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Itamar Nir

Publications and source records attributed to Itamar Nir.

3 recordsLinked to original sources

Finding Integer Roots of Polynomials in Nearly Optimal Time

Let $f\in\mathbb Z[x]$ be a polynomial of degree $n$ with integer coefficients of absolute value less than $2^b$. Using Pan's approximate factorization theorem, we give a deterministic algorithm that finds all distinct integer roots of $f$ in $\widetilde O(nb)$ bit operations. This matches the bit size of the input up to logarithmic factors and does not require $f$ to be square-free. Since we were unable to verify parts of the running time analysis of Pan's theorem, we also give a self-contained deterministic algorithm with running time $\widetilde O(nb+\min(n,b)^3b^2)$, which is $\widetilde O(nb)$ whenever $b\leq n^{1/4}$. This answers a question of Harvey and Hittmeir (2022), who asked whether integer roots can be found deterministically in quasilinear time, conditionally on Pan's theorem, and unconditionally for $b\leq n^{1/4}$. The fastest previous deterministic algorithm, due to Nir, takes $\widetilde O(n^{3/2}b)$ bit operations and works only for square-free polynomials. Instead of $p$-adic lifting, we combine approximate complex root finding with exact polynomial evaluation. We first approximate the complex roots of the polynomial formed by the top $\min(n,b)+1$ coefficients of $f$. Every integer root $r$ of $f$ with $|r|\geq 2$ lies within distance $2$ of some complex root of this truncated polynomial. Rounding the real parts of the approximate roots therefore gives a list of $O(\min(n,b))$ candidate integers that is guaranteed to contain all integer roots of $f$. Although a single candidate can have up to $b$ bits, a bound via the Mahler measure shows that the bit lengths of all candidates sum to $O(b)$. This allows us to test all candidates by exact multipoint evaluation in $\widetilde O(nb)$ bit operations.

math.NT↗

Faster Deterministic Integer Root Finding for Integer Polynomials

We give a deterministic algorithm for finding all integer roots of a square-free polynomial $f\in\mathbb Z[x]$ of degree $n$ with $\lVert f\rVert_\infty<2^b$. The running time is $$ \tilde{O}(n^{3/2}b), $$ improving the $\tilde{O}(n^2b)$ bound of Harvey and Hittmeir (Research in Number Theory, 2022). The algorithm follows the classical $p$-adic framework: find roots modulo a prime $p$, lift them modulo a high power of $p$, and verify the lifted candidates. The main new idea is to avoid searching for a prime for which $f\bmod p$ is square-free. Instead, we find a prime for which the total multiplicity of repeated roots modulo $p$ is small. This requires lifting repeated roots, which we handle using a weighted lifting tree. We also give a faster deterministic candidate-verification algorithm: given $n$ candidate integers smaller in absolute value than $2^b$, we decide which are roots of $f$ in $$ \tilde{O}(nb+\min(n^2,nb^2)) $$ bit operations. Together, these ingredients give the first deterministic subquadratic-in-$n$ improvement for integer root finding in the square-free case.

math.NT↗

Deterministically finding an element of large order in $\mathbb{Z}_N^*$

In this paper, we present an improvement for the problem of deterministically finding an element of large multiplicative order modulo some integer $N$. This problem arises as a key subroutine in current deterministic factoring algorithms, such as those proposed by Harvey and Hittmeir [Mathematics of Computation, 2021]. Specifically, let $D \exp\left(\sqrt{2\log N \log \log N}\right). \end{equation} We give a deterministic algorithm that does one of the following: Returns an element $a \in \mathbb{Z}_N^*$ with $\operatorname{ord}_N(a) > D$; Returns a non-trivial factor of $N$; Or reports that $N$ is prime. The running time of our algorithm is $O(D^{1/2 + o(1)})$. Similar results were independently and concurrently obtained by Harvey and Hittmeir [arXiv:2601.11131, 2026] in work that appeared while this manuscript was in preparation. Prior to these works, the best known algorithm for finding an element with order larger than $D$ was given by Oznovich and Volk [SODA 2026], requiring $D > N^{\frac{1}{6}}$. We also present a simpler algorithm that applies for any $D < N$ and runs in $O(D^{2.5+o(1)}\operatorname{polylog}(N))$.

cs.DS↗