Information Capacity Research Articles

All-Metal Coding Metasurfaces for Broadband Terahertz RCS Reduction and Infrared Invisibility

With the rapid advancement of modern technology and radar detection systems, electromagnetic (EM) stealth technology has become increasingly significant, particularly in aircraft stealth and military radar applications. In this work, an all-metal metasurface is designed for broadband terahertz radar cross-section (RCS) reduction and infrared invisibility. The all-metal metasurface possesses extremely low infrared emissivity and high polarization conversion in the terahertz band. Through the joint simulation of MATLAB and CST, a genetic algorithm is used to optimize the random phase distribution of 2, 3, and 4-bit metasurfaces, so that the reflected wave is scattered to achieve broadband terahertz RCS reduction. Simulation results show that the metasurface can simultaneously achieve broadband terahertz RCS reduction in 3–5 THz and infrared invisibility in 24–38 THz (8–12.5 μm). The RCS reduction of the coding metasurface is greater than 10 dB compared to the metal plate, and the maximum RCS reduction of the 4-bit metasurface can reach 21.1 dB. Compared to the traditional design method, the proposed method can reduce time consumption and find the optimal result to achieve high performance. We believe the proposed method can provide significant guidance for surface coating in camouflage applications and opens up new possibilities for improving the information capacity of coding metasurfaces.

A minimum assumption approach to MEG sensor array design.

Objective.Our objective is to formulate the problem of the magnetoencephalographic (MEG) sensor array design as a well-posed engineering problem of accurately measuring the neuronal magnetic fields. This is in contrast to the traditional approach that formulates the sensor array design problem in terms of neurobiological interpretability the sensor array measurements.Approach.We use the vector spherical harmonics (VSH) formalism to define a figure-of-merit for an MEG sensor array. We start with an observation that, under certain reasonable assumptions, any array ofmperfectly noiseless sensors will attain exactly the same performance, regardless of the sensors' locations and orientations (with the exception of a negligible set of singularly bad sensor configurations). We proceed to the conclusion that under the aforementioned assumptions, the only difference between different array configurations is the effect of (sensor) noise on their performance. We then propose a figure-of-merit that quantifies, with a single number, how much the sensor array in question amplifies the sensor noise.Main results.We derive a formula for intuitively meaningful, yet mathematically rigorous figure-of-merit that summarizes how desirable a particular sensor array design is. We demonstrate that this figure-of-merit is well-behaved enough to be used as a cost function for a general-purpose nonlinear optimization methods such as simulated annealing. We also show that sensor array configurations obtained by such optimizations exhibit properties that are typically expected of 'high-quality' MEG sensor arrays, e.g. high channel information capacity.Significance.Our work paves the way toward designing better MEG sensor arrays by isolating the engineering problem of measuring the neuromagnetic fields out of the bigger problem of studying brain function through neuromagnetic measurements.

ATC-YOLOv5: Fruit Appearance Quality Classification Algorithm Based on the Improved YOLOv5 Model for Passion Fruits

Passion fruit, renowned for its significant nutritional, medicinal, and economic value, is extensively cultivated in subtropical regions such as China, India, and Vietnam. In the production and processing industry, the quality grading of passion fruit plays a crucial role in the supply chain. However, the current process relies heavily on manual labor, resulting in inefficiency and high costs, which reflects the importance of expanding the application of fruit appearance quality classification mechanisms based on computer vision. Moreover, the existing passion fruit detection algorithms mainly focus on real-time detection and overlook the quality-classification aspect. This paper proposes the ATC-YOLOv5 model based on deep learning for passion fruit detection and quality classification. First, an improved Asymptotic Feature Pyramid Network (APFN) is utilized as the feature-extraction network, which is the network modified in this study by adding weighted feature concat pathways. This optimization enhances the feature flow between different levels and nodes, allowing for the adaptive and asymptotic fusion of richer feature information related to passion fruit quality. Secondly, the Transformer Cross Stage Partial (TRCSP) layer is constructed based on the introduction of the Multi-Head Self-Attention (MHSA) layer in the Cross Stage Partial (CSP) layer, enabling the network to achieve a better performance in modeling long-range dependencies. In addition, the Coordinate Attention (CA) mechanism is introduced to enhance the network’s learning capacity for both local and non-local information, as well as the fine-grained features of passion fruit. Moreover, to validate the performance of the proposed model, a self-made passion fruit dataset is constructed to classify passion fruit into four quality grades. The original YOLOv5 serves as the baseline model. According to the experimental results, the mean average precision (mAP) of ATC-YOLOv5 reaches 95.36%, and the mean detection time (mDT) is 3.2 ms, which improves the mAP by 4.83% and the detection speed by 11.1%, and the number of parameters is reduced by 10.54% compared to the baseline, maintaining the lightweight characteristics while improving the accuracy. These experimental results validate the high detection efficiency of the proposed model for fruit quality classification, contributing to the realization of intelligent agriculture and fruit industries.

