Color codes are a class of topological quantum codes with a high error threshold and a large set of transversal encoded gates and are thus suitable for fault-tolerant quantum computation in two-dimensional architectur...
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Color codes are a class of topological quantum codes with a high error threshold and a large set of transversal encoded gates and are thus suitable for fault-tolerant quantum computation in two-dimensional architectures. Recently, computationally efficient decoders for the color codes were proposed. We describe an alternate efficient iterative decoder for topological color codes and apply it to the color code on the hexagonal lattice embedded on a torus. In numerical simulations, we find an error threshold of 7.8% for independent dephasing and spin-flip errors.
The newly released Distributed System Interface 3 ( DSI3) Bus Standard specification defines three modulation levels form which 16 valid symbols are coded. This complex structure is best decoded with symbol pattern re...
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The newly released Distributed System Interface 3 ( DSI3) Bus Standard specification defines three modulation levels form which 16 valid symbols are coded. This complex structure is best decoded with symbol pattern recognition. This paper proposes a simplification of the correlation score calculation that sharply reduces the required number of operations. Additionally, the paper describes how the pattern recognition is achieved using correlation scores and a decoding algorithm. The performance of this method is demonstrated by mean of simulations with different load models between the master and the sensors and varying noise injection on the channel. We prove than the pattern recognition can decode symbols without any error for up to 24dBm.
The observation of Zc(3900) by the BESIII Collaboration in the invariant mass spectrum of J/ψπ± in e+e−→J/ψπ+π− at the center of mass 4.260 GeV suggests the existence of a charged D¯D*+DD¯* molecu...
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The observation of Zc(3900) by the BESIII Collaboration in the invariant mass spectrum of J/ψπ± in e+e−→J/ψπ+π− at the center of mass 4.260 GeV suggests the existence of a charged D¯D*+DD¯* molecular state with I(JP)=1(1+), which could be an isovector brother of the famous X(3872) and an analogue of Zb(10610) claimed by the Belle Collaboration. We demonstrate that this observation provides strong evidence that the mysterious Y(4260) is a D¯D1(2420)+DD¯1(2420) molecular state. Especially, we show that the decay of this molecule naturally populates low momentum D¯D* pairs and leads unavoidably to a cusp at the D¯D* threshold. We discuss the signatures that distinguish such a D¯D* cusp from the presence of a true resonance.
We study the feasibility and capability of the kernel temporal difference (KTD)(lambda) algorithm for neural decoding. KTD(lambda) is an online, kernel-based learning algorithm, which has been introduced to estimate v...
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We study the feasibility and capability of the kernel temporal difference (KTD)(lambda) algorithm for neural decoding. KTD(lambda) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithmseeks a propermapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces.
The aim of this study is to build a linear decoding model that reveals the relationship between the movement information and the EOG (electrooculogram) data to online control a cursor continuously with blinks and eye ...
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The aim of this study is to build a linear decoding model that reveals the relationship between the movement information and the EOG (electrooculogram) data to online control a cursor continuously with blinks and eye pursuit movements. First of all, a blink detection method is proposed to reject a voluntary single eye blink or double-blink information from EOG. Then, a linear decoding model of time series is developed to predict the position of gaze, and the model parameters are calibrated by the RLS (Recursive Least Square) algorithm;besides, the assessment of decoding accuracy is assessed through cross-validation procedure. Additionally, the subsection processing, increment control, and online calibration are presented to realize the online control. Finally, the technology is applied to the volitional and online control of a cursor to hit the multiple predefined targets. Experimental results show that the blink detection algorithm performs well with the voluntary blink detection rate over 95%. Through combining the merits of blinks and smooth pursuit movements, the movement information of eyes can be decoded in good conformity with the average Pearson correlation coefficient which is up to 0.9592, and all signal-to-noise ratios are greater than 0. The novel system allows people to successfully and economically control a cursor online with a hit rate of 98%.
Frequency discrimination is a fundamental task of the auditory system. The mammalian inner ear, or cochlea, provides a place code in which different frequencies are detected at different spatial locations. However, a ...
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Frequency discrimination is a fundamental task of the auditory system. The mammalian inner ear, or cochlea, provides a place code in which different frequencies are detected at different spatial locations. However, a temporal code based on spike timing is also available: action potentials evoked in an auditory-nerve fiber by a low-frequency tone occur at a preferred phase of the stimulus-they exhibit phase locking-and thus provide temporal information about the tone's frequency. Humans employ this temporal information for discrimination of low frequencies. How might such temporal information be read out in the brain? Here we employ statistical and numerical methods to demonstrate that recurrent random neural networks in which connections between neurons introduce characteristic time delays, and in which neurons require temporally coinciding inputs for spike initiation, can perform sharp frequency discrimination when stimulated with phase-locked inputs. Although the frequency resolution achieved by such networks is limited by the noise in phase locking, the resolution for realistic values reaches the tiny frequency difference of 0.2% that has been measured in humans.
Reed Solomon codes are indeed an elegant illustration of a very practical application of abstract algebra. An interesting discovery was the fact that Euclid's algorithm for finding greatest common divisors of poly...
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Reed Solomon codes are indeed an elegant illustration of a very practical application of abstract algebra. An interesting discovery was the fact that Euclid's algorithm for finding greatest common divisors of polynomials, could be used for decoding these codes. In this article we explain this connection.
Network coding is a new direction in the information and communication theory. In this area algebraic coding for wire channels is based on Grassmann metric which is also called subspace metric. In the theory the main ...
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ISBN:
(纸本)9781479970124
Network coding is a new direction in the information and communication theory. In this area algebraic coding for wire channels is based on Grassmann metric which is also called subspace metric. In the theory the main problem is to construct codes with great cardinality and create fast decoding algorithms. Here, we deliver the low bound of subspace network codes. We calculate cardinality of some concrete codes and describe decoding algorithms. We show the interest cases where the cardinality approaches the upper bound.
Low-Density Parity-Check (LDPC) codes are applied into ultraviolet (UV) communication system. In this paper, LU decomposition algorithm is adopted as the channel coding method. Simulations are conducted to compare the...
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ISBN:
(纸本)9781728127644
Low-Density Parity-Check (LDPC) codes are applied into ultraviolet (UV) communication system. In this paper, LU decomposition algorithm is adopted as the channel coding method. Simulations are conducted to compare the performance of different LDPC decoding algorithms in UV communication system. The results show that the belief propagation (BP) based UV system has a better bit error ratio (BER) performance than the one with the bit flipping (BF) decoding algorithm. Moreover, communication system performance trade-offs among transmission distance, path loss, frame length and BER are studied.
The design and implementation of adaptive coded apertures (diffraction) has advanced significantly since the first SPIE conference on Adaptive Coded Aperture Imaging and Non-Imaging Sensors held in 2007. Core algorith...
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ISBN:
(纸本)9780819483140
The design and implementation of adaptive coded apertures (diffraction) has advanced significantly since the first SPIE conference on Adaptive Coded Aperture Imaging and Non-Imaging Sensors held in 2007. Core algorithmic concepts relating to coding and decoding techniques remain steeply based in its non-diffractive design origins. We discuss adaptive coded aperture imaging's current capabilities in light of recent advances as well as methods of improvement for future systems design. The advantages of implementing reconfigurable mask patterns compared to fixed ones will also be discussed, as well as potential improvement in angular resolution by means of reconfigurable masks.
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