Yann Tal | Searcharxiv

arXiv2026

Quantum Algorithms for Modular Factorials

We give a bounded-error quantum algorithm that, given a prime $p$, a divisor $q\mid(p-1)$, and an integer $0<n<p$, computes $n!\bmod p$ in expected time $\widetilde{O}(q^c+\sqrt{p/q})$ for some absolute constant $c\ge 1$. When $p-1$ has a divisor of size $q\approx p^{1/(2c+1)}$, this gives the exponent $c/(2c+1)<1/2$. To our knowledge, this is the first algorithm to break the exponent $1/2$ barrier for modular factorials under such a divisor promise. The main technical ingredient is a quantum algorithm that reconstructs the relevant Jacobi sum exactly in compact algebraic form, with polynomial dependence on $q$ and $\log p$. We further extend the same asymptotic bound to the computation of $n!\bmod p^2$, uniformly over $0\le n<p^2$. At $n=p-1$, this determines the Wilson quotient $\frac{(p-1)!+1}{p}\pmod p$. We conjecture that the condition $q\mid(p-1)$ is a technical limitation of the present method rather than an inherent obstruction, and that a uniform quantum algorithm exists for all primes.

quant-ph↗

arXiv2026

Polynomial Identity Testing and Reconstruction for Depth-4 Powering Circuits of High Degree

We study deterministic polynomial identity testing (PIT) and reconstruction algorithms for depth-$4$ arithmetic circuits of the form \[ \Sigma^{[r]}\!\wedge^{[d]}\!\Sigma^{[s]}\!\Pi^{[\delta]}. \] This model generalizes Waring decompositions and diagonal circuits, and captures sums of powers of low-degree sparse polynomials. Specifically, each circuit computes a sum of $r$ terms, where each term is a $d$-th power of an $s$-sparse polynomial of degree $\delta$. This model also includes algebraic representations that arise in tensor decomposition and moment-based learning tasks such as mixture models and subspace learning. We give deterministic worst-case algorithms for PIT and reconstruction in this model. Our PIT construction applies when $d>r^2$ and yields explicit hitting sets of size $O(r^4 s^4 n^2 d \delta^3)$. The reconstruction algorithm runs in time $\textrm{poly}(n,s,d)$ under the condition $d=\Omega(r^4\delta)$, and in particular it tolerates polynomially large top fan-in $r$ and bottom degree $\delta$. Both results hold over fields of characteristic zero and over fields of sufficiently large characteristic. These algorithms provide the first polynomial-time deterministic solutions for depth-$4$ powering circuits with unbounded top fan-in. In particular, the reconstruction result improves upon previous work which required non-degeneracy or average-case assumptions. The PIT construction relies on the ABC theorem for function fields (Mason-Stothers theorem), which ensures linear independence of high-degree powers of sparse polynomials after a suitable projection. The reconstruction algorithm combines this with Wronskian-based differential operators, structural properties of their kernels, and a robust version of the Klivans-Spielman hitting set.

cs.CC↗