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\documentclass{article}
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\usepackage{amsmath}
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\title{Notes on FRI and STIR}
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\author{arnaucube}
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\date{February 2023}
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\begin{document}
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\maketitle
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\begin{abstract}
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Notes taken from \href{https://sites.google.com/site/vincenzoiovinoit/}{Vincenzo Iovino} \cite{vincenzoiovino} explanations about FRI \cite{fri}, \cite{cryptoeprint:2022/1216}, \cite{cryptoeprint:2019/1020}.
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These notes are for self-consumption, are not complete, don't include all the steps neither all the proofs.
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An implementation of FRI can be found at\\ \href{https://github.com/arnaucube/fri-commitment}{https://github.com/arnaucube/fri-commitment} \cite{fri-impl}.
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Update(2024-03-22): notes on STIR \cite{cryptoeprint:2024/390} from explanations by \href{https://hecmas.github.io/}{Héctor Masip Ardevol} \cite{hectormasipardevol}.
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\end{abstract}
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\tableofcontents
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\section{Preliminaries}
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\subsection{General degree d test}
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Query at points $\{ x_i \}_0^{d+1},~z$ (with rand $z \overset{R}{\in} \mathbb{F}$).
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Interpolate $p(x)$ at $\{f(x_i)\}_0^{d+1}$ to reconstruct the unique polynomial $p$ of degree $d$ such that $p(x_i)=f(x_i)~\forall i=1, \ldots, d+1$.
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V checks $p(z)=f(z)$, if the check passes, then V is convinced with high probability.
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This needs $d+2$ queries, is linear, $\mathcal{O}(n)$. With FRI we will have the test in $\mathcal{O}(\log{}d)$.
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\section{FRI protocol}
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Allows to test if a function $f$ is a poly of degree $\leq d$ in $\mathcal{O}(\log{}d)$.
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Note: "P \emph{sends} $f(x)$ to V", "\emph{sends}", in the ideal IOP model means that all the table of $f(x)$ is sent, in practice is sent a commitment to $f(x)$.
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\subsection{Intuition}
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V wants to check that two functions $g,~h$ are both polynomials of degree $\leq d$.
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Consider the following protocol:
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\begin{enumerate}
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\item V sends $\alpha \in \mathbb{F}$ to P. P sends $f(x) = g(x) + \alpha h(x)$ to V.
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\item P sends $f(x)=g(x) + \alpha h(x)$ to V.
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\item V queries $f(r), ~g(r), ~h(r)$ for rand $r \in \mathbb{F}$.
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\item V checks $f(r)=g(r) + \alpha h(r)$. (Schwartz-Zippel lema).
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If holds, V can be certain that $f(x)=g(x)+ \alpha h(x)$.
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\item P proves that $deg(f) \leq d$.
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\item If V is convinced that $deg(f) \leq d$, V believes that both $g, h$ have $deg \leq d$.
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\end{enumerate}
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%/// TODO tabulate this next lines
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With high probablility, $\alpha$ will not cancel the coeffs with $deg \geq d+1$. % TODO check which is the name of this theorem or why this is true
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Let $g(x)=a \cdot x^{d+1}, ~~ h(x)=b \cdot x^{d+1}$, and set $f(x) = g(x) + \alpha h(x)$.
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Imagine that P can chose $\alpha$ such that $a x^{d+1} + \alpha \cdot b x^{d+1} = 0$, then, in $f(x)$ the coefficients of degree $d+1$ would cancel.
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%///
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\quad
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Here, P proves $g,~h$ both have $deg \leq d$, but instead of doing $2 \cdot (d+2)$ queries ($d+2$ for $g$, and $d+2$ for $h$), it is done in $d+2$ queries (for $f$).
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So we halved the number of queries.
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\subsection{FRI-LDT}\label{sec:fri-ldt}
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FRI low degree testing.\\
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Both P and V have oracle access to function $f$.
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V wants to test if $f$ is polynomial with $deg(f) \leq d$.
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Let $f_0(x)=f(x)$.
