Compact Form Research Articles

Efficient ultra-broadband low-resolution astrophotonic spectrographs

Broadband low-resolution near-infrared spectrographs in a compact form are crucial for ground- and space-based astronomy and other fields of sensing. Astronomical spectroscopy poses stringent requirements including high efficiency, broad band operation (> 300 nm), and in some cases, polarization insensitivity. We present and compare experimental results from the design, fabrication, and characterization of broadband (1200 - 1650 nm) arrayed waveguide grating (AWG) spectrographs built using the two most promising low-loss platforms - Si3N4 (rectangular waveguides) and doped-SiO2 (square waveguides). These AWGs have a resolving power (λ/Δλ) of ∼200, free spectral range of ∼ 200-350 nm, and a small footprint of ∼ 50-100 mm2. The peak overall (fiber-chip-fiber) efficiency of the doped-SiO2 AWG was ∼ 79% (1 dB), and it exhibited a negligible polarization-dependent shift compared to the channel spacing. For Si3N4 AWGs, the peak overall efficiency in TE mode was ∼ 50% (3 dB), and the main loss component was found to be fiber-to-chip coupling losses. These broadband AWGs are key to enabling compact integrations such as multi-object spectrographs or dispersion back-ends for other astrophotonic devices such as photonic lanterns or nulling interferometers.

Hybrid Integrated Silicon Photonics Based on Nanomaterials

Integrated photonic platforms have rapidly emerged as highly promising and extensively investigated systems for advancing classical and quantum information technologies, since their ability to seamlessly integrate photonic components within the telecommunication band with existing silicon-based industrial processes offers significant advantages. However, despite this integration facilitating the development of novel devices, fostering fast and reliable communication protocols and the manipulation of quantum information, traditional integrated silicon photonics faces inherent physical limitations that necessitate a challenging trade-off between device efficiency and spatial footprint. To address this issue, researchers are focusing on the integration of nanoscale materials into photonic platforms, offering a novel approach to enhance device performance while reducing spatial requirements. These developments are of paramount importance in both classical and quantum information technologies, potentially revolutionizing the industry. In this review, we explore the latest endeavors in hybrid photonic platforms leveraging the combination of integrated silicon photonic platforms and nanoscale materials, allowing for the unlocking of increased device efficiency and compact form factors. Finally, we provide insights into future developments and the evolving landscape of hybrid integrated photonic nanomaterial platforms.

Review of Hardware Platforms for Designing of Internet of Things (IoT) system

Microcontrollers are pivotal components in the realm of the Internet of Things (IoT), providing necessary computational power, memory, and connectivity for a wide range of applications. This review explores the key characteristics of microcontrollers that make suitable for IoT, considering their wide use and new emerging models. Study delves into the fundamental features required for IoT applications, such as low power consumption, compact form factors, diverse connectivity options, and flexible I/O (input-output) capabilities. The review covers a spectrum of microcontroller families from leading manufacturers, assessing their performance, energy efficiency, scalability, and ease of integration with various external devices for automation purpose.

Reduction-based creative telescoping for definite summation of D-finite functions

Creative telescoping is an algorithmic method initiated by Zeilberger to compute definite sums by synthesizing summands that telescope, called certificates. We describe a creative telescoping algorithm that computes telescopers for definite sums of D-finite functions as well as the associated certificates in a compact form. The algorithm relies on a discrete analogue of the generalized Hermite reduction, or equivalently, a generalization of the Abramov-Petkovšek reduction. We provide a Maple implementation with good timings on a variety of examples.

Actively tunable laser action in GeSn nanomechanical oscillators.

Mechanical forces induced by high-speed oscillations provide an elegant way to dynamically alter the fundamental properties of materials such as refractive index, absorption coefficient and gain dynamics. Although the precise control of mechanical oscillation has been well developed in the past decades, the notion of dynamic mechanical forces has not been harnessed for developing tunable lasers. Here we demonstrate actively tunable mid-infrared laser action in group-IV nanomechanical oscillators with a compact form factor. A suspended GeSn cantilever nanobeam on a Si substrate is resonantly driven by radio-frequency waves. Electrically controlled mechanical oscillation induces elastic strain that periodically varies with time in the GeSn nanobeam, enabling actively tunable lasing emission at >2 μm wavelengths. By utilizing mechanical resonances in the radio frequency as a driving mechanism, this work presents wide-range mid-infrared tunable lasers with ultralow tuning power consumption.

