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At least 361 records · Page 20

Imaging stress and magnetism at high pressures using a nanoscale quantum sensor

Pressure alters the physical, chemical, and electronic properties of matter. The diamond anvil cell enables tabletop experiments to investigate a diverse landscape of high-pressure phenomena. In this work, we introduce and use a nanoscale sensing platform that integrates nitrogen-vacancy (NV) color centers directly into the culet of diamond anvils. We demonstrate the versatility of this platform by performing diffraction-limited imaging of both stress fields and magnetism as a function of pressure and temperature. We quantify all normal and shear stress components and demonstrate vector magnetic field imaging, enabling measurement of the pressure-driven α ↔ ϵ phase transition in iron and the complex pressure-temperature phase diagram of gadolinium. A complementary NV-sensing modality using noise spectroscopy enables the characterization of phase transitions even in the absence of static magnetic signatures.

36 MATERIALS SCIENCE↗

Search for dark matter produced in association with a leptonically decaying Z boson in proton-proton collisions at $\sqrt{s} =$ 13 TeV

A search for dark matter particles is performed using events with a Z boson candidate and large missing transverse momentum. The analysis is based on proton–proton collision data at a center-of-mass energy of 13$\,\text {Te}\text {V}$, collected by the CMS experiment at the LHC in 2016–2018, corresponding to an integrated luminosity of 137$\,\text {fb}^{-1}$. The search uses the decay channels ${\mathrm{Z}} \rightarrow {\mathrm{e}} {\mathrm{e}} $ and ${\mathrm{Z}} \rightarrow {{\upmu }{}{}} {{\upmu }{}{}} $. No significant excess of events is observed over the background expected from the standard model. Limits are set on dark matter particle production in the context of simplified models with vector, axial-vector, scalar, and pseudoscalar mediators, as well as on a two-Higgs-doublet model with an additional pseudoscalar mediator. In addition, limits are provided for spin-dependent and spin-independent scattering cross sections and are compared to those from direct-detection experiments. The results are also interpreted in the context of models of invisible Higgs boson decays, unparticles, and large extra dimensions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A New Capability of E4D For 3D Parallel Joint Inversion of DC Resistivity And Traveltime Data on Unstructured Mesh

A major challenge in interpreting geophysical data is how to derive consistent three-dimensional (3D) earth models of different physical properties from spatially and temporally limited measurements. Joint inversion with cross-gradient constraints is an approach to find such models by imposing structural similarities between different physical parameters. We have developed a parallel distributed-memory joint inversion code for direct-current (DC) resistivity and traveltime data using the cross-gradient constraint on unstructured mesh. The code utilizes existing E4D framework for parallel forward simulation, distributed storage and computation of the Jacobian matrix of forward operator, and parallel execution of matrix-vector multiplication during inversion. Besides, the joint inversion is solved by nonlinear conjugate gradient algorithm parallelized for DC resistivity and traveltime data. The joint inversion capability of E4D was tested using synthetic data from cross-borehole DC resistivity and traveltime data. The results indicate that the shape and size of the anomalies from the joint inversion are more reliable than those from separate inversions.

58 GEOSCIENCES↗

Subspace Methods in Multi-Parameter Seismic Full Waveform Inversion

In full waveform inversion (FWI) high-resolution subsurface model parameters are sought. FWI is normally treated as a nonlinear least-squares inverse problem, in which the minimum of the corresponding misfit function is found by updating the model parameters. When multiple elastic or acoustic properties are solved for, simple gradient methods tend to confuse parameter classes. This is referred to as parameter cross-talk; it leads to incorrect model solutions, poor convergence and strong dependence on the scaling of the different parameter types. Determining step lengths in a subspace domain, rather than directly in terms of gradients of different parameters, is a potentially valuable approach to address this problem. The particular subspace used can be defined over a span of different sets of data or different parameter classes, provided it involves a small number of vectors compared to those contained in the whole model space. Additionally, in a subspace method, the basis vectors are defined first, and a local minimum is found in the space spanned by these. We examine the application of the subspace method within acoustic FWI in determining simultaneously updates for velocity and density. We first discuss the choice of basis vectors to construct the spanned space, from linear updates by distinguishing only the contributions of different parameter classes towards nonlinear updates by adding the contributions of higher-order perturbations of each parameter class. The numerical character of FWI solutions generated via subspace methods involving different basis vectors is then analyzed and compared with traditional FWI methods. The subspace methods can provide better reconstructions of the model, especially for the velocity, as well as improved convergence rates, while the computational costs are still comparable with the traditional FWI methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Single-qubit multi-party transmission using universal symmetric quantum cloning

