EIP7594: Universal Verification in verify_cell_kzg_proof_batch

specs/_features/eip7594/polynomial-commitments-sampling.md

@@ -22,6 +22,7 @@
     - [`_fft_field`](#_fft_field)
     - [`fft_field`](#fft_field)
     - [`coset_fft_field`](#coset_fft_field)
+    - [`compute_verify_cell_kzg_proof_batch_challenge`](#compute_verify_cell_kzg_proof_batch_challenge)
   - [Polynomials in coefficient form](#polynomials-in-coefficient-form)
     - [`polynomial_eval_to_coeff`](#polynomial_eval_to_coeff)
     - [`add_polynomialcoeff`](#add_polynomialcoeff)
@@ -34,7 +35,9 @@
   - [KZG multiproofs](#kzg-multiproofs)
     - [`compute_kzg_proof_multi_impl`](#compute_kzg_proof_multi_impl)
     - [`verify_kzg_proof_multi_impl`](#verify_kzg_proof_multi_impl)
+    - [`verify_cell_kzg_proof_batch_impl`](#verify_cell_kzg_proof_batch_impl)
   - [Cell cosets](#cell-cosets)
+    - [`coset_shift_for_cell`](#coset_shift_for_cell)
     - [`coset_for_cell`](#coset_for_cell)
 - [Cells](#cells-1)
   - [Cell computation](#cell-computation)
@@ -193,17 +196,17 @@ def coset_fft_field(vals: Sequence[BLSFieldElement],
                     roots_of_unity: Sequence[BLSFieldElement],
                     inv: bool=False) -> Sequence[BLSFieldElement]:
     """
-    Computes an FFT/IFFT over a coset of the roots of unity. 
-    This is useful for when one wants to divide by a polynomial which 
+    Computes an FFT/IFFT over a coset of the roots of unity.
+    This is useful for when one wants to divide by a polynomial which
     vanishes on one or more elements in the domain.
     """
     vals = vals.copy()
-    
+
     def shift_vals(vals: Sequence[BLSFieldElement], factor: BLSFieldElement) -> Sequence[BLSFieldElement]:
-        """  
-        Multiply each entry in `vals` by succeeding powers of `factor`  
-        i.e., [vals[0] * factor^0, vals[1] * factor^1, ..., vals[n] * factor^n]  
-        """  
+        """
+        Multiply each entry in `vals` by succeeding powers of `factor`
+        i.e., [vals[0] * factor^0, vals[1] * factor^1, ..., vals[n] * factor^n]
+        """
         shift = 1
         for i in range(len(vals)):
             vals[i] = BLSFieldElement((int(vals[i]) * shift) % BLS_MODULUS)
@@ -222,6 +225,49 @@ def coset_fft_field(vals: Sequence[BLSFieldElement],
         return fft_field(vals, roots_of_unity, inv)
 ```
 
+#### `compute_verify_cell_kzg_proof_batch_challenge`
+
+```python
+def compute_verify_cell_kzg_proof_batch_challenge(row_commitments: Sequence[KZGCommitment],
+                                                  row_indices: Sequence[RowIndex],
+                                                  column_indices: Sequence[ColumnIndex],
+                                                  cosets_evals: Sequence[CosetEvals],
+                                                  proofs: Sequence[KZGProof]) -> BLSFieldElement:
+    """
+    Compute a random challenge r used in the universal verification equation, see
+    https://ethresear.ch/t/a-universal-verification-equation-for-data-availability-sampling/13240
+
+    To compute the challenge, `RANDOM_CHALLENGE_KZG_CELL_BATCH_DOMAIN` should be used as a hash prefix
+    """
+    # input the domain separator
+    hashinput = RANDOM_CHALLENGE_KZG_CELL_BATCH_DOMAIN
+
+    # input the field elements per cell
+    hashinput += int.to_bytes(FIELD_ELEMENTS_PER_CELL, 8, KZG_ENDIANNESS)
+
+    # input the number of commitments
+    num_commitments = len(row_commitments)
+    hashinput += int.to_bytes(num_commitments, 8, KZG_ENDIANNESS)
+
+    # input the number of cells
+    num_cells = len(row_indices)
+    hashinput += int.to_bytes(num_cells, 8, KZG_ENDIANNESS)
+
+    # input all commitments
+    for commitment in row_commitments:
+        hashinput += commitment
+
+    # input each cell with its indices and proof
+    for k in range(num_cells):
+        hashinput += int.to_bytes(row_indices[k], 8, KZG_ENDIANNESS)
+        hashinput += int.to_bytes(column_indices[k], 8, KZG_ENDIANNESS)
+        for eval in cosets_evals[k]:
+            hashinput += bls_field_to_bytes(eval)
+        hashinput += proofs[k]
+
+    return hash_to_bls_field(hashinput)
+```
+
 ### Polynomials in coefficient form
 
 #### `polynomial_eval_to_coeff`
@@ -362,12 +408,12 @@ def compute_kzg_proof_multi_impl(
     """
     Compute a KZG multi-evaluation proof for a set of `k` points.
 
-    This is done by committing to the following quotient polynomial:  
+    This is done by committing to the following quotient polynomial:
         Q(X) = f(X) - I(X) / Z(X)
     Where:
         - I(X) is the degree `k-1` polynomial that agrees with f(x) at all `k` points
         - Z(X) is the degree `k` polynomial that evaluates to zero on all `k` points
-    
+
     We further note that since the degree of I(X) is less than the degree of Z(X),
     the computation can be simplified in monomial form to Q(X) = f(X) / Z(X)
     """
@@ -401,7 +447,7 @@ def verify_kzg_proof_multi_impl(commitment: KZGCommitment,
         Q(X) is the quotient polynomial computed by the prover
         I(X) is the degree k-1 polynomial that evaluates to `ys` at all `zs`` points
         Z(X) is the polynomial that evaluates to zero on all `k` points
-    
+
     The verifier receives the commitments to Q(X) and f(X), so they check the equation
     holds by using the following pairing equation:
         e([Q(X)]_1, [Z(X)]_2) == e([f(X)]_1 - [I(X)]_1, [1]_2)
@@ -423,8 +469,112 @@ def verify_kzg_proof_multi_impl(commitment: KZGCommitment,
     ]))
 ```
 
