Ternary Syndrome Decoding with Large Weight

The Syndrome Decoding problem is at the core of many code-based cryptosystems. In this paper, we study ternary Syndrome Decoding in large weight. This problem has been introduced in the Wave signature scheme but has never been thoroughly studied. We perform an algorithmic study of this problem which results in an update of the Wave parameters. On a more fundamental level, we show that ternary Syndrome Decoding with large weight is a really harder problem than the binary Syndrome Decoding problem, which could have several applications for the design of code-based cryptosystems

Use of ERTS-1 data to access and monitor change in the west side of the San Joaquin Valley and central coastal zone of California

There are no author-identified significant results in this report

Fully-Functional Suffix Trees and Optimal Text Searching in BWT-runs Bounded Space

Indexing highly repetitive texts - such as genomic databases, software repositories and versioned text collections - has become an important problem since the turn of the millennium. A relevant compressibility measure for repetitive texts is r, the number of runs in their Burrows-Wheeler Transforms (BWTs). One of the earliest indexes for repetitive collections, the Run-Length FM-index, used O(r) space and was able to efficiently count the number of occurrences of a pattern of length m in the text (in loglogarithmic time per pattern symbol, with current techniques). However, it was unable to locate the positions of those occurrences efficiently within a space bounded in terms of r. In this paper we close this long-standing problem, showing how to extend the Run-Length FM-index so that it can locate the occ occurrences efficiently within O(r) space (in loglogarithmic time each), and reaching optimal time, O(m + occ), within O(r log log w ({\sigma} + n/r)) space, for a text of length n over an alphabet of size {\sigma} on a RAM machine with words of w = {\Omega}(log n) bits. Within that space, our index can also count in optimal time, O(m). Multiplying the space by O(w/ log {\sigma}), we support count and locate in O(dm log({\sigma})/we) and O(dm log({\sigma})/we + occ) time, which is optimal in the packed setting and had not been obtained before in compressed space. We also describe a structure using O(r log(n/r)) space that replaces the text and extracts any text substring of length ` in almost-optimal time O(log(n/r) + ` log({\sigma})/w). Within that space, we similarly provide direct access to suffix array, inverse suffix array, and longest common prefix array cells, and extend these capabilities to full suffix tree functionality, typically in O(log(n/r)) time per operation.Comment: submitted version; optimal count and locate in smaller space: O(r log log_w(n/r + sigma)

A New Large N Expansion for General Matrix-Tensor Models

We define a new large $N$ limit for general $\text{O}(N)^{R}$ or $\text{U}(N)^{R}$ invariant tensor models, based on an enhanced large $N$ scaling of the coupling constants. The resulting large $N$ expansion is organized in terms of a half-integer associated with Feynman graphs that we call the index. This index has a natural interpretation in terms of the many matrix models embedded in the tensor model. Our new scaling can be shown to be optimal for a wide class of non-melonic interactions, which includes all the maximally single-trace terms. Our construction allows to define a new large $D$ expansion of the sum over diagrams of fixed genus in matrix models with an additional $\text{O}(D)^{r}$ global symmetry. When the interaction is the complete vertex of order $R+1$, we identify in detail the leading order graphs for $R$ a prime number. This slightly surprising condition is equivalent to the complete interaction being maximally single-trace.Comment: 57 pages, 20 figures (additional discussion in Sec. 4.1.1. and additional figure (Fig. 5)

The problem with the SURF scheme

There is a serious problem with one of the assumptions made in the security proof of the SURF scheme. This problem turns out to be easy in the regime of parameters needed for the SURF scheme to work. We give afterwards the old version of the paper for the reader's convenience.Comment: Warning : we found a serious problem in the security proof of the SURF scheme. We explain this problem here and give the old version of the paper afterward