Hybrid Quantum-inspired Resnet and Densenet for Pattern Recognition with Completeness Analysis

With the contemporary digital technology approaching, deep neural networks are emerging as the foundational algorithm of the artificial intelligence boom. Whereas, the evolving social demands have been emphasizing the necessity of novel methodologies to substitute traditional neural networks. Concurrently, the advent of the post-Moore era has spurred the development of quantum-inspired neural networks with outstanding potentials at certain circumstances. Nonetheless, a definitive evaluating system with detailed metrics is tremendously vital and indispensable owing to the vague indicators in comparison between the novel and traditional deep learning models at present. Hence, to improve and evaluate the performances of the novel neural networks more comprehensively in complex and unpredictable environments, we propose two hybrid quantum-inspired neural networks which are rooted in residual and dense connections respectively for pattern recognitions with completeness representation theory for model assessment. Comparative analyses against pure classical models with detailed frameworks reveal that our hybrid models with lower parameter complexity not only match the generalization power of pure classical models, but also outperform them notably in resistance to parameter attacks with various asymmetric noises. Moreover, our hybrid models indicate unique superiority to prevent gradient explosion problems through theoretical argumentation. Eventually, We elaborate on the application scenarios where our hybrid models are applicable and efficient, which paves the way for their industrialization and commercialization.Comment: 12 pages for main paper with 13-page supplementary materials with a hyperlink in the last page of the main pape

Quantum-accelerated algorithms for generating random primitive polynomials over finite fields

Primitive polynomials over finite fields are crucial for various domains of computer science, including classical pseudo-random number generation, coding theory and post-quantum cryptography. Nevertheless, the pursuit of an efficient classical algorithm for generating random primitive polynomials over finite fields remains an ongoing challenge. In this paper, we show how to solve this problem efficiently through hybrid quantum-classical algorithms, and designs of the specific quantum circuits to implement them are also presented. Our research paves the way for the rapid and real-time generation of random primitive polynomials in diverse quantum communication and computation applications

Comparing Adolescent Only Children with Those Who Have Siblings on Academic Related Outcomes and Psychosocial Adjustment

This study uses a large and representative sample of adolescents to test the theoretically informed hypotheses comparing adolescent singletons with those who have siblings. The results found that, for academic related outcomes (educational expectations, time spent on homework, and self-reported grades), there are no differences between singletons and firstborns who have any number of younger siblings. Singletons are also not different from laterborns from two-child families. In contrast, singletons are more advantageous compared to laterborns who have two or more siblings on educational expectations and grades. Singletons also spend more time on homework than laterborns who have three or more siblings. For psychosocial outcomes (psychological distress, susceptibility to negative peer pressure, and problem behaviors), singletons are not different from both firstborns and laterborns with any number of siblings. The findings suggest that singletons are not at any disadvantage compared to their peers who have siblings and they enjoy some advantages over laterborns from medium to large families on academic related outcomes

Corrosion Types of Magnesium Alloys

Magnesium (Mg) alloys are susceptible to corrosion in aggressive environments. Corrosion of Mg alloys depends greatly on their composition and microstructure (grain size, the size, shape and distribution of second phases), post-processing and media. In most cases, localized corrosion, such as pitting corrosion and filiform corrosion, generally occurs due to microgalvanic corrosion between the intermetallic compounds and their neighboring α-Mg matrix. However, open literature reported that several corrosion morphologies, that is, intergranular corrosion (IGC) and exfoliation corrosion (EFC), cannot appear on Mg alloys. In this chapter, all typical corrosion modes of Mg alloys and influencing factors are introduced, including general corrosion, galvanic corrosion, pitting corrosion, filiform corrosion, IGC, EFC, stress corrosion cracking (SCC), corrosion fatigue (CF) and so on. The focus is laid on pitting corrosion and EFC. Corrosion mechanisms of Mg alloys are also discussed

Optical Properties and Radiative Forcing of Aged BC due to Hygroscopic Growth: Effects of the Aggregate Structure

Black carbon (BC) particles become hydrophilic after mixing with soluble matter in the atmosphere, and their optical and radiative properties can be significantly modified accordingly. This study investigates the impact of aggregate structure on optical and radiative properties of aged BC, that is, BC coated by sulfate or organic aerosols, especially during hygroscopic growth. A more realistic BC morphology based on fractal aggregates is considered, and inhomogeneous mixtures of BC aggregates are treated more realistically (with respect to particle geometries) in the multiple sphere T‐matrix method for optical property simulations. As relative humidity increases, BC extinction is significantly enhanced due to an increase in scattering, and the enhancement depends on the amount and hydrophilicity of the coating. The absorption exhibits less variation during hygroscopic growth because the coating of aerosols already leads to BC absorption close to the maximum. Furthermore, hygroscopic growth not only results in negative radiative forcing (RF) at the top of the atmosphere but also slightly weakens the absorption in the atmosphere (inducing a negative RF in the atmosphere). Compared to the more realistic model with BC as aggregates, the currently popular core‐shell model reasonably approximates the top of the atmosphere RF but underestimates the atmospheric RF due to hygroscopic growth by up to 40%. Furthermore, for the RF caused by internal mixing, the core‐shell model overestimates the RFs at the surface and in the atmosphere by ~10%