bluuebunny/crossref_metadata_2025_split huggingface dataset:
The FinFET effect in lateral 4H-SiC and Silicon multi-gate MOSFETs
Authors: Naydenov K , Wang Q , Udrea F , Fujioka H , Tomita H , Nishiwaki T , Kumazawa T , Fujiwara H 
Published: November 2024

Abstract
This paper presents a comprehensive investigation on the role and manifestation of the FinFET effect in low voltage 4H-SiC MOSFETs as compared to their Si counterparts. For this purpose, a finite element model of a fabricated SiC FinFET with a fin width of 55 nm is constructed and calibrated to experimental data at a range of operating temperatures. The resulting TCAD model is then applied to examine the impact of the FinFET effect on the threshold voltage and the spatial variation of the carrier density and the drift mobility in the channel for a range of doping concentrations N

A
of the p-well. It is thereby shown that by reducing the fin width

W

fin

from conventional values

≳

500 nm down to an interval of optimal values ∼40 nm (keeping everything else constant), it is possible to enhance the channel mobility ∼2.5 times. This improvement is not only found to be much larger than the one predicted in Si (where it is ∼ 15% according to the TCAD model) but also arises at a larger fin width (for a given N

A
). In this respect, it is demonstrated that this optimal range of fin widths can be moved to even larger, more practical values by reducing the doping of the p-well. As an alternative, the on-state performance of the gate-all-around FET is also examined in detail following a similar procedure. It is hence shown that this structure can display the FinFET effect at an even larger, nearly conventional

W

fin

of ∼250 nm, whilst attaining a higher channel mobility and inversion layer density even than a stripe FinFET operated at the same overdrive. Thus, in light of all these advantages, the FinFET topology can play a key role in reducing the channel resistance of SiC power MOSFETs.
A control-oriented magnetorheological elastomer isolator for high-tech facilities: development and experimental verification
Authors: Li Wang , Li Peidong , Fu Jie , Yu Miao 
Published: November 2024

Abstract
To protect high-tech facilities from micro-amplitude vibrations, a control-oriented magnetorheological (MR) elastomer (MRE) isolator (MRE-I) is developed. The MRE-I, which combines features of high bearing capacity and large MR effect, works in a stacked type compression and shear mixed mode. Meanwhile, index of high magnetic-energy ratio for MRE-I, with considering both the MR effect and power consumption is defined in this paper. Firstly, the magnetic field function of the MRE-I works in mixed mode is deduced. Taking high magnetic-energy ratio as the optimization objective, and using a genetic algorithm to solve the problem, the structure parameters are obtained. Subsequently, force to displacement tests with multi-operating conditions are conducted on the prototype, demonstrating an increase of 1604.29% in output force under a medium level of magnetic field. Lastly, vibration control tests using a fuzzy controller are carried out under an excitation of 1 m s−2 in a frequency sweep condition ranging from 90 Hz to 135 Hz, reaching 40% reduction in root mean squared of acceleration response, demonstrating the feasibility of this MRE-I for time-varying, micro-amplitude and wide-band vibration control of high-tech facilities.
Analysis of thermal grooving effects on vortex penetration in vapor-diffused Nb3Sn
Authors: Lechner Eric M , Trofimova Olga , Angle Jonathan W , DiGuilio Madison C , Pudasaini Uttar 
Published: November 2024

Abstract
While Nb3Sn theoretically offers better superconducting radio-frequency (RF) cavity performance (Q
0 and

E

acc

) to Nb at any given temperature, peak RF magnetic fields consistently fall short of the ∼400 mT prediction. The relatively rough topography of vapor-diffused Nb3Sn is widely conjectured to be one of the factors that limit the attainable performance of Nb3Sn-coated Nb cavities prepared via Sn vapor diffusion. Here we investigate the effect of coating duration on the topography of vapor-diffused Nb3Sn on Nb and calculate the associated magnetic field enhancement and superheating field suppression factors using atomic force microscopy topographies. It is shown that the thermally grooved grain boundaries are major defects which may contribute to a substantial decrease in the achievable accelerating field. The severity of these grooves increases with total coating duration due to the deepening of thermal grooves during the coating process.
Electromagnetic properties of superconductive low-β 325 MHz half-wave resonators at low RF field
Authors: Sukhotski A , Bychanok D , Volunets H , Gilev A , Huseu S , Gurnevich E , Maksimenko S , Petrakovski V , Pakrouski A , Pobol A , Burin A , Pobol I , Zalessky V , Gusarova M , Lalayan M , Polozov S , Tamashevich Y , Cherkunov D , Kotova A , Bespalov Y , Nikiforov D , Butenko A , Syresin E , Trubnikov G 
Published: November 2024