+#### `verify_cell_kzg_proof_batch_impl`
+
+```python
+def verify_cell_kzg_proof_batch_impl(row_commitments: Sequence[KZGCommitment],
+                                     row_indices: Sequence[RowIndex],
+                                     column_indices: Sequence[ColumnIndex],
+                                     cosets_evals: Sequence[CosetEvals],
+                                     proofs: Sequence[KZGProof]) -> bool:
+    """
+    Verify a set of cells, given their corresponding proofs and their coordinates (row_index, column_index) in the blob
+    matrix. The i-th cell is in row row_indices[i] and in column column_indices[i].
+    The list of all commitments is provided in row_commitments_bytes.
+
+    This function implements the universal verification equation introduced here:
+    https://ethresear.ch/t/a-universal-verification-equation-for-data-availability-sampling/13240
+    """
+
+    # The verification equation that we will check is pairing (LL, LR) = pairing (RL, [1]), where
+    # LL = sum_k r^k proofs[k],
+    # LR = [s^n]
+    # RL = RLC - RLI + RLP, where
+    #   RLC = sum_i (sum_{k_i} r^{k_i}) commitments[i]
+    #   RLI = [sum_k r^k interpolation_poly_k(s)]
+    #   RLP = sum_k (r^k * h_k^n) proofs[k]
+    #
+    # Here, the variables have the following meaning:
+    # - k < len(row_indices) is an index iterating over all cells in the input
+    # - r is a random coefficient, derived from hashing all data provided by the prover
+    # - s is the secret embedded in the KZG setup
+    # - n = FIELD_ELEMENTS_PER_CELL is the size of the evaluation domain
+    # - i ranges over all rows that are touched
+    # - k_i < len(row_indices) ranges over all cells that are in row i
+    # - interpolation_poly_k is the interpolation polynomial for the kth cell
+    # - h_k is the coset shift specifying the evaluation domain of the kth cell
+
+    # Preparation
+    num_cells = len(row_indices)
+    n = FIELD_ELEMENTS_PER_CELL
+    num_rows = len(row_commitments)
+
+    # Step 1: Compute a challenge r and its powers r^0, ..., r^{num_cells-1}
+    r = compute_verify_cell_kzg_proof_batch_challenge(
+        row_commitments,
+        row_indices,
+        column_indices,
+        cosets_evals,
+        proofs
+    )
+    r_powers = compute_powers(r, num_cells)
+
+    # Step 2: Compute LL = sum_k r^k proofs[k]
+    ll = bls.bytes48_to_G1(g1_lincomb(proofs, r_powers))
+
+    # Step 3: Compute LR = [s^n]
+    lr = bls.bytes96_to_G2(KZG_SETUP_G2_MONOMIAL[n])
+
+    # Step 4: Compute RL = RLC - RLI + RLP
+    # Step 4.1: Compute RLC = sum_i (sum_{k_i} r^{k_i}) commitments[i]
+    commitment_weights = [0] * num_rows
+    for k in range(num_cells):
+        commitment_weights[row_indices[k]] = (commitment_weights[row_indices[k]] + int(r_powers[k])) % BLS_MODULUS
+    rlc = bls.bytes48_to_G1(g1_lincomb(row_commitments, commitment_weights))
+
+    # Step 4.2: Compute RLI = [sum_k r^k interpolation_poly_k(s)]
+    # Note: an efficient implementation would use the IDFT based method explained in the blog post
+    sum_interp_polys_coeff = [0]
+    for k in range(num_cells):
+        interp_poly_coeff = interpolate_polynomialcoeff(coset_for_cell(column_indices[k]), cosets_evals[k])
+        interp_poly_scaled_coeff = multiply_polynomialcoeff([r_powers[k]], interp_poly_coeff)
+        sum_interp_polys_coeff = add_polynomialcoeff(sum_interp_polys_coeff, interp_poly_scaled_coeff)
+    rli = bls.bytes48_to_G1(g1_lincomb(KZG_SETUP_G1_MONOMIAL[:n], sum_interp_polys_coeff))
+
+    # Step 4.3: Compute RLP = sum_k (r^k * h_k^n) proofs[k]
+    weighted_r_powers = []
+    for k in range(num_cells):
+        cosetshift = int(coset_shift_for_cell(column_indices[k]))
+        cosetshift_pow = pow(cosetshift, n, BLS_MODULUS)
+        wrp = (int(r_powers[k]) * cosetshift_pow) % BLS_MODULUS
+        weighted_r_powers.append(wrp)
+    rlp = bls.bytes48_to_G1(g1_lincomb(proofs, weighted_r_powers))
+
+    # Step 4.4: Compute RL = RLC - RLI + RLP
+    rl = bls.add(rlc, bls.neg(rli))
+    rl = bls.add(rl, rlp)
+
+    # Step 5: Check pairing (LL, LR) = pairing (RL, [1])
+    return (bls.pairing_check([[ll, lr], [rl, bls.neg(bls.bytes96_to_G2(KZG_SETUP_G2_MONOMIAL[0])), ], ]))
+```
+
+
 ### Cell cosets
 