Comparative Study of the Atmospheric Gas Composition Detection Capabilities of FY-3D/HIRAS-I and FY-3E/HIRAS-II Based on Information Capacity

Fengyun-3E (FY-3E)/Hyperspectral Infrared Atmospheric Sounder-II (HIRAS-II) is an extension Fengyun-3D (FY-3D)/HIRAS-I. It is crucial to fully explore and analyze the detection capabilities of these two instruments for atmospheric gas composition. Based on the observed spectral data from the infrared hyperspectral detection instruments FY-3D/HIRAS-I and FY-3E/HIRAS-II, simulated radiance data and Jacobian matrices are obtained using the Rapid Radiative Transfer Model RTTOV (Radiative Transfer for TOVS (TIROS Operational Vertical Sounder)). By perturbing temperature (T), surface temperature (Tsurf), water vapor (H2O), ozone (O3), carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and nitrous oxide (N2O), the brightness temperature differences before and after the perturbations are calculated to analyze the sensitivity of temperature and various atmospheric gas components. The Improved Optimal Sensitivity Profile (OSP) algorithm is used to select the channels for atmospheric gas retrieval. The observation error covariance and background error covariance matrices are calculated, and then the information capacity is calculated, specifically the degrees of freedom for signal(DFS) and the entropy reduction (ER). Based on this, a comparative analysis is conducted on the information capacity of atmospheric water vapor and ozone components contained in the hyperspectral detection data from HIRAS-I and HIRAS-II instruments, respectively, to explore the retrieval capabilities of the two instruments for atmospheric gas components. We selected clear-sky data from the African oceanic region and the Chinese Yangtze River Delta terrestrial region for quantitative analysis of the information capacity of HIRAS-I and HIRAS-II. The results show that FY-3D/HIRAS-I and FY-3E/HIRAS-II exhibit different sensitivities to atmospheric gas components. In different experimental regions, temperature and water vapor show the most dramatic sensitivity changes, followed by ozone, methane, and nitrous oxide, while carbon monoxide and carbon dioxide exhibit the lowest variability. Regarding channel selection, HIRAS-II identifies more gas channels compared to HIRAS-I. The experiments concluded that HIRAS-II has a significantly higher information capacity than HIRAS-I, and the information capacity of atmospheric gas components varies across different experimental regions. Water vapor and ozone exhibit the highest information capacity, followed by nitrous oxide and methane, while carbon monoxide and carbon dioxide demonstrate the lowest capacity. The H2O ER (DFS) contained in FY-3E/HIRAS-II is 1.51 (0.35) higher than that in FY-3D/HIRAS-I, the O3 ER (DFS) in FY-3E/HIRAS-II is 1.51 (0.36) higher than that in FY-3D/HIRAS-I, while the N2O ER (DFS) in FY-3E/HIRAS-II is 0.17 (0.19) higher and the CH4 ER (DFS) is 0.07 (0.04) higher than that in FY-3D/HIRAS-I.

Flexible generation of high-performance superposed perfect vortex beams with metasurfaces

Vortex beams have been adopted as optical communications tools to improve the information capacity of free-space communication. Topological charge (TC) is a key parameter for analyzing vortex beams, specifically when defining wavelength division multiplexing and information coding capabilities. TC is typically proportional to the radial intensity profile and orbital angular momentum. The radial intensity profile of perfect vortex (PV) beams is TC-independent, thereby improving the efficiency of image processing and optical fiber transmission; however, PV beams generated in traditional ways are restricted in their degree of freedom for multiplexing and it can be difficult to distinguish PV beams with different TCs. Herein, we numerically simulate a single all-dielectric geometric metasurface to generate PV beams with intensity patterns corresponding to the TC. We increase the types of intensity modes by superposing specific polarization states of Laguerre–Gaussian beams, creating many options for optical communication transmission purposes.

