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At least 199 records · Page 11

Diabatic error and propagation of Majorana zero modes in interacting quantum dots systems

Motivated by recent experimental progress in realizing Majorana zero modes (MZMs) using quantum dot systems, we investigate the diabatic errors associated with the movement of those MZMs. The movement is achieved by tuning time-dependent gate potentials applied to individual quantum dots, effectively creating a moving potential wall. To probe the optimized movement of MZMs, we calculate the experimentally accessible time-dependent fidelity and local density-of-states using many-body time-dependent numerical methods. Furthermore, our analysis reveals that an optimal potential wall height is crucial to preserve the well-localized nature of the MZM during its movement. Moreover, we analyze diabatic errors in realistic quantum-dot systems, incorporating the effects of repulsive Coulomb interactions and disorder in both hopping and pairing terms. Additionally, we provide a comparative study of diabatic errors arising from the simultaneous versus sequential tuning of multiple gates during the MZMs movement. Finally, we estimate the timescale required for MZM transfer in a six-quantum-dot system, demonstrating that MZM movement is feasible and can be completed well within the qubit's operational lifetime in practical quantum-dot setups.

Density of states↗

Optimal filtering and generation of entangled photons for quantum applications in the presence of noise

Filtering is commonly used in quantum optics to reject noise photons, and also to enable interference between independent photons. However, filtering the joint spectrum of photon pairs can reduce the inherent coincidence probability or loss-independent heralding efficiency. Here we investigate filtering for multiphoton applications based on entanglement and interference (e.g., quantum teleportation). We multiplex C-band entangled photons and C-band classical communications into the same long-distance fibers, which enables scalable low-loss quantum networking but requires filtering of spontaneous Raman scattering noise from classical light. Using tunable-bandwidth filters, low-jitter detectors, and polarization filters, we distribute wavelength-degenerate time-bin entangled photons in the C band (1536.5 nm) over 25 km/25 km standard fibers (50 km) each carrying 10 Gbit/s C-band classical data signals. Narrow filtering enables milliwatt-level C-band power, which exceeds the power achieved by comparable studies by roughly an order of magnitude and could feasibly support terabit per second classical rates. We evaluate how performance depends on pump and filter bandwidths, multipair emission, filter shapes, loss, phase matching, and how quantum information is measured. We find a trade-off between reducing noise impact and increasing single-mode purity, and discuss mitigation methods toward optimal multiphoton applications. Importantly, these results apply to noise in free space and in quantum devices (sources, frequency converters, switches, detectors, etc.) and provide insight into filter-induced degradation of single-photon purity and rates even in noise-free environments.

Thomas, Jordan M. [Fermilab; Northwestern U.]↗

Towards Automatically Matching Security Advisories to CPEs: String Similarity-based Vendor Matching

When a vulnerability is reported by the National Vulnerability Database (NVD), affected products are listed in the structured Common Platform Enumeration (CPE) format. Unfortunately, if the vulnerability is in a software library (e.g., Log4j), it will not include CPEs for each product containing that library. In these cases, security operators need to manually read the vendor's or third-party security advisories to see if their product is affected. However, these advisories do not report affected products in a structured format, which prevents automated processing, This paper makes the first effort towards automatically constructing structured CPEs for the vulnerable products in a non-NVD security advisory from the unstructured data in the advisory. Since this is a very challenging problem, this paper specifically focuses on the initial but key step of matching the un-structured vendor names in security advisories to the structured vendor representations in the standard CPE format. We explore the feasibility of using string similarity to solve the problem. The basic idea is to compare a vendor name from the non-NVD advisory with each vendor in the official CPE dictionary. The CPE vendor with the highest similarity score to the advisory's vendor will be considered as the match. We first conduct an experimental, comparative study of multiple mainstream string similarity metrics for this matching problem. To improve the performance, we then design a new string similarity metric that is adapted from an existing metric by weighing different tokens in the advisory's vendor name differently.

McClanahan, Kylie↗

Analysis and Comparison of Different Metrics of DC-DC Converters to Determine Fuel Cell Stack Architectures in Heavy Duty Fuel Cell Vehicle Applications

This paper presents a comparative study of the DC-DC converters used in heavy-duty fuel cell electric vehicles for different input fuel cell stack configurations and voltages in terms of various important metrics including efficiency, cost, weight and power density. Contrary to conventional use of an interleaved boost topology, the analysis presented in this paper demonstrates that improved converter metrics can be achieved for an interleaved buck topology that uses a different input fuel cell stack. An insight to the optimal choice of number of interleaved phases for each metric is also presented. Results presented in the tables and plots convey the findings.