This study considers the hypothetical quantum network case where Alice wishes to transmit one qubit of information (specifically a pure quantum state) to M parties, where M is some large number. The remote receivers locally perform single-qubit quantum state tomography on the transmitted qubits in order to compute the quantum state within some error rate (dependent on the tomography technique and the number of transmitted qubits). We show that with the use of an intermediate optimal symmetric universal quantum cloning machine (between Alice and the remote receivers) as a repeater-type node in a hypothetical quantum network, Alice can send significantly fewer qubits compared to direct transmission of the message qubits to each of the M remote receivers. This is possible due to two properties of quantum cloning. The first is that single qubit quantum clones retain the same Bloch angle as the initial quantum state. This means that if the mixed state of the quantum clone can be computed to high enough accuracy, the original pure quantum state can be inferred by extrapolating that vector to the surface of the Bloch sphere. The second property is that the state overlap of approximate quantum clones, with respect to the original pure quantum state, quickly converges (specifically for 1 → M , the limit of the fidelity as M goes to infinity is $\frac{2}{3}$). This means that Alice can prepare a constant number of qubits (which are then passed through the quantum cloning machine) in order to achieve a desired error rate if M is large enough. Combined, these two properties mean that for a large M , Alice can prepare many orders of magnitude fewer qubits in order to achieve the same single qubit transmission accuracy compared to the naive direct qubit transmission approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Gravitational soft theorem from emergent soft gauge symmetries

We consider and derive the gravitational soft theorem up to the sub-subleading power from the perspective of effective Lagrangians. The emergent soft gauge symmetries of the effective Lagrangian provide a transparent explanation of why soft graviton emission is universal to sub-subleading power, but gauge boson emission is not. They also suggest a physical interpretation of the form of the soft factors in terms of the charges related to the soft transformations and the kinematics of the multipole expansion. The derivation is done directly at Lagrangian level, resulting in an operatorial form of the soft theorems. In order to highlight the differences and similarities of the gauge-theory and gravitational soft theorems, we include an extensive discussion of soft gauge-boson emission from scalar, fermionic and vector matter at subleading power.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗

Towards the extraction of the crystal cell parameters from pair distribution function profiles

The approach based on atomic pair distribution function (PDF) has revolutionized structural investigations by X-ray/electron diffraction of nano or quasi-amorphous materials, opening up the possibility of exploring short-range order. However, the ab initio crystal structural solution by the PDF is far from being achieved due to the difficulty in determining the crystallographic properties of the unit cell. A method for estimating the crystal cell parameters directly from a PDF profile is presented, which is composed of two steps: first, the type of crystal cell is inferred using machine-learning approaches applied to the PDF profile; second, the crystal cell parameters are extracted by means of multivariate analysis combined with vector superposition techniques. The procedure has been validated on a large number of PDF profiles calculated from known crystal structures and on a small number of measured PDF profiles. The lattice determination step has been benchmarked by a comprehensive exploration of different classifiers and different input data. The highest performance is obtained using the k -nearest neighbours classifier applied to whole PDF profiles. Descriptors calculated from the PDF profiles by recurrence quantitative analysis produce results that can be interpreted in terms of PDF properties, and the significance of each descriptor in determining the prediction is evaluated. The cell parameter extraction step depends on the cell metric rather than its type. Monometric, dimetric and trimetric cells have top-1 estimates that are correct 40, 20 and 5% of the time, respectively. Promising results were obtained when analysing real nanocrystals, where unit cells close to the true ones are found within the top-1 ranked solution in the case of monometric cells and within the top-6 ranked solutions in the case of dimetric cells, even in the presence of a crystalline impurity with a weight fraction up to 40%.