Adaptive markets hypothesis and economic-institutional environment: a cross-country analysis

Purpose This study’s goal was to identify how several markets have developed over time and what determinants have influenced this process, based on adaptive markets hypothesis (AMH). In this regard, the authors consider that agents are driven by the seeking for abnormal returns to stay “alive” and their environment could somehow modify their decision-making processes, as well as influence the degree of efficiency of the market.Design/methodology/approach The authors collected the daily closing-of-the-market index from 50 countries, between 1990 and 2022. The sample includes emerging countries, developed countries and frontier markets. Then, the authors ran multilevel modeling using Hurst exponent as an informational efficiency metric estimated by two different moving windows: 500 and 1,250 observations (approximately 2 and 5 years).Findings The results indicate that the efficiency of the markets is not constant over time. The authors also have identified that markets follow a cyclical pattern of efficiency/inefficiency, and they are currently in a period of convergence to efficiency, possibly explained by the increase in computational capacity and speed of the available information to agents. In addition, this study identified that country characteristics are associated with market efficiency, considering institutional factors.Originality/value Studies of this nature contribute to the literature, considering the importance of better comprehension of market efficiency dynamics and their determinants, specially observing other theories on the relationship between information and markets (like AMH), which work with other investor assumptions than those used by efficient market hypothesis.

Wideband optical edge detection based on dielectric metasurface

Optical image edge detection manifests itself as the advantages of fast speed, low energy consumption, parallel operation, and large information capacity, playing a crucial role in object and image recognition in the realms of biology, medicine, and artificial intelligence. In this paper, a dielectric metasurface that can achieve object edge detection in the full visible band is proposed. By combining two optical differential methods referring to spatial spectrum-dependent transmission function and 4f system-based spatial spectrum phase shift, a tetratomic macropixel metasurface that enables polarization-correlated interference based on dual geometric phase modulation is designed, which can achieve object edge detection under 473, 530, and 633 nm wavelengths, and even under white light conditions. This coherent filtering metasurface operator provides a flexible approach for achieving wideband two-dimensional edge detection.

Cell-autonomous diversification in bacteria arises from calcium dynamics self-organizing at a critical point.

How dynamic bacterial calcium is regulated, with kinetics faster than typical mechanisms of cellular adaptation, is unknown. We discover bacterial calcium fluctuations are temporal-fractals resulting from a property known as self-organized criticality (SOC). SOC processes are poised at a phase transition separating ordered and chaotic dynamical regimes and are observed in many natural and anthropogenic systems. SOC in bacterial calcium emerges due to calcium channel coupling mediated via membrane voltage. Environmental or genetic perturbations modify calcium dynamics and the critical exponent suggesting a continuum of critical attractors. Moving along this continuum alters the collective information capacity of bacterial populations. We find that the stochastic transition from motile to sessile lifestyle is partially mediated by SOC-governed calcium fluctuations through the regulation of c-di-GMP. In summary, bacteria co-opt the physics of phase transitions to maintain dynamic calcium equilibrium, and this enables cell-autonomous population diversification during surface colonization by leveraging the stochasticity inherent at a boundary between phases.

Visual information processing through the interplay between fine and coarse signal pathways

Object recognition is often viewed as a feedforward, bottom-up process in machine learning, but in real neural systems, object recognition is a complicated process which involves the interplay between two signal pathways. One is the parvocellular pathway (P-pathway), which is slow and extracts fine features of objects; the other is the magnocellular pathway (M-pathway), which is fast and extracts coarse features of objects. It has been suggested that the interplay between the two pathways endows the neural system with the capacity of processing visual information rapidly, adaptively, and robustly. However, the underlying computational mechanism remains largely unknown. In this study, we build a two-pathway model to elucidate the computational properties associated with the interactions between two visual pathways. Specifically, we model two visual pathways using two convolution neural networks: one mimics the P-pathway, referred to as FineNet, which is deep, has small-size kernels, and receives detailed visual inputs; the other mimics the M-pathway, referred to as CoarseNet, which is shallow, has large-size kernels, and receives blurred visual inputs. We show that CoarseNet can learn from FineNet through imitation to improve its performance, FineNet can benefit from the feedback of CoarseNet to improve its robustness to noise; and the two pathways interact with each other to achieve rough-to-fine information processing. Using visual backward masking as an example, we further demonstrate that our model can explain visual cognitive behaviors that involve the interplay between two pathways. We hope that this study gives us insight into understanding the interaction principles between two visual pathways.

