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This paper presents constructions of DNA codes that satisfy biological and combinatorial constraints for DNA-based data storage systems. We introduce an algorithm that generates DNA blocks containing sequences that meet the required constraints for DNA codes. The constructed DNA sequences satisfy biological constraints: balanced GC-content, avoidance of secondary structures, and prevention of homopolymer runs.

DNA-based data storage systems face practical challenges due to the high cost of DNA synthesis. A strategy to address the problem entails encoding data via topological modifications of the DNA sugar-phosphate backbone. The DNA Punchcards system, which introduces nicks (cuts) in the DNA backbone, encodes only one bit per nicking site, limiting density. We propose DNA Tails, a storage paradigm that encodes nonbinary symbols at nicking sites by growing enzymatically synthesized single-stranded DNA of varied lengths.

The number of zeros and the number of ones in a binary string are referred to as the composition of the string, and the prefix-suffix compositions of a string are a multiset formed by the compositions of the prefixes and suffixes of all possible lengths of the string. In this work, we present binary codes of length n in which every codeword can be efficiently reconstructed from its erroneous prefix-suffix compositions with at most t composition errors.

This paper studies two problems that are motivated by the novel recent approach of composite DNA that takes advantage of the DNA synthesis property which generates a huge number of copies for every synthesized strand. Under this paradigm, every composite symbols does not store a single nucleotide but a mixture of the four DNA nucleotides. The first problem studies the expected number of strand reads in order to decode a composite strand or a group of composite strands.

Synchronization errors, arising from both synthesis and sequencing noise, present a fundamental challenge in DNA-based data storage systems. These errors are often modeled as insertion-deletion-substitution (IDS) channels, for which maximum-likelihood decoding is quite computationally expensive. In this work, we propose a data-driven approach based on neural polar decoders (NPDs) to design decoders with reduced complexity for channels with synchronization errors.

As a potential implementation of data storage using DNA molecules, multiple strands of DNA are stored unordered in a liquid container. When the data are needed, an array of DNA readers will sample the strands with replacement, producing a Poisson-distributed number of noisy reads for each strand. The primary challenge here is to design an algorithm that reconstructs data from these unsorted, repetitive, and noisy reads.

An m-uniform quantum state on n qubits is an entangled state in which every m-qubit subsystem is maximally mixed. Starting with an m-uniform state realized as the graph state associated with an m-regular graph, and a classical n,k,d≥m+1 binary linear code with certain additional properties, we show that pure [n,k,m+1]]2 quantum error-correcting codes (QECCs) can be constructed within the codeword stabilized (CWS) code framework. As illustrations, we construct pure [[22r-1,22r-2r-3,3]]2 and [[(24r-1)2,(24r-1)2-32r-7,5]]2 QECCs.

The standard approach to universal fault-tolerant quantum computing is to develop a general purpose quantum error correction mechanism that can implement a universal set of logical gates fault-tolerantly. Given such a scheme, any quantum algorithm can be realized fault-tolerantly by composing the relevant logical gates from this set. However, we know that quantum computers provide a significant quantum advantage only for specific quantum algorithms.

The number of degrees of freedom (NDoF) in a communication channel fundamentally limits the number of independent spatial modes available for transmitting and receiving information. Although the NDoF can be computed numerically for specific configurations using singular value decomposition (SVD) of the channel operator, this approach provides limited physical insight. In this paper, we introduce a simple analytical estimate for the NDoF between arbitrarily shaped transmitter and receiver regions in free space.