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Related papers: On the rank of $n\times n$ matrix multiplication

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The rank of the matrix multiplication operator for nxn matrices is one of the most studied quantities in algebraic complexity theory. I prove that the rank is at least n^2-o(n^2). More precisely, for any integer p\leq n -1, the rank is at…

Computational Complexity · Computer Science 2013-10-31 J. M. Landsberg

The border rank of the matrix multiplication operator for n by n matrices is a standard measure of its complexity. Using techniques from algebraic geometry and representation theory, we show the border rank is at least 2n^2-n. Our bounds…

Computational Complexity · Computer Science 2013-06-04 J. M. Landsberg , Giorgio Ottaviani

We develop a notion of {\em inner rank} as a tool for obtaining lower bounds on the rank of matrix multiplication tensors. We use it to give a short proof that the border rank (and therefore rank) of the tensor associated with $n\times n$…

Computational Complexity · Computer Science 2019-05-15 Joel Friedman

Let M_n denote the matrix multiplication tensor for nxn matrices. We use the border substitution method combined with Koszul flattenings to prove the border rank lower bound of 2n^2-log(n)-1 for M_n.

Computational Complexity · Computer Science 2016-08-29 J. M. Landsberg , Mateusz Michałek

Let $M_{\langle u,v,w\rangle}\in C^{uv}\otimes C^{vw}\otimes C^{wu}$ denote the matrix multiplication tensor (and write $M_n=M_{\langle n,n,n\rangle}$) and let $det_3\in ( C^9)^{\otimes 3}$ denote the determinant polynomial considered as a…

Algebraic Geometry · Mathematics 2019-11-20 Austin Conner , Alicia Harper , J. M. Landsberg

We study the algorithmic problem of multiplying large matrices that are rectangular. We prove that the method that has been used to construct the fastest algorithms for rectangular matrix multiplication cannot give algorithms with…

Computational Complexity · Computer Science 2025-11-10 Matthias Christandl , François Le Gall , Vladimir Lysikov , Jeroen Zuiddam

We show that the border support rank of the tensor corresponding to two-by-two matrix multiplication is seven over the complex numbers. We do this by constructing two polynomials that vanish on all complex tensors with format…

Computational Complexity · Computer Science 2018-09-26 Markus Bläser , Matthias Christandl , Jeroen Zuiddam

We prove lower bounds of order $n\log n$ for both the problem to multiply polynomials of degree $n$, and to divide polynomials with remainder, in the model of bounded coefficient arithmetic circuits over the complex numbers. These lower…

Computational Complexity · Computer Science 2007-05-23 Peter Buergisser , Martin Lotz

We present a prime-generating polynomial $(1+2n)(p -2n) + 2$ where $p>2$ is a lower member of a pair of twin primes less than $41$ and the integer $n$ is such that $\: \frac {1-p}{2} < n < p-1$.

General Mathematics · Mathematics 2017-02-23 Madieyna Diouf

We make an in-depth study of the known border rank (i.e. approximate) algorithms for the matrix multiplication tensor encoding the multiplication of an n x 2 matrix by a 2 x 2 matrix.

Numerical Analysis · Computer Science 2015-09-29 J. M. Landsberg , Nicholas Ryder

It is widely known that the lower bound for the algorithmic complexity of square matrix multiplication resorts to at least $n^2$ arithmetic operations. The justification builds upon the following reasoning: given that there are $2 n^2$…

Data Structures and Algorithms · Computer Science 2023-11-13 Hugo Daniel Macedo

We present new methods for determining polynomials in the ideal of the variety of bilinear maps of border rank at most r. We apply these methods to several cases including the case r = 6 in the space of bilinear maps C^4 x C^4 -> C^4. This…

Computational Complexity · Computer Science 2013-07-10 Jonathan D. Hauenstein , Christian Ikenmeyer , J. M. Landsberg

We estimate the frequency of singular matrices and of matrices of a given rank whose entries are parametrised by arbitrary polynomials over the integers and modulo a prime $p$. In particular, in the integer case, we improve a recent bound…

Number Theory · Mathematics 2023-10-20 Ali Mohammadi , Alina Ostafe , Igor Shparlinski

In this paper we develop algorithms for approximating matrix multiplication with respect to the spectral norm. Let A\in{\RR^{n\times m}} and B\in\RR^{n \times p} be two matrices and \eps>0. We approximate the product A^\top B using two…

Data Structures and Algorithms · Computer Science 2010-10-28 Avner Magen , Anastasios Zouzias

We establish basic information about border rank algorithms for the matrix multiplication tensor and other tensors with symmetry. We prove that border rank algorithms for tensors with symmetry (such as matrix multiplication and the…

Algebraic Geometry · Mathematics 2016-02-01 J. M. Landsberg , Mateusz Michałek

Using an approach of Bergh, we give an alternate proof of Bennett's result on lower bounds for non-negative matrices acting on non-increasing non-negative sequences in $l^p$ when $p \geq 1$ and its dual version, the upper bounds when $0<p…

Functional Analysis · Mathematics 2009-06-16 Peng Gao

Algebraic matrix multiplication algorithms are designed by bounding the rank of matrix multiplication tensors, and then using a recursive method. However, designing algorithms in this way quickly leads to large constant factors: if one…

Computational Complexity · Computer Science 2024-10-29 Josh Alman , Hantao Yu

Let ${\mathcal D}(n)$ be the maximal determinant for $n \times n$ $\{\pm 1\}$-matrices, and $\mathcal R(n) = {\mathcal D}(n)/n^{n/2}$ be the ratio of ${\mathcal D}(n)$ to the Hadamard upper bound. Using the probabilistic method, we prove…

Combinatorics · Mathematics 2016-11-02 Richard P. Brent , Judy-anne H. Osborn , Warren D. Smith

We show that lower bounds on the border rank of matrix multiplication can be used to non-trivially derandomize polynomial identity testing for small algebraic circuits. Letting $\underline{R}(n)$ denote the border rank of $n \times n \times…

Computational Complexity · Computer Science 2024-04-18 Robert Andrews

Let p be a prime, and let M_p(n) denote the bit complexity of multiplying two polynomials in F_p[X] of degree less than n. For n large compared to p, we establish the bound M_p(n) = O(n log n 8^(log^* n) log p), where log^* is the iterated…

Computational Complexity · Computer Science 2014-07-15 David Harvey , Joris van der Hoeven , Grégoire Lecerf
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