Mukherjee, Subho↗

Understanding Reliability Trade-Offs in 1T-nC and 2T-nC FeRAM Designs

Ferroelectric random access memory (FeRAM) is a promising candidate for energy-efficient nonvolatile memory, particularly for logic-in-memory and compute-in-memory (CIM) applications. Among the available cell architectures, One-Transistor–n-Capacitor (1T-nC) and two-transistor–n-capacitor (2T-nC) FeRAMs each offer distinct trade-offs in density, scalability, and reliability. In this work, we present a comparative study of these two architectures under both dimensional scaling ( XY/Z shrinkage) and vertical integration (increasing stacked capacitors per cell). Using technology computer-aided design (TCAD) and circuit-level simulations, we analyze how scaling impacts ferroelectric capacitance, parasitic coupling, and floating-node (FN) dynamics, which together dictate sense margin (SM) and read stability. A key mitigation strategy—floating unselected capacitors—is applied to both architectures, effectively decoupling the SM from the number of stacked capacitors and enabling tractable analysis across scaling regimes. Results show that 1T-nC suffers more from charge sharing with the bitline (BL), while 2T-nC benefits from transistor isolation and stronger low-voltage sensing at the cost of increased area. By systematically evaluating these behaviors across scaling directions, this work establishes the reliability trade-offs of 1T-nC and 2T-nC cells and provides design guidelines for high-density, vertically integrated FeRAM systems.

1T-nC↗

Testbed and Experiments for Quantum-Conventional Networking

The realization of quantum networks requires the development of devices and methods unprecedented in conventional networks, and yet they critically depend on the latter for implementing foundational blocks and essential operations. We describe a testbed to support the development and testing of their functionality and performance by providing quantum and conventional data planes and devices, together with a secure conventional control plane. It incorporates a variety of entangled photon sources, qubit technologies, detector technologies, photonic components, and supporting conventional switches and workstations. It implements a novel fiber telescoping scheme that provides suites of connections using fiber spools and inground-aerial fiber loops. We briefly summarize a variety of experiments conducted over this testbed including: (i) flex-grid quantum connection experiments, (ii) quantum state and channel tomography, (iii) utilization of quantum key distribution keys to secure conventional encryption and firewall devices, (iv) comparative study of analytical capacity estimates and entanglement throughput, (v) deployed squeezing coexisting with conventional communications, and (iv) measurement of polarization time variation.

Rao, Nageswara [ORNL] (ORCID:0000000234085941)↗

Advancing Reel-to-Reel Inspection Techniques for Long HTS Conductors: Comparison and Innovations

The continuous advancement of high-temperature superconductor (HTS) technologies has greatly accelerated the development and deployment of HTS applications. Among the critical tools supporting these advancements are reel-to-reel (R2R) critical current (I c ) measurement techniques, which are extensively used by both manufacturers and end users to characterize long-length REBCO conductors. These techniques play a vital role in quality assurance and quality control (QA/QC), ensuring the reliability and performance of HTS conductors and applications throughout the production cycle. We have developed a range of in-house devices for R2R measurements at the University of Houston and Princeton Plasma Physics Laboratory. These include one-dimensional (1D) scan using a magnetic circuit (MC) and two-dimensional (2D) magnetic field mapping systems based on scanning probe array microscope (SPAM) or scanning probe microscopy (SPM). Each technique offers distinct advantages: the MC system provides ultra-fast scanning speeds, ideal for rapid inspection in large-scale industrial production; the high-resolution SPM delivers detailed insights for conductor research and development; and the SPAM, with its simpler mechanical setup, can be upgraded for higher field and lower temperature conditions with a balanced 2D resolution. Here we compared the magnetization and detection capabilities of these techniques through experiments on rare-earth barium copper oxide (REBCO) coated conductor samples, with data analysis supported by numerical simulations. Based on our comprehensive comparative studies, we propose enhancements for each measurement system and provide guidelines for selecting the optimal technique combinations to meet specific application requirements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spike-Free Adaptive Sliding Mode Control: Application to Permanent Magnet Synchronous Motors

A new methodology for adaptive sliding mode control (ASMC) has been widely used to improve the control performance in various systems. This method exhibits several advantages, including low sliding mode control (SMC) chattering, no knowledge of the system disturbance bound, and no overestimation of the control gain. Despite its advantages, this method can be hampered by the spike phenomenon, slow control gain convergence, and difficulty in achieving optimal performance under varying disturbances. Consequently, this article proposes a spike-free ASMC method with a disturbance observer (DOB) to address these problems. Previous ASMC methods have been analyzed via simulations to verify the aforementioned problems. Here, this analysis highlights the need for disturbance compensation and improvements in the SMC gain adaptation law. Therefore, a DOB is designed to mitigate the spike phenomenon by compensating for disturbances. Subsequently, an SMC gain adaptation law based on disturbance error estimation is designed to eliminate the spike phenomenon completely. The proposed adaptation law makes the SMC gain to converge to a slightly higher value than the disturbance estimation error. Consequently, the proposed method not only eliminates the spike phenomenon, but also ensures optimal performance under varying disturbances. The performance of the proposed method is experimen tally validated through a comparative study.

