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We study the problem of erasure correction (node repair) for regenerating codes defined on graphs wherein the cost of transmitting the information to the failed node depends on the graphical distance from this node to the helper vertices of the graph. The information passed to the failed node from the helpers traverses several vertices of the graph, and savings in communication complexity can be attained if the intermediate vertices process the information rather than simply relaying it toward the failed node. We derive simple information-theoretic bounds on the amount of information communicated between the nodes in the course of the repair. Next we show that Minimum Storage Regenerating (MSR) codes can be modified to perform the intermediate processing, thereby attaining the lower bound on the information exchange on the graph. We also consider node repair when the underlying graph is random, deriving conditions on the parameters that support recovery of the failed node with communication complexity smaller than required by the simple relaying. [ABSTRACT FROM AUTHOR]

We revise the proof of low-rate upper bounds on the reliability function of discrete memoryless channels for ordinary and list-decoding schemes, in particular Berlekamp and Blinovsky’s zero-rate bound, as well as Blahut’s bound for low rates. The available proofs of the zero-rate bound devised by Berlekamp and Blinovsky are somehow complicated in that they contain in one form or another some “non-standard” procedures or computations. Here we follow Blinovsky’s idea of using a Ramsey-theoretic result by Komlós, and we complement it with some missing steps to present a proof which is rigorous and easier to inspect. Furthermore, we show how these techniques can be used to fix an error that invalidated the proof of Blahut’s low-rate bound, which is here presented in an extended form for list decoding and for general channels. [ABSTRACT FROM AUTHOR]

In this article, we propose an adaptation of the algorithmic reduction theory of lattices to binary codes. This includes the celebrated LLL algorithm (Lenstra, Lenstra, Lovasz, 1982), as well as adaptations of associated algorithms such as the Nearest Plane Algorithm of Babai (1986). Interestingly, the adaptation of LLL to binary codes can be interpreted as an algorithmic version of the bound of Griesmer (1960) on the minimal distance of a code. Using these algorithms, we demonstrate—both with a heuristic analysis and in practice—a small polynomial speed-up over the Information-Set Decoding algorithm of Lee and Brickell (1988) for random binary codes. This appears to be the first such speed-up that is not based on a time-memory trade-off. The above speed-up should be read as a very preliminary example of the potential of a reduction theory for codes, for example in cryptanalysis. [ABSTRACT FROM AUTHOR]

We consider noisy communications and storage systems that are hampered by varying offset of unknown magnitude such as low-frequency signals of unknown amplitude added to the sent signal. We study and analyze a new detection method whose error performance is independent of both unknown base offset and offset’s slew rate. The new method requires, for a codeword length $n\geq 12$ , less than 1.5 dB more noise margin than Euclidean distance detection. The relationship with constrained codes based on mass-centered codewords and the new detection method is discussed. [ABSTRACT FROM AUTHOR]

We present an explicit and efficient algebraic construction of capacity-achieving list decodable codes with both constant alphabet and constant list sizes. More specifically, for any $R \in (0,1)$ and $\epsilon >0$ , we give an algebraic construction of an infinite family of error-correcting codes of rate $R$ , over an alphabet of size $(1/\epsilon)^{O(1/\epsilon ^{2})}$ , that can be list decoded from a $(1-R-\epsilon)$ -fraction of errors with list size at most $\exp (\mathrm {poly}(1/ \epsilon))$. Moreover, the codes can be encoded in time $\mathrm {poly}(1/ \epsilon,n)$ , the output list is contained in a linear subspace of dimension at most $\mathrm {poly}(1/ \epsilon)$ , and a basis for this subspace can be found in time $\mathrm {poly}(1 /\epsilon, n)$. Thus, both encoding and list decoding can be performed in fully polynomial-time $\mathrm {poly}(1/ \epsilon,n)$ , except for pruning the subspace and outputting the final list which takes time $\exp (\mathrm {poly}(1/ \epsilon)) \cdot \mathrm {poly} (n)$. In contrast, prior explicit and efficient constructions of capacity-achieving list decodable codes either required a much higher complexity in terms of $1/ \epsilon $ (and were additionally much less structured), or had super-constant alphabet or list sizes. Our codes are quite natural and structured. Specifically, we use algebraic-geometric (AG) codes with evaluation points restricted to a subfield, and with the message space restricted to a (carefully chosen) linear subspace. Our main observation is that the output list of AG codes with subfield evaluation points is contained in an affine shift of the image of a block-triangular-Toeplitz (BTT) matrix, and that the list size can potentially be reduced to a constant by restricting the message space to a BTT evasive subspace, which is a large subspace that intersects the image of any BTT matrix in a constant number of points. We further show how to explicitly construct such BTT evasive subspaces, based on the explicit subspace designs of Guruswami and Kopparty (Combinatorica, 2016), and composition. [ABSTRACT FROM AUTHOR]

