cronokirby

(2026-02) -mathsf{Spectra}; Interval-Agnostic Vector Range Argument for Unstructured Range Assertions

2026-02-20

Abstract

A structured vector range argument proves that a committed vector v\mathbf{v} lies in a well-structured range of the form [0,2d1][0,2^d-1]. This structure makes the protocol extremely efficient, although it cannot handle more sophisticated range assertions, such as those arising from non-membership attestations. To address this gap, we study a more general setting not captured by prior constructions. In this setting, for each ii, the admissible integer set for viv_i is a union of kk intervals Ri=defj=0k1[li,j,ri,j]\mathsf{R}_i \overset{\text{def}}{=} \bigcup_{j=0}^{k-1}\left[l_{i,j},r_{i,j}\right]. In this work, we present novel techniques to prove that vZpn\mathbf{v} \in \mathbb{Z}^n_p lies within R0×R1××Rn1\mathsf{R}_0 \times \mathsf{R}_1 \times \cdots \times \mathsf{R}_{n-1}. We first introduce RangeLift\mathsf{RangeLift}, a generic compiler that lifts a structured vector range argument to support such unstructured range assertions. Then we present Spectra\mathsf{Spectra}, a realization of RangeLift\mathsf{RangeLift} over the KZG\mathsf{KZG}-based vector commitment scheme. Spectra\mathsf{Spectra} achieves succinct communication and verifier time; its prover complexity is O(n\logN\log\logN\log(n\logN\log\logN))O(n\,\tfrac{\log N}{\log\log N}\cdot \log(n\tfrac{\log N}{\log\log N})), where NN upper bounds the maximum interval size across all Ri\mathsf{R}_i. Notably, Spectra\mathsf{Spectra} is interval-agnostic, meaning its prover complexity is independent of the number of intervals kk; therefore, its prover cost matches the single-interval case even when each Ri\mathsf{R}_i is composed of hundreds of thousands of intervals. We also obtain two new structured vector range arguments and a batching-friendly variant of the Cq+\mathsf{Cq}^{+} lookup argument (PKC'24), which are also of independent interest. Experiments show that Spectra\mathsf{Spectra} outperforms well-known curve-based vector range arguments on standard metrics while supporting strictly more expressive range assertions.