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Each polynomial $f(x)$ of degree that is a power of $2$, can be written as
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$$f(x) = f^L(x^2) + x f^R(x^2)$$
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for some polynomials $f^L,~f^R$ of degree $\frac{deg(f)}{2}$, each one containing the even and odd degree coefficients as follows:
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% $f^L(x)$ is built from the even degree coefficients divided by $x$, and $f^R(x)$ from the odd degree coefficients divided by $x$.
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$$f^L(x)= \sum_0^{\frac{d+1}{2}-1} c_{2i} x^i ,~~ f^R(x)= \sum_0^{\frac{d+1}{2}-1} c_{2i+1} x^i$$
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eg. for $f(x)=x^4+x^3+x^2+x+1$,
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\begin{align*}
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\begin{rcases}
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f^L(x)=x^2+x+1\\
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f^R(x)=x+1
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\end{rcases}
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~f(x) = f^L(x^2) &+ x \cdot f^R(x^2)\\
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= (x^2)^2 + (x^2) + 1 &+ x \cdot ((x^2) + 1)\\
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= x^4 + x^2 + 1 &+ x^3 + x
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\end{align*}
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% \begin{enumerate}
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% \item V sends to P some $\alpha_0 \in \mathbb{F}$.
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% Let
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% \begin{equation}\tag{$A_0$}
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% f_0(x) = f_0^L(x^2) + x f_0^R(x^2)
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% \end{equation}
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% \item P sends
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% \begin{equation}\tag{$B_0$}
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% f_1(x) = f_0^L(x) + \alpha_0 f_0^R(x)
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% \end{equation}
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% to V.
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%
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% (remember that "sends" in IOP model is that P commits to it)
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% \item V sends to P some $\alpha_1 \in \mathbb{F}$.
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% Let
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% \begin{equation}\tag{$A_1$}
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% f_1(x) = f_1^L(x^2) + x f_1^R(x^2)
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% \end{equation}
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% \item P sends
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% \begin{equation}\tag{$B_1$}
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% f_2(x) = f_1^L(x) + \alpha_1 f_1^R(x)
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% \end{equation}
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% to V.
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% \item Keep repeating the process, eg. let
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% \begin{equation}\tag{$A_2$}
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% f_2(x) = f_2^L(x^2) + x f_2^R(x^2)
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% \end{equation}
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% until $f_i^L,~ f_i^R$ are constant (degree 0 polynomials).
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% \item Once $f_i^L,~ f_i^R$ are constant, P sends them to V.
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% \end{enumerate}
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%
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% Notice that at each step, $deg(f_i)$ halves.
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\vspace{30px}
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\paragraph{Proof generation}
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\emph{(Commitment phase)}
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P starts from $f(x)$, and for $i=0$ sets $f_0(x)=f(x)$.
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\begin{enumerate}
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\item $\forall~i \in \{0, log(d)\}$, with $d = deg~f(x)$,\\
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P computes $f_i^L(x),~ f_i^R(x)$ for which
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\begin{equation}\tag{eq. $A_i$}
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f_i(x) = f_i^L(x^2) + x f_i^R(x^2)
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\end{equation}
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holds.
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\item V sends challenge $\alpha_i \in \mathbb{F}$
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\item P commits to the random linear combination $f_{i+1}$, for
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\begin{equation}\tag{eq. $B_i$}
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f_{i+1}(x) = f_i^L(x) + \alpha_i f_i^R(x)
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\end{equation}
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\item P sets $f_i(x) := f_{i+1}(x)$ and starts again the iteration.
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\end{enumerate}
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Notice that at each step, $deg(f_i)$ halves.
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This is done until the last step, where $f_i^L(x),~ f_i^R(x)$ are constant (degree 0 polynomials). For which P does not commit but gives their values directly to V.
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\emph{(Query phase)}
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P would receive a challenge $z \in D$ set by V (where $D$ is the evaluation domain, $D \in \mathbb{F}$), and P would open the commitments at $\{z^{2^i}, -z^{2^i}\}$ for each step $i$.
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(Recall, "opening" means that would provide a proof (MerkleProof) of it).