Resistive memories, such as phase change memories and resistive random access memories have attracted significant attention in recent years due to their better scalability, speed, rewritability, and yet non-volatility. However, their limited endurance is still a major drawback that has to be improved before they can be widely adapted in large-scale systems. In this work, in order to reduce the wear out of the cells, we propose a new coding scheme, called endurance-limited memories (ELM) codes, that increases the endurance of these memories by limiting the number of cell programming operations. Namely, an $\ell $ -change $t$ -write ELM code is a coding scheme that allows to write $t$ messages into some $n$ binary cells while guaranteeing that each cell is programmed at most $\ell $ times. In case $\ell =1$ , these codes coincide with the well-studied write-once memory (WOM) codes. We study some models of these codes which depend upon whether the encoder knows on each write the number of times each cell was programmed, knows only the memory state, or even does not know anything. For the decoder, we consider these similar three cases. We fully characterize the capacity regions and the maximum sum-rates of three models where the encoder knows on each write the number of times each cell was programmed. In particular, it is shown that in these models the maximum sum-rate is $\log \sum _{i=0}^{\ell } {\binom{t }{ i}}$. We also study and expose the capacity regions of the models where the decoder is informed with the number of times each cell was programmed. Finally we present the most practical model where the encoder read the memory before encoding new data and the decoder has no information about the previous states of the memory. [ABSTRACT FROM AUTHOR]

This study considers the unconditional smooth Rényi entropy proposed by Renner and Wolf [ASIACRYPT, 2005], the smooth conditional Rényi entropy proposed by Kuzuoka [IEEE Trans. Inf. Th., 66(3), 1674–1690, 2020], and a novel quantity which we term the conditional smooth-⋆ entropy. The latter two quantities can be specialized to the first in the absence of side-information. We explore the operational roles of these smooth Rényi entropies by establishing one-shot coding theorems for several information-theoretic problems, including Campbell’s source coding problem, the Arıkan–Massey guessing problem, and the Bunte–Lapidoth task encoding problem. We consider these problems in cases where the errors are non-vanishing and for each problem, we consider two error formalisms: the average and maximum error criteria, where the averaging and maximization are taken with respect to the side-information. Using the one-shot coding theorems, we conclude that Kuzuoka’s smooth conditional Rényi entropy and the conditional smooth-⋆ entropy are the solutions to the problems involving the average and maximum error criteria, respectively. Furthermore, we examine asymptotic expansions of these entropies when the underlying source with its side-information is stationary and memoryless. Applying our asymptotic expansions to the one-shot coding theorems, we derive various fundamental limits for these problems. We show that, under non-degenerate settings, the first-order fundamental limits differ under the average and maximum error criteria. This is in contrast to a different but related setting considered by the present authors [IEEE Trans. Inf. Th., 66(12), 7565–7587, 2020], for variable-length conditional source coding allowing errors, in which the first-order terms are identical but the second-order terms are different under these error criteria. [ABSTRACT FROM AUTHOR]

A novel fault-tolerant computation technique based on array Belief Propagation (BP)-decodable XOR (BP-XOR) codes is proposed for distributed matrix-matrix multiplication. The proposed scheme is shown to be configurable and suited for modern hierarchical compute architectures such as Graphical Processing Units (GPUs) equipped with multiple nodes, whereby each has many small independent processing units with increased core-to-core communications. The proposed scheme is shown to outperform a few of the well–known earlier strategies in terms of total end-to-end execution time while in presence of slow nodes, called stragglers. This performance advantage is due to the careful design of array codes which distributes the encoding operation over the cluster (slave) nodes at the expense of increased master-slave communication. An interesting trade-off between end-to-end latency and total communication cost is precisely described. In addition, to be able to address an identified problem of scaling stragglers, an asymptotic version of array BP-XOR codes based on projection geometry is proposed at the expense of some computation overhead. A thorough latency analysis is conducted for all schemes to demonstrate that the proposed scheme achieves order-optimal computation in both the sublinear as well as the linear regimes in the size of the computed product from an end-to-end delay perspective. [ABSTRACT FROM AUTHOR]

We propose a new model of asynchronous batch codes that allow for parallel recovery of information symbols from a coded database in an asynchronous manner, i.e. when requests arrive at random times and they take varying time to process. We show that the graph-based batch codes studied by Rawat et al. are asynchronous. Further, we demonstrate that hypergraphs of Berge girth larger or equal to 4, respectively larger or equal to 3, yield graph-based asynchronous batch codes, respectively private information retrieval (PIR) codes. We prove a hypergraph-theoretic proposition that the maximum number of hyperedges in a hypergraph of a fixed Berge girth equals the quantity in a certain generalization of the hypergraph-theoretic (6,3)-problem, first posed by Brown, Erdős and Sós. We then apply the constructions and bounds by Erdős, Frankl and Rödl about this generalization of the (6,3)-problem, known as the ($3\varrho $ -3, $\varrho $)-problem, to obtain batch code constructions and bounds on the redundancy of the graph-based asynchronous batch and PIR codes. We derive bounds on the optimal redundancy of several families of asynchronous batch codes with the query size $t=2$. In particular, we show that the optimal redundancy $\rho (k)$ of graph-based asynchronous batch codes of dimension $k$ for $t=2$ is $2\sqrt {k}$. Moreover, for graph-based asynchronous batch codes with $t \ge 3$ , $\rho (k) = O\left ({{k}^{1/(2-\epsilon)}}\right)$ for any small $\epsilon >0$. [ABSTRACT FROM AUTHOR]

New asymptotic upper bounds are presented on the rate of sequences of locally repairable codes (LRCs) with a prescribed relative minimum distance and locality over a finite field $F$. The bounds apply to LRCs in which the recovery functions are linear; in particular, the bounds apply to linear LRCs over $F$. The new bounds are shown to improve on previously published results, especially when the repair groups are disjoint, namely, they form a partition of the set of coordinates. [ABSTRACT FROM AUTHOR]

We derive an upper bound on the reliability function of mismatched decoding for zero-rate codes. The bound is based on a result by Komlós that shows the existence of a subcode with certain symmetry properties. The bound is shown to coincide with the expurgated exponent at rate zero for a broad family of channel-decoding metric pairs. [ABSTRACT FROM AUTHOR]

