Algebraic dependencies and PSPACE algorithms in approximative complexity
Zeyu Guo, Nitin Saxena, Amit Sinhababu

TL;DR
This paper introduces new complexity bounds for algebraic dependence testing of polynomials, showing it lies in AM ∩ coAM, and studies the complexity of approximate polynomial satisfiability, placing it in PSPACE, with implications for algebraic complexity theory.
Contribution
It proves algebraic dependence testing is in AM ∩ coAM and introduces the concept of approximate polynomial satisfiability, placing it in PSPACE, advancing understanding of these problems' complexity.
Findings
Algebraic dependence testing is unlikely to be NP-hard.
Approximate polynomial satisfiability is NP-hard but in PSPACE.
Hitting-set construction for ar VP is in PSPACE.
Abstract
Testing whether a set of polynomials has an algebraic dependence is a basic problem with several applications. The polynomials are given as algebraic circuits. Algebraic independence testing question is wide open over finite fields (Dvir, Gabizon, Wigderson, FOCS'07). The best complexity known is NP (Mittmann, Saxena, Scheiblechner, Trans.AMS'14). In this work we put the problem in AM coAM. In particular, dependence testing is unlikely to be NP-hard and joins the league of problems of "intermediate" complexity, eg. graph isomorphism & integer factoring. Our proof method is algebro-geometric-- estimating the size of the image/preimage of the polynomial map over the finite field. A gap in this size is utilized in the AM protocols. Next, we study the open question of testing whether every annihilator of has zero constant term…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Formal Methods in Verification