42 ENGINEERING↗

Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution Systems

Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. In conclusion, the framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Re-Evaluating Virtual Reality Manipulation Techniques for Precise Alignment of Complex 3D Objects

Prior research has developed a number of manipulation techniques that can achieve precise object placement in virtual reality, but studies of these techniques typically use simple objects. We conducted a study comparing two existing techniques, (AMP-IT and WISDOM), during alignment of objects with complex geometry to evaluate the potential influence of geometric complexity on performance, usability, workload and preference. Our findings indicate that participants had faster completion times and higher trial completion rates with AMP-IT on high-precision alignment tasks, contrary to earlier findings that used simple objects. Yet WISDOM is still preferred and considered more usable, despite increased workload and poorer performance, exposing participants' willingness to trade objective performance for comfort during use.

97 MATHEMATICS AND COMPUTING↗

Rethinking the soil core microbiome

The concept of a core microbiome emerged from host-associated research to describe microbial members or functions conserved across clearly defined spatial, temporal, and biological boundaries. In soil- and plant-associated microbiome research, however, the term has increasingly shifted toward analytically defined subsets selected using study-specific thresholds or criteria. Synthesizing recent literature and cross-site analyses of bioenergy crop field soils, we show that the original biological meaning of the core microbiome has been blurred by dataset-specific analytical criteria. Taxa designated as ‘core’ were highly sensitive to methodological choices and often reflected explanatory value rather than conserved biological membership. Moreover, many studies that identify taxonomic ‘core’ members interpret their significance in functional terms, suggesting that functional conservation may be the biological interest. Taxonomic conservation may not be the most biologically meaningful target in highly heterogeneous soil and rhizosphere systems, where functional conservation may persist despite taxonomic turnover. Accordingly, ‘core microbiome’ should be reserved for microbial components explicitly demonstrated to be conserved across defined spatial, temporal, and environmental dimensions and linked to conserved ecological functions, while taxa selected for explanatory value are better described as ‘explanatory subsets of taxa’. Greater terminological precision will improve cross-study comparability and strengthen ecological inference in plant–soil microbiome research.

bioenergy crops↗

Draft genome of the switchgrass head smut pathogen Tilletia maclaganii

Tilletia maclaganii is a smut fungal pathogen that causes significant biomass reduction of switchgrass ( Panicum virgatum ) used for animal forage and biofuel production. Here we present the annotated genome of T. maclaganii , strain Tm001-NY21, estimated at 42.79 Mb in size, in 53 assembled contigs and encoding 10,235 predicted genes. This genome will be important for future comparative studies of Ustilaginales across its geographic and host range.

PacBio↗

Assessment of Electric Grid Transmission System Simulator for Human Factors Research

Over the past decades, various technologies have been developed for electric grid operations to support clean energy, meet rising electricity demands, and address infrastructure concerns. However, the human factors aspect is often overlooked during rapid integration. Questions persist about how these technologies impact human performance. Simulators play a critical role in supporting investigation of human factors design concepts and conducting comprehensive usability testing to evaluate human performance and assess human reliability. This paper aims to address human factors research simulator requirements and conduct a comparative study of six different simulators. A detailed evaluation reveals that the evaluated simulators lack the ability to customize user interfaces. Additionally, their user interface designs do not fulfill the basic human factors design principles, potentially leading to increased response variability and reduced statistical power when conducting controlled experimental research. In the future, it is essential to develop scripting tools to integrate customizable user interfaces and simulation models, ensuring meeting research requirements.

Li, Ruixuan↗

Parallelizing autotuning for HPC applications: Unveiling the potential of the speculation strategy in Bayesian optimization

In the exascale computing era, tuning High-Performance Computing (HPC) applications has become a significant computational challenge. Although Bayesian optimization (BO) has emerged as a promising tool for HPC performance tuning, the BO workflow is inherently sequential (i.e., one function evaluation at a time) and cannot leverage the huge amount of parallel resources present in modern supercomputers, resulting in a considerable underutilization of their computational capabilities. This paper explores the trade-off between search quality and parallelism in BO, investigating a diverse set of methods. Building upon both previous approaches from the literature and novel methodologies introduced in this work, our study provides a deep analysis to accelerate BO performance tuning. By examining a set of synthetic functions and practical HPC applications, our exploration analyzes the interaction among various BO methods for parallelization, the quantity of parallel resources, the runtime distribution of target HPC applications, and the costs associated with different search orchestration mechanisms that have been overlooked in previous studies. Compared to sequential BO, our novel methodology achieves comparable quality while demonstrating robust scalability in search time as the amount of parallel resources increases; it also outperforms a state-of-the-art tuner, which supports parallelization, achieving up to 3.67x faster search time. We provide high-value insights for practitioners seeking to leverage the power of parallel computing for efficient HPC application tuning. Additionally, to further assist researchers in accelerating the performance tuning of their HPC applications, we provide an extension of an existing open-source tuning framework that incorporates our methods.