We study the fundamental problem of index coding under an additional privacy constraint that requires each receiver to learn nothing more about the collection of messages beyond its demanded messages from the server and what is available to it as side information. To enable such private communication, we allow the use of a collection of independent secret keys, each of which is shared amongst a subset of users and is known to the server. The goal is to study properties of the key access structures that make the problem feasible and then design encoding and decoding schemes efficient in the size of the server transmission as well as the sizes of the secret keys. We call this the private index coding problem. We begin by characterizing the key access structures that make private index coding feasible. We also give conditions to check if a given linear scheme is a valid private index code. For up to three users, we characterize the rate region of feasible server transmission and key rates, and show that all feasible rates can be achieved using scalar linear coding and time sharing; we also show that scalar linear codes are sub-optimal for four receivers. The outer bounds used in the case of three users are extended to arbitrary number of users and seen as a generalized version of the well-known polymatroidal bounds for the standard non-private index coding. We also show that the presence of common randomness and private randomness does not change the rate region. Furthermore, we study the case where the server has the ability to multicast to any subset of users, and demonstrate how this flexibility can be used to provide privacy and characterize the minimum number of server multicasts required. [ABSTRACT FROM AUTHOR]

We study private classical communication over quantum multiple-access channels. For an arbitrary number of transmitters, we derive a regularized expression of the capacity region. In the case of degradable channels, we establish a single-letter expression for the best achievable sum-rate and prove that this quantity also corresponds to the best achievable sum-rate for quantum communication over degradable quantum multiple-access channels. In our achievability result, we decouple the reliability and privacy constraints, which are handled via source coding with quantum side information and universal hashing, respectively. Hence, we also establish that the multi-user coding problem under consideration can be handled solely via point-to-point coding techniques. As a by-product of independent interest, we derive a distributed leftover hash lemma against quantum side information that ensures privacy in our achievability result. [ABSTRACT FROM AUTHOR]

Physical platforms such as trapped ions suffer from coherent noise that does not follow a simple stochastic model. Stochastic errors in quantum systems occur randomly but coherent errors are more damaging since they can accumulate in a particular direction. We consider coherent noise acting transversally, giving rise to an effective error which is a $Z$ -rotation on each qubit by some angle $\theta $. Rather than address coherent noise through active error correction, we investigate passive mitigation through decoherence free subspaces. In the language of stabilizer codes, we require the noise to preserve the code space, and to act trivially (as the logical identity operator) on the protected information. Thus, we develop necessary and sufficient conditions for all transversal $Z$ -rotations to preserve the code space of a stabilizer code. These conditions require the weight- $2~Z$ -stabilizers to cover all the qubits that are in the support of the $X$ -component of some stabilizer. Furthermore, the weight- $2~Z$ -stabilizers generate a direct product of single-parity-check codes with even block length. By adjusting the sizes of these components, we are able to construct a large family of QECC codes oblivious to coherent noise, one that includes the $[[4L^{2}, 1, 2L]]$ Shor codes. The Shor codes are examples of constant excitation codes, where logical qubits are encoded as a code state that is a sum of physical states indexed by binary vectors with the same weight. Constant excitation codes are oblivious to coherent noise since a transversal $Z$ -rotation acts as a global phase. We prove that a CSS code is oblivious to coherent noise if and only if it is a constant excitation code, and that if the code is error-detecting, then the (constant) weights in different cosets of the $X$ -stabilizers are identical. [ABSTRACT FROM AUTHOR]

In this work, we present linear exact repair schemes for one or two erasures in decreasing monomial-Cartesian codes (DM-CC), a family of codes which provides a framework for polar codes. In the case of two erasures, the positions of the erasures should satisfy a certain restriction. We present families of augmented Reed-Muller (ARM) and augmented Cartesian codes (ACar) which are families of evaluation codes obtained by strategically adding vectors to Reed-Muller and Cartesian codes, respectively. We develop repair schemes for one or two erasures for these families of augmented codes. Unlike the repair scheme for two erasures of DM-CC, the repair scheme for two erasures for the augmented codes has no restrictions on the positions of the erasures. When the dimension and base field are fixed, we give examples where ARM and ACar codes provide a lower bandwidth (resp., bitwidth) in comparison with Reed-Solomon (resp., Hermitian) codes. When the length and base field are fixed, we give examples where ACar codes provide a lower bandwidth in comparison with ARM. Finally, we analyze the asymptotic behavior when the augmented codes achieve the maximum rate. [ABSTRACT FROM AUTHOR]

We consider a complex Gaussian wiretap channel with finite-resolution analog-to-digital converters (ADCs) at both the legitimate receiver and the eavesdropper. For this channel, we show that a positive secrecy rate is always achievable as long as the channel gains at the legitimate receiver and at the eavesdropper are different, regardless of the quantization levels of the ADCs. For the achievability, we first consider the case of the one-bit ADCs at the legitimate receiver and apply a binary input distribution where the two input points have the same phase when the channel gain at the legitimate receiver is less than that at the eavesdropper, and otherwise the opposite phase. Then the result is generalized for the case of arbitrary finite-resolution ADCs at the legitimate receiver by translating the input distribution appropriately. We also provide numerical lower bounds on the achievable secrecy rates, and analyze the tendency of the secrecy rates according to the channel difference, the power constraint, and the quantization levels for some cases. For the special case of the real Gaussian wiretap channel with one-bit ADCs at both the legitimate receiver and the eavesdropper, we show that our choice of phase does not lose any optimality for the Wyner code. [ABSTRACT FROM AUTHOR]

