# Technical lemma about curves used in original proof of PCP theorem

I am reading the proof from here and found a technical lemma that seems to be incorrect (its proof is short and very vague). I know this is rather specific and the context is problematic, but I couldn't figure it out myself.

In page 67 (when proving a claim that is used for soundness of local decoding of low degree polynomials procedure), the writers use a "fact" A.9 (regarding "Well Distribution Lemma in Curves") that is located in page 156.

The proof is very short and I cannot grasp it.

Moreover, the statement seems to be incorrect by the following example:

Let $$S=\{x_1\}$$, then $$\forall$$ curve $$C\in P(\langle x_1,\dots,x_k\rangle)$$ we have $$|C\cap S|\geq 1$$ as $$C$$ is a multiset, so $$\mathbb{E}\left[\frac{|C\cap S|}{|C|}\right]\geq\mathbb{E}\left[\frac{1}{|C|}\right]>\frac{1}{|\mathbb{F}|^m}=\frac{|S|}{|\mathbb{F}|^m}$$ Maybe, I miss something in the statement of the lemma...

I will appreciate any help in understanding this problem.

• @A.2 So, how is it later combined with the averaging principle? I mean, how does your statement helps in proving the claim in page 67? And do u understand the proof for it? Mar 18, 2020 at 17:58
• @A.2 The lemma in question is explicitly stated in terms of "the average of $|C\cap S|$, among all curves $C\in P(\langle x_1,\dot, x_k\rangle)$" (emphasis mine), not probabilities, though. Mar 18, 2020 at 23:49

Notation: Let $$P(\langle x_1,\dots,x_k\rangle)$$ the set of degree $$k$$ curves that evaluates to $$x_1,\dots,x_k\in\mathbb{F}^m$$ at the first $$k$$ field elements in $$\mathbb{F}$$ and we will use just $$P$$ as a shorthand for this set. Let $$S$$ be any subset of $$\mathbb{F}^m$$. Below, we assume that multiplicity is taken into account when set cardinalities are computed and for any curve $$C\in P$$, $$|C|:=|\{C(i) : k+1.

Claim 1: $$\mathbb{E}_{C}\big[ \frac{|C\cap S|}{|C|} \big]=\frac{|S|}{|\mathbb{F}|^m}$$ where $$C$$ is a random curve in $$P$$.

Proof: $$\mathbb{E}_{C}\big[ \frac{|C\cap S|}{|C|} \big]=\sum_{C'\in P}\Pr_{C}\big[C=C' \big]\cdot\Pr_{i}\big[C'(i) \in S\big]= \Pr_{C,i} \big[C(i)\in S \big]= \frac{|S|}{|F|^m}$$

Here $$C$$ is a random curve in $$P$$ and $$i$$ is randomly sampled from $$\{k+1,\dots,\mathbb{F} \}$$. The last line holds because sampling a random curve from $$P$$ and then evaluating the curve at a random $$i$$ gives a random element from $$\mathbb{F}^m$$. To see why this is true consider the bipartite graph on $$P\cup \mathbb{F}^m$$ where for each $$i\in \{k+1,\dots,\mathbb{F}\}$$, each curve $$C\in P$$ has a neighbor $$C(i)\in \mathbb{F}^m$$. Its easy to check that this is a bi-regular graph. Thus, the distribution that samples a random $$C$$ and outputs a random neighbor $$C(i)\in \mathbb{F}^m$$ , is same as the distribution that randomly outputs an element from $$\mathbb{F}^m$$. The claim follows.

Remark 1: Claim 1 implies that if $$|S|/|\mathbb{F}|^m\leq \delta$$ then we must have $$\Pr_{c}[\Pr_{i}[~c(i)\in \mathcal{S}] > \sqrt\delta] \leq \sqrt{\delta}$$. This I believe is the claim (from the linked thesis) that OP refers to.

Remark 2: What happens if we just sample a random point $$i$$ from the entire field $$\mathbb{F}$$ instead of $$\{k+1,\dots,\mathbb{F} \}$$. Nothing will change much as it will incur a small(if $$k\ll |\mathbb{F}|$$) additive error of $$k/|\mathbb{F}|$$. In  below this error is there in the argument in page 38.

• Thanks a lot, it clarified the argument in a very nice way! Mar 22, 2020 at 9:27