Bayesian optimization↗

Experimental study of airpath electrification in an opposed-piston two stroke (OP2S) engine architecture

The opposed-piston two stroke (OP2S) engine shows potential as an alternative engine architecture to the conventional four stroke engine due to its high-power density, thermal efficiency, and versatile airpath management system. Since the pistons of a two-stroke engine do not pump the air into and out of the cylinder like in a four-stroke engine, the selection of the air induction devices and airpath actuators becomes critical to optimize engine performance. Both the pumping losses and the in-cylinder combustion process can be affected by the scavenging process in a two-stroke engine. Therefore, this study compares two different airpath configurations for the same family of OP2S engines and investigates performance metrics like scavenging control, pumping work, net indicated and brake efficiencies, and engine-out emissions associated with each airpath. Data was collected on a 3.2 L, two-cylinder OP2S engine with an electrically assisted turbocharger (EAT) and a 4.9 L displacement, three-cylinder engine with a variable geometry turbocharger (VGT) and a supercharger. The experiments consisted of speed and load sweeps for both engines at the same operating conditions to compare scavenge control in both architectures. For the three-cylinder layout, the SE sweep range was much higher, and the intake pressure could be independently varied with air flowrate, thus providing more flexibility for scavenging control. The supercharger and the VGT usage was optimized based on its efficiency map and thus, this layout had lower pumping losses compared to the EAT. The two-cylinder engine had a higher overall SE as compared to the three-cylinder engine, but the intake pressure and air flowrate could not be decoupled, leading to over scavenging and increased short circuiting of fresh charge into the exhaust.

Bhatt, Ankur [Clemson University, Clemson, SC, USA↗

CUDO: closed-form universal dwell-time optimization for computer-controlled optical surfacing

Precision optical figuring demands fast and accurate dwell time optimization to reach nanometer- and sub-nanometer-level accuracy in next-generation optical systems. We introduce CUDO (closed-form universal dwell-time optimization), the first, to the best of our knowledge, unified closed-form analytical framework that supports both function-form and matrix-form dwell time models in computer-controlled optical surfacing (CCOS). In contrast to traditional methods, which rely on iterative optimization and hyperparameter tuning, our framework derives direct analytical solutions with no adjustable parameters. This approach unifies the solution principles of existing methods within a single mathematical model, delivering three key advantages: (1) accuracy on par with, or superior to, iterative solvers, (2) substantial reduction in computation time, and (3) numerical robustness. Comparative studies with prior art confirm that closed-form solutions achieve equivalent residual error while removing runtime bottlenecks. By simplifying the implementation and enabling real-time, scalable deployment, CUDO establishes a practical foundation for future deterministic fabrication of large-aperture and high-performance optics.

36 MATERIALS SCIENCE↗

VECTOR Phase 1 Dataset: CAV Trajectory and Energy Consumption Records

This dataset contains benchmark experimental data from Phase 1 of the VECTOR project, focusing on the energy impact of CAV hardware components. The dataset includes vehicle trajectory data (speed and position) and corresponding energy consumption records collected from a CAV platform equipped with lidar, cameras, onboard computation units, and communication modules. The primary objective is to quantify the baseline energy consumption attributable to sensing and computing systems, independent of any advanced cooperative control strategies. During experiments, the leading vehicle followed a predetermined velocity profile, and the following CAV mirrored this trajectory using a basic car-following control to ensure consistent driving behavior. This setup enables a reliable benchmark for assessing the energy cost introduced by onboard CDA hardware (e.g., lidar and GPU-based processing). The dataset is essential for evaluating energy baselines and supports future comparative studies involving additional cooperative strategies. ![system img](system.png) ![vector img](vector.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessing convergence in global sensitivity analysis: a review of methods for assessing and monitoring convergence

In global sensitivity analysis (GSA) of a model, a proper convergence analysis of metrics is essential for ensuring a level of confidence or trustworthiness in sensitivity results obtained, yet is somewhat deficient in practice. The level of confidence in sensitivity measures, particularly in relation to their influence and support for decisions from scientific, social and policy perspectives, is heavily reliant on the convergence of GSA. We review the literature and summarize the available methods for monitoring and assessing convergence of sensitivity measures based on application purposes. The aim is to expose the various choices for convergence assessment and encourage further testing of available methods to clarify their level of robustness. Furthermore, the review identifies a pressing need for comparative studies on convergence assessment methods to establish a clear hierarchy of effectiveness and encourages the adoption of systematic approaches for enhanced robustness in sensitivity analysis.

54 ENVIRONMENTAL SCIENCES↗