A family of error-correcting codes is list-decodable from error fraction $p$ if, for every code in the family, the number of codewords in any Hamming ball of fractional radius $p$ is less than some integer $L$. It is said to be list-recoverable for input list size $\ell $ if for every sufficiently large subset of at least $L$ codewords, there is a coordinate where the codewords take more than $\ell $ values. In this work, we study the list size of random linear codes for both list-decoding and list-recovery as the rate approaches capacity. We show the following claims hold with high probability over the choice of the code (below $q$ is the alphabet size, and $ \varepsilon > 0$ is the gap to capacity). (1) A random linear code of rate $1 - \log _{q}(\ell) - \varepsilon $ requires list size $L \ge \ell ^{\Omega (1/ \varepsilon)}$ for list-recovery from input list size $\ell $. (2) A random linear code of rate $1 - h_{q}(p) - \varepsilon $ requires list size $L \ge \left \lfloor{ {h_{q}(p)/ \varepsilon +0.99}}\right \rfloor $ for list-decoding from error fraction $p$. (3) A random binary linear code of rate $1 - h_{2}(p) - \varepsilon $ is list-decodable from average error fraction $p$ with list size with $L \leq \left \lfloor{ {h_{2}(p)/ \varepsilon }}\right \rfloor + 2$. Our lower bounds follow by exhibiting an explicit subset of codewords so that this subset—or some symbol-wise permutation of it—lies in a random linear code with high probability. Our upper bound follows by strengthening a result of (Li, Wootters, 2018). [ABSTRACT FROM AUTHOR]

Minkowski proved that any $n$ -dimensional lattice of unit determinant has a nonzero vector of Euclidean norm at most $\sqrt {n}$ ; in fact, there are $2^{\Omega (n)}$ such lattice vectors. Lattices whose minimum distances come close to Minkowski’s bound provide excellent sphere packings and error-correcting codes in ${\mathbb {R}}^{n}$. The focus of this work is a certain family of efficiently constructible $n$ -dimensional lattices due to Barnes and Sloane, whose minimum distances are within an $O(\sqrt {\log n})$ factor of Minkowski’s bound. Our primary contribution is a polynomial-time algorithm that list decodes this family to distances approaching $1/\sqrt {2}$ of the minimum distance. The main technique is to decode Reed-Solomon codes under error measured in the Euclidean norm, using the Koetter-Vardy “soft decision” variant of the Guruswami-Sudan list-decoding algorithm. [ABSTRACT FROM AUTHOR]

We consider the problem of (almost) lossless separate encodings and joint decoding of two correlated discrete memoryless sources (DMSs), that is, the well-known Slepian-Wolf (S-W) source coding problem. Traditionally, ensembles of S–W codes are defined such that every bin of each $n$ –vector of each source is randomly drawn under the uniform distribution across the sets $\{0,1,\ldots,2^{nR_{X}}-1\}$ and $\{0,1,\ldots,2^{nR_{Y}}-1\}$ , where $R_{X}$ and $R_{Y}$ are the coding rates of the two sources, $X$ and $Y$ , respectively. In a few more recent works, where only one source, say, $X$ , is compressed and the other one, $Y$ , serves as side information available at the decoder, the scope is extended to variable–rate S–W (VRSW) codes, where the rate is allowed to depend on the type class of the source string, but still, the random–binning distribution is assumed uniform within the corresponding, type–dependent, bin index set. In this expository work, we investigate the role of the uniformity of the random binning distribution from the perspective of the trade-off between the reliability (defined in terms of the error exponent) and the compression performance (measured from the viewpoint of the source coding exponent). To this end, we study a much wider class of random–binning distributions, which includes the ensemble of VRSW codes as a special case, but it also goes considerably beyond. We first show that, with the exception of some pathological cases, the smaller ensemble, of VRSW codes, is as good as the larger ensemble in terms the trade-off between the error exponent and the source coding exponent. Notwithstanding this finding, the wider class of ensembles proposed is motivated in two ways. The first is that it outperforms VRSW codes in the above–mentioned pathological cases, and the second is that it allows robustness: in the event of a system failure that causes unavailability of the compressed bit–stream from one of the sources, it still allows reconstruction of the other source within some controllable distortion. [ABSTRACT FROM AUTHOR]

It is known that continuous variable quantum information cannot be protected against naturally occurring noise using Gaussian states and operations only. Noh et al. proposed bosonic oscillator-to-oscillator codes relying on non-Gaussian resource states as an alternative, and showed that these encodings can lead to a reduction of the effective error strength at the logical level as measured by the variance of the classical displacement noise channel. An oscillator-to-oscillator code embeds K logical bosonic modes (in an arbitrary state) into N physical modes by means of a Gaussian N-mode unitary and N-K auxiliary one-mode Gottesman-Kitaev-Preskill-states. Here we ask if – in analogy to qubit error-correcting codes – there are families of oscillator-to-oscillator codes with the following threshold property: They allow to convert physical displacement noise with variance below some threshold value to logical noise with variance upper bounded by any (arbitrary) constant. We find that this is not the case if encoding unitaries involving a constant amount of squeezing and maximum likelihood error decoding are used. We show a general lower bound on the logical error probability which is only a function of the amount of squeezing and independent of the number of modes. As a consequence, any physically implementable family of oscillator-to-oscillator codes combined with maximum likelihood error decoding does not admit a threshold. [ABSTRACT FROM AUTHOR]