Spatially multiple-dimensional orbital angular momentum multiplexed holography for information encryption

Optical orbital angular momentum (OAM) holography provides a critical method for holographic information storage systems and experimentally demonstrates the feasibility of holographic multiplexation. Herein, the elliptic perfect optical vortex orbital angular momentum (EPOV-OAM) multiplexed holography is proposed and experimentally implemented. The mode selectivity of the ellipticity and rotation angle are investigated, respectively, which demonstrates that those parameters can be used as additional encoded degrees of freedom for the holographic multiplexing. The combination of the topological charge (TC), scaling factor, rotation angle, ellipticity can provide a four-dimensional multiplexed holography for information encryption. Furthermore, the minimum interval of TC for holographic multiplexing could reach 0.01. The method proposed here can enhance the information capacity and the security level of the holographic optical encryption systems.

Position‐aware pushing and grasping synergy with deep reinforcement learning in clutter

AbstractThe positional information of objects is crucial to enable robots to perform grasping and pushing manipulations in clutter. To effectively perform grasping and pushing manipulations, robots need to perceive the position information of objects, including the coordinates and spatial relationship between objects (e.g., proximity, adjacency). The authors propose an end‐to‐end position‐aware deep Q‐learning framework to achieve efficient collaborative pushing and grasping in clutter. Specifically, a pair of conjugate pushing and grasping attention modules are proposed to capture the position information of objects and generate high‐quality affordance maps of operating positions with features of pushing and grasping operations. In addition, the authors propose an object isolation metric and clutter metric based on instance segmentation to measure the spatial relationships between objects in cluttered environments. To further enhance the perception capacity of position information of the objects, the authors associate the change in the object isolation metric and clutter metric in cluttered environment before and after performing the action with reward function. A series of experiments are carried out in simulation and real‐world which indicate that the method improves sample efficiency, task completion rate, grasping success rate and action efficiency compared to state‐of‐the‐art end‐to‐end methods. Noted that the authors’ system can be robustly applied to real‐world use and extended to novel objects. Supplementary material is available at https://youtu.be/NhG\_k5v3NnM}{https://youtu.be/NhG\_k5v3NnM.

Impacts of a DUF2207 Family Protein on Streptococcus mutans Stress Tolerance Responses and Biofilm Formation.

Locus SMU.243 in Streptococcus mutans was annotated as a member of the DUF2207 family proteins highly conserved in all bacteria but with unknown function. To investigate its role in S. mutans physiology, a SMU.243-deficient mutant was constructed using allelic exchange mutagenesis, and the impacts of SMU.243 deletion on bacterial growth, stress tolerance response, and biofilm formation were analyzed. Compared to the wild-type UA159, S. mutans lacking SMU.243 displayed a reduced growth rate and a reduced overnight culture density (p < 0.01) when grown at low pH and in the presence of methyl viologen. Relative to the parent strain, the deficient mutant also had a reduced survival rate following incubation in a buffer of pH 2.8 (p < 0.01) and in a buffer containing hydrogen peroxide at 58 mM after 60 min (p < 0.001) and had a reduced capacity in biofilm formation especially in the presence of sucrose (p < 0.01). To study any ensuing functional/phenotypical links between SMU.243 and uppP, which is located immediately downstream of SMU.243 and encodes an undecaprenyl pyrophosphate phosphatase involved in recycling of carrier lipid undecaprenyl phosphate, a uppP deficient mutant was generated using allelic exchange mutagenesis. Unlike the SMU.243 mutant, deletion of uppP affected cell envelope biogenesis and caused major increases in susceptibility to bacitracin. In addition, two variant morphological mutants, one forming rough colonies and the other forming mucoid, smooth colonies, also emerged following the deletion of uppP. The results suggest that the SMU.243-encoded protein of the DUF2207 family in S. mutans plays an important role in stress tolerance response and biofilm formation, but unlike the downstream uppP, does not seem to be involved in cell envelope biogenesis, although the exact roles in S. mutans' physiology awaits further investigation.

