Information Theory and Reliable Communication

Rydberg atoms with principal quantum number $n⪢1$ have exaggerated atomic properties including dipole-dipole interactions that scale as ${n}^{4}$ and radiative lifetimes that scale as ${n}^{3}$. It was proposed a decade ago to take advantage of these properties to implement quantum gates between neutral atom qubits. The availability of a strong long-range interaction that can be coherently turned on and off is an enabling resource for a wide range of quantum information tasks stretching far beyond the original gate proposal. Rydberg enabled capabilities include long-range two-qubit gates, collective encoding of multiqubit registers, implementation of robust light-atom quantum interfaces, and the potential for simulating quantum many-body physics. The advances of the last decade are reviewed, covering both theoretical and experimental aspects of Rydberg-mediated quantum information processing.

Quantum information with Rydberg atoms

Sphere Packings, Lattices and Groups

We describe a simple and novel cryptographic construction that we call a fuzzy vault. Alice may place a secret value /spl kappa/ in a fuzzy vault and "lock" it using an unordered set A of elements from some public universe U. If Bob tries to "unlock" the vault using an unordered set B, he obtains /spl kappa/ only if B is close to A, i.e., only if A and B overlap substantially.

A fuzzy vault scheme

We describe a successive-cancellation list decoder for polar codes, which is a generalization of the classic successive-cancellation decoder of Arikan. In the proposed list decoder, up to L decoding paths are considered concurrently at each decoding stage. Simulation results show that the resulting performance is very close to that of a maximum-likelihood decoder, even for moderate values of L. Thus it appears that the proposed list decoder bridges the gap between successive-cancellation and maximum-likelihood decoding of polar codes. The specific list-decoding algorithm that achieves this performance doubles the number of decoding paths at each decoding step, and then uses a pruning procedure to discard all but the L “best” paths. In order to implement this algorithm, we introduce a natural pruning criterion that can be easily evaluated. Nevertheless, straightforward implementation still requires O(L · n2) time, which is in stark contrast with the O(n log n) complexity of the original successive-cancellation decoder. We utilize the structure of polar codes to overcome this problem. Specifically, we devise an efficient, numerically stable, implementation taking only O(L · n log n) time and O(L · n) space.

/pdf/list-decoding-of-polar-codes-18d63eiy9d.pdf

List decoding of polar codes

We show that the minimum distance d of a linear code is not approximable to within any constant factor in random polynomial time (RP), unless nondeterministic polynomial time (NP) equals RP. We also show that the minimum distance is not approximable to within an additive error that is linear in the block length n of the code. Under the stronger assumption that NP is not contained in random quasi-polynomial time (RQP), we show that the minimum distance is not approximable to within the factor 2/sup log1-/spl epsi//(n), for any /spl epsi/>0. Our results hold for codes over any finite field, including binary codes. In the process, we show that it is hard to find approximately nearest codewords even if the number of errors exceeds the unique decoding radius d/2 by only an arbitrarily small fraction /spl epsi/d. We also prove the hardness of the nearest codeword problem for asymptotically good codes, provided the number of errors exceeds (2/3)d. Our results for the minimum distance problem strengthen (though using stronger assumptions) a previous result of Vardy (1997) who showed that the minimum distance cannot be computed exactly in deterministic polynomial time (P), unless P = NP. Our results are obtained by adapting proofs of analogous results for integer lattices due to Ajtai (1998) and Micciancio (see SIAM J. Computing, vol.30, no.6, p.2008-2035, 2001). A critical component in the adaptation is our use of linear codes that perform better than random (linear) codes.

/pdf/hardness-of-approximating-the-minimum-distance-of-a-linear-4f6i4l7w0w.pdf

Hardness of approximating the minimum distance of a linear code

Recursive list decoding is considered for Reed-Muller (RM) codes. The algorithm repeatedly relegates itself to the shorter RM codes by recalculating the posterior probabilities of their symbols. Intermediate decodings are only performed when these recalculations reach the trivial RM codes. In turn, the updated lists of most plausible codewords are used in subsequent decodings. The algorithm is further improved by using permutation techniques on code positions and by eliminating the most error-prone information bits. Simulation results show that for all RM codes of length 256 and many subcodes of length 512, these algorithms approach maximum-likelihood (ML) performance within a margin of 0.1 dB. As a result, we present tight experimental bounds on ML performance for these codes

/pdf/soft-decision-decoding-of-reed-muller-codes-recursive-lists-2unkw3yvrc.pdf

Soft-decision decoding of Reed-Muller codes: recursive lists

Recursive decoding techniques are considered for Reed-Muller (RM) codes of growing length n and fixed order r. An algorithm is designed that has complexity of order nlogn and corrects most error patterns of weight up to n(1/2-/spl epsiv/) given that /spl epsiv/ exceeds n/sup -1/2r/. This improves the asymptotic bounds known for decoding RM codes with nonexponential complexity. To evaluate decoding capability, we develop a probabilistic technique that disintegrates decoding into a sequence of recursive steps. Although dependent, subsequent outputs can be tightly evaluated under the assumption that all preceding decodings are correct. In turn, this allows us to employ second-order analysis and find the error weights for which the decoding error probability vanishes on the entire sequence of decoding steps as the code length n grows.

/pdf/recursive-decoding-and-its-performance-for-low-rate-reed-4lkzbncv95.pdf

Recursive decoding and its performance for low-rate Reed-Muller codes

Recursive decoding techniques are considered for Reed-Muller (RM) codes of growing length $n$ and fixed order $r.$ An algorithm is designed that has complexity of order $n\log n$ and corrects most error patterns of weight up to $n(1/2-\varepsilon)$ given that $\varepsilon$ exceeds $n^{-1/2^{r}}.$ This improves the asymptotic bounds known for decoding RM codes with nonexponential complexity.

Recursive Decoding and Its Performance for Low-Rate Reed-Muller Codes

Soft-decision decoding is considered for general Reed-Muller (RM) codes of length n and distance d used over a memoryless channel. A recursive decoding algorithm is designed and its decoding threshold is derived for long RM codes. The algorithm has complexity of order nlnn and corrects most error patterns of the Euclidean weight of order radicn/lnn, instead of the decoding threshold radicd/2 of the bounded distance decoding. Also, for long RM codes of fixed rate R, the new algorithm increases 4/pi times the decoding threshold of its hard-decision counterpart

/pdf/soft-decision-decoding-of-reed-muller-codes-a-simplified-5gtb76z8fw.pdf

Ilya Dumer

Papers

Hardness of approximating the minimum distance of a linear code

Soft-decision decoding of Reed-Muller codes: recursive lists

Recursive decoding and its performance for low-rate Reed-Muller codes

Recursive Decoding and Its Performance for Low-Rate Reed-Muller Codes

Soft-decision decoding of Reed-Muller codes: a simplified algorithm