Abstract
A niobium prototype and two test unjacketed 325 MHz coaxial half-wave cavities with β = 0.21 were designed, fabricated, and tested at low RF fields. Electromagnetic properties were investigated using a vector network analyzer in the frequency domain and an RF generator, directional couplers, and power detectors in the time domain (both continuous wave and pulse mode). We analyzed and compared the response of the low-beta cavity in both normal and superconducting states. We studied the relationship between the resonator parameters and coupling devices to optimize the design of the RF power coupler and field probe antenna, aiming to achieve accurate cavity characterization. We proposed a tunable power coupler design that allows for varying the coupling coefficient when operating in a vacuum at liquid helium temperature. The typical responses of the cavity in case of under-, critical-, and over-coupling conditions obtained within a single cool-down are presented and analyzed. We introduced a simplified method based on decay measurements with cavity port switching for effective cavity characterization at low RF amplitudes. This method aligns well with standard Q-factor measurement protocols and can expedite experimental investigations with small RF signals. The

Q
0

(

E
acc

)

curve for half-wave resonators at ultra-low amplitudes is analyzed and discussed. Experiments with coaxial half-wave cavities showed an almost constant Q
0 at RF fields ranging from 1 × 10−4 MV m−1 to 1 × 10−1 MV m−1. Additionally, a significant increase in the quality factor was observed after 120 ∘C baking. The presented results are discussed in the context of potential low-field applications of superconductive cavities.
Effect of dynamic resistance reduction in spiral copper-plated multifilament coated conductors
Authors: Sogabe Yusuke , Amemiya Naoyuki 
Published: November 2024

Abstract
Theoretically, it has been shown that the dynamic resistances of coated conductors can be reduced by decreasing their effective width through multifilamentation. In the case of copper-plated multifilament coated conductors, coupling currents are expected to worsen the effect of multifilamentation in reducing dynamic resistance. Therefore, the purpose of this study is to experimentally investigate the dynamic resistances of spiral copper-plated multifilament coated conductors, which are expected to reduce the coupling time constant in a manner similar to twisted low-T
c superconducting wires. We measured the dynamic resistance of four different samples—straight monofilament, straight multifilament, spiral monofilament, and spiral multifilament coated conductors—using the four-terminal method. We discuss the dynamic resistivity characteristics of the copper-plated multifilament coated conductors by comparing the magnetic field dependence of the dynamic resistivity, normalized by the critical current of each sample.
A quench detection method for closed-loop superconducting coils based on currents redistribution in co-windings
Authors: Hu Changhao , Lin Yi , Tan Yunfei , Wang Lei , Geng Jianzhao 
Published: November 2024

Abstract
Closed-loop operation of superconducting magnets can significantly reduce cryogenic heat load and enhance magnetic field stability, which has been widely applied in systems such as magnetic resonance imaging and electro-dynamic suspension. Quench detection for closed-loop superconducting magnets, especially high-T
c superconducting (HTS) magnets, has long been a challenging issue. In this paper, we derived quench-induced currents redistribution characteristics in parallel co-wound closed-loop superconducting magnets, and proposed a current-redistribution based quench detection method for such magnets. Artificial quench tests on a small scale co-wound closed-loop HTS coil were staged, with AC background magnetic field applied to simulate tough working conditions such as in HTS maglevs and HTS machines. Results show that the method can sensitively and reliably detect a quench even at its inception, long before the coil field change becoming identifiable, and the method is robust against background AC magnetic fields. This work may potentially be useful for reducing the quench damage risk in closed-loop superconducting magnet for various applications.
Time arrow without past hypothesis: a toy model explanation
Authors: Arrighi Pablo , Dowek Gilles , Durbec Amélia 
Published: November 2024