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\paragraph{Data sent from P to V}
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\begin{itemize}
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\item[] Commitments: $\{Comm(f_i)\}_0^{log(d)}$\\
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{\scriptsize eg. $\{Comm(f_0),~ Comm(f_1),~ Comm(f_2),~ ...,~ Comm(f_{log(d)})\}$ }
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\item[] Openings: $\{ f_i(z^{2^i}),~f_i(-(z^{2^i})) \}_0^{log(d)}$\\
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for a challenge $z \in D$ set by V\\
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{\scriptsize eg. $f_0(z),~ f_0(-z),~ f_1(z^2),~ f_1(-z^2),~ f_2(z^4),~ f_2(-z^4),~ f_3(z^8),~ f_3(-z^8),~ \ldots$}
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\item[] Constant values of last iteration: $\{f_k^L,~f_k^R\}$, for $k=log(d)$
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\end{itemize}
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% \begin{figure}[htp]
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% \centering
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% \begin{footnotesize}
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% \begin{sequencediagram}
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% \newinst[0]{p}{Prover}
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% \newinst[5]{v}{Verifier}
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%
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% \mess{p}{$\{Comm(f_i)\}_0^{log(d)},~ \{f_i(z^{2^i}),~f_i(-(z^{2^i})) \}_0^{log(d)},~ \{f_k^L,~ f_k^R\}$}{v}
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%
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% \end{sequencediagram}
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% \end{footnotesize}
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% \caption[FRI-LDT]{sketch of the FRI-LDT flow}
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% \label{fig:fri-ldt}
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% \end{figure}
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\paragraph{Verification}
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V receives:
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\begin{align*}
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\text{Commitments:}~ &Comm(f_i),~ \forall i \in \{0, log(d)\}\\
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\text{Openings:}~ &\{o_i, o_i'\}=\{ f_i(z^{2^i}),~f_i(-(z^{2^i})) \},~ \forall i \in \{0, log(d)\}\\
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\text{Constant vals:}~ &\{f_k^L,~f_k^R\}
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\end{align*}
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\vspace{20px}
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For all $i \in \{0, log(d)\}$, V knows the openings at $z^{2^i}$ and $-(z^{2^i})$ for\\
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$Comm(f_i(x))$, which are $o_i=f_i(z^{2^i})$ and $o_i'=f_i(-(z^{2^i}))$ respectively.
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V, from (eq. $A_i$), knows that
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$$f_i(x)=f_i^L(x^2) + x f_i^R(x^2)$$
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should hold, thus
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$$f_i(z)=f_i^L(z^2) + z f_i^R(z^2)$$
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where $f_i(z)$ is known, but $f_i^L(z^2),~f_i^R(z^2)$ are unknown.
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But, V also knows the value for $f_i(-z)$, which can be represented as
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$$f_i(-z)=f_i^L(z^2) - z f_i^R(z^2)$$
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(note that when replacing $x$ by $-z$, it loses the negative in the power, not in the linear combination).
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Thus, we have the system of independent linear equations
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\begin{align*} % TODO add braces on left
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f_i(z)&=f_i^L(z^2) + z f_i^R(z^2)\\
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f_i(-z)&=f_i^L(z^2) - z f_i^R(z^2)
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\end{align*}
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for which V will find the value of $f_i^L(z^{2^i}),~f_i^R(z^{2^i})$.
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Equivalently it can be represented by
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$$
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\begin{pmatrix}
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1 & z\\
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1 & -z
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\end{pmatrix}
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\begin{pmatrix}
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f_i^L(z^2)\\
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f_i^R(z^2)
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\end{pmatrix}
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=
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\begin{pmatrix}
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f_i(z)\\
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f_i(-z)
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\end{pmatrix}
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$$
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where V will find the values of $f_i^L(z^{2^i}),~f_i^R(z^{2^i})$ being
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\begin{align*}
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f_i^L(z^{2^i})=\frac{f_i(z) + f_i(-z)}{2}\\
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f_i^R(z^{2^i})=\frac{f_i(z) - f_i(-z)}{2z}\\
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\end{align*}
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Once, V has computed $f_i^L(z^{2^i}),~f_i^R(z^{2^i})$, can use them to compute the linear combination of
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$$
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f_{i+1}(z^{2^i}) = f_i^L(z^{2^i}) + \alpha_i f_i^R(z^{2^i})
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$$
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obtaining then $f_{i+1}(z^{2^i})$. This comes from (eq. $B_i$).
