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    # FRI协议之,共线性测试的通用概述 ## 概述 本文针对FRI中的split and fold环节,对于从 $f_{i}(x)$ 迭代成 $f_{i+1}(x)$ 过程,所需要满足的约束,进行演进概述。 并试图,揭示更General的,折 $N=2^k$ 情况下(而非对半折,N=2), 更通用的由 $f_{i}(x)$ 迭代成 $f_{i+1}(x)$ 的演进证明。 ## 经典FRI 定义fold前的函数为 $f_{i}(x)$ ,将其进行按奇偶项进行split and fold, $$f_{i}(x)=f_{E}(x^2)+xf_{O}(x^2)$$ 这里,我们若取用 $y$ 来代替 $x^2$,即 $y=x^2$ 时,则上式变为: $$f_{i}(x,y)=f_{E}(y)+xf_{O}(y)$$ 需要注意的是:这个函数视为一个关于(x,y)的二元函数,并不要求 $y=x^2$ 我们若在这个式子中,固定y值 $y=\beta$,则变为一个关于x的degree=1的线性函数: $$f_{i}(x)=f_{E}(\beta)+xf_{O}(\beta)$$ 那么,在这个线性函数上,我们任取三点,这三点都是共线的(degree=1)。 我们取 $y=\beta$ 时,对应的两点 $x_{0}$、 $x_{1}$ ,即 $\beta=x_{0}^2=x_{1}^2$ 。我们再随机取一点 $x=\alpha$ 可知在 $y$ 被固定为 $\beta$ 时,可知这三点 $(\alpha,f_{i+1}(\alpha)),(x0,f_{i}(x0)),(x1,f_{i}(x1)$是共线性的。 这里需要注意到,由于$\beta=x_{0}^2=x_{1}^2$ ,那么$f_{E}(\beta)+xf_{O}(\beta)$的计算,其实与原使的 $f_{i}(x)$是一样的。 而对于 $x=\alpha$ 时,我们将 $f_{i}(x)$ 看作为一个固定了 $x=\alpha$ ,的关于 $y$ 的函数,变化为 $f_{i}(y)$ ,最终为方便统一形式,其实就可以表达为split后下一Layer的 $f_{i+1}(x)$ $$f_{i}(x)=f_{i}(y)=f_{E}(y)+\alpha f_{O}(y)$$ $$f_{i+1}(x)=f_{E}(x)+\alpha f_{O}(x)$$ 综上可知:$(\alpha,f_{i+1}(x)),(x0,f_{i}(x0)),(x1,f_{i}(x1)$ ## 对于折N折的情况 对于折N折的情况,我们参考V神的文章,其实可以知道,具有类似的属性。 ![image](https://hackmd.io/_uploads/HkQEKMhjR.png) 如上图,当按 $y=x^N$ 来折叠为时,那么有图中的N+1个点,其构成了 $degree=N-1$ 的一个多项式。 将一个多项式fi(x),按 $y=x^N$ 折叠后,变为: $$f_{i}(x)=f_{4}(y)+x^3 f_{3}(y)+x^2 f_{2}(y)+x f_{1}(y)$$ 这里按 $x$ 幂次,拆成了四个函数。那么,当固定 $y=\beta=x_{0}^4=x_{1}^4=x_{2}^4=x_{3}^4$ 时,上式变为一个关于 $x$ 的degree为3的函数。 $$f_{i}(x)=f_{4}(\beta)+x^3 f_{3}(\beta)+x^2 f_{2}(\beta)+x f_{1}(\beta)$$同样,当固定 $x=\alpha$时,该式可视为 $f_{i+1}(y)$是关于 $y$ 的函数。 同理可以得到: $(x_{0},f_{i}(x_{0})),(x_{1},f_{i}(x_{1})),(x_{2},f_{i}(x_{2})),(x_{3},f_{i}(x_{3}))与 (\alpha, f_{i+1}(\beta))$,这五点是构成一个degree为3的函数。这里只需要验证这一点即可。 ## 共线性测试,与从$f_{i}$到$f_{i+1}$的进化,是等价的 直接将手算的过程放上。可见是等价的。代码中可按三点的degree=1 来进行测试即可。 ![image](https://hackmd.io/_uploads/SJq7nz2j0.png) ## 扩展研究 ### V神文章中的N折 V神文章中,举了1000为例。实际上是类似的,即取一个固定的y值,得到的1001个点(1000个在 $y=x^{1000}$ 上,另一个是 $(\alpha,f_{i+1}(y))$ ,是形成一个degree<1000的多项式。 ### 按N折需要研究的 1、按N=2^k折,那么其安全性,计算量,是与N=2是一样的吗? 2、这样,能证明的degree跨度更大了?原来只能证明degree在 $2^k$ 的区间,现在只能证明在 $N^k$ 的取间了。 3、研究Keep说的RISC0是按16折 https://www.youtube.com/watch?v=wqRuoyH3Mqk 在这个视频中的32分钟 ~ 35 分钟提到RISC0 按照16 来折叠的

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