x(i, &betas, &deltas);
+            let pow_i2 = pow_i(i, &bxd);
+            assert_eq!(pow_i1.evaluate(&x), pow_i2);
+        }
     }
 
     #[test]
@@ -431,15 +474,15 @@ mod tests {
     }
 
     #[test]
-    fn test_fold() {
+    fn test_fold_native_case() {
         let mut rng = ark_std::test_rng();
         let pedersen_params = Pedersen::<G1Projective>::new_params(&mut rng, 100); // 100 is wip, will get it from actual vec
         let poseidon_config = poseidon_test_config::<Fr>();
 
-        let k = 5;
+        let k = 6;
 
         let r1cs = get_test_r1cs::<Fr>();
-        let mut z = get_test_z::<Fr>(3);
+        let z = get_test_z::<Fr>(3);
         let mut zs: Vec<Vec<Fr>> = Vec::new();
         for i in 0..k {
             let z_i = get_test_z::<Fr>(i + 4);
@@ -452,8 +495,6 @@ mod tests {
 
         let n = z.len();
         let t = log2(n) as usize;
-        dbg!(n);
-        dbg!(t);
 
         let beta = Fr::rand(&mut rng);
         let betas = powers_of_beta(beta, t);
@@ -489,30 +530,30 @@ mod tests {
 
         let (F_coeffs, K_coeffs, folded_instance, folded_witness) = Folding::<G1Projective>::prover(
             &mut transcript_p,
-            &pedersen_params,
             &r1cs,
             instance.clone(),
             witness,
             instances.clone(),
             witnesses,
         );
-        dbg!(&F_coeffs);
 
         // veriier
         let folded_instance_v = Folding::<G1Projective>::verifier(
             &mut transcript_v,
-            &pedersen_params,
-            r1cs.clone(), // TODO rm clone do borrow
+            &r1cs,
             instance,
             instances,
             F_coeffs,
             K_coeffs,
         );
 
+        // check that prover & verifier folded instances are the same values
         assert_eq!(folded_instance.phi.0, folded_instance_v.phi.0);
         assert_eq!(folded_instance.betas, folded_instance_v.betas);
         assert_eq!(folded_instance.e, folded_instance_v.e);
+        assert!(!folded_instance.e.is_zero());
 
-        // assert!(check_instance(&r1cs, folded_instance, folded_witness));
+        // check that the folded instance satisfies the relation
+        assert!(check_instance(&r1cs, folded_instance, folded_witness));
     }
 }

src/transcript.rs

@@ -1,4 +1,4 @@
-/// transcript.rs file and adapted from https://github.com/arnaucube/nova-study
+/// transcript.rs file adapted from https://github.com/arnaucube/nova-study
 use ark_ec::{AffineRepr, CurveGroup};
 use ark_ff::PrimeField;
 use std::marker::PhantomData;

src/utils.rs

@@ -1,7 +1,7 @@
 use ark_ff::fields::PrimeField;
 use ark_std::cfg_iter;
 
-pub fn vec_add<F: PrimeField>(a: &Vec<F>, b: &[F]) -> Vec<F> {
+pub fn vec_add<F: PrimeField>(a: &[F], b: &[F]) -> Vec<F> {
     let mut r: Vec<F> = vec![F::zero(); a.len()];
     for i in 0..a.len() {
         r[i] = a[i] + b[i];
@@ -9,7 +9,7 @@ pub fn vec_add(a: &Vec, b: &[F]) -> Vec {
     r
 }
 
-pub fn vec_sub<F: PrimeField>(a: &Vec<F>, b: &Vec<F>) -> Vec<F> {
+pub fn vec_sub<F: PrimeField>(a: &[F], b: &[F]) -> Vec<F> {
     let mut r: Vec<F> = vec![F::zero(); a.len()];
     for i in 0..a.len() {
         r[i] = a[i] - b[i];
@@ -45,7 +45,7 @@ pub fn mat_vec_mul(M: &Vec>, z: &[F]) -> Vec {
     r
 }
 
-pub fn hadamard<F: PrimeField>(a: &Vec<F>, b: &Vec<F>) -> Vec<F> {
+pub fn hadamard<F: PrimeField>(a: &[F], b: &[F]) -> Vec<F> {
     cfg_iter!(a).zip(b).map(|(a, b)| *a * b).collect()
 }