A flag of codes $C_{0} \subsetneq C_{1} \subsetneq \cdots \subsetneq C_{s} \subseteq \mathbb {F}_{q} ^{n}$ is said to satisfy the isometry-dual property if there exists ${\mathbf{x}}\in (\mathbb {F}_{q}^{*})^{n}$ such that the code $C_{i}$ is x-isometric to the dual code $C_{s-i}^\perp $ for all $i=0,\ldots, s$. For $P$ and $Q$ rational places in a function field $\mathcal {F}$ , we investigate the existence of isometry-dual flags of codes in the families of two-point algebraic geometry codes $C_{\mathcal {L}}(D, a_{0}P+bQ)\subsetneq C_{\mathcal {L}}(D, a_{1}P+bQ)\subsetneq {\dots } \subsetneq C_{\mathcal {L}}(D, a_{s}P+bQ)$ , where the divisor $D$ is the sum of pairwise different rational places of $\mathcal {F}$ and $P, Q$ are not in $\mathop {\mathrm {supp}}\nolimits (D)$. We characterize those sequences in terms of $b$ for general function fields. We then apply the result to the broad class of Kummer extensions $\mathcal {F}$ defined by affine equations of the form $y^{m}=f(x)$ , for $f(x)$ a separable polynomial of degree $r$ , where $\gcd (r, m)=1$. For $P$ the rational place at infinity and $Q$ the rational place associated to one of the roots of $f(x)$ , and for $D$ an $Aut(\mathcal {F}/ \mathbb {F}_{q})$ -invariant sum of rational places of $\mathcal {F}$ , such that $P, Q \notin \mathop {\mathrm {supp}}\nolimits D$ , it is shown that the flag of two-point algebraic geometry codes has the isometry-dual property if and only if $m$ divides $2b+1$. At the end we illustrate our results by applying them to two-point codes over several well know function fields. [ABSTRACT FROM AUTHOR]

Suppose that $\mathcal {P}$ is a property that may be satisfied by a random code $C \subset \Sigma ^{n}$. For example, for some $p \in (0,1)$ , $\mathcal {P}$ might be the property that there exist three elements of $C$ that lie in some Hamming ball of radius $pn$. We say that $R^{\ast}$ is the threshold rate for $\mathcal {P}$ if a random code of rate $R^{\ast} + \varepsilon $ is very likely to satisfy $\mathcal {P}$ , while a random code of rate $R^{\ast} - \varepsilon $ is very unlikely to satisfy $\mathcal {P}$. While random codes are well-studied in coding theory, even the threshold rates for relatively simple properties like the one above are not well understood. We characterize threshold rates for a rich class of properties. These properties, like the example above, are defined by the inclusion of specific sets of codewords which are also suitably “symmetric.” For properties in this class, we show that the threshold rate is in fact equal to the lower bound that a simple first-moment calculation obtains. Our techniques not only pin down the threshold rate for the property $\mathcal {P}$ above, they give sharp bounds on the threshold rate for list-recovery in several parameter regimes, as well as an efficient algorithm for estimating the threshold rates for list-recovery in general. [ABSTRACT FROM AUTHOR]

We present methods for computing the distance from a Boolean polynomial on $m$ variables of degree $m-3$ (i.e., a member of the Reed–Muller code $RM(m-3, m)$) to the space of lower-degree polynomials ($RM(m-4, m)$). The methods give verifiable certificates for both the lower and upper bounds on this distance. By applying these methods to representative lists of polynomials, we show that the covering radius of $RM(4,8)$ in $RM(5,8)$ is 26 and the covering radius of $RM(5,9)$ in $RM(6,9)$ is between 28 and 32 inclusive, and we get improved lower bounds for higher $m$. We also apply our methods to various polynomials in the literature, thereby improving the known bounds on the distance from 2-resilient polynomials to $RM(m-4, m)$. [ABSTRACT FROM AUTHOR]

We construct and analyze a family of low-density parity check (LDPC) quantum codes with a linear encoding rate, distance scaling as $n^\epsilon $ for $\epsilon > 0$ and efficient decoding schemes. The code family is based on tessellations of closed, four-dimensional, hyperbolic manifolds, as first suggested by Guth and Lubotzky. The main contribution of this work is the construction of suitable manifolds via finite presentations of Coxeter groups, their linear representations over Galois fields and topological coverings. We establish a lower bound on the encoding rate $k/n$ of $13/72 = 0.180\ldots $ and we show that the bound is tight for the examples that we construct. Numerical simulations give evidence that parallelizable decoding schemes of low computational complexity suffice to obtain high performance. These decoding schemes can deal with syndrome noise, so that parity check measurements do not have to be repeated to decode. Our data is consistent with a threshold of around 4% in the phenomenological noise model with syndrome noise in the single-shot regime. [ABSTRACT FROM AUTHOR]

This article discusses the security of McEliece-like encryption schemes using subspace subcodes of Reed–Solomon codes, i.e. subcodes of Reed–Solomon codes over ${\mathbb {F}_{q^{m}}}$ whose entries lie in a fixed collection of ${\mathbb {F}_{q}}$ –subspaces of ${\mathbb {F}_{q^{m}}}$. These codes appear to be a natural generalisation of Goppa and alternant codes and provide a broader flexibility in designing code based encryption schemes. For the security analysis, we introduce a new operation on codes called the twisted product which yields a polynomial time distinguisher on such subspace subcodes as soon as the chosen ${\mathbb {F}_{q}}$ –subspaces have dimension larger than $m/2$. From this distinguisher, we build an efficient attack which in particular breaks some parameters of a recent proposal due to Khathuria, Rosenthal and Weger. [ABSTRACT FROM AUTHOR]