+#### `coset_shift_for_cell`
+
+```python
+def coset_shift_for_cell(cell_index: CellIndex) -> BLSFieldElement:
+    """
+    Get the shift that determines the coset for a given ``cell_index``.
+    """
+    assert cell_index < CELLS_PER_EXT_BLOB
+    roots_of_unity_brp = bit_reversal_permutation(
+        compute_roots_of_unity(FIELD_ELEMENTS_PER_EXT_BLOB)
+    )
+    return roots_of_unity_brp[FIELD_ELEMENTS_PER_CELL * cell_index]
+```
+
 #### `coset_for_cell`
 
 ```python
@@ -457,7 +607,7 @@ def compute_cells_and_kzg_proofs(blob: Blob) -> Tuple[
     Public method.
     """
     assert len(blob) == BYTES_PER_BLOB
-    
+
     polynomial = blob_to_polynomial(blob)
     polynomial_coeff = polynomial_eval_to_coeff(polynomial)
 
@@ -491,7 +641,7 @@ def verify_cell_kzg_proof(commitment_bytes: Bytes48,
     assert cell_index < CELLS_PER_EXT_BLOB
     assert len(cell) == BYTES_PER_CELL
     assert len(proof_bytes) == BYTES_PER_PROOF
-    
+
     coset = coset_for_cell(cell_index)
 
     return verify_kzg_proof_multi_impl(
@@ -511,18 +661,15 @@ def verify_cell_kzg_proof_batch(row_commitments_bytes: Sequence[Bytes48],
                                 proofs_bytes: Sequence[Bytes48]) -> bool:
     """
     Verify a set of cells, given their corresponding proofs and their coordinates (row_index, column_index) in the blob
-    matrix. The list of all commitments is also provided in row_commitments_bytes.
+    matrix. The i-th cell is in row = row_indices[i] and in column = column_indices[i].
+    The list of all commitments is provided in row_commitments_bytes.
 
-    This function implements the naive algorithm of checking every cell
-    individually; an efficient algorithm can be found here:
+    This function implements the universal verification equation that has been introduced here:
     https://ethresear.ch/t/a-universal-verification-equation-for-data-availability-sampling/13240
 
-    This implementation does not require randomness, but for the algorithm that
-    requires it, `RANDOM_CHALLENGE_KZG_CELL_BATCH_DOMAIN` should be used to compute
-    the challenge value.
-
     Public method.
     """
+
     assert len(cells) == len(proofs_bytes) == len(row_indices) == len(column_indices)
     for commitment_bytes in row_commitments_bytes:
         assert len(commitment_bytes) == BYTES_PER_COMMITMENT
@@ -535,18 +682,13 @@ def verify_cell_kzg_proof_batch(row_commitments_bytes: Sequence[Bytes48],
     for proof_bytes in proofs_bytes:
         assert len(proof_bytes) == BYTES_PER_PROOF
 
-    # Get commitments via row indices
-    commitments_bytes = [row_commitments_bytes[row_index] for row_index in row_indices]
-
     # Get objects from bytes
-    commitments = [bytes_to_kzg_commitment(commitment_bytes) for commitment_bytes in commitments_bytes]
+    row_commitments = [bytes_to_kzg_commitment(commitment_bytes) for commitment_bytes in row_commitments_bytes]
     cosets_evals = [cell_to_coset_evals(cell) for cell in cells]
     proofs = [bytes_to_kzg_proof(proof_bytes) for proof_bytes in proofs_bytes]
 
-    return all(
-        verify_kzg_proof_multi_impl(commitment, coset_for_cell(column_index), coset_evals, proof)
-        for commitment, column_index, coset_evals, proof in zip(commitments, column_indices, cosets_evals, proofs)
-    )
+    # Do the actual verification
+    return verify_cell_kzg_proof_batch_impl(row_commitments, row_indices, column_indices, cosets_evals, proofs)
 ```
 