36 MATERIALS SCIENCE↗

Effects of upstream rotor tilt on a downstream floating wind turbine

This work quantifies the relationship between the design tilt of an upstream rotor and the structural response of a spar floating offshore wind turbine located in its wake. Three wind speed scenarios are considered: below, at, and above rated operation. The inflow is generated with the Mann model and the wake and loads are simulated with FAST.Farm. As the upstream rotor tilt goes from 0° to 6°, we find that the mean wake is displaced upward by more than 0.2 rotor diameters (D) by a downstream distance of 7 D. The vertical velocities increase by up to 35 cm/s in the center of the wake. As a result, the downstream rotor is partially waked and experiences a rotated velocity vector. With a higher upstream rotor tilt, the velocities and moments on the downstream turbine increase their mean axial value and their lateral and vertical standard deviation. These changes affect the blade and tower loading and the floater motion primarily in the out-of-plane direction: the damage-equivalent loads for the tower pitch moment and blade-root moment increase by up to 10% because of higher variability at the first mode for the tower and at one blade passing frequency for the blade root. Lesser effects are observed for the roll moments and for floater sway and heave. When the joint effect of rotor tilt and platform motion is considered, the load response on the downstream system is amplified primarily for tower pitch and blade out-of-plane moment.

17 WIND ENERGY↗

Heating neutron stars with GeV dark matter

An old neutron star (NS) may capture halo dark matter (DM) and get heated up by the deposited kinetic energy, thus behaving like a thermal DM detector with sensitivity to a wide range of DM masses and a variety of DM-quark interactions. Near future infrared telescopes will measure NS temperatures down to a few thousand Kelvin and probe NS heating by DM capture. We focus on GeV-mass Dirac fermion DM (which is beyond the reach of current DM direct detection experiments) in scenarios in which the DM capture rate can saturate the geometric limit. For concreteness, we study (1) a model that invokes dark decays of the neutron to explain the neutron lifetime anomaly, and (2) a framework of DM coupled to quarks through a vector current portal. In the neutron dark decay model a NS can have a substantial DM population, so that the DM capture rate can reach the geometric limit through DM self-interactions even if the DM-neutron scattering cross section is tiny. We find NS heating to have greater sensitivity than multipion signatures in large underground detectors for the neutron dark decay model, and sub-GeV gamma-ray signatures for the quark vector portal model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Anisotropic Cahn-Hilliard free energy and interfacial energies for binary alloys with pairwise interactions

The original Cahn-Hilliard derivation of the contribution of compositional inhomogeneity to the free energy of a binary alloy with pairwise interactions is extended to include higher-order inhomogeneity terms. For alloys on a cubic lattice, the coefficient of the first inhomogeneity is a second-rank tensor and reduces to a scalar, but it is shown that the second order and the third order inhomogeneity terms are weighted by fourth-rank and sixth-rank tensors, thus resulting in anisotropic contributions. Furthermore, each interaction shell generates a unique set of inhomogeneity coefficients that is determined by the set of vectors connecting an atom to its neighbors on that shell. These coefficients are calculated for fcc and bcc alloys with interactions up fourth nearest neighbors. Phase field simulations based on these extended Cahn-Hilliard free energies are performed to measure interface free energies along specific crystallographic directions as a function of temperature, and to obtain the equilibrium shape of precipitates. Interface free energies, and the resulting anisotropies, are compared to those obtained by discrete models and Monte Carlo simulations.

36 MATERIALS SCIENCE↗

Exact hopfion vortices in a 3D Heisenberg ferromagnet

Here, we find exact static soliton solutions for the unit spin vector field of an inhomogeneous, anisotropic three-dimensional Heisenberg ferromagnet. Each soliton is labeled by two integers n and m. It is a (modified) skyrmion in the z = 0 plane with winding number n, which twists out of the plane m times in the z-direction to become a 3D soliton. Here m arises due to the periodic boundary condition at the z-boundaries. We use Whitehead’s integral expression to find that the Hopf invariant of the soliton is an integer H = nm. It represents a hopfion vortex. Plots of the preimages of this topological soliton show that they are either unknots or nontrivial knots, depending on n and m. Any pair of preimage curves links H times, corroborating the interpretation of H as a linking number. We also calculate the exact energy of the hopfion vortex, and show that its topological lower bound has a sublinear dependence on H. Using Derrick’s scaling analysis, we demonstrate that the presence of a spatial inhomogeneity in the anisotropic interaction, which in turn introduces a characteristic length scale in the system, leads to the stability of the hopfion vortex.