In this work, two practical concepts related to private information retrieval (PIR) are introduced and coined full support-rank PIR and strongly linear PIR. Being of full support-rank is a technical, yet natural condition required to prove a converse result for a capacity expression and satisfied by almost all currently known capacity-achieving schemes, while strong linearity is a practical requirement enabling implementation over small finite fields with low subpacketization degree. Then, the capacity of MDS-coded, linear, full support-rank PIR in the presence of colluding servers is derived, as well as the capacity of symmetric, linear PIR with colluding, adversarial, and nonresponsive servers for the recently introduced concept of matched randomness. This positively settles the capacity conjectures stated by Freij-Hollanti et al. and Tajeddine et al. in the presented cases. It is also shown that, further restricting to strongly-linear PIR schemes with deterministic linear interference cancellation, the so-called star product scheme proposed by Freij-Hollanti et al. is essentially optimal and induces no capacity loss. [ABSTRACT FROM AUTHOR]

A minimax converse for the identification via channels is derived. By this converse, a general formula for the identification capacity, which coincides with the transmission capacity, is proved without the assumption of the strong converse property. Furthermore, the optimal second-order coding rate of the identification via channels is characterized when the type I error probability is non-vanishing and the type II error probability is vanishing. Our converse is built upon the so-called partial channel resolvability approach; however, the minimax argument enables us to circumvent a flaw reported in the literature. [ABSTRACT FROM AUTHOR]

Error-correcting codes over sets, with applications to DNA storage, are studied. The DNA-storage channel receives a set of sequences, and produces a corrupted version of the set, including sequence loss, symbol substitution, symbol insertion/deletion, and limited-magnitude errors in symbols. Various parameter regimes are studied. New bounds on code parameters are provided, which improve upon known bounds. New codes are constructed, at times matching the bounds up to lower-order terms or small constant factors. [ABSTRACT FROM AUTHOR]

Several applications in communication, control, and learning require approximating target distributions to within small informational divergence. The additional requirement of invertibility usually leads to using encoders that are one-to-one mappings, also known as distribution matchers. However, even the best one-to-one encoders have divergences that grow logarithmically with the block length. To overcome this limitation, an encoder is proposed that has an invertible one-to-many mapping and a low-rate random number generator (RNG). Two algorithms are developed to design the mapping by assigning strings in either a most-likely first or least-likely first order. Both algorithms give information rates approaching the entropy of the target distribution with exponentially decreasing divergence and with vanishing RNG rate in the block length. [ABSTRACT FROM AUTHOR]

We give a construction of quantum LDPC codes of dimension $\Theta (\log N)$ and distance $\Theta (N/\log N)$ as the code length $N\to \infty $. Using a product of chain complexes this construction also provides a family of quantum LDPC codes of distance $\Omega (N^{1-\alpha /2}/\log N)$ and dimension $\Omega (N^\alpha \log N)$ , where $0 \le \alpha < 1$. We also introduce and study a new operation called lifted product, which naturally generalizes the product operations for quantum codes and chain complexes. Moreover, as a simple byproduct of our results on quantum codes, we obtain a new result on classical codes. We show that for any fixed $R < 1$ there exists an asymptotically good family of classical quasi-cyclic LDPC codes of rate at least $R$ with, in some sense, optimal circulant size $\Omega (N/\log N)$ as the code length $N\to \infty $. [ABSTRACT FROM AUTHOR]

Let $\mathcal {X}= \{x_{1},x_{2},\ldots, x_{q}\}$ and let $n(m,q,\ell)$ be the smallest $n$ for which there is a code $C \subseteq \mathcal {X} ^{n}$ of $m$ elements such that for every list $w_{1}, w_{2}, \ldots, w_{\ell +1}$ of distinct codewords from $C$ , there is a coordinate $j \in [n]$ such that $\{w_{1}[j], w_{2}[j], \ldots, w_{\ell +1}[j]\} = \mathcal {X}$. We show that there is a constant $A>0$ such that for $\epsilon < 1/5$ , for all large $q$ and large enough $m$ ($m>q^{5}$), we have $n(m,q, \lceil \epsilon q\ln {q}\rceil) \geq \exp {(Aq^{1-5\epsilon })}\log _{2}{m}$. This bound has consequences for the zero-error list-decoding capacity of the $q/(q-1)$ channel studied by Elias (1988). Our result implies that for $A$ and $\epsilon $ as above, the zero-error list-decoding capacity of the $q/(q-1)$ channel with list-size $\epsilon q\ln {q}$ is at most $\exp (-Aq^{1-5\epsilon })$ , that is, it falls exponentially as $q$ increases. This confirms a conjecture of Chakraborty et al. (2006). [ABSTRACT FROM AUTHOR]