 ## Reconstruction
@@ -558,7 +700,7 @@ def construct_vanishing_polynomial(missing_cell_indices: Sequence[CellIndex]) ->
     """
     Given the cells indices that are missing from the data, compute the polynomial that vanishes at every point that
     corresponds to a missing field element.
-    
+
     This method assumes that all of the cells cannot be missing. In this case the vanishing polynomial
     could be computed as Z(x) = x^n - 1, where `n` is FIELD_ELEMENTS_PER_EXT_BLOB.
 
@@ -617,7 +759,7 @@ def recover_data(cell_indices: Sequence[CellIndex],
     extended_evaluation_times_zero = [BLSFieldElement(int(a) * int(b) % BLS_MODULUS)
                                       for a, b in zip(zero_poly_eval, extended_evaluation)]
 
-    # Convert (E*Z)(x) to monomial form 
+    # Convert (E*Z)(x) to monomial form
     extended_evaluation_times_zero_coeffs = fft_field(extended_evaluation_times_zero, roots_of_unity_extended, inv=True)
 
     # Convert (E*Z)(x) to evaluation form over a coset of the FFT domain
@@ -688,7 +830,7 @@ def recover_cells_and_kzg_proofs(cell_indices: Sequence[CellIndex],
     recovered_cells = [
         coset_evals_to_cell(reconstructed_data[i * FIELD_ELEMENTS_PER_CELL:(i + 1) * FIELD_ELEMENTS_PER_CELL])
         for i in range(CELLS_PER_EXT_BLOB)]
-    
+
     polynomial_eval = reconstructed_data[:FIELD_ELEMENTS_PER_BLOB]
     polynomial_coeff = polynomial_eval_to_coeff(polynomial_eval)
     recovered_proofs = [None] * CELLS_PER_EXT_BLOB
@@ -700,6 +842,6 @@ def recover_cells_and_kzg_proofs(cell_indices: Sequence[CellIndex],
             proof, ys = compute_kzg_proof_multi_impl(polynomial_coeff, coset)
             assert coset_evals_to_cell(ys) == recovered_cells[i]
             recovered_proofs[i] = proof
- 
+
     return recovered_cells, recovered_proofs
 ```