Abstract
The laws of Physics are time-reversible, making no qualitative distinction between the past and the future—yet we can only go towards the future. This apparent contradiction is known as the ‘arrow of time problem’. Its current resolution states that the future is the direction of increasing entropy. But entropy can only increase towards the future if it was low in the past, and past low entropy is a very strong assumption to make, because low entropy states are rather improbable, non-generic. Recent works from the Physics literature suggest, however, we may do away with this so-called ‘past hypothesis’, in the presence of reversible dynamical laws featuring expansion. We prove that this can be the case in principle, within a toy model. It consists in graphs upon which particles circulate and interact according to local reversible rules. Some rules locally shrink or expand the graph. We prove that almost all states expand; entropy always increases as a consequence of expansion—thereby providing a local explanation for the rise of an entropic arrow of time without the need for a past hypothesis. The discrete setting of this toy model allows us to deploy the full rigour of theoretical Computer Science proof techniques. It also allows for the numerical exploration of several physically-motivated variants: a time-symmetric variant; two inflationary variants; and a damping variant—which slows down thermal death. The fact that all of these models exhibit similar behaviours suggests that local reversible expansion mechanisms constitute a robust recipe for a time arrow without past hypothesis. In this qualitative sense, the explanation may therefore also be relevant at the cosmological level.
Hidden complex multistable dynamical analysis and FPGA implementation of integer-fractional order memristive-memcapacitive chaotic system
Authors: Xu Jingjing , Zhang Xiaohong , Zhong Shaojiang 
Published: November 2024

Abstract
A chaotic circuit based on a magnetic-controlled memristor and charge-controlled memcapacitor is proposed in this paper. The study reveals that it is a hyperchaotic system with hidden characteristics in integer-order. Furthermore, as the parameters change, the attractors exhibit rich evolutionary phenomena. Even after adjusting some parameters to very large values, the system still maintains hyperchaotic behavior. Interestingly, the basin of attraction shows the multistability of the system. Under initial value control, coexisting attractors are categorized into two types: those with initial offset-boosting behavior and nested attractors. When under parameter control, coexisting attractors are divided into two types: symmetric coexisting attractors and nested coexisting attractors. By analyzing the spectral entropy (SE) complexity of the system and using a complexity distribution diagram with two parameters and two initial values, the existence of multiple complex dynamic behaviors in the system has been verified. The fractional-order memristive-memcapacitive system based on the Grunwald-Letnikov algorithm and the five fractional-order values of q

i
(i = 1, 2, 3, 4, 5) are taken as different in the numerical simulation, it also displays multiple coexisting phenomena similar to those of the integer-order. Finally, Matlab/Simulink and DSP Builder software platform are used to design the fractional-order five-dimensional chaotic memristive-memcapacitive system, and then combined with VHDL and Verilog HDL hardware language, the proposed circuit system is verified on the EP4CE115F29C7 FPGA main chip of Cyclone IV E series. The consistency of hardware implementation and software simulation shows the correctness and feasibility of the design.
Solitonic solutions for the reduced Maxwell-Bloch equations via the Darboux transformation and artificial neural network in nonlinear wave dynamics
Authors: Riaz H W A , Farooq Aamir 
Published: November 2024

Abstract
In this article, we explore nonlinear wave dynamics by presenting solitonic solutions for the reduced Maxwell-Bloch equations, a model relevant to both nonlinear optics and Bose–Einstein condensates. First, we write the Lax pair for the system and apply a Darboux transformation to obtain and analyze the soliton solutions. Then, we introduce a novel approach by integrating the Darboux transformation, a powerful analytical tool, with the Levenberg-Marquardt artificial neural network, a reliable numerical method. This combination enables the identification and validation of soliton solutions, supported by detailed graphical and tabular analyses. The Levenberg-Marquardt artificial neural network effectively demonstrates the uniqueness and convergence of the solutions, with the accuracy of the results validated through comprehensive graphical representations.
Area-delay efficient BCD adder in quantum dot cellular automata
Authors: S R Ramesh , T Jagadeep , Vamsi Krishna Maddala , Abhishek Sista Venkata Datta Sai , Vegunta Suraj Sai 
Published: November 2024

