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At least 1,225 records · Page 68

Robust Avoidance of Edge-Localized Modes alongside Gradient Formation in the Negative Triangularity Tokamak Edge

In a series of high performance diverted discharges on DIII-D, we demonstrate that strong negative triangularity (NT) shaping robustly suppresses all edge-localized mode (ELM) activity over a wide range of plasma conditions: ⟨n⟩ = 0.1 − 1.5 × 1020 m−3, Paux = 0 − 15 MW and |Bt| = 1 − 2.2 T, corresponding to Ploss/PLH08 ∼ 8. The full dataset is consistent with the theoretical prediction that magnetic shear in the NT edge inhibits access to ELMing H-mode regimes; all experimental pressure profiles are found to be at or below the infinite-n ballooning stability limit. Our present dataset also features edge pressure gradients in strong NT that are closer to an H–mode than a typical L-mode plasma, supporting the consideration of NT for reactor design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Robust Quantum Control via Multipath Interference for Thousandfold Phase Amplification in a Resonant Atom Interferometer

We introduce a novel technique for enhancing the robustness of light-pulse atom interferometers against the pulse infidelities that typically limit their sensitivities. The technique uses quantum optimal control to favorably harness the multipath interference of the stray trajectories produced by imperfect atom-optics operations. We apply this method to a resonant atom interferometer and achieve thousandfold phase amplification, representing a 50-fold improvement over the performance observed without optimized control. Moreover, we find that spurious interference can arise from the interplay of spontaneous emission and many-pulse sequences and demonstrate optimization strategies to mitigate this effect. Given the ubiquity of spontaneous emission in quantum systems, these results may be valuable for improving the performance of a diverse array of quantum sensors. We anticipate our findings will significantly benefit the performance of matter-wave interferometers for a variety of applications, including dark matter, dark energy, and gravitational wave detection.

47 OTHER INSTRUMENTATION↗

Noise robust detection of quantum phase transitions

Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the study of ground-states of condensed matter models, and the transitions between them. However, current levels of hardware noise can require extensive application of error-mitigation techniques to achieve reliable computations. In this work, we use several IBM devices to explore a finite-size spin model with multiple “phaselike” regions characterized by distinct ground-state configurations. Using preoptimized Variational Quantum Eigensolver (VQE) solutions, we demonstrate that in contrast to calculating the energy, where zero-noise extrapolation is required in order to obtain qualitatively accurate yet still unreliable results, calculations of the energy derivative, two-site spin correlation functions, and the fidelity susceptibility yield accurate behavior across multiple regions, even with minimal or no application of error-mitigation approaches. Taken together, these sets of observables could be used to identify level crossings in a simple, noise-robust manner which is agnostic to the method of ground state preparation. This work shows promising potential for near-term application to identifying quantum phase transitions, including avoided crossings and nonadiabatic conical intersections in electronic structure calculations. Published by the American Physical Society 2024

Lively, Kevin (ORCID:0000000320981494)↗

Robust preparation of ground state phases under noisy imaginary time evolution

Nonunitary state preparation protocols such as imaginary time evolution (ITE) offer substantial advantages relative to unitary ones, including the ability to prepare certain long-range correlated states more efficiently. Here, we ask whether such protocols are also robust to noise arising due to coupling to the environment. We consider a nonunitary ITE “circuit” subjected to a variety of noise models and investigate whether the resulting steady state remains in the same phase as the target state of the ITE at finite noise strength. Taking the one-dimensional quantum Ising model as a concrete example, we find that the ground-state order and associated phase transition persist in the presence of noise, provided the noise does not explicitly break the symmetry that protects the phase transition. That is, the noise must possess the protecting symmetry in a weak (or average) form. Our analysis is facilitated by a mapping to an effective Hamiltonian picture in a doubled Hilbert space. We discuss possible implications of these findings for quantum simulation on noisy quantum hardware. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robust Ferromagnetism in Highly Strained SrCoO 3 Thin Films

Epitaxial strain provides important pathways to control the magnetic and electronic states in transition-metal oxides. However, the large strain is usually accompanied by a strong reduction of the oxygen-vacancy formation energy, which hinders the direct manipulation of their intrinsic properties. Here, using a postdeposition ozone annealing method, we obtain a series of oxygen stoichiometric SrCoO 3 thin films with the tensile strain up to 3.0%. We observe a robust ferromagnetic ground state in all strained thin films, while interestingly the tensile strain triggers a distinct metal-to-insulator transition along with the increase of the tensile strain. The persistent ferromagnetic state across the electrical transition therefore suggests that the magnetic state is directly correlated with the localized electrons, rather than the itinerant ones, which then calls for further investigation of the intrinsic mechanism of this magnetic compound beyond the double-exchange mechanism.

