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At least 1,441 records · Page 80

Detecting axionlike dark matter with linearly polarized pulsar light

QCD axions or axionlike particles are among the most popular candidates for cold dark matter (DM) in the Universe. We proposed to detect axionlike DM, using linearly polarized pulsar light as a probe. Because of birefringence effect potentially caused by an oscillating galactic axion DM background, when pulsar light travels across the Galaxy, its linear polarization angle may vary with time. With a soliton + NFW galactic DM halo profile, we show that this strategy can potentially probe an axion-photon coupling as small as ~10 –13 GeV –1 for axion mass $m_a$ ~ 10 –22 –10 –20 eV , given the current measurement accuracy. An exclusion limit stronger than CAST (~ 10 –10 GeV –1 ) and SN1987A (~ 10 –11 GeV –1 ) could be extended up to $m_a$ ~ 10 –18 eV and ~10 –19 eV, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

Neutrino fast flavor oscillations with moments: Linear stability analysis and application to neutron star mergers

Providing an accurate modeling of neutrino physics in dense astrophysical environments such as binary neutron star mergers presents a challenge for hydrodynamic simulations. Nevertheless, understanding how flavor transformation can occur and affect the dynamics, the mass ejection, and the nucleosynthesis will need to be achieved in the future. Computationally expensive, large-scale simulations frequently evolve the first classical angular moments of the neutrino distributions. By promoting these quantities to matrices in flavor space, we develop a linear stability analysis of fast flavor oscillations using only the first two “quantum” moments, which notably requires generalizing the classical closure relations that appropriately truncate the hierarchy of moment equations in order to treat quantum flavor coherence. After showing the efficiency of this method on a well-understood test situation, we perform a systematic search of the occurrence of fast flavor instabilities in a neutron star merger simulation. Here, we discuss the successes and shortcomings of moment linear stability analysis, as this framework provides a time-efficient way to design and study better closure prescriptions in the future.

79 ASTRONOMY AND ASTROPHYSICS↗

Cosmic distance inference from purely geometric BAO methods: Linear point standard ruler and correlation function model fitting

Leveraging the baryon acoustic oscillations (BAO) feature present in clustering 2-point statistics, we aim to measure cosmological distances independently of the underlying background cosmological model. However this inference is complicated by late-time nonlinearities that introduce model and tracer dependencies in the clustering correlation function and power spectrum, which must be properly accounted for. With this in mind, we introduce the “purely geometric-BAO,” which provides a rigorous tool to measure cosmological distances without assuming a specific background cosmology. We focus on the 2-point clustering correlation function monopole, and show how to implement such an inference scheme employing two different methodologies: the linear point standard ruler (LP) and correlation-function model-fitting (CF-MF). For the first time we demonstrate how, by means of the CF-MF, we can measure very precisely the sound-horizon/isotropic-volume-distance ratio, r d /DV(z¯), while correctly propagating all the uncertainties. Using synthetic data, we compare the outcomes of the two methodologies, and find that the LP provides up to 50% more precise measurements than the CF-MF. Finally, we test a procedure widely employed in BAO analyses: fitting the 2-point function while fixing the cosmological and the non-linear-damping parameters at fiducial values. We find that this underestimates the distance errors by nearly a factor of 2. Furthermore, we recommend that this practice be reconsidered, whether for parameter determination or model selection.

79 ASTRONOMY AND ASTROPHYSICS↗

Linear magnetoresistance caused by mobility fluctuations in n -doped Cd 3 As 2

Cd 3 As 2 is a candidate three-dimensional Dirac semimetal which has exceedingly high mobility and nonsaturating linear magnetoresistance that may be relevant for future practical applications. We report magnetotransport and tunnel diode oscillation measurements on Cd 3 As 2 , in magnetic fields up to 65 T and temperatures between 1.5 and 300 K. We find that the nonsaturating linear magnetoresistance persists up to 65 T and it is likely caused by disorder effects, as it scales with the high mobility rather than directly linked to Fermi surface changes even when approaching the quantum limit. As a result of the observed quantum oscillations, we determine the bulk three-dimensional Fermi surface having signatures of Dirac behavior with a nontrivial Berry phase shift, very light effective quasiparticle masses, and clear deviations from the band-structure predictions. In very high fields we also detect signatures of large Zeeman spin splitting (g~16).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Self-sustained micro mechanical oscillator with linear feedback