Barriers to off-grid energy development: Evidence from a comparative survey of private sector energy service providers in Eastern Africa

In light of recent growth and falling costs of solar photovoltaic technology, this paper examines the barriers and opportunities facing off-grid development in Ethiopia, Kenya, Tanzania and Uganda, four countries whose off-grid sectors vary in maturity. We compare and link the perspectives of nearly 200 private companies to the development of the sector in each country, and measure trade-offs among different institutional designs for regulating and supporting off-grid investment. The survey reveals a set of common challenges but also considerable variation within and across countries. Development of the market is constrained by a lack of market information and technical capacity, insufficiently comprehensive regulation, and in specific countries, informal sector competition (Tanzania), the cost of doing business (Ethiopia), poor tariff policy (Tanzania), and lack of funding (Uganda). Moreover, firm responses emphasize the need for several policy supports: subsidy, financing, access to foreign exchange, technical assistance for regulatory matters, and capacity building. A discrete choice experiment clarifies these policy preferences, but reveals trade-offs as well as country differences. Though the off-grid sector is growing in all four countries, many policy and regulatory obstacles remain, and these will continue to challenge achievement of SDG7: Sustainable, modern energy for all.

Broadband plasmonic metasurface for spin-selective hologram in near-infrared band

Metasurface holography is a significant technology for the development of ultrathin optical devices. Multichannel holography has received close attention due to its applications in increasing information capacity and optical secret sharing. However, existing design methods for multichannel holography mainly focus on interleaved metasurface imaging in the vertical direction, which will inevitably suffer from the unexpected crosstalk affecting imaging quality. This work presents noninterleaved spin-selective metasurfaces by combining the geometric phase and the propagating phase. It can achieve independent phase control on two orthogonal circular polarizations and image at the desired angle. As a proof-of-concept, two broadband plasmonic metasurfaces are designed for multichannel holographic imaging in the near-infrared band (800–1200 nm). When two orthogonal circularly polarized waves are normally incident, the first plasmonic metasurface displays two different holograms in the vertical direction, thus achieving dual-channel imaging, and the second plasmonic metasurface can make two holograms deflected to the desired angle. It means that these two holograms can be displayed without overlapping for a linearly polarized wave, and the orientable three-channel holographic imaging is realized. Our work provides a general and compact scheme for multichannel orientable holographic imaging.

Spatial Scene Memories Are Biased Towards a Fixed Amount of Semantic Information.

Scene memory has known spatial biases. Boundary extension is a well-known bias whereby observers remember visual information beyond an image's boundaries. While recent studies demonstrate that boundary contraction also reliably occurs based on intrinsic image properties, the specific properties that drive the effect are unknown. This study assesses the extent to which scene memory might have a fixed capacity for information. We assessed both visual and semantic information in a scene database using techniques from image processing and natural language processing, respectively. We then assessed how both types of information predicted memory errors for scene boundaries using a standard rapid serial visual presentation (RSVP) forced error paradigm. A linear regression model indicated that memories for scene boundaries were significantly predicted by semantic, but not visual, information and that this effect persisted when scene depth was considered. Boundary extension was observed for images with low semantic information, and contraction was observed for images with high semantic information. This suggests a cognitive process that normalizes the amount of semantic information held in memory.

Centralized Regime Gaining Information Capacity: Can China Approach Innovation Frontiers?

ABSTRACT Why does the Chinese government have unsatisfactory policy performance in frontier innovation compared to its extraordinary achievements in the world factory model? Since the perspective of political system cannot provide an effective explanation, this article looks at this phenomenon from the viewpoint of information capacity. This article argues, the Chinese state has insufficient information capacity to promote frontier innovation—it has not developed an effective system to seize enough information through industrial practice to forge policies for frontier innovation. With the market-oriented reforms, the Chinese government has abandoned a top-down administrative coordinative system to organize science and technology (S&T) activities, and employed more market-oriented innovation policies. This article quantitatively assesses three main types of innovation policies, showing that the Chinese government has not achieved its expected goals of promoting frontier innovation. Interviews and long-term observations prove that the Chinese government lacks professional and penetrating capacities to seize and interpret information through industrial practice, and to effectively formulate and implement innovation policies—especially those aiming at frontier technologies with more complex information. This article sheds light on the relationship between the state and the market in the new era and state capacity building for technology and industrial policies.

Models of criterion evaluation of the image processing systems effectiveness

The criteria used to evaluate the effectiveness of image processing systems are investigated in the article. The requirements for performance criteria are analyzed. Private criteria which are used for image processing systems are selected and justified. Such parameters as performance, system cost, hardware costs characterize the system itself and depend on its specific type. It was shown that the information capacity, the probability of completing the task, and the accuracy of the image processing algorithm are the main criteria that characterize the quality of the processing method. It is shown that such a reliability criterion as normalized root mean square error best meets the requirements of efficiency criteria. Criteria models that are based on the normalized root mean square error in relation to discrete images have been studied. The simulation results and obtained dependences of cost functions on the speed of system information processing are given. The methodology for choosing a generalized criterion, which characterizes not only the information processing system, but also the methods used to implement this system was found. We obtained a generalized cost criterion, which arguments are the accuracy of system operation, speed of operation, and cost advantages.

