From 9ef1c0fc18690c80782cdfc0eedca749e4facc91 Mon Sep 17 00:00:00 2001
From: han0110 <han0110@users.noreply.github.com>
Date: Wed, 8 Nov 2023 13:21:59 +0000
Subject: [PATCH] deploy: 69481d6729c86ab6359d6708c6685a6099b8683d

---
 .../poly/kzg/multiopen/shplonk/prover.rs.html      | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/src/halo2_proofs/poly/kzg/multiopen/shplonk/prover.rs.html b/src/halo2_proofs/poly/kzg/multiopen/shplonk/prover.rs.html
index 1892e0242e..b94bb83af3 100644
--- a/src/halo2_proofs/poly/kzg/multiopen/shplonk/prover.rs.html
+++ b/src/halo2_proofs/poly/kzg/multiopen/shplonk/prover.rs.html
@@ -449,7 +449,7 @@
         R: RngCore,
     {
         <span class="comment">// TODO: explore if it is safe to use same challenge
-        // for different sets that are already combined with anoter challenge
+        // for different sets that are already combined with another challenge
         </span><span class="kw">let </span>y: ChallengeY&lt;<span class="kw">_</span>&gt; = transcript.squeeze_challenge_scalar();
 
         <span class="kw">let </span>quotient_contribution = |rotation_set: <span class="kw-2">&amp;</span>RotationSetExtension&lt;E::G1Affine&gt;| {
@@ -465,7 +465,7 @@
             <span class="comment">// define numerator polynomial as
             // N_i_j(X) = (P_i_j(X) - R_i_j(X))
             // and combine polynomials with same evaluation point set
-            // N_i(X) = linear_combinination(y, N_i_j(X))
+            // N_i(X) = linear_combination(y, N_i_j(X))
             // where y is random scalar to combine numerator polynomials
             </span><span class="kw">let </span>n_x = numerators
                 .into_iter()
@@ -537,7 +537,7 @@
             <span class="comment">// calculate difference vanishing polynomial evaluation
             </span><span class="kw">let </span>z_i = evaluate_vanishing_polynomial(<span class="kw-2">&amp;</span>diffs[..], <span class="kw-2">*</span>u);
 
-            <span class="comment">// inner linearisation contibutions are
+            <span class="comment">// inner linearisation contributions are
             // [P_i_0(X) - r_i_0, P_i_1(X) - r_i_1, ... ] where
             // r_i_j = R_i_j(u) is the evaluation of low degree equivalent polynomial
             // where u is random evaluation point
@@ -552,8 +552,8 @@
             <span class="comment">// define inner contributor polynomial as
             // L_i_j(X) = (P_i_j(X) - r_i_j)
             // and combine polynomials with same evaluation point set
-            // L_i(X) = linear_combinination(y, L_i_j(X))
-            // where y is random scalar to combine inner contibutors
+            // L_i(X) = linear_combination(y, L_i_j(X))
+            // where y is random scalar to combine inner contributors
             </span><span class="kw">let </span>l_x: Polynomial&lt;E::Scalar, Coeff&gt; = inner_contributions
                 .into_iter()
                 .zip(powers(<span class="kw-2">*</span>y))
@@ -566,7 +566,7 @@
         };
 
         <span class="attr">#[allow(clippy::type_complexity)]
-        </span><span class="kw">let </span>(linearisation_contibutions, z_diffs): (
+        </span><span class="kw">let </span>(linearisation_contributions, z_diffs): (
             Vec&lt;Polynomial&lt;E::Scalar, Coeff&gt;&gt;,
             Vec&lt;E::Scalar&gt;,
         ) = rotation_sets
@@ -574,7 +574,7 @@
             .map(linearisation_contribution)
             .unzip();
 
-        <span class="kw">let </span>l_x: Polynomial&lt;E::Scalar, Coeff&gt; = linearisation_contibutions
+        <span class="kw">let </span>l_x: Polynomial&lt;E::Scalar, Coeff&gt; = linearisation_contributions
             .into_iter()
             .zip(powers(<span class="kw-2">*</span>v))
             .map(|(poly, power_of_v)| poly * power_of_v)