Autonomous oscillators, such as clocks and lasers, produce periodic signals without any external frequency reference. In order to sustain stable periodic motions, there needs to be external energy supply as well as nonlinearity built into the oscillator to regulate the amplitude. Usually, nonlinearity is provided by the sustaining feedback mechanism, which also supplies energy, whereas the constituent resonator that determines the output frequency stays linear. Here we propose a new self-sustaining scheme that relies on the nonlinearity originating from the resonator itself to limit the oscillation amplitude, while the feedback remains linear. We introduce a model to describe the working principle of the self-sustained oscillations and validate it with experiments performed on a nonlinear microelectromechanical (MEMS) based oscillator.

42 ENGINEERING↗

Electron-Phonon Coupling from Ab Initio Linear-Response Theory within the G W Method: Correlation-Enhanced Interactions and Superconductivity in Ba 1 - x K x BiO 3

We present a new first-principles linear-response theory of changes due to perturbations in the quasiparticle self-energy operator within the GW method. This approach, named GW perturbation theory ( GW PT), is applied to calculate the electron-phonon ( e -ph) interactions with the full inclusion of the GW nonlocal, energy-dependent self-energy effects, going beyond density-functional perturbation theory. Avoiding limitations of the frozen-phonon technique, GW PT gives access to e -ph matrix elements at the GW level for all phonons and scattering processes, and the computational cost scales linearly with the number of phonon modes (wave vectors and branches) investigated. We demonstrate the capabilities of GW PT by studying the e -ph coupling and superconductivity in Ba 0.6 K 0.4 BiO 3 . We show that many-electron correlations significantly enhance the e -ph interactions for states near the Fermi surface, and explain the observed high superconductivity transition temperature of Ba 0.6 K 0.4 BiO 3 as well as its doping dependence.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Emergence of Topologically Nontrivial Spin-Polarized States in a Segmented Linear Chain

The synthesis of new materials with novel or useful properties is one of the most important drivers in the fields of condensed matter physics and materials science. Discoveries of this kind are especially significant when they point to promising future basic research and applications. Van der Waals bonded materials comprised of lower-dimensional building blocks have been shown to exhibit emergent properties when isolated in an atomically thin form. Here, we report the discovery of a transition metal chalcogenide in a heretofore unknown segmented linear chain form, where basic building blocks each consisting of two hafnium atoms and nine tellurium atoms (Hf 2 Te 9 ) are van der Waals bonded end-to-end. First-principle calculations based on density functional theory reveal striking crystal-symmetry-related features in the electronic structure of the segmented chain, including giant spin splitting and nontrivial topological phases of selected energy band states. In this work, atomic-resolution scanning transmission electron microscopy reveals single segmented Hf 2 Te 9 chains isolated within the hollow cores of carbon nanotubes, with a structure consistent with theoretical predictions. Van der Waals-bonded segmented linear chain transition metal chalcogenide materials could open up new opportunities in low-dimensional, gate-tunable, magnetic and topological crystalline systems.

36 MATERIALS SCIENCE↗

CBETA: The first multi-pass superconducting linear accelerator with energy recovery

Energy recovery has been achieved in a multipass linear accelerator, demonstrating a technology for more compact particle accelerators operating at higher currents and reduced energy consumption. Energy delivered to the beam during the first four passes through the accelerating structure was recovered during four subsequent decelerating passes. High-energy efficiency was achieved by the use of superconducting accelerating cavities and permanent magnets. The fixed-field alternating-gradient optical system used for the return loop successfully transported electron bunches of 42, 78, 114, and 150 MeV in a common vacuum chamber. This new kind of accelerator, an eight-pass energy recovery linac, has the potential to accelerate much higher current than existing linear accelerators while maintaining small beam dimensions and consuming much less energy per electron.

