42 research outputs found
Lower bounds for constant query affine-invariant LCCs and LTCs
Affine-invariant codes are codes whose coordinates form a vector space over a
finite field and which are invariant under affine transformations of the
coordinate space. They form a natural, well-studied class of codes; they
include popular codes such as Reed-Muller and Reed-Solomon. A particularly
appealing feature of affine-invariant codes is that they seem well-suited to
admit local correctors and testers.
In this work, we give lower bounds on the length of locally correctable and
locally testable affine-invariant codes with constant query complexity. We show
that if a code is an -query
locally correctable code (LCC), where is a finite field and
is a finite alphabet, then the number of codewords in is
at most . Also, we show that if
is an -query locally testable
code (LTC), then the number of codewords in is at most
. The dependence on in these
bounds is tight for constant-query LCCs/LTCs, since Guo, Kopparty and Sudan
(ITCS `13) construct affine-invariant codes via lifting that have the same
asymptotic tradeoffs. Note that our result holds for non-linear codes, whereas
previously, Ben-Sasson and Sudan (RANDOM `11) assumed linearity to derive
similar results.
Our analysis uses higher-order Fourier analysis. In particular, we show that
the codewords corresponding to an affine-invariant LCC/LTC must be far from
each other with respect to Gowers norm of an appropriate order. This then
allows us to bound the number of codewords, using known decomposition theorems
which approximate any bounded function in terms of a finite number of
low-degree non-classical polynomials, upto a small error in the Gowers norm
Lower Bounds for 2-Query LCCs over Large Alphabet
A locally correctable code (LCC) is an error correcting code that allows correction of any arbitrary coordinate of a corrupted codeword by querying only a few coordinates. We show that any 2-query locally correctable code C:{0,1}^k -> Sigma^n that can correct a constant fraction of corrupted symbols must have n >= exp(k/log|Sigma|) under the assumption that the LCC is zero-error. We say that an LCC is zero-error if there exists a non-adaptive corrector algorithm that succeeds with probability 1 when the input is an uncorrupted codeword. All known constructions of LCCs are zero-error.
Our result is tight upto constant factors in the exponent. The only previous lower bound on the length of 2-query LCCs over large alphabet was Omega((k/log|Sigma|)^2) due to Katz and Trevisan (STOC 2000). Our bound implies that zero-error LCCs cannot yield 2-server private information retrieval (PIR) schemes with sub-polynomial communication. Since there exists a 2-server PIR scheme with sub-polynomial communication (STOC 2015) based on a zero-error 2-query locally decodable code (LDC), we also obtain a separation between LDCs and LCCs over large alphabet
Locality via Partially Lifted Codes
In error-correcting codes, locality refers to several different ways of quantifying how easily a small amount of information can be recovered from encoded data. In this work, we study a notion of locality called the s-Disjoint-Repair-Group Property (s-DRGP). This notion can interpolate between two very different settings in coding theory: that of Locally Correctable Codes (LCCs) when s is large - a very strong guarantee - and Locally Recoverable Codes (LRCs) when s is small - a relatively weaker guarantee. This motivates the study of the s-DRGP for intermediate s, which is the focus of our paper. We construct codes in this parameter regime which have a higher rate than previously known codes. Our construction is based on a novel variant of the lifted codes of Guo, Kopparty and Sudan. Beyond the results on the s-DRGP, we hope that our construction is of independent interest, and will find uses elsewhere
Spanoids - An Abstraction of Spanning Structures, and a Barrier for LCCs
We introduce a simple logical inference structure we call a spanoid (generalizing the notion of a matroid), which captures well-studied problems in several areas. These include combinatorial geometry (point-line incidences), algebra (arrangements of hypersurfaces and ideals), statistical physics (bootstrap percolation), network theory (gossip / infection processes) and coding theory. We initiate a thorough investigation of spanoids, from computational and structural viewpoints, focusing on parameters relevant to the applications areas above and, in particular, to questions regarding Locally Correctable Codes (LCCs).
One central parameter we study is the rank of a spanoid, extending the rank of a matroid and related to the dimension of codes. This leads to one main application of our work, establishing the first known barrier to improving the nearly 20-year old bound of Katz-Trevisan (KT) on the dimension of LCCs. On the one hand, we prove that the KT bound (and its more recent refinements) holds for the much more general setting of spanoid rank. On the other hand we show that there exist (random) spanoids whose rank matches these bounds. Thus, to significantly improve the known bounds one must step out of the spanoid framework.