We give a complete answer to the following basic question: “What is the maximal fraction of deletions or insertions tolerable by $q$ -ary list-decodable codes with non-vanishing information rate?” This question has been open even for binary codes, including the restriction to the binary insertion-only setting, where the best-known result was that a $\gamma \leq 0.707$ fraction of insertions is tolerable by some binary code family. For any desired $\varepsilon > 0$ , we construct a family of binary codes of positive rate which can be efficiently list-decoded from any combination of $\gamma $ fraction of insertions and $\delta $ fraction of deletions as long as $\gamma + 2\delta \leq 1 - \varepsilon $. On the other hand, for any $\gamma, \delta $ with $\gamma + 2\delta = 1$ list-decoding is impossible. Our result thus precisely characterizes the feasibility region of binary list-decodable codes for insertions and deletions. We further generalize our result to codes over any finite alphabet of size $q$. Surprisingly, our work reveals that the feasibility region for $q>2$ is not the natural generalization of the binary bound above. We provide tight upper and lower bounds that precisely pin down the feasibility region, which turns out to have a $(q-1)$ -piece-wise linear boundary whose $q$ corner-points lie on a quadratic curve. The main technical work in our results is proving the existence of code families of sufficiently large size with good list-decoding properties for any combination of $\delta,\gamma $ within the claimed feasibility region. We achieve this via an intricate analysis of codes introduced by [Bukh and Ma, 2014]. Finally, we give a simple yet powerful concatenation scheme for list-decodable insertion-deletion codes which transforms any such (non-efficient) code family (with vanishing information rate) into an efficiently decodable code family with constant rate. [ABSTRACT FROM AUTHOR]

The subblock energy-constrained codes (SECCs) and sliding window-constrained codes (SWCCs) have recently attracted attention due to various applications in communication systems such as simultaneous energy and information transfer. In a SECC, each codeword is divided into smaller non-overlapping windows, called subblocks, and every subblock is constrained to carry sufficient energy. In a SWCC, however, the energy constraint is enforced over every window. In this work, we focus on the binary channel, where sufficient energy is achieved theoretically by using relatively high weight codes, and study the bounded SECCs and bounded SWCCs, where the weight in every window is bounded between a minimum and maximum number. Particularly, we focus on the cases of parameters that there is no rate loss, i.e. the channel capacity is one, and propose two methods to construct capacity-approaching codes with low redundancy and linear-time complexity, based on Knuth’s balancing technique and sequence replacement technique. These methods can be further extended to construct SECCs and SWCCs. For certain codes parameters, our methods incur only one redundant bit. We also impose the minimum distance constraint for error correction capability of the designed codes, which helps to reduce the error propagation during decoding as well. [ABSTRACT FROM AUTHOR]

This study investigates the fundamental limits of variable-length compression in which prefix-free constraints are not imposed (i.e., one-to-one codes are studied) and non-vanishing error probabilities are permitted. Due in part to a crucial relation between the variable-length and fixed-length compression problems, our analysis requires a careful and refined analysis of the fundamental limits of fixed-length compression in the setting where the error probabilities are allowed to approach either zero or one polynomially in the blocklength. To obtain the refinements, we employ tools from moderate deviations and strong large deviations. Finally, we provide the third-order asymptotics for the problem of variable-length compression with non-vanishing error probabilities. We show that unlike several other information-theoretic problems in which the third-order asymptotics are known, for the problem of interest here, the third-order term depends on the permissible error probability. [ABSTRACT FROM AUTHOR]

Lifted Reed-Solomon and multiplicity codes are classes of codes, constructed from specific sets of $m$ -variate polynomials. These codes allow for the design of high-rate codes that can recover every codeword or information symbol from many disjoint sets. Recently, the underlying approaches have been combined for the bi-variate case to construct lifted multiplicity codes, a generalization of lifted codes that can offer further rate improvements. We continue the study of these codes by first establishing new lower bounds on the rate of lifted Reed-Solomon codes for any number of variables $m$ , which improve upon the known bounds for any $m\ge 4$. Next, we use these results to provide lower bounds on the rate and distance of lifted multiplicity codes obtained from polynomials in an arbitrary number of variables, which improve upon the known results for any $m\ge 3$. Specifically, we investigate a subcode of a lifted multiplicity code formed by the linear span of $m$ -variate monomials whose restriction to an arbitrary line in ${\mathbb {F}}_{q}^{m}$ is equivalent to a low-degree univariate polynomial. We find the tight asymptotic behavior of the fraction of such monomials when the number of variables $m$ is fixed and the alphabet size $q=2^\ell $ is large. Using these results, we give a new explicit construction of batch codes utilizing lifted Reed-Solomon codes. For some parameter regimes, these codes have a better trade-off between parameters than previously known batch codes. Further, we show that lifted multiplicity codes have a better trade-off between redundancy and the number of disjoint recovering sets for every codeword or information symbol than previously known constructions, thereby providing the best known PIR codes for some parameter regimes. Additionally, we present a new local self-correction algorithm for lifted multiplicity codes. [ABSTRACT FROM AUTHOR]

Motivated by an application to database linear querying, such as private information-retrieval protocols, we suggest a fundamental property of linear codes– the generalized covering radius. The generalized covering-radius hierarchy of a linear code characterizes the trade-off between storage amount, latency, and access complexity, in such database systems. Several equivalent definitions are provided, showing this as a combinatorial, geometric, and algebraic notion. We derive bounds on the code parameters in relation with the generalized covering radii, study the effect of simple code operations, and describe a connection with generalized Hamming weights. [ABSTRACT FROM AUTHOR]

Exponential error bounds achievable by universal coding and decoding are derived for frame-asynchronous discrete memoryless multiple access channels with two senders, via the method of subtypes, a refinement of the method of types. An empirical entropy decoder is employed. A key tool is an improved packing lemma, that overcomes the technical difficulty caused by codeword repetitions via an induction based new argument. The asymptotic form of the bounds admits numerical evaluation. This demonstrates that error exponents achievable by synchronous transmission can be superseded via controlled asynchronism, i.e. a deliberate shift of the codewords. [ABSTRACT FROM AUTHOR]