36 MATERIALS SCIENCE↗

Robust Nodal Behavior in the Thermal Conductivity of Superconducting UTe 2

The superconducting state of the heavy-fermion metal UTe 2 has attracted considerable interest because of evidence of spin-triplet Cooper pairing and nontrivial topology. Progress on these questions requires identifying the presence or absence of nodes in the superconducting gap function and their dimension. In this article, we report a comprehensive study of the influence of disorder on the thermal transport in the superconducting state of UTe 2 . Through detailed measurements of the magnetic-field dependence of the thermal conductivity in the zero-temperature limit, we obtain clear evidence of the presence of point nodes in the superconducting gap for all samples with transition temperatures ranging from 1.6 to 2.1 K obtained by different synthesis methods, including a refined self-flux method. This robustness implies the presence of symmetry-imposed nodes throughout the range studied, further confirmed via disorder-dependent calculations of the thermal transport in a model with a single pair of nodes. In addition to capturing the temperature dependence of the thermal conductivity up to 𝑇 𝑐 , this model provides some information about the locations of the nodes, suggesting a 𝐵 1⁢𝑢 or 𝐵 2⁢𝑢 symmetry for the superconducting order parameter. Additionally, comparing the new, ultrahigh conductivity samples to older samples reveals a crossover between a low-field and a high-field regime at a single value of the magnetic field in all samples. In the high-field regime, the thermal conductivity at different disorder levels differs from each other by a simple offset, suggesting that some simple principle determines the physics of the mixed state, a fact which may illuminate trends observed in other clean nodal superconductors.

spin-triplet pairing↗

Robust negativity in the quantum-to-classical transition of Kerr dynamics

Here, we quantify the quantum-to-classical transition of the single-mode Kerr nonlinear dynamics in the presence of loss. We establish three timescales that govern the dynamics, each with distinct characteristics. For times short compared with the Ehrenfest time, the evolution is classical, characterized by Gaussian dynamics. For sufficiently long times, as we increase the initial photon number, unitary Kerr evolution would generate macroscopic superpositions of coherent states (so-called kitten states). However, this is severely restricted in the presence of small photon loss, and the expectation values of observables coincide with their classical values. The intermediate timescale, however, shows resilient quantum behavior in the macroscopic limit. We show that in the mean-field non-Gaussian regime, the Kerr Hamiltonian (with small photon loss) generates a significant amount of Wigner-negativity, and classical flow is recovered only if the loss rate grows with system size. Our results broaden the usual understanding of quantum-to-classical transitions and demonstrate the potential for creating robust nonclassical resources for continuous-variable quantum information processing in the presence of loss.

Raza, Mohsin [University of New Mexico, Albuquerqu↗

Seniority Structure in Neutron-Rich Nucleus 128 Ag : Evidence for Robustness of 𝑁 = 82 Shell Closure in Silver Isotopes

The spectroscopic studies of very neutron-rich nucleus 128 Ag have been performed for the first time at the Radioactive Isotope Beam Factory of RIKEN. A new seniority isomer with a half-life of 1.60(7) μs has been identified and is proposed to have a spin-parity of 16 - with a maximally aligned configuration comprising three proton holes in the g 9/2 orbital and one neutron hole in the h 11/2 orbital. The new level structure in 128 Ag is quite well described by shell model calculations without invoking excitations across the Z = 50 and N = 82 shell gaps, and presents a good case of seniority scheme in odd-odd nuclei in the south vicinity of the double-magic nucleus 132 Sn. With a classification of various components of the proton-neutron interaction, the inversion of lowest-lying 9 - and 10 - states between 128 Ag and its neighboring isotone 130 In is found to be dynamically ascribed to the seniority-nonconserving proton-neutron interaction components. The structure above 10 - up to the 16 - isomer in 128 Ag shows remarkable similarities to seniority structures in the semimagic nuclei 128 Pd and 130 Cd. These spectroscopic features in 128 Ag indicate that the N = 82 shell closure is still robust in silver isotopes.

Luo, D. W. [Peking University, Beijing (China); et↗

K-space algorithmic reconstruction (KAREN): a robust statistical methodology to separate Bragg and diffuse scattering