Another parameter we explore is the functional rank of a spanoid, which captures the possibility of turning a given spanoid into an actual code. The question of the relationship between rank and functional rank is one of the main questions we raise as it may reveal new avenues for constructing new LCCs (perhaps even matching the KT bound). As a first step, we develop an entropy relaxation of functional rank to create a small constant gap and amplify it by tensoring to construct a spanoid whose functional rank is smaller than rank by a polynomial factor. This is evidence that the entropy method we develop can prove polynomially better bounds than KT-type methods on the dimension of LCCs.
To facilitate the above results we also develop some basic structural results on spanoids including an equivalent formulation of spanoids as set systems and properties of spanoid products. We feel that given these initial findings and their motivations, the abstract study of spanoids merits further investigation. We leave plenty of concrete open problems and directions
Lifted Multiplicity Codes and the Disjoint Repair Group Property
Lifted Reed Solomon Codes (Guo, Kopparty, Sudan 2013) were introduced in the context of locally correctable and testable codes. They are multivariate polynomials whose restriction to any line is a codeword of a Reed-Solomon code. We consider a generalization of their construction, which we call lifted multiplicity codes. These are multivariate polynomial codes whose restriction to any line is a codeword of a multiplicity code (Kopparty, Saraf, Yekhanin 2014). We show that lifted multiplicity codes have a better trade-off between redundancy and a notion of locality called the t-disjoint-repair-group property than previously known constructions. More precisely, we show that, for t <=sqrt{N}, lifted multiplicity codes with length N and redundancy O(t^{0.585} sqrt{N}) have the property that any symbol of a codeword can be reconstructed in t different ways, each using a disjoint subset of the other coordinates. This gives the best known trade-off for this problem for any super-constant t < sqrt{N}. We also give an alternative analysis of lifted Reed Solomon codes using dual codes, which may be of independent interest
Improved rank bounds for design matrices and a new proof of Kelly's theorem
We study the rank of complex sparse matrices in which the supports of
different columns have small intersections. The rank of these matrices, called
design matrices, was the focus of a recent work by Barak et. al. (BDWY11) in
which they were used to answer questions regarding point configurations. In
this work we derive near-optimal rank bounds for these matrices and use them to
obtain asymptotically tight bounds in many of the geometric applications. As a
consequence of our improved analysis, we also obtain a new, linear algebraic,
proof of Kelly's theorem, which is the complex analog of the Sylvester-Gallai
theorem
On Relaxed Locally Decodable Codes for Hamming and Insertion-Deletion Errors
Locally Decodable Codes (LDCs) are error-correcting codes
with super-fast decoding algorithms. They are
important mathematical objects in many areas of theoretical computer science,
yet the best constructions so far have codeword length that is
super-polynomial in , for codes with constant query complexity and constant
alphabet size. In a very surprising result, Ben-Sasson et al. showed how to
construct a relaxed version of LDCs (RLDCs) with constant query complexity and
almost linear codeword length over the binary alphabet, and used them to obtain
significantly-improved constructions of Probabilistically Checkable Proofs. In
this work, we study RLDCs in the standard Hamming-error setting, and introduce
their variants in the insertion and deletion (Insdel) error setting. Insdel
LDCs were first studied by Ostrovsky and Paskin-Cherniavsky, and are further
motivated by recent advances in DNA random access bio-technologies, in which
the goal is to retrieve individual files from a DNA storage database. Our first
result is an exponential lower bound on the length of Hamming RLDCs making 2
queries, over the binary alphabet. This answers a question explicitly raised by
Gur and Lachish. Our result exhibits a "phase-transition"-type behavior on the
codeword length for constant-query Hamming RLDCs. We further define two
variants of RLDCs in the Insdel-error setting, a weak and a strong version. On
the one hand, we construct weak Insdel RLDCs with with parameters matching
those of the Hamming variants. On the other hand, we prove exponential lower
bounds for strong Insdel RLDCs. These results demonstrate that, while these
variants are equivalent in the Hamming setting, they are significantly
different in the insdel setting. Our results also prove a strict separation
between Hamming RLDCs and Insdel RLDCs
Any Errors in this Dissertation are Probably Fixable: Topics in Probability and Error Correcting Codes.
We study two problems in coding theory, list-decoding and local-decoding. We take a probabilistic approach to these problems, in contrast to more typical algebraic approaches.
In list-decoding, we settle two open problems about the list-decodability of some well-studied ensembles of codes. First, we show that random linear codes are optimally list-decodable, and second, we show that there exist Reed-Solomon codes which are (nearly) optimally list-decodable. Our approach uses high-dimensional probability. We extend this framework to apply to a large family of codes obtained through random operations.
In local-decoding, we use expander codes to construct locally-correctible linear codes with rate approaching 1. Until recently, such codes were conjectured not to exist, and before this work the only known constructions relied on algebraic, rather than probabilistic and combinatorial, methods.PhDMathematicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/108844/1/wootters_1.pd