Abstract
Quantum-dot Cellular Automata (QCA) technology presents a promising avenue for the realization of ultralow-power and high-speed digital circuits owing to its inherent quantum properties and nanoscale dimensions. In this study, a novel design and analysis of a binary-coded decimal (BCD) adder implemented using QCA technology is proposed. The BCD adder is a fundamental component of digital arithmetic circuits and is widely applied in various computational systems, including calculators, processors, and digital signal processors. Leveraging the unique features of QCA, such as the absence of current flow and the potential for highly compact layouts, we present a detailed design methodology for the BCD adder circuit, including the implementation of basic QCA gates and construction of the BCD addition logic. Performance metrics, such as area, delay, and power consumption, were evaluated through extensive simulations using QCA Designer, QCA design, and a simulation tool. The Ripple Carry Adder (RCA) is one of the major blocks in the BCD circuit and a prominent factor in determining the area and delay of the circuit. Therefore, an efficient full adder was used to design an RCA with less area and delay. Clocking in a QCA impacts the polarization state of a QCA cell, and this scheme is utilized efficiently to achieve novelty. The proposed design occupies 15.625% less area, and the cell count is reduced by 11.55% compared with the existing state-of-the-art design. Power dissipation reports were obtained using the QCA Pro tool, which briefly describes the average leakage and average dissipation energy of the total circuit, and a spectrum to depict the energy dissipation of each cell in the circuit. The results demonstrate the feasibility and efficiency of the proposed BCD adder design in QCA technology, demonstrating its potential for realizing energy-efficient and high-performance digital arithmetic circuits. This work contributes to the growing body of research on QCA-based digital circuit design and lays the groundwork for the further exploration of QCA technology in practical computing applications.
Relay Observation Scheduling of Global Distributed Telescope Array Based on Integer Programming
Authors: Ju Junhan , Yu Ce , Hu Yi , Zhang Yajie , Sun Chao , Wei Jizeng 
Published: November 2024

Abstract
Certain transients require regular observations over several days at intervals of hours or shorter, which cannot be accomplished by telescopes at a single site. The deployment of globally distributed telescopes at geographic locations of different longitudes enables the periodic monitoring of transients through relay observation. However, the simultaneous relay observation of numerous targets requires a telescope array of multiple telescopes that can be efficiently coordinated, and an automated scheduler for the array. This paper proposes IPROS, an integer programming model relay observation scheduler for a telescope array, that accounts for the entire process of relay observation and is consistent with the practical scenarios. We introduce the integer programming mathematical model for the relay observation scheduling problem with the telescope array, upon which the scheduler is based. Additionally, we propose an algorithm to provide a comprehensive formulation of the optimization objective of minimizing cadence deviation in the model. Experimental results demonstrate that the relay observation scheduler based on the integer programming model can effectively address the telescope array relay observation problem. It shows superiority over a scheduler with non-specific consideration of relay observation in the modeling and a scheduler based on greedy thought.
Neural networks for reconstruction and uncertainty quantification of fast-ion phase-space distributions using FILD and INPA measurements
Authors: Schmidt B. S. , Rueda-Rueda J. , Galdon-Quíroga J. , García-Muñoz M. , Schneider P. A. , Salewski M. ,   the ASDEX Upgrade Team
Published: November 2024

Abstract
This study introduces the use of a deep convolutional neural network for reconstructing fast-ion velocity distributions from fast-ion loss detectors and imaging neutral particle analyzers (INPAs), automatically integrating uncertainty quantification through Monte Carlo dropout. The network-based reconstructions reveal pitch-angle splitting in high-energy features of lost fast-ion velocity distributions at ASDEX Upgrade during active neutral beam injection, a previously observed phenomenon now confirmed through neural networks. Moreover, contrary to common theories attributing these high-energy features to edge localized mode (ELM)-driven acceleration, we provide experimental evidence that they also occur in type-I ELM-quiescent phases. Additionally, we demonstrate improved reconstructions from INPA measurements, both synthetic and from an ASDEX Upgrade commissioning discharge, with the reconstructions closely matching TRANSP simulations. These findings suggest that neural networks can provide robust reconstructions with well-defined uncertainties, improving the reliability of interpretations of fast-ion behavior in magnetically confined plasmas.
Interlacing eigenvectors of large Gaussian matrices
Authors: Attal Elie , Allez Romain 
Published: November 2024