43 PARTICLE ACCELERATORS↗

Linearly aligned single-chiral vortices in hexagonal manganites by in situ electric arc heating

Nanoscale topological defects, such as vortices and skyrmions in ferroic systems, have been intensively investigated due to their intriguing properties and behaviors. In addition to harnessing and tuning their functionalities, spatial manipulation and control of topological defects as functional elements are important for future nanotechnologies. Here in this paper, we report a linear alignment behavior of single-chiral vortices observed in thin transmission electron microscopy samples of multiferroic hexagonal manganites during an in situ heating experiment. In order to avoid chemical degradation during high-temperature heating in vacuum, we have utilized a rapid heating and quenching by in situ electric arcing. Using atomic resolution electron microscopy and phase-field simulation, we found that vortices and antivortices formed near the phase transition temperature are pulled out in the opposite directions by mechanical strain to leave single-chiral vortices linearly aligned along an isothermal line formed during quenching. In conclusion, Oour study provides important insight into spatial manipulation of the topological defects in oxide multiferroics by investigating far-equilibrium dynamics of symmetry-breaking continuous phase transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Memristive linear algebra

The advent of memristive devices offers a promising avenue for efficient and scalable analog computing, particularly for linear algebra operations essential in various scientific and engineering applications. This paper investigates the potential of memristive crossbars in implementing matrix inversion algorithms. We explore both static and dynamic approaches, emphasizing the advantages of analog and in-memory computing for matrix operations beyond multiplication. In particular, we demonstrate that the electrical properties of memristive crossbars uniquely suit them for the evolution of a family of matrix exponentials, which can be exploited for the efficient computation of matrix inverses and online solutions for linear problems. Our results demonstrate that memristive arrays can reduce computational complexity. We also study power consumption and show a tradeoff between precision and energy. Furthermore, we address the challenges of device variability, precision, and scalability, providing insights into the practical implementation of these algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analyzer-free linear dichroic ptychography

Linear dichroism is an important tool to characterize the transmission matrix and determine the crystal or orbital orientation in a material. To achieve high-resolution mapping of transmission properties, we introduce the linear-dichroism scattering model in ptychographic imaging and develop an efficient two-stage reconstruction algorithm. Using the proposed algorithm on a uniaxial material, the dichroic transmission matrix can be recovered without an analyzer by using ptychography measurements with as few as three different polarization angles, with the help of an empty region to remove phase ambiguities.

97 MATHEMATICS AND COMPUTING↗

Adaptive Linear State Estimation for Unbalanced Distribution System

The inclusion of PMU functionality in distribution relays enables the implementation of a linear state estimator (LSE) in Distribution Systems (DS). However, the unbalanced topology and phase coupling in distribution lines necessitate modifications to the LSE formulation. Additionally, the higher fault frequency in distribution systems requires a state estimation approach that is resilient to contingencies. This work proposes an adaptive linear state estimation algorithm tailored for unbalanced distribution systems with single-phase and two-phase laterals. Furthermore, a modified Optimal PMU Placement (OPP) strategy is introduced to ensure full observability in distribution systems with single-phase and two-phase buses. To maintain adaptability to topology changes, the state estimator incorporates circuit breaker status data provided by PMUs, ensuring robust performance during topology changes triggered by faults. The performance of the algorithm is verified on the IEEE 13-bus, 34-bus, and 123-bus systems.

PMUs↗

Scaling Up Data-Parallel Analytics Platforms: Linear Algebraic Operation Cases

Linear algebraic operations such as matrix manipulations form the kernel of many machine learning and other crucial algorithms. Scaling up as well as scaling out such algorithms are key to supporting large scale data analysis that require efficient processing over millions of data samples. To this end, we present, ARION, a hardware acceleration based approach for scaling-up individual tasks of Spark, a popular data-parallel analytics platform. We support both linear algebraic operations of between two dense matrices, and between sparse and dense matrices in distributed environments. ARION provides a flexible control of acceleration according to matrix density, along with efficient scheduling based on runtime resource utilization. We demonstrate the benefit of our approach for general matrix multiplication operations over large matrices with up to four billion elements by using Gramian matrix computation that is commonly used in machine learning. Experiments show that our approach achieves more than 2× and 1.5× end-to-end performance speedups for dense and sparse matrices, respectively, and up to 57.04× faster computation compared to MLlib, a state of the art Spark-based implementation. This work is sponsored in part by the NSF under the grants: CNS-1565314, CNS-1405697, and CNS-1615411. The manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