Diffuse scattering occurring in the Bragg diffraction pattern of a long-range-ordered structure represents local deviation from the governing regular lattice. However, interpreting the real-space structure from the diffraction pattern presents a significant challenge because of the dramatic difference in intensity between the Bragg and diffuse components of the total scattering function. In contrast to the sharp Bragg diffraction, the diffuse signal has generally been considered to be a weak expansive or continuous background signal. In this paper, using 1D and 2D models, it is demonstrated that diffuse scattering in fact consists of a complex array of high-frequency features that must not be averaged into a low-frequency background signal. To evaluate the actual diffuse scattering effectively, an algorithm has been developed that uses robust statistics and traditional signal processing techniques to identify Bragg peaks as signal outliers which can be removed from the overall scattering data and then replaced by statistically valid fill values. This method, described as a 'K-space algorithmic reconstruction' (KAREN), can identify Bragg reflections independent of prior knowledge of a system's unit cell. KAREN does not alter any data other than that in the immediate vicinity of the Bragg reflections, and reconstructs the diffuse component surrounding the Bragg peaks without introducing discontinuities which induce Fourier ripples or artifacts from underfilling `punched' voids. The KAREN algorithm for reconstructing diffuse scattering provides demonstrably better resolution than can be obtained from previously described punch-and-fill methods. The superior structural resolution obtained using the KAREN method is demonstrated by evaluating the complex ordered diffuse scattering observed from the neutron diffraction of a single plastic crystal of CBr 4 using pair distribution function analysis.

36 MATERIALS SCIENCE↗

Instrumentation and experimental procedures for robust collection of X-ray diffraction data from protein crystals across physiological temperatures

Traditional X-ray diffraction data collected at cryo-temperatures have delivered invaluable insights into the three-dimensional structures of proteins, providing the backbone of structure–function studies. While cryo-cooling mitigates radiation damage, cryo-temperatures can alter protein conformational ensembles and solvent structure. Furthermore, conformational ensembles underlie protein function and energetics, and recent advances in room-temperature X-ray crystallography have delivered conformational heterogeneity information that can be directly related to biological function. Given this capability, the next challenge is to develop a robust and broadly applicable method to collect single-crystal X-ray diffraction data at and above room temperature. This challenge is addressed herein. The approach described provides complete diffraction data sets with total collection times as short as ~5 s from single protein crystals, dramatically increasing the quantity of data that can be collected within allocated synchrotron beam time. Its applicability was demonstrated by collecting 1.09–1.54 Å resolution data over a temperature range of 293–363 K for proteinase K, thaumatin and lysozyme crystals at BL14-1 at the Stanford Synchrotron Radiation Lightsource. Here, the analyses presented here indicate that the diffraction data are of high quality and do not suffer from excessive dehydration or radiation damage.

36 MATERIALS SCIENCE↗

LaueMatching: an approach for rapid and robust indexing of Laue diffraction patterns

Traditional Laue diffraction pattern indexing often struggles with noisy data, weak signals, peak overlap and missing reflections, particularly from complex or deformed microstructures. Here, we introduce LaueMatching, a high-throughput indexing algorithm designed to overcome these limitations. LaueMatching utilizes a fundamentally different approach based on direct pattern correlation: experimentally pre-processed images are compared against a comprehensive pre-computed library of simulated diffraction patterns corresponding to a dense grid of possible orientations. This approach bypasses the need for explicit peak identification and fitting, steps that are often a failure point for traditional methods. The algorithm rapidly and robustly indexes multiple crystallographic orientations and crystal systems simultaneously, even from challenging patterns. LaueMatching's effectiveness and accuracy have been rigorously tested and validated on diverse experimental (Ni, Al, EuAl 2 O 4 ) and simulated diffraction patterns, demonstrating high-fidelity orientation refinement. Code to implement this approach on both CPU and GPU resources can be downloaded from https://github.com/AdvancedPhotonSource/LaueMatching.

36 MATERIALS SCIENCE↗

Robust framework and software implementation for fast speciation mapping

One of the greatest benefits of synchrotron radiation is the ability to perform chemical speciation analysis through X-ray absorption spectroscopies (XAS). XAS imaging of large sample areas can be performed with either full-field or raster-scanning modalities. A common practice to reduce acquisition time while decreasing dose and/or increasing spatial resolution is to compare X-ray fluorescence images collected at a few diagnostic energies. In this work, several authors have used different multivariate data processing strategies to establish speciation maps. Furthermore, the theoretical aspects and assumptions that are often made in the analysis of these datasets are focused on. A robust framework is developed to perform speciation mapping in large bulk samples at high spatial resolution by comparison with known references. Two fully operational software implementations are provided: a user-friendly implementation within the MicroAnalysis Toolkit software, and a dedicated script developed under the R environment. The procedure is exemplified through the study of a cross section of a typical fossil specimen. Additionally, the algorithm provides accurate speciation and concentration mapping while decreasing the data collection time by typically two or three orders of magnitude compared with the collection of whole spectra at each pixel. Whereas acquisition of spectral datacubes on large areas leads to very high irradiation times and doses, which can considerably lengthen experiments and generate significant alteration of radiation-sensitive materials, this sparse excitation energy procedure brings the total irradiation dose greatly below radiation damage thresholds identified in previous studies. This approach is particularly adapted to the chemical study of heterogeneous radiation-sensitive samples encountered in environmental, material, and life sciences.

