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Rank Bounds for Design Matrices and Applications Shubhangi Saraf Rutgers University Based on joint works with Albert Ai, Zeev Dvir, Avi Wigderson
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Sylvester-Gallai Theorem (1893) v v v v Suppose that every line through two points passes through a third
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Sylvester Gallai Theorem v v vv Suppose that every line through two points passes through a third
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Proof of Sylvester-Gallai: By contradiction. If possible, for every pair of points, the line through them contains a third. Consider the point-line pair with the smallest distance. ℓ P m Q dist(Q, m) < dist(P, ℓ) Contradiction!
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Several extensions and variations studied – Complexes, other fields, colorful, quantitative, high-dimensional Several recent connections to complexity theory – Structure of arithmetic circuits – Locally Correctable Codes BDWY: – Connections of Incidence theorems to rank bounds for design matrices – Lower bounds on the rank of design matrices – Strong quantitative bounds for incidence theorems – 2-query LCCs over the Reals do not exist This work: builds upon their approach – Improved and optimal rank bounds – Improved and often optimal incidence results – Stable incidence thms stable LCCs over R do not exist
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The Plan Extensions of the SG Theorem Improved rank bounds for design matrices From rank bounds to incidence theorems Proof of rank bound Stable Sylvester-Gallai Theorems – Applications to LCCs
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Points in Complex space Hesse Configuration [Elkies, Pretorius, Swanpoel 2006]: First elementary proof This work: New proof using basic linear algebra
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Quantitative SG vivi
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Stable Sylvester-Gallai Theorem v v v v
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Stable Sylvester Gallai Theorem v v vv
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Other extensions High dimensional Sylvester-Gallai Theorem Colorful Sylvester-Gallai Theorem Average Sylvester-Gallai Theorem Generalization of Freiman’s Lemma
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The Plan Extensions of the SG Theorem Improved rank bounds for design matrices From rank bounds to incidence theorems Proof of rank bound Stable Sylvester-Gallai Theorems – Applications to LCCs
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Design Matrices An m x n matrix is a (q,k,t)-design matrix if: 1.Each row has at most q non-zeros 2.Each column has at least k non-zeros 3.The supports of every two columns intersect in at most t rows m n · t · q ¸ k
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(q,k,t)-design matrix q = 3 k = 5 t = 2 An example
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Not true over fields of small characteristic! Holds for any field of char=0 (or very large positive char) Main Theorem: Rank Bound
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Rank Bound: no dependence on q
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Square Matrices Any matrix over the Reals/complex numbers with same zero-nonzero pattern as incidence matrix of the projective plane has high rank – Not true over small fields! Rigidity?
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The Plan Extensions of the SG Theorem Improved rank bounds for design matrices From rank bounds to incidence theorems Proof of rank bound Stable Sylvester-Gallai Theorems – Applications to LCCs
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Rank Bounds to Incidence Theorems
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The Plan Extensions of the SG Theorem Improved rank bounds for design matrices From rank bounds to incidence theorems Proof of rank bound Stable Sylvester-Gallai Theorems – Applications to LCCs
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Proof Easy case: All entries are either zero or one AtAt A = m m n n n n Diagonal entries ¸ k Off-diagonals · t “diagonal-dominant matrix”
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Idea (BDWY) : reduce to easy case using matrix- scaling: r1r2......rmr1r2......rm c 1 c 2 … c n Replace A ij with r i ¢ c j ¢ A ij r i, c j positive reals Same rank, support. Has ‘balanced’ coefficients: General Case: Matrix scaling
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Matrix scaling theorem Sinkhorn (1964) / Rothblum and Schneider (1989) Thm: Let A be a real m x n matrix with non- negative entries. Suppose every zero minor of A of size a x b satisfies Then for every ² there exists a scaling of A with row sums 1 ± ² and column sums (m/n) ± ² Can be applied also to squares of entries!
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Bounding the rank of perturbed identity matrices
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The Plan Extensions of the SG Theorem Improved rank bounds for design matrices From rank bounds to incidence theorems Proof of rank bound Stable Sylvester-Gallai Theorems – Applications to LCCs
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Stable Sylvester-Gallai Theorem v v v v
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Stable Sylvester Gallai Theorem v v vv
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Not true in general..
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Bounded Distances
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Theorem
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Incidence theorems to design matrices
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proof
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The Plan Extensions of the SG Theorem Improved rank bounds for design matrices From rank bounds to incidence theorems Proof of rank bound Stable Sylvester-Gallai Theorems – Applications to LCCs
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Correcting from Errors Message Encoding Corrupted Encoding Correction Decoding
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Local Correction & Decoding Message Encoding Corrupted Encoding Correction Decoding Local
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Stable Codes over the Reals
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Our Results Constant query stable LCCs over the Reals do not exist. (Was not known for 2-query LCCs) There are no constant query LCCs over the Reals with decoding using bounded coefficients
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Thanks!
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