Some trade-off results for polynomial calculus

We present size-space trade-offs for the polynomial calculus (PC) and polynomial calculus resolution (PCR) proof systems. These are the first true size-space trade-offs in any algebraic proof system, showing that size and space cannot be simultaneously optimized in these models. We achieve this by extending essentially all known size-space trade-offs for resolution to PC and PCR. As such, our results cover space complexity from constant all the way up to exponential and yield mostly superpolynomial or even exponential size blow-ups. Since the upper bounds in our trade-offs hold for resolution, our work shows that there are formulas for which adding algebraic reasoning on top of resolution does not improve the trade-off properties in any significant way. As byproducts of our analysis, we also obtain trade-offs between space and degree in PC and PCR exactly matching analogous results for space versus width in resolution, and strengthen the resolution trade-offs in [Beame, Beck, and Impagliazzo '12] to apply also to k-CNF formulas. Categories and Subject Descriptors: F.2.3[Analysis of Algorithms and Problem Complexity]: Tradeoffs among Complexity Measures; F.1.3[Computation by Abstract Devices]: Complexity Measures and Classes Relations among complexity measures; I.2.3[Artificial Intelligence]: Deduction and Theorem Proving; F.4.1 [Mathematical Logic and Formal Languages]: Mathematical Logic computational logic