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At least 361 records · Page 20

Fast decoding of a d(min) = 6 RS code

A method for high speed decoding a d sub min = 6 Reed-Solomon (RS) code is presented. Properties of the two byte error correcting and three byte error detecting RS code are discussed. Decoding using a quadratic equation is shown. Theorems and concomitant proofs are included to substantiate this decoding method.

Deng, H.↗

Performance Bounds on Two Concatenated, Interleaved Codes

A method has been developed of computing bounds on the performance of a code comprised of two linear binary codes generated by two encoders serially concatenated through an interleaver. Originally intended for use in evaluating the performances of some codes proposed for deep-space communication links, the method can also be used in evaluating the performances of short-block-length codes in other applications. The method applies, more specifically, to a communication system in which following processes take place: At the transmitter, the original binary information that one seeks to transmit is first processed by an encoder into an outer code (Co) characterized by, among other things, a pair of numbers (n,k), where n (n > k)is the total number of code bits associated with k information bits and n k bits are used for correcting or at least detecting errors. Next, the outer code is processed through either a block or a convolutional interleaver. In the block interleaver, the words of the outer code are processed in blocks of I words. In the convolutional interleaver, the interleaving operation is performed bit-wise in N rows with delays that are multiples of B bits. The output of the interleaver is processed through a second encoder to obtain an inner code (Ci) characterized by (ni,ki). The output of the inner code is transmitted over an additive-white-Gaussian- noise channel characterized by a symbol signal-to-noise ratio (SNR) Es/No and a bit SNR Eb/No. At the receiver, an inner decoder generates estimates of bits. Depending on whether a block or a convolutional interleaver is used at the transmitter, the sequence of estimated bits is processed through a block or a convolutional de-interleaver, respectively, to obtain estimates of code words. Then the estimates of the code words are processed through an outer decoder, which generates estimates of the original information along with flags indicating which estimates are presumed to be correct and which are found to be erroneous. From the perspective of the present method, the topic of major interest is the performance of the communication system as quantified in the word-error rate and the undetected-error rate as functions of the SNRs and the total latency of the interleaver and inner code. The method is embodied in equations that describe bounds on these functions. Throughout the derivation of the equations that embody the method, it is assumed that the decoder for the outer code corrects any error pattern of t or fewer errors, detects any error pattern of s or fewer errors, may detect some error patterns of more than s errors, and does not correct any patterns of more than t errors. Because a mathematically complete description of the equations that embody the method and of the derivation of the equations would greatly exceed the space available for this article, it must suffice to summarize by reporting that the derivation includes consideration of several complex issues, including relationships between latency and memory requirements for block and convolutional codes, burst error statistics, enumeration of error-event intersections, and effects of different interleaving depths. In a demonstration, the method was used to calculate bounds on the performances of several communication systems, each based on serial concatenation of a (63,56) expurgated Hamming code with a convolutional inner code through a convolutional interleaver. The bounds calculated by use of the method were compared with results of numerical simulations of performances of the systems to show the regions where the bounds are tight (see figure).

Moision, Bruce↗

Cyclic unequal error protection codes constructed from cyclic codes of composite length

The distance structure of cyclic codes of composite length was investigated. A lower bound on the minimum distance for this class of codes is derived. In many cases, the lower bound gives the true minimum distance of a code. Then the distance structure of the direct sum of two cyclic codes of composite length were investigated. It was shown that, under certain conditions, the direct-sum code provides two levels of error correcting capability, and hence is a two-level unequal error protection (UEP) code. Finally, a class of two-level UEP cyclic direct-sum codes and a decoding algorithm for a subclass of these codes are presented.

Lin, Shu↗

Efficient bit-error detecting code

Two highly reliable codes termed "Modified b-adjacent interleaving codes" provide fail-safe operation of launch processing and control system in which common memory is coordination point for interconnection of up to 64 minicomputers. Codes detect and correct bit errors in computer data transmission.

Hockenberger, R. W.↗

High-Performance, Low-Complexity Codes Researched for Communication Channels

NASA Lewis Research Center s Communications Technology Division has an ongoing program in the development of efficient channel coding schemes for satellite communications applications. Through a university grant, as a part of this research, the University of Toledo is investigating the performance of turbocodes, which use parallel concatenation of non-systematic convolutional encoders with an interleaver. The error correcting capacity of these codes is close to the Shannon limit. The research emphasis is on the development of low-complexity, but higher rate (greater than one half), turbocodes and on the iterative decoding of block codes.

Kwatra, Subhash C.↗

Error Prevention Aid

In a complex computer environment there is ample opportunity for error, a mistake by a programmer, or a software-induced undesirable side effect. In insurance, errors can cost a company heavily, so protection against inadvertent change is a must for the efficient firm. The data processing center at Transport Life Insurance Company has taken a step to guard against accidental changes by adopting a software package called EQNINT (Equations Interpreter Program). EQNINT cross checks the basic formulas in a program against the formulas that make up the major production system. EQNINT assures that formulas are coded correctly and helps catch errors before they affect the customer service or its profitability.

Source record↗

Efficient program for decoding the /255, 223/ Reed-Solomon code over GF/2 to the 8th/ with both errors and erasures, using transform decoding

The paper deals with a method developed for decoding a (255, 223) Reed-Solomon code over GF(2 to the 8th) with both errors and erasures. The matrix of decoding times for correcting errors and erasures of the code using a simplified decoder is presented. It is shown that the algorithm proposed is faster by a factor of from three to seven.