Xu, Luna↗

TeaLeaf: A Mini-Application to Enable Design-Space Explorations for Iterative Sparse Linear Solvers

Iterative sparse linear solvers are an important class of algorithm in high performance computing, and form a crucial component of many scientific codes. As intra and inter node parallelism continues to increase rapidly, the design of new, scalable solvers which can target next generation architectures becomes increasingly important. In this work we present TeaLeaf, a recent mini-app constructed to explore design space choices for highly scalable solvers. We then use TeaLeaf to compare the standard CG algorithm with a Chebyshev Polynomially Preconditioned Conjugate Gradient (CPPCG) iterative sparse linear solver. CPPCG is a communication-avoiding algorithm, requiring less global communication than previous approaches. TeaLeaf includes support for many-core processors, such as GPUs and Xeon Phi, and we include strong-scaling results across a range of world-leading Petascale supercomputers, including Titan and Piz Daint.

97 MATHEMATICS AND COMPUTING↗

THz and Mid-Infrared Linear Dichroism in the High Tc Superconductor La2-xSrxCuO4

We measure the rotation of the linear polarization of light that is transmitted through a high Tc superconductor film as a function of sample orientation. We observe a linear dichroism signal over the entire probing range from 2 to 230 meV, which is consistent with anisotropic in-plane conductivity. The La2- xSrxCuO4 thin film sample is epitaxially constrained to be tetragonal, so the symmetry breaking is purely electronic.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Comparison of Linear and Rotary Electric Machine Topologies for a Hybrid Hydraulic Electric Architecture of Off-Highway Vehicles

Electrification of off-highway vehicles offers the benefits of improved energy efficiency, enhanced controllability, and reduction in greenhouse gas emissions. However, progress towards electrification has been limited by the low power density of electric components compared to hydraulic components. A recently proposed hybrid hydraulic electric vehicle architecture provides a potential solution to these power density challenges by minimizing the required power rating of the electric components. This paper investigates the optimal design of linear and rotary electric machines for this new system architecture. Key performance metrics are identified for the electric machine, several variants of electric machines are analytically sized and compared for two different power levels, and an FEA-assisted design optimization is performed on promising candidates. Based on the optimization results, it is shown that an axial flux rotary machine is most suitable for implements requiring high power ratings, while the linear machine's form factor makes it a compelling candidate for lower power implements.

42 ENGINEERING↗

Iterative Linearization for Phasor-Defined Optimal Power Dispatch

Optimal power flow (OPF) problems, which dispatch power targets to controllable generating units across a network, must generally account for non-convex constraints on power flow. Furthermore, adapting those problems so as to make them solvable with convex optimization techniques is an area of much academic and operational interest. In this paper, we present a method for solving OPF as a quadratic program by iteratively refining and re-initializing a linearized model of power flow based on the outputs of an associated nonlinear solver. The linear model on which we demonstrate this method is an adapted version of an approximation designed for use with unbalanced distribution networks. As an important benefit, the model allows for the explicit inclusion of nodal voltage phasor values in both the OPF problem's objective and its constraints, which opens the door to the idea of phasor-based control (PBC) design. We show in simulations on the IEEE 13-node test feeder that our method quickly converges to a set of phasor targets that are sufficiently precise for use in operations at the distribution level.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Linear Solver for Electromagnetic Simulation of General Distribution Feeders

High-fidelity electromagnetic transient (EMT) modeling is required for accurate simulation and analysis of power system dynamics in modern distribution feeders. However, the high-fidelity of EMT models often leads to significant computational challenges, particularly in terms of computational resources and simulation time. This paper investigates the development and application of a detailed EMT model for general distribution feeders, with a focus on improving computational efficiency. A direct linear solver is proposed for a bordered block diagonal (BBD) matrix structure commonly encountered in a EMT model of distribution feeders. The solver integrates the Schur complement method with the block tridiagonal matrix algorithm to enhance the computational performance. The proposed solver is validated using the primary feeder of the IEEE 342-node test system, demonstrating its accuracy and efficiency in EMT simulations. Furthermore, the solver’s performance is benchmarked against MATLAB’s built-in linear solvers, showing significant improvements in computation time while maintaining high fidelity and accuracy in simulation results.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