36 MATERIALS SCIENCE↗

Lightweight and effective tensor sensitivity for atomistic neural networks

Atomistic machine learning focuses on the creation of models that obey fundamental symmetries of atomistic configurations, such as permutation, translation, and rotation invariances. In many of these schemes, translation and rotation invariance are achieved by building on scalar invariants, e.g., distances between atom pairs. There is growing interest in molecular representations that work internally with higher rank rotational tensors, e.g., vector displacements between atoms, and tensor products thereof. Here, we present a framework for extending the Hierarchically Interacting Particle Neural Network (HIP-NN) with Tensor Sensitivity information (HIP-NN-TS) from each local atomic environment. Crucially, the method employs a weight tying strategy that allows direct incorporation of many-body information while adding very few model parameters. We show that HIP-NN-TS is more accurate than HIP-NN, with negligible increase in parameter count, for several datasets and network sizes. As the dataset becomes more complex, tensor sensitivities provide greater improvements to model accuracy. In particular, HIP-NN-TS achieves a record mean absolute error of 0.927 $\frac{\text{kcal}}{\text{mol}}$ for conformational energy variation on the challenging COMP6 benchmark, which includes a broad set of organic molecules. We also compare the computational performance of HIP-NN-TS to HIP-NN and other models in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resolution of zigzag magnetic correlations in Na-deficient Na x IrO 3 without long-range ordering

The materials search for Kitaev quantum spin liquids led to the discovery of many honeycomb lattice materials. Much attention has been paid to materials without magnetic order down to the lowest temperatures. The newly synthesized Na-deficient Na x IrO 3 has been found to bear no sign of long-range magnetic order above 1 K from physical property measurements. In this paper, we report momentum-and energy-resolved excitation spectra in Na-deficient Na x IrO 3 measured using a resonant inelastic x-ray scattering spectrometer. Orbital excitation spectra show that the octahedral and trigonal crystal field splittings are larger in Na x IrO 3 than in Na 2 IrO 3 . On the other hand, the low-energy spectrum at low temperature shows a wave-vector dispersion and a spectral weight distribution that are similar to those of Na 2 IrO 3 , revealing that the two-dimensional zigzag magnetic correlations in Na x IrO 3 are similar to those in Na 2 IrO 3 in terms of the ordered magnetic moment direction and three dynamically fluctuating zigzag orders. The azimuth angle dependence of the low-energy spectrum corroborates these results. The two-dimensional zigzag magnetic correlations rapidly weaken until 50 K. At high temperatures, the spectral weight distribution of the low-energy excitation resembles that of the pure Kitaev model, indicating that the Kitaev interaction dominates the dynamic magnetic response at high temperature. Here we suggest that the larger crystal field and distortion and the weakened longer-range Heisenberg exchange interactions due to the Na deficiency in Na x IrO 3 contribute to bring Na x IrO 3 away from the zigzag long-range magnetic order phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Characterization of Impedance and Stability for Doubly-Fed Induction Generator Based on Voltage-Modulated Direct Power Control