Two algorithms for the classification of linear codes over finite fields are presented. One of the algorithms is based on canonical augmentation and the other one on lattice point enumeration. New classification results over fields with 2, 3 and 4 elements are obtained. [ABSTRACT FROM AUTHOR]

We investigate fat projective linear codes over ${\mathbb Z}_{p^{m}}$ , $m\geqslant 2$ , with two nonzero homogeneous weights (“two-weight codes”), building on the graph theory approach developed by Delsarte for codes over fields. Our main result is the classification of such codes under the additional assumption that the columns of a generator matrix of the code determine a cap in the projective Hjelmslev geometry $\mathop {\mathrm {PHG}}\nolimits (k-1, {\mathbb Z}_{p^{m}})$. This generalizes a result on projective two weight codes with dual distance at least four (Calderbank, 1982). The proof relies on a careful analysis of a certain strongly regular graph built on the cosets of the dual code, and on an interpretation of its parameters in terms of projective Hjelmslev geometry. [ABSTRACT FROM AUTHOR]

Consider the following communication scenario. An encoder observes a stochastic process and causally decides when and what to transmit about it, under a constraint on the expected number of bits transmitted per second. A decoder uses the received codewords to causally estimate the process in real time. The encoder and the decoder are synchronized in time. For a class of continuous Markov processes satisfying regularity conditions, we find the optimal encoding and decoding policies that minimize the end-to-end estimation mean-square error under the rate constraint. We show that the optimal encoding policy transmits a 1-bit codeword once the process innovation passes one of two thresholds. The optimal decoder noiselessly recovers the last sample from the 1-bit codewords and codeword-generating time stamps, and uses it to decide the running estimate of the current process, until the next codeword arrives. In particular, we show the optimal causal code for the Ornstein-Uhlenbeck process and calculate its distortion-rate function. Furthermore, we show that the optimal causal code also minimizes the mean-square cost of a continuous-time control system driven by a continuous Markov process and controlled by an additive control signal. [ABSTRACT FROM AUTHOR]

We present a new systematic approach to constructing spherical codes in dimensions $2^{k}$ , based on Hopf foliations. Using the fact that a sphere $S^{2n-1}$ is foliated by manifolds $S_{\cos \eta }^{n-1} \times S_{\sin \eta }^{n-1}$ , $\eta \in [0,\pi /2]$ , we distribute points in dimension $2^{k}$ via a recursive algorithm from a basic construction in $\mathbb {R}^{4}$. Our procedure outperforms some current constructive methods in several small-distance regimes and constitutes a compromise between achieving a large number of codewords for a minimum given distance and effective constructiveness with low encoding computational cost. Bounds for the asymptotic density are derived and compared with other constructions. The encoding process has storage complexity $O(n)$ and time complexity $O(n \log n)$. We also propose a sub-optimal decoding procedure, which does not require storing the codebook and has time complexity $O(n \log n)$. [ABSTRACT FROM AUTHOR]

An $(n,k,\ell)$ -vector MDS code over a field $\mathbb {F}$ is a $\mathbb {F}$ -linear subspace of $(\mathbb {F}^\ell)^{n}$ of dimension $k\ell $ , such that any $k$ (vector) symbols of the codeword suffice to determine the remaining $r=n-k$ (vector) symbols. The length $\ell $ of each codeword symbol is called the sub-packetization of the code. Such a code is called minimum storage regenerating (MSR), if any single symbol of a codeword can be recovered by downloading $\ell /r$ field elements (which is known to be the minimum possible) from each of the other symbols. MSR codes are attractive for use in distributed storage systems, and by now a variety of ingenious constructions of MSR codes are available. However, they all suffer from exponentially large sub-packetization $\ell \gtrsim r^{k/r}$. Our main result is an almost tight lower bound showing that for an MSR code, one must have $\ell \geqslant \exp (\Omega (k/r))$. Previously, a lower bound of $\approx \exp (\sqrt {k/r})$ , and a tight lower bound for a restricted class of “optimal access” MSR codes, were known. [ABSTRACT FROM AUTHOR]

We study the codes of the title by the CRT method, that decomposes such codes into constituent codes, which are shorter codes over larger alphabets. Criteria on these constituent codes for self-duality and linear complementary duality of the decomposed codes are derived. The special class of the one-generator codes is given a polynomial representation and exactly enumerated. In particular, we present some illustrative examples of binary optimal linear codes with respect to the Griesmer bound derived from the $\mathbb {Z}_{2} \mathbb {Z}_{4}$ -additive quasi-cyclic codes. [ABSTRACT FROM AUTHOR]

The sequence reconstruction problem corresponds to the model in which a sequence from some code is transmitted over several noisy channels that produce distinct outputs. Then, the channels’ outputs, received by the decoder, are used to recover the transmitted sequence, and the main problem under this paradigm is to calculate the minimum number of channels that enables unique reconstruction of the transmitted word. This problem is equivalent to finding the size of the largest intersection of channels’ outputs sets received after transmitting distinct codewords. Motivated by the error behavior observed in DNA storage systems, the present work extends the study of the reconstruction model to the case in which a binary word is transmitted over channels prone to substitutions, insertions, and deletions. Furthermore, we also study the size of the error balls generated by either one deletion and at most a fixed number of substitutions or one insertion and at most one substitution in a binary word. For the case of only substitutions, we present a decoder of optimal complexity, which improves upon a recent construction of such a decoder. Lastly, a simplification of that decoder is studied in case there are more channels than the minimum required number. [ABSTRACT FROM AUTHOR]