A feature compression method based on similarity matching

In collaborative intelligent applications, it is attractive to split the neural network into two parts. The front part is deployed on an edge device and the remaining part on the cloud side. It is a promising approach to compress the intermediate features for high efficiency. In this paper, a novel feature compression method based on feature similarity matching is presented. According to the statistical characteristics of features, the noninformative features that are not sensitive to the compression distortion are determined. The similarity degree between the noninformative features and other features is calculated and the feature with the high similarity degree will be removed in the encoder and replaced by the noninformative features in the decoder. In addition, transformation is introduced to transform the features in a compact form to reduce the statistical redundancy. Without loss of generality, the image classification is taken as intelligent task to validate the effectiveness of the proposed method. Experimental results show that the proposed method can achieve higher compression efficiency in various bit rate. In comparison with different feature compression algorithms, at least 24% bitrate saving is obtained.

Novel solution strategies for multiparametric nonlinear optimization problems with convex objective function and linear constraints

AbstractThis paper expands the multiparametric quadratic programming (mp-QP) framework presented in Narciso et al. (Comput Chem Eng 164:107882, 2022. https://doi.org/10.1016/j.compchemeng.2022.107882) to the more general multiparametric nonlinear programming (mp-NLP) case. First, the vector of parameters in mp-NLP problems is recast so that a unique transformed parameter is implicitly assigned to each of the inequality constraints. Maps of critical regions in this transformed space of parameters feature a set of 1-dimensional parametric edges (two per inequality constraint), which then greatly facilitate solution calculation. In the mp-NLP case, however, parametric edges define nonlinear semi-infinite lines; this requires an adaptation to the mp-QP algorithm (deals with linear parametric edges only), to enable a suitable calculation path to the more general nonlinear case. Three routes are proposed to mp-NLPs: the first route delivers solutions in compact form (same format as in mp-QP) using a single reference point per edge; the second route delivers explicit solutions using a hybrid approach for critical region construction, where all active sets not detected in the parameters space are excluded from the solution (equivalent to first route concerning accuracy); the third route builds on the initial explicit solution and further partitions the parameters space until all solution fragments satisfy an error check. Five algorithms were coded for these routes, and tested in a large range of mp-NLP problems. These strategies enable significant improvements in terms of solution accuracy, algorithm efficiency, and interpretability when compared to the state-of-the-art mp-NLP algorithms.

Neural étendue expander for ultra-wide-angle high-fidelity holographic display

Holographic displays can generate light fields by dynamically modulating the wavefront of a coherent beam of light using a spatial light modulator, promising rich virtual and augmented reality applications. However, the limited spatial resolution of existing dynamic spatial light modulators imposes a tight bound on the diffraction angle. As a result, modern holographic displays possess low étendue, which is the product of the display area and the maximum solid angle of diffracted light. The low étendue forces a sacrifice of either the field-of-view (FOV) or the display size. In this work, we lift this limitation by presenting neural étendue expanders. This new breed of optical elements, which is learned from a natural image dataset, enables higher diffraction angles for ultra-wide FOV while maintaining both a compact form factor and the fidelity of displayed contents to human viewers. With neural étendue expanders, we experimentally achieve 64 × étendue expansion of natural images in full color, expanding the FOV by an order of magnitude horizontally and vertically, with high-fidelity reconstruction quality (measured in PSNR) over 29 dB on retinal-resolution images.

Monocular reconstruction of shapes of natural objects from orthographic and perspective images.

Human subjects were tested in perception of shapes of 3D objects. The subjects reconstructed 3D shapes by viewing orthographic and perspective images. Perception of natural shapes was very close to veridical and was clearly better than perception of random symmetrical polyhedra. Viewing perspective images led to only slightly better performance than viewing orthographic images. In order to account for subjects' performance, we elaborated the previous computational models of 3D shape reconstruction. The previous models used as constraints mirror-symmetry and 3D compactness. The critical additional constraint was the use of a secondary mirror-symmetry that exists in most natural shapes. It is known that two planes of mirror symmetry are sufficient for a unique and veridical shape reconstruction. We also generalized the model so that it applies to both orthographic and perspective images. The results of our experiment suggest that the human visual system uses two planes of symmetry in addition to two forms of 3D compactness. Performance of the new model was highly correlated with subjects' performance with both orthographic and perspective images, which supports the claim that the most important 3D shape constraints that are used by the human visual system have been identified.