Voltage-modulated direct power control (VM-DPC) applied to the doubly-fed induction generator (DFIG) offers superior steady-state and transient performance but remains underexplored for suppressing wideband oscillations. Here, this article proposes a comprehensive impedance for the VM-DPC-based DFIG, analyzing its impedance characteristics and stability mechanisms compared with the DFIG based on vector-oriented control (VOC). The unified power transfer function is defined for DFIGs employing VM-DPC or VOC to ensure consistent comparison benchmarks. The comprehensive impedance of VM-DPC-based DFIG, incorporating mechanical and grid-side converter (GSC) dynamics, is derived using complex vector modeling in the αβ -frame. Furthermore, the influence of VM-DPC parameters and grid strength on the stability of grid-connected DFIG systems is assessed through eigenvalue trajectory analysis. Impedance analysis reveals the significant contributions of mechanical and GSC dynamics to DFIG impedance, as well as the narrower frequency range of negative resistance in the VM-DPC-based DFIG compared to the VOC-based DFIG. Stability analysis identifies the VM-DPC parameters of the rotor-side converter as dominant factors affecting system stability and confirms that the VM-DPC-based DFIG achieves better stability under weak grid conditions than its VOC-based counterpart. These findings are validated through simulations and experiments.

42 ENGINEERING↗

Improved Statistics for F-theory Standard Models

Much of the analysis of F-theory-based Standard Models boils down to computing cohomologies of line bundles on matter curves. By varying parameters one can degenerate such matter curves to singular ones, typically with many nodes, where the computation is combinatorial and straightforward. The question remains to relate the (a priori possibly smaller) value on the original curve to the singular one. In this work, we introduce some elementary techniques (pruning trees and removing interior edges) for simplifying the resulting nodal curves to a small collection of terminal ones that can be handled directly. When applied to the QSMs, these techniques yield optimal results in the sense that obtaining more precise answers would require currently unavailable information about the QSM geometries. This provides us with an opportunity to enhance the statistical bounds established in earlier research regarding the absence of vector-like exotics on the quark-doublet curve.

Bies, Martin↗

Water dynamics in C–S–H and M-S-H cement pastes: A revised jump-diffusion and rotation-diffusion model

The Quasi-Elastic Neutron Scattering (QENS) spectra from four cement pastes are re-analyzed by a new revised jump-diffusion and rotation-diffusion model (rJRM). From the QENS fit, it can be seen that the rJRM is an improved model to fit QENS spectra within the whole detected neutron energy transfer and scattering vector. By the rJRM fitting, the structure parameters extracted from QENS spectra show that both the additives aluminum-silicate nanotubes (ASN) and carboxyl group functionalized ASN (ASN-COOH) can improve magnesium-silicate-hydrate (M-S-H) toward calcium-silicate-hydrate (C–S–H) direction in mechanical properties, but the improvement is weakened with decreasing temperatures. The extracted dynamical parameters show that there is a dynamic anomaly near 230 K in not only translational but also rotational diffusion of water confined in all the investigated samples. In conclusion, the anomaly in rotational diffusion is new compared with those results obtained by the QENS fit using other models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nanoscale Control of Polar Surface Phases in Layered van der Waals CuInP 2 S 6

Antiferroelectric (AFE) materials, in which alternating dipole moments cancel out to a zero net macroscopic polarization, can be used for high-density energy storage and memory applications. The AFE phase can exist in bulk CuInP 2 Se 6 , CuBiP 2 S 6 , and a few other transition-metal thiophosphates below 200 K. The required low temperature poses challenges for practical applications. In this work, we report the coexistence of ferrielectric (FE) states and a stable surface phase that does not show piezoelectric response (“zero-response phase”) in bulk CuInP 2 S 6 at room temperature. Using piezoresponse force microscopy (PFM) tomographic imaging together with density functional theory, we find that direct and alternating voltages can locally and stably convert FE to zero-response phases and vice versa. While PFM loops show pinched hystereses reminiscent of antiferroelectricity, PFM tomography reveals that the zero-response areas form only on top of the FE phase in which the polarization vector is pointing up. Theoretical calculations suggest that the zero-response phase may correspond to AFE ordering where stacked CuInP 2 S 6 layers have alternating polarization orientations thereby leading to a net-zero polarization. Consistent with experimental findings, theory predicts that the FE polarization pointing down is robust up to the top surface, whereas FE polarization pointing up energetically favors the formation of an AFE surface layer, whose thickness is likely to be sensitive to local strains. AFE order is likely to be more robust against detrimental size effects than polar order, therefore providing additional opportunities to create multifunctional heterostructures with 2D electronic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