Some trade-off results for polynomial calculus
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Some trade-off results for polynomial calculus. / Beck, Chris; Nordström, Jakob; Tang, Bangsheng.
STOC 2013 - Proceedings of the 2013 ACM Symposium on Theory of Computing. 2013. p. 813-822 (Proceedings of the Annual ACM Symposium on Theory of Computing).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Some trade-off results for polynomial calculus
AU - Beck, Chris
AU - Nordström, Jakob
AU - Tang, Bangsheng
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Degree
KW - PCR
KW - Pebble games
KW - Pebbling formulas
KW - Polynomial calculus
KW - Proof complexity
KW - Resolution
KW - Size
KW - Space
KW - Trade-offs
KW - Tseitin formulas
UR - http://www.scopus.com/inward/record.url?scp=84879820217&partnerID=8YFLogxK
U2 - 10.1145/2488608.2488711
DO - 10.1145/2488608.2488711
M3 - Article in proceedings
AN - SCOPUS:84879820217
SN - 9781450320290
T3 - Proceedings of the Annual ACM Symposium on Theory of Computing
SP - 813
EP - 822
BT - STOC 2013 - Proceedings of the 2013 ACM Symposium on Theory of Computing
T2 - 45th Annual ACM Symposium on Theory of Computing, STOC 2013
Y2 - 1 June 2013 through 4 June 2013
ER -
ID: 251870197