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Now, V checks that the obtained $f_{i+1}(z^{2^i})$ is equal to the received opening $o_{i+1}=f_{i+1}(z^{2^i})$ from the commitment done by P.
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V checks also the commitment of $Comm(f_{i+1}(x))$ for the opening $o_{i+1}=f_{i+1}(z^{2^i})$.\\
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If the checks pass, V is convinced that $f_1(x)$ was committed honestly.
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Now, sets $i := i+1$ and starts a new iteration.
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For the last iteration, V checks that the obtained $f_i^L(z^{2^i}),~f_i^R(z^{2^i})$ are equal to the constant values $\{f_k^L,~f_k^R\}$ received from P.
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\vspace{10px}
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It needs $log(d)$ iterations, and the number of queries (commitments + openings sent and verified) needed is $2 \cdot log(d)$.
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\subsection{Parameters}
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P commits to $f_i$ restricted to a subfield $F_0 \subset \mathbb{F}$.
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Let $0<\rho<1$ be the \emph{rate} of the code, such that
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$$|F_0| = \rho^{-1} \cdot d$$
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\begin{theorem}
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For $\delta \in (0, 1-\sqrt{\rho})$, we have that if V accepts, then w.v.h.p. (with very high probability) $\Delta(f_0,~ p^d) \leq \delta$.
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\end{theorem}
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\section{FRI as polynomial commitment scheme}
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This section overviews the trick from \cite{cryptoeprint:2019/1020} to convert FRI into a polynomial commitment.
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Want to check that the evaluation of $f(x)$ at $r$ is $f(r)$, which is equivalent to proving that $\exists ~Q \in \mathbb{F}[x]$ with $deg(Q)=d-1$, such that
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$$
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f(x)-f(r) = Q(x) \cdot (x-r)
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$$
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note that $f(x)-f(r)$ evaluated at $r$ is $0$, so $(x-r) | (f(x)-f(r))$, in other words
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$(f(x)-f(r))$ is a multiple of $(x-r)$ for a polynomial $Q(x)$.
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Let us define $g(x) = \frac{f(x)-f(r)}{x-r}$.
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Prover uses FRI-LDT \ref{sec:fri-ldt} to commit to $g(x)$, and then prove w.v.h.p that $deg(g) \leq d-1$ ($\Longleftrightarrow \Delta(g,~ p^{d-1} \leq \delta$).
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Prover was already proving that $deg(f) \leq d$.
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Now, the missing thing to prove is that $g(x)$ has the right shape. We can relate $g$ to $f$ as follows:
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V does the normal FRI-LDT, but in addition, at the first iteration:
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V has $f(z)$ and $g(z)$ openings, so can verify
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$$g(z) = (f(z)-f(r))\cdot (z-r)^{-1}$$
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\section{STIR (main idea)}
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\emph{Update from 2024-03-22, notes from Héctor Masip Ardevol (\href{https://hecmas.github.io/}{https://hecmas.github.io}) explanations.}
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\vspace{0.3cm}
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Let $p \in \mathbb{F}[x]^{<n}$.
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In FRI we decompose $p(x)$ as
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$$p(x) = p_e(x^2) + x \cdot p_o(x^2)$$
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with $p_e, p_o \in \mahtbb{F}[x]^{<n}$ containing the even and odd powers respectively.
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The next FRI polynomial is
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$$p_1(x) = p_e(x) + \alpha p_o(x)$$
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for $\alpha \in^R \mathbb{F}$.
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In STIR, this would be $q(x)=x^2$,
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$$Q(z,y) = p_e(y) + z \cdot p_o(y)$$
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and then, $p(x) = Q(x, q(x))$. And $Q$ fullfills the degree from Fact 4.6 from the STIR paper.
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We can generalize to a $q$ with bigger degree, or with another shape, and adapting $Q$ on the choice of $q$.
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eg. for $q(x)=x^3$, we can take
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$$Q(z,y) = p_1(y) + z \cdot p_2(y) + z^2 \cdot p_3(y)$$
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with $p_1, p_2, p_3 \in \mathbb{F}[x]^{<n/3}$ with coefficients taken every 3 powers alternating.
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\bibliography{paper-notes.bib}
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\bibliographystyle{unsrt}
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\end{document}
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