Scattering matrix for chiral harmonic generation and frequency mixing in nonlinear metasurfaces

We generalize the concept of optical scattering matrix (S-matrix) to characterize harmonic generation and frequency mixing in planar metasurfaces in the limit of undepleted pump approximation. We show that the symmetry properties of such nonlinear S-matrix are determined by the metasurface symmetries at the macroscopic and microscopic scale. We demonstrate that for description of degenerate frequency mixing processes such as optical harmonic generation, the multidimensional S-matrix can be replaced with a reduced two-dimensional S-matrix. We show that for metasurfaces possessing specific point group symmetries, the selection rules determining the transformation of the reduced nonlinear S-matrix are simplified substantially and can be expressed in a compact form. We apply the developed approach to analyze chiral harmonic generation in nonlinear metasurfaces with various symmetries including rotational, inversion, in-plane mirror, and out-of-plane mirror symmetries. For each of those symmetries, we confirm the results of the developed analysis by full-wave numerical calculations. We believe our results provide a new paradigm for engineering nonlinear optical properties of metasurfaces which may find applications in active and nonlinear optics, biosensing, and quantum information processing.

Production and verification of novel Osmanthus hybrids

Osmanthus fragrans Lour. is prized for its fragrant, cool-season blooms, smooth leaves, and compact tree form; however, the species is limited in production and use to USDA Hardiness Zones 7 and higher. Increasing the total amount of genetic variability available for evaluation, selection, and breeding is foundational to the development of novel Osmanthus cultivars with increased cold-hardiness and improved ornamental characteristics such as high rooting rates, faster growth, fragrant flowers, and an evergreen or semi-evergreen habit. Hybridization among Osmanthus species should generate novel phenotypes and allow trait introgression among populations and breeding lines. The objectives of this study were to produce, verify, and evaluate Osmanthus hybrids by making controlled and open-pollinated crosses among Osmanthus species, using SSR markers to determine parentage of cross progeny, and comparing flowering, leaf shape, and form of hybrids offspring with parents. Fifty-eight of 66 progenies (88%) were assigned paternity at the 95% confidence level or above and 47 progenies (71%) were assigned paternity at the 99% confidence level. Novel Osmanthus hybrids were produced including O. armatus × O. fortunei, O. armatus × O. heterophyllus, and O. armatus × O. fragrans. Open-pollinated families increased in height an average of 204% and 159% per year in the first and second growing seasons, respectively. Male flower type was significantly associated with progeny flower type (χ2 = 17.5, p < 0.0001) while leaf margin was not associated with cross family (χ2 = 0.83, p = 0.84). Evaluation of more Osmanthus accessions and subsequent hybridizations will be necessary to introgress favorable genes and generate the variation necessary to expand the genus into new markets.

Computing a compact local Smith–McMillan form

We define a compact local Smith–McMillan form of a rational matrix R ( λ ) as the diagonal matrix whose diagonal elements are the nonzero entries of a local Smith-McMillan form of R ( λ ) . We show that a recursive rank search procedure, applied to a block-Toeplitz matrix built on the Laurent expansion of R ( λ ) around an arbitrary complex point λ 0 , allows us to compute a compact local Smith-McMillan form of that rational matrix R ( λ ) at the point λ 0 , provided we keep track of the transformation matrices used in the rank search. It also allows us to recover the root polynomials of a polynomial matrix and root vectors of a rational matrix, at an expansion point λ 0 . Numerical tests illustrate the promising performance of the resulting algorithm.

Resilient data‐driven asymmetric bipartite consensus for nonlinear multi‐agent systems against DoS attacks

AbstractIn this article, we study an unified resilient asymmetric bipartite consensus (URABC) problem for nonlinear multi‐agent systems with both cooperative and antagonistic interactions under denial‐of‐service (DoS) attacks. We first prove that the URABC problem is solved by stabilizing the neighborhood asymmetric bipartite consensus error. Then, we develop a distributed compact form dynamic linearization method to linearize the neighborhood asymmetric bipartite consensus error. By using an attack compensation mechanism to eliminate the adverse effects of DoS attacks and an extended discrete state observer to enhance the robustness against unknown dynamics, we finally propose a distributed resilient data‐driven adaptive control (DDAC) algorithm to solve the URABC problem. A numerical example validates the proposed results.