47 OTHER INSTRUMENTATION↗

Robust Cubature Kalman Filter for Dynamic State Estimation of Synchronous Machines Under Unknown Measurement Noise Statistics

The Kalman-type filtering techniques including cubature Kalman filter (CKF) does not work well in non-Gaussian environments, especially in the presence of outliers. To solve this problem, Huber's M-estimation-based robust CKF (RCKF) is proposed for synchronous machines by combining the Huber's M-estimation theory with the classical CKF, which is capable of coping with the deterioration in performance and discretization of tracking curves when measurement noise statistics deviate from the prior noise statistics. The proposed RCKF algorithm has good adaptability to unknown measurement noise statistics characteristics including non-Gaussian measurement noise and outliers. The simulation results on the WSCC 3-machine 9-bus system and New England 16-machine 68-bus system verify the effectiveness of the proposed method and its advantage over the classical CKF.

42 ENGINEERING↗

Robust Structural Analysis and Design of Distributed Control Systems to Prevent Zero Dynamics Attacks

We consider the design and analysis of robust distributed control systems (DCSs) to ensure the detection of integrity attacks. DCSs are often managed by independent agents and are implemented using a diverse set of sensors and controllers. However, the heterogeneous nature of DCSs along with their scale leave such systems vulnerable to adversarial behavior. To mitigate this reality, we provide tools that allow operators to prevent zero dynamics attacks when as many as p agents and sensors are corrupted. Such a design ensures attack detectability in deterministic systems while removing the threat of a class of stealthy attacks in stochastic systems. To achieve this goal, we use graph theory to obtain necessary and sufficient conditions for the presence of zero dynamics attacks in terms of the structural interactions between agents and sensors. We then formulate and solve optimization problems which minimize communication networks while also ensuring a resource limited adversary cannot perform a zero dynamics attacks. Polynomial time algorithms for design and analysis are provided.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

adaptation models↗

Disruption-Robust Community Detection Using Consensus Clustering in Complex Networks

Topological (graph-theoretic) analysis of critical infrastructure networks provides insight on several aspects of resilience. Graph clustering or community detection, which identifies densely connected components in a graph, has been employed for analysis. In this paper, we propose employing consensus clustering, which is a technique to determine consensus from a collection of different clusters on an input, such that the resulting clustering is robust to disruptions, where a disruption is represented as loss of one or more vertices or edges in the graph. Using two critical infrastructure networks as case studies, we empirically demonstrate the need to compute consensus clustering in order to address the drastic changes in the topology due to disruptions in the network.

Hussain, Md Taufique↗

Reducing Conservativeness of Polytopic Linear-Parameter-Varying Robust Vehicle Sideslip Angle Observer Through Minimum-Area Convex Quadrilateral Design

The polytopic linear-parameter-varying (LPV) method has become increasingly popular for designing intelligent control and estimation systems for ground vehicles, particularly for the vehicle sideslip angle observer. In vehicle lateral dynamics, the vehicle longitudinal velocity-induced nonlinearities are conventionally outer-approximated with polytopes such as rectangles or triangles to obtain a polytopic LPV system. Yet, such polytopic approximations tend to be conservative and may lead to inadequate observer performance. To address this issue, a minimum-area convex quadrilateral construction is proposed in this paper to reduce design conservatism. The suggested design is demonstrated through the synthesis of an LPV H ∞ robust vehicle sideslip angle observer. Furthermore, a dSPACE-ASM simulation study is conducted to demonstrate the effectiveness and the advantage of the proposed polytopic construction over a baseline approach.

Zhou, Xingyu↗

2 kV, 0.7 mΩ•cm2 Vertical Ga2O3 Superjunction Schottky Rectifier with Dynamic Robustness

We report the first experimental demonstration of a vertical superjunction device in ultra-wide bandgap (UWBG) Ga 2 O 3 . The device features 1.8 μm wide, 2×10 17 cm -3 doped n-Ga 2 O 3 pillars wrapped by the charge-balanced p-type nickel oxide (NiO). The sidewall NiO is sputtered through a novel self-align process. Benefited from the high doping in Ga 2 O 3 , the superjunction Schottky barrier diode (SJ-SBD) achieves a ultra-low specific on-resistance (R ON,SP ) of 0.7 mΩ•cm 2 with a low turn-on voltage of 1 V and high breakdown voltage (BV) of 2000 V. The R ON,SP ~BV trade-off is among the best in all WBG and UWBG power SBDs. The device also shows good thermal stability with BV > 1.8 kV at 175 °C. In the unclamped inductive switching tests, the device shows a dynamic BV of 2.2 kV and no degradation under 1.7 kV repetitive switching, verifying the fast acceptor depletion in NiO under dynamic switching. Such high-temperature and switching robustness are reported for the first time in a heterogeneous superjunction. These results show the great potential of UWBG superjunction power devices.

Qin, Yuan↗