The Knowledge of Improved Onion Production Practices of Farmers in Gaya, District in Bihar

A study was conducted in Gaya District of Bihar during the 2022-23 period to assess the level of knowledge among farmers regarding improved onion production practices. The study selected a total of 120 respondents from five villages within the Bodhgaya block, based on the high concentration of onion growers in the district. The data was collected through personnel interviews using a pre-structured interview schedule and subsequently analyzed using appropriate statistical methods. The findings revealed that the majority of respondents (62.5%) belonged to the middle age range, and 43.33% of them had marginal land holdings. Most respondents had a moderate level of extension contact, scientific orientation, risk orientation, and economic motivation. Additionally, 64.17% of the respondents exhibited a medium level of knowledge regarding onion production practices. The respondents displayed a good understanding of topics such as soil types, ploughing, farmyard manure (FYM) application, onion varieties, seed treatment, sowing time, nursery transplanting, seed rate, weeding and hoeing, and the suitable season for growing and harvesting onions. However, they had relatively less knowledge about seed treatment and nursery transplanting. Furthermore, factors such as age, educational qualifications, family size, housing patterns, land holdings, annual income, extension contact, source of information, scientific orientation, economic motivation, and risk-bearing capacity showed positive and significant correlations with the knowledge levels of onion growers. In summary, the study demonstrated that farmers in the Gaya District of Bihar had varying levels of knowledge regarding improved onion production practices. While they possessed a good understanding of certain aspects, there were areas where their knowledge could be further enhanced.

THE KUYTUN VALLEY AS AN EXOGEODYNAMIC TEST SITE FOR PRACTICING THE APPLICATION OF METHODOLOGY FOR INTERDISCIPLINARY RESEARCH IN THE SEDIMENTATION SETTINGS OF LOESS-LIKE COVER DEPOSITS IN THE LATE PLEISTOCENE TRANSBAIKALIA

An interdisciplinary research in the Late Quaternary loess-like cover deposits in the valley of the Kuytunka River (Western Transbaikalia) was aimed at reconstructing the conditions and dynamics of regional sedimentation. Particular attention is paid to assessing the information capacity of the methods involved therein: lithofacies analysis, grain-size analysis, and petromagnetic and lithochemical analyses. It is shown that the results of each method independently provide additional information on the processes of sedimentation, are not duplicated, and make it possible to obtain a full characterization of the factors and features of sedimentogenesis. It was found that the valley sedimentation was of cyclic character: warm (soil formation) periods changed to the periods of cooling-(accumulation of sandy-loamy strata); all processes occurred predominantly in semi-arid climate with slight fluctuations in humidity. The mode of the normal formation of a blanket of sedimentary material manifests itself in the structure and properties of deposits exposed on the southern slope of the valley (Kuytun-1 section). Intensive slope processes, and reworking and remixing of sediments on the gentle valley north-exposure slope by catastrophic flows (slope mudflows) and cryogenesis are reflected in the structure and properties of the deposits exposed in the Kuytun-2 section. There are shown the advantages of an integrated approach for detailing the structure of the sections, explaining the genesis of sediments, determining the most probable source areas for the sediment and modes of sediment transport, and reconstructing sedimentary environments.

Tunable holography with independent transflective information channels enabled by interleaved soft materials

Holography is promising to fully record and reconstruct various fundamental properties of light. However, the simultaneous realization of multifunctional holographic channels, prompt tunability and broadband working spectrum for holography remains challenging. Here, we propose and experimentally demonstrate a transflective holography scheme based on the interleaved soft materials of achiral and chiral liquid crystals (LCs). The desired phase profile is programmed into the tailored surface alignment of the achiral and chiral LCs by photopatterning, while the coexistence of such soft materials is configured by a micro-regional patterned polymer template. Correspondingly, a pair of independent holographic images is achieved along the transmission and reflection channels, which is also characterized by the distinctive response to the polarization of incidence. Benefitting from the excellent electrical responsiveness, the transmission holography can be conveniently tuned among a large spectral range under a mild voltage, and meanwhile the broadband working spectrum of reflection holography is well maintained. We expect this work to enrich the functionalities of LC holography and inspire more advances for the higher integration level, greater information capacity of holography.