Magnetoacoustic waves in a partially ionized astrophysical plasma with the thermal misbalance: A two-fluid approach

We consider the propagation of magnetoacoustic (MA) and acoustic waves of various frequency ranges in a partially ionized plasma at an arbitrary angle to the magnetic field, taking into account the influence of heating, radiative, and thermo-conductive cooling, as well as ion-neutral collisions. A dispersion equation that describes the evolution of nine modes was obtained in a compact mathematical form using the two-fluid model. The number and type of propagating waves (modified fast and slow MA waves, MA waves in the ion component, acoustic waves in the neutral component, as well as isothermal MA and isothermal acoustic waves) vary in different frequency ranges depending on the parameters of the medium. Analytical expressions are found for the speed and damping rates of all these propagating waves, and it is shown how dispersion and damping are formed by three processes: thermal misbalance, ion-neutral collisions, and thermal conductivity. Comparison of analytical calculations of the velocity and damping rates of MA waves with the numerical solution of the dispersion relation under conditions characteristic of the low solar atmosphere and prominences showed high accuracy of the obtained analytical expressions. The strong influence of thermal misbalance caused by gasdynamic perturbations on the speed and damping rate of modified magnetoacoustic waves in a strongly coupled region is shown as well.

Design and Implementation of Low Power and High Data Rate Edge Coded Signaling Architecture for IoT Devices

Abstract Edge coded signaling (ECS) is a recently introduced communication protocol designed for single-channel signaling among constrained internet of things (IoT) nodes. This study aims to enhance the data rate of ECS, without increasing the clock frequency or power consumption. The goal is to develop an improved protocol that maintains the inherent advantages of ECS while achieving a higher data rate. The proposed solution, double data rate ECS (DDR-ECS), leverages both pulse edges of the ECS pulse stream for information encoding, drawing an analogy to DDR memory systems. The study presents a detailed design of low-power architecture for the DDR-ECS transceiver. This design was synthesized using a 65 nm ASIC process to evaluate its performance in terms of power consumption, gate count, and data rate. The synthesis results demonstrate that the DDR-ECS transceiver preserves the key features of ECS, including tolerance to clock frequency variations and compatibility with lightweight cryptographic algorithms. It effectively doubles the dynamic data rate to the range of 12–73.5 Mb/s while consuming an equivalent power of 13 μW and occupying a compact form factor of only 1,755 gates. The introduction of DDR-ECS represents a significant advancement in the ECS protocol, offering a novel approach to doubling the data rate without increasing the clock frequency or power envelope. This innovation retains the simplicity and efficiency of ECS, providing an enhanced communication solution for constrained IoT nodes.

DNA Packaging and Polycation Length Determine DNA Susceptibility to Free Radical Damage in Condensed DNA.

In nature, DNA exists primarily in a highly compacted form. The compaction of DNA in vivo is mediated by cationic proteins: histones in somatic nuclei and protamines in sperm chromatin. The extreme, nearly crystalline packaging of DNA by protamines in spermatozoa is thought to be essential for both efficient genetic delivery as well as DNA protection against damage by mutagens and oxidative species. The protective role of protamines is required in sperm, as they are sensitive to ROS damage due to the progressive loss of DNA repair mechanisms during maturation. The degree to which DNA packaging directly relates to DNA protection in the condensed state, however, is poorly understood. Here, we utilized different polycation condensing agents to achieve varying DNA packaging densities and quantify DNA damage by free radical oxidation within the condensates. Although we see that tighter DNA packaging generally leads to better protection, the length of the polycation also plays a significant role. Molecular dynamics simulations suggest that longer polyarginine chains offer increased protection by occupying more space on the DNA surface and forming more stable interactions. Taken together, our results suggest a complex interplay among polycation properties, DNA packaging density, and DNA protection against free radical damage within condensed states.

