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Computing Jacobi symbols modulo sparse integers and polynomials and some applications (0)

by I Shparlinski
Venue:J. Algorithms
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Detecting lacunary perfect powers and computing their roots

by Mark Giesbrecht, Daniel S. Roche , 2009
"... We consider the problem of determining whether a lacunary (also called a sparse or super-sparse) polynomial f is a perfect power, that is, f = h r for some other polynomial h and r ∈ N, and of finding h and r should they exist. We show how to determine if f is a perfect power in time polynomial in t ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
We consider the problem of determining whether a lacunary (also called a sparse or super-sparse) polynomial f is a perfect power, that is, f = h r for some other polynomial h and r ∈ N, and of finding h and r should they exist. We show how to determine if f is a perfect power in time polynomial in the number of non-zero terms of f, and in terms of log deg f, i.e., polynomial in the size of the lacunary representation. The algorithm works over Fq[x] (for large characteristic) and over Z[x], where the cost is also polynomial in log ‖f‖∞. We also give a Monte Carlo algorithm to find h if it exists, for which our proposed algorithm requires polynomial time in the output size, i.e., the sparsity and height of h. Conjectures of Erdös and Schinzel, and recent work of Zannier, suggest that h must be sparse. Subject to a slightly stronger conjectures we give an extremely efficient algorithm to find h via a form of sparse Newton iteration. We demonstrate the efficiency of these algorithms with an implementation using the C++ library NTL. 1.
The National Science Foundation
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