logup GKR stwo implementation steps

Include challenge in input MLE

question 1: the challenge in logup denominators are really necessary to be in MLE?

yes, this challenge is irrelevant to the GKR protocol (don’t mess it with the challenges in sum-check and challenges for later random linear combination of MLE evaluations), \(\frac{1}{\alpha +x}\) \(\alpha\) guarantees …

Stwo logup-GKR : build test example

step 1: get the most important 2 ingredients:

when create a component like this:

there are two important thing:

  • FrameworkComponent
  • eval that implement FrameworkEval

we can see the example actually use two types of Component, one is from FrameworkComponent (MleCoeffColumnComponent), one is from MleEvalProverComponent, which is defined specifically for MLE …

Logup GKR – 3: Air constraint for STARK

Committed Traces

The traces that will be interpreted as multilinear polynomial evaluations from STARK:

talking about a single lookup relation, for multiple lookup, it means the

Extra traces that dedicated for Logup-GKR and need to be built additionally

Circuit Example:

using a simple example to describe the GKR circuit

bus …

Logup GKR 2

following previous post

Input Layer Encoding (witness encoding)

trace columns are interpreted as functions, the inputs of the function are bits, enough number of bits that can present \(n\) number of witness in this column.

for trace \(i\), with \(n\) number of rows (trace degree, trace length)

\(f_i(b_0,b_1,b_2,…,b_n)=a_{b_n,…,b_2,b_1,b_0} \)

at …

Logup GKR

following this post

Witness encoding:

trace columns are interpreted as functions, the inputs of the function are bits, enough number of bits that can present \(n\) number of witness in this column.

for trace \(i\), with \(n\) number of rows (trace degree, trace length)

\(f_i(b_0,b_1,b_2,…,b_n)=a_{b_n,…,b_2,b_1,b_0} \)

the multi-linear polynomial for …

Commonly used tricks in Multilinear polynomials

Equation function

Turn a function in binary field to its multilinear extension.

let \(\mathcal{G}\) be a function in binary field, its multi-linear extension can be presented as:

$$\mathcal{G}(r_1,…,r_m)=\sum\limits_{x\in\{0,1\}^m}\mathcal{G}(x)\prod\limits^{m}_{i=1}\underbrace{(r_i\cdot x_i + (1-r_i)(1-x_i))}_{x_i=0 \rightarrow 1-r_i, x=1 \rightarrow r_i }$$

emphasize:

\(r_i \in \mathbb{F}\)

\(x \in \{0,1\}^m\)

\(x_i \) is 0 or 1…

High degree constraint in Plonky3 and Stwo

How to define high degree constraint in Plonky3 and Stwo as a user

Plonky3:

A user must verify the following equation when determining the degree of the constraint (further explanation is provided in the next section):

let \(d\) be the degree of the constraint:

\(d-1\leq 2^{\text{log_blow_up_factor}}\)

If this condition is …

The bus_id in Bus

I am using a simplified circuit for case demonstration purpose:

The bus statement to be proved is:

\([x_0,x_1]\) in [0] with \(bus_{id}\)=a,

this case has only one valid witness [0,0], with multiplicity to be 2

Original protocol:

The above statement essentially proves:

\(\frac{1}{\alpha -x_0}+\frac{1}{\alpha -x_1}=\frac{2}{\alpha}\)

where \(\alpha\) is a random …

Note for bus in stwo 2

continue from this blog

Another thought: proving everying thing together and logup by stwo as extra.

Building LogUp trace

basic steps:
  • logup trace generator, size is determined.
    let mut logup_gen = LogupTraceGenerator::new(log_size);
    • generate columns that is associated with this logup trace generator 
    let mut col_gen = logup_gen.new_col();
    • write fraction, building
    …