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We analyse the ergodic properties of quantum channels that are covariant with respect to diagonal orthogonal transformations. We prove that the ergodic behaviour of a channel in this class is essentially governed by a classical stochastic matrix. This allows us to exploit tools from classical ergodic theory to study quantum ergodicity of such channels. As an application of our analysis, we study dual unitary brickwork circuits which have recently been proposed as minimal models of quantum chaos in many-body systems. Upon imposing a local diagonal orthogonal invariance symmetry on these circuits, the long-term behaviour of spatio-temporal correlations between local observables in such circuits is completely determined by the ergodic properties of a channel that is covariant under diagonal orthogonal transformations. We utilize this fact to show that such symmetric dual unitary circuits exhibit a rich variety of ergodic behaviours, thus emphasizing their importance. [ABSTRACT FROM AUTHOR]

Divisive Normalization and the Wilson–Cowan equations are well-known influential models of nonlinear neural interaction (Carandini and Heeger in Nat Rev Neurosci 13(1):51, 2012; Wilson and Cowan in Kybernetik 13(2):55, 1973). However, they have been always treated as different approaches and have not been analytically related yet. In this work, we show that Divisive Normalization can be derived from the Wilson–Cowan dynamics. Specifically, assuming that Divisive Normalization is the steady state of the Wilson–Cowan differential equations, we find that the kernel that controls neural interactions in Divisive Normalization depends on the Wilson–Cowan kernel but also depends on the signal. A standard stability analysis of a Wilson–Cowan model with the parameters obtained from our relation shows that the Divisive Normalization solution is a stable node. This stability suggests the appropriateness of our steady state assumption. The proposed theory provides a mechanistic foundation for the suggestions that have been done on the need of signal-dependent Divisive Normalization in Coen-Cagli et al. (PLoS Comput Biol 8(3):e1002405, 2012). Moreover, this theory explains the modifications that had to be introduced ad hoc in Gaussian kernels of Divisive Normalization in Martinez-Garcia et al. (Front Neurosci 13:8, 2019) to reproduce contrast responses in V1 cortex. Finally, the derived relation implies that the Wilson–Cowan dynamics also reproduce visual masking and subjective image distortion, which up to now had been explained mainly via Divisive Normalization. [ABSTRACT FROM AUTHOR]

The darkness of the sky is a critical parameter for assessing the suitability of an astronomical site. Among various sources of light pollution, urban lights pose the most significant threat to ground-based optical astronomical and planetary observations. Quantitatively assessing the impact of urban lights with varying scales and fluxes is indispensable for selecting an ideal optical observation site. In order to quantitatively assess the changes in Night Sky Brightness (NSB) relative to the distance from urban areas and to establish a foundation for safeguarding the light environment at the newly developed Lenghu astronomical site on the Tibetan Plateau, we employed both a Sky Quality Meter and a pre-calibrated smartphone. These instruments were used to measure the NSB in the vicinity of two cities, Da Qaidam and Delingha, which vary in size and radiant flux, on the Tibetan Plateau. The findings indicate that the NSB around both cities decreases significantly as the distance from the city center increases, although the rate of decrease varies between the two locations. This decline can be effectively modeled using an exponential decay function. Notably, the influence of city lights on NSB becomes negligible at distances exceeding 30 km from Da Qaidam, while for Delingha, this distance extends to 50 km due to its larger city size and higher total radiant flux. The methodologies and results presented in this paper offer valuable insights for the selection of astronomical observation sites and the development of light pollution management policies. [ABSTRACT FROM AUTHOR]

The substitution box (S-box) is the core component of any block cipher that creates confusion in the ciphertext. This research contributes to creating a substitution box based on bent Boolean functions. Bent Boolean functions are constructed using the Maiorana–McFarland method and used as the coordinate functions of the substitution box. They are maximal nonlinear and inherently imbalanced, making them unsuitable for direct use in constructing a confusion component. The imbalance nature of the coordinate Boolean function directly impacts the bijective property of the nonlinear component. To create a bijective confusion component, we focus on mitigating the imbalance of each coordinate Boolean function. The methodology adopted is simple and efficient as compared to other heuristic techniques. By defining an empty matrix and putting bent Boolean functions side by side as matrix elements, we shape the initial 2 n × k sized substitution box, k ∈ (2 ,... , n) . We limit the number of occurrences of each possible outcome of initial 2 n × k substitution box to make a bijective n × n S-box. These small initial S-boxes lay a good foundation for constructing strong subsequent S-boxes. Experimental results based on the generation of 8 × 8 substitution box indicate that the suggested algorithm outperforms other competing heuristic approaches in nonlinearity, while maintaining sufficient performance in the strict avalanche criterion, bit-independence, linear and differential probability properties. The suggested nonlinear component is tested using well-known images from the literature, and the histogram analysis of the confused images demonstrates a high degree of randomness. [ABSTRACT FROM AUTHOR]

Muscles are stretched with bursts of spikes that come from motor neurons connected to the cerebellum through the spinal cord. Then, alpha motor neurons directly innervate the muscles to complete the motor command coming from upper biological structures. Nevertheless, classical robotic systems usually require complex computational capabilities and relative high-power consumption to process their control algorithm, which requires information from the robot's proprioceptive sensors. The way in which the information is encoded and transmitted is an important difference between biological systems and robotic machines. Neuromorphic engineering mimics these behaviors found in biology into engineering solutions to produce more efficient systems and for a better understanding of neural systems. This paper presents the application of a Spike-based Proportional-Integral-Derivative controller to a 6-DoF Scorbot ER-VII robotic arm, feeding the motors with Pulse-Frequency-Modulation instead of Pulse-Width-Modulation, mimicking the way in which motor neurons act over muscles. The presented frameworks allow the robot to be commanded and monitored locally or remotely from both a Python software running on a computer or from a spike-based neuromorphic hardware. Multi-FPGA and single-PSoC solutions are compared. These frameworks are intended for experimental use of the neuromorphic community as a testbed platform and for dataset recording for machine learning purposes. [ABSTRACT FROM AUTHOR]

At present, the spectrum correction method based on medical image restoration has the problems of low reconstruction accuracy and long calculation time. However, the method based on compressed sensing can use the sparse characteristics of medical images to improve the reconstruction performance of images. In this paper, a signal reconstruction algorithm based on composite cosine conjugate gradient smoothing L0 (CCGSL0) is proposed. Firstly, we construct a new smooth function family called composite cosine function family (FCCF), which can approximate the mathematical representation of L0 norm. Secondly, the conjugate gradient method (CGM) is used to form the FCCF-CGM optimization strategy to improve the signal reconstruction rate and image restoration accuracy. Finally, the block mechanism is used for parallel processing of the original signal to reduce the processing time of the signal, thereby greatly improving the speed of image restoration. In addition, the computed tomography images and magnetic resonance imaging images in Gaussian and Poisson noise environment were simulated. Experimental results show that CCGSL0 can improve image reconstruction accuracy by 0.4–1.6 dB and reduce reconstruction time by 30–70%. CCGSL0 has better robustness and can save more image signal details. [ABSTRACT FROM AUTHOR]

According to their strength, the tracing properties of a code can be categorized as frameproof, separating, IPP and TA. It is known that, if the minimum distance of the code is larger than a certain threshold then the TA property implies the rest. Silverberg et al. ask if there is some kind of tracing capability left when the minimum distance falls below the threshold. Under different assumptions, several papers have given a negative answer to the question. In this paper, further progress is made. We establish values of the minimum distance for which Reed-Solomon codes do not posses the separating property. [ABSTRACT FROM AUTHOR]