Miller, R. L.↗

Phase-engineered bosonic quantum codes

Continuous-variable systems protected by bosonic quantum codes have emerged as a promising platform for quantum information. To date, the design of code words has centered on optimizing the state occupation in the relevant basis to generate the distance needed for error correction. Here, we show tuning the phase degree of freedom in the design of code words can affect, and potentially enhance, the protection against Markovian errors that involve excitation exchange with the environment. As illustrations, we first consider phase engineering bosonic codes with uniform spacing in the Fock basis that correct excitation loss with a Kerr unitary and show that these modified codes feature destructive interference between error code words and, with an adapted “two-level” recovery, the error protection is significantly enhanced. We then study protection against energy decay with the presence of mode nonlinearities and analyze the role of phase for optimal code designs. As a result, we extend the principle of phase engineering to bosonic codes defined in other bases and multiqubit codes, demonstrating its broad applicability in quantum error correction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sensor-Assisted Fault Mitigation in Quantum Computation

We propose a method for assisting fault mitigation in quantum computation through the use of sensors, co-located near physical qubits. Specifically, we consider using transition edge sensors co-located on silicon substrates hosting superconducting qubits to monitor for energy injection from ionizing radiation that has been demonstrated to increase decoherence in transmon qubits. We generalize from these two physical device concepts and explore the potential advantages of co-located sensors to assist fault mitigation in quantum computation. In the simplest scheme, co-located sensors beneficially assist rejection of calculations potentially affected by environmental disturbances. Investigating the potential computational advantage further required development of an extension to the standard formulation of quantum error correction. In a specific case the standard three-qubit, bit flip quantum correction code, we show that given a 20% overall error probability per qubit, approximately 90% of repeated calculation attempts are correctable. However, when sensor-detectable errors account for 45% of overall error probability, the use of colocated sensors uniquely associated with independent qubits, boosts the fraction of correct final-state calculations to 96% at the cost of rejecting 7% of repeated calculation attempts.

Orrell, John L.↗

Quantum repeaters based on concatenated bosonic and discrete-variable quantum codes

Abstract We propose an architecture of quantum-error-correction-based quantum repeaters that combines techniques used in discrete- and continuous-variable quantum information. Specifically, we propose to encode the transmitted qubits in a concatenated code consisting of two levels. On the first level we use a continuous-variable GKP code encoding the qubit in a single bosonic mode. On the second level we use a small discrete-variable code. Such an architecture has two important features. Firstly, errors on each of the two levels are corrected in repeaters of two different types. This enables for achieving performance needed in practical scenarios with a reduced cost with respect to an architecture for which all repeaters are the same. Secondly, the use of continuous-variable GKP code on the lower level generates additional analog information which enhances the error-correcting capabilities of the second-level code such that long-distance communication becomes possible with encodings consisting of only four or seven optical modes.

Physics↗

Properties of the new $ \mathcal{N} $ = 1 AdS 4 vacuum of maximal supergravity

The recent comprehensive numerical study of critical points of the scalar potential of four-dimensional N = 8, SO(8) gauged supergravity using Machine Learning software in [1] has led to a discovery of a new N = 1 vacuum with a triality-invariant SO(3) symmetry. Guided by the numerical data for that point, we obtain a consistent SO(3) × Z 2 -invariant truncation of the N = 8 theory to an N = 1 supergravity with three chiral multiplets. Critical points of the truncated scalar potential include both the N = 1 point as well as two new non-supersymmetric and perturbatively unstable points not found by previous searches. Studying the structure of the submanifold of SO(3) × Z 2 -invariant supergravity scalars, we find that it has a simple interpretation as a submanifold of the 14-dimensional Z $3\atop{2}$ -invariant scalar manifold (SU(1, 1)/U(1)) 7 , for which we find a rather remarkable superpotential whose structure matches the single bit error correcting (7, 4) Hamming code. This 14-dimensional scalar manifold contains approximately one quarter of the known critical points. We also show that there exists a smooth supersymmetric domain wall which interpolates between the new N = 1 AdS4 solution and the maximally supersymmetric AdS4 vacuum. Using holography, this result indicates the existence of an N = 1 RG flow from the ABJM SCFT to a new strongly interacting conformal fixed point in the IR.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Self testing and repairing computer - A concept

STAR computer has five redundant modular function units, fixed store, arithmetic, memory, input, and output. Each unit is connected to a diagnostic control unit, each is coded for error detection and error correction. Separation into function units permits assembly of many different systems from the set of units.

Avizienis, A. A.↗

Self-Checking Memory Interface

Memory-interface integrated circuit not only detects errors in data from other circuits but also detects errors within itself. Memory-interface chip encodes 16-bit words with Hamming code for single-error correction or double-error detection. Chip used in fault-tolerant computers under development by NASA.

Sievers, M. W.↗

VLSI single-chip (255,223) Reed-Solomon encoder with interleaver

The invention relates to a concatenated Reed-Solomon/convolutional encoding system consisting of a Reed-Solomon outer code and a convolutional inner code for downlink telemetry in space missions, and more particularly to a Reed-Solomon encoder with programmable interleaving of the information symbols and code correction symbols to combat error bursts in the Viterbi decoder.

Hsu, In-Shek↗

A (72, 36; 15) box code

A (72,36;15) box code is constructed as a 9 x 8 matrix whose columns add to form an extended BCH-Hamming (8,4;4) code and whose rows sum to odd or even parity. The newly constructed code, due to its matrix form, is easily decodable for all seven-error and many eight-error patterns. The code comes from a slight modification in the parity (eighth) dimension of the Reed-Solomon (8,4;5) code over GF(512). Error correction uses the row sum parity information to detect errors, which then become erasures in a Reed-Solomon correction algorithm.

Solomon, G.↗