A compact and efficiently designed two-port MIMO antenna for N78/48 5G applications

A tightly packed irregular polygon with a distinctive protruding strip, specifically tailored for the N78/48 application, enhances a highly compact and effectively designed two-port MIMO (multiple-input, multiple-output) antenna. Its dimensions measure 20x31.5 × 1.6 mm3, with εr being 4.4 of FR-4 substrate, and it impressively delivers an extensive impedance bandwidth (Sxx < −10 dB) spanning the 3.25–3.85 GHz range. The design incorporates a MIMO antenna with closely spaced elements, merely 1.5 mm (0.012 λ0) apart. The microstrip inserts a feeding line with a partially truncated ground, a grounded stub, and a side stubs embedded in the ground plane, which improve isolation. Positioning T shaped decoupling elements between radiators helps the antenna's bandwidth enhance and improves isolation (S21) across the band. Extensive validation of the antenna's performance has been carried out through comprehensive s-parameter analysis, closely mirroring the results obtained through measurements. Despite its compact form, this antenna efficiently minimizes coupling, achieving S21 levels exceeding −19.25 dB throughout the band. Notably, the antenna attains an impressive peak gain of 3.3 dBi and exhibits a radiation efficiency of 92%. A total affective reflection coefficient (TARC) that starts at-10 dB, a MEG of 0.481 dB, and a channel capacity loss (CCL) of 0.3016 bits/s/Hz are some of the things that make up its MIMO diversity performance. The envelope correlation coefficient (ECC) is 0.0089. It's particularly suitable for 5G-NR sub-6GHz requirements, offering an efficient and compact solution.

Wind Energy Conversion System with Integrated Power Smoothing Capability based on an EVT-coupled Flywheel

This paper presents a wind energy conversion system that integrates, in a compact form, both generation and power smoothing functions. The system is based on a vertical axis wind turbine (VAWT) and a low-speed flywheel that are coupled by an electric variable transmission (EVT). The EVT performs a dual function by simultaneously injecting power to the grid and regulating the power flow to the flywheel to smooth the power fluctuation caused by wind turbulences. The main advantages of the presented generation/smoothing topology are integrating two machines (generator and motor) in the same physical structure and the reduced power demanded by the converter that feeds the flywheel’s rotor. A theoretical analysis is carried out to determine an appropriate control law and flywheel sizing to satisfy a desired attenuation of the power fluctuation. Simulation results show an effective smoothing action, as the power fluctuation is reduced to an adequate level. In addition, the validity of the flywheel sizing procedure is verified.

Simple modulation of Lissajous MEMS laser beam scanning with reconfigurable structured light patterns for 3D imaging

Structured light 3D imaging systems commonly employ panel-based projectors or 1-axis MEMS mirrors with beam expander lens to project multi-frame barcodes or dot clouds, addressing challenges posed by objects with multi-scale feature sizes. However, these methods often result in large system volumes due to the required projection multi-lens modules, high hardware costs, or limited light pattern generation capabilities that hindering measurement precision enhancement. This paper introduces an innovative approach to reconfigurable spatial light pattern projection using a single bi-axial MEMS mirror with Lissajous scanning. In contrast to the pixel-by-pixel pre-defined image patterns encoding of conventional 2D laser beam scanning, the proposed method simply aligns the MEMS bi-axial resonance frequencies with laser pulse modulation, enabling the projection of diverse structured light patterns such as stripes, lines, dot matrices, and random dot clouds, which can adapt to different 3D imaging algorithms demands. It eliminates the need for multi-frame encoding and streamlines data caching, simplifies digital logic hardware. A prototype 3D imaging system was developed to demonstrate the mathematical model for laser modulation and the technical feasibility based on the proposed principle. Beyond its lens-free essence, the system supports focal-free optics and a compact projection form factor, which accommodates to a broad range of projection distances and field-of-views based on object’s location. 3D depth map of polynomial surface and blocks objects are extracted through single-frame pattern projection with a relative high accuracy. The presented modulation theory for diverse structured light pattern generation opens avenues for versatile and compact 3D imaging applications of LiDAR and robotic 3D vision.

Advances in Optical Fiber Speckle Sensing: A Comprehensive Review

Optical fiber sensors have been studied, developed, and already used in the industry for more than 50 years due to their multiplexing capabilities, lightweight design, compact form factors, and electromagnetic field immunity. The scientific community continuously studies new materials, schemes, and architectures aiming to improve existing technologies. Navigating through diverse sensor technologies, including interferometry, intensity variation, nonlinear effects, and grating-based sensors, fiber specklegram sensors (FSSs) emerge as promising alternatives due to their simplicity and low cost. This review paper, emphasizing the potential of FSSs, contributes insights to the present state and future prospects for FSSs, providing a holistic view of advancements propelling FSSs to new frontiers of innovation. Subsequent sections explore recent research, technological trends, and emerging applications, contributing to a deeper understanding of the intricacies shaping the future of FFS sensor technologies.