,
Mrinal Kumar,
Adrian She,
Ben Lee Volk
Creative Commons Attribution 3.0 Unported license
We show that any Algebraic Branching Program (ABP) computing the polynomial ∑_{i=1}^n xⁿ_i has at least Ω(n²) vertices. This improves upon the lower bound of Ω(nlog n), which follows from the classical result of Baur and Strassen [Volker Strassen, 1973; Walter Baur and Volker Strassen, 1983], and extends the results of Kumar [Mrinal Kumar, 2019], which showed a quadratic lower bound for homogeneous ABPs computing the same polynomial.
Our proof relies on a notion of depth reduction which is reminiscent of similar statements in the context of matrix rigidity, and shows that any small enough ABP computing the polynomial ∑_{i=1}^n xⁿ_i can be depth reduced to essentially a homogeneous ABP of the same size which computes the polynomial ∑_{i=1}^n xⁿ_i + ε(𝐱), for a structured "error polynomial" ε(𝐱). To complete the proof, we then observe that the lower bound in [Mrinal Kumar, 2019] is robust enough and continues to hold for all polynomials ∑_{i=1}^n xⁿ_i + ε(𝐱), where ε(𝐱) has the appropriate structure.
@InProceedings{chatterjee_et_al:LIPIcs.CCC.2020.2,
author = {Chatterjee, Prerona and Kumar, Mrinal and She, Adrian and Volk, Ben Lee},
title = {{A Quadratic Lower Bound for Algebraic Branching Programs}},
booktitle = {35th Computational Complexity Conference (CCC 2020)},
pages = {2:1--2:21},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-156-6},
ISSN = {1868-8969},
year = {2020},
volume = {169},
editor = {Saraf, Shubhangi},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2020.2},
URN = {urn:nbn:de:0030-drops-125546},
doi = {10.4230/LIPIcs.CCC.2020.2},
annote = {Keywords: Algebraic Branching Programs, Lower Bound}
}