Abstract
We consider the eigenvectors of the principal minor of dimension n < N of the Dyson Brownian motion in

R

N

and investigate their asymptotic overlaps with the eigenvectors of the full matrix in the limit of large dimension. We explicitly compute the limiting rescaled mean squared overlaps in the large

n

,
N

limit with

n

/

N

tending to a fixed ratio q, for any initial symmetric matrix A. This is accomplished using a Burgers-type evolution equation for a specific resolvent. In the Gaussian orthogonal ensemble case, our formula simplifies, and we identify an eigenvector analogue of the well-known interlacing of eigenvalues. We investigate in particular the case where A has isolated eigenvalues. Our method is based on analysing the eigenvector flow under the Dyson Brownian motion.
Synthesis and characterization of space-time light sheets: a tutorial
Authors: Romer Miguel A , Hall Layton A , Abouraddy Ayman F 
Published: November 2024

Abstract
Space-time wave packets (STWPs) are a new class of pulsed optical beams with many unique and intriguing attributes, including propagation invariance and tunable group velocity in linear optical media. STWPs are a form of spatiotemporally structured light, so their synthesis poses challenges that are not shared by conventional monochromatic structured light fields. We present here a detailed description of the synthesis of STWPs that are localized along one transverse dimension and uniform along the other; i.e. space-time light sheets. We also describe the main characterization schemes needed for benchmarking the unique properties of space-time light sheets.
DPSNN: spiking neural network for low-latency streaming speech enhancement
Authors: Sun Tao , Bohté Sander 
Published: November 2024

Abstract
Speech enhancement improves communication in noisy environments, affecting areas such as automatic speech recognition (ASR), hearing aids, and telecommunications. With these domains typically being power-constrained and event-based, and often requiring low latency, neuromorphic algorithms–particularly spiking neural networks (SNNs)–hold significant potential. However, current effective SNN solutions require a long temporal window to calculate Short Time Fourier Transforms (STFTs) and thus impose substantial latency, typically around 32 ms, which is too long for applications such as hearing aids. Inspired by the Dual-Path Recurrent Neural Network (DPRNN) in deep neural networks (DNNs), we develop a two-phase time-domain streaming SNN fframework for speech enhancement, named Dual-Path Spiking Neural Network (DPSNN). DPSNNs achieve low latency by replacing the STFT and inverse STFT (iSTFT) in traditional frequency-domain models with a learned convolutional encoder and decoder. In the DPSNN, the first phase uses Spiking Convolutional Neural Networks (SCNNs) to capture temporal contextual information, while the second phase uses Spiking Recurrent Neural Networks (SRNNs) to focus on frequency-related features. In addition, threshold-based activation suppression, along with L
1 regularization loss, is applied to specific non-spiking layers in DPSNNs to further improve their energy efficiency. Evaluating on the Voice Cloning Toolkit (VCTK) Corpus and Intel N-DNS Challenge dataset, our approach demonstrates excellent performance in speech objective metrics, along with the very low latency (approximately 5 ms) required for applications like hearing aids.
Constructing Victimhood: Innocence, Guilt, and Definitional Dilemmas
Authors: Lawther Cheryl 
Published: November 2024

AbstractChapter 2 critically unpacks the complexity of victimhood post-conflict. Drawing from Christie (1986a), the first part of the chapter examines the construction of ‘ideal’ and ‘innocent’ victims. This conceptualisation of victimhood is then set against the increasing recognition of the ‘complex political victim’. These international debates are brought to bear on the Northern Ireland context in the second half of the chapter. Under the heading of ‘Victimhood as a “repertoire of contention”’, the chapter explores the construction and politicisation of victimhood in Northern Ireland. Conceptualising victimhood as a ‘definitional dilemma’ and competing interpretations of victimhood as ‘victimhood as innocence’ and ‘victimhood as resistance’, it is argued that defining victims as ‘innocent’ or ‘guilty’, ‘deserving’ or ‘undeserving’ may be less about victims’ needs and circumstances and more about making a statement on the ‘justifiability’ of the harms inflicted and the causes and consequences of the conflict within which their victimisation occurred.