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At least 109 records · Page 6

Theoretical investigation of plasma wave generation by pulsed electron beams in space

Here, we report theoretical calculations of plasma wave generation in the whistler modes and in the extraordinary modes, by pulsed electron beams in a magnetized plasma. The numerical simulations of the wave generation take into account the longitudinal expansion of the electron beam due to the space charge force and the energy spread. The work presented in this article provides predictions for the wave generation performance of the beam plasma interactions experiment (Beam PIE), where pulsed electron beams were produced by a spaceborne radio frequency (RF) linear accelerator. We also theoretically explore the desirable properties of the pulsed electron beam for future space experiments, which will be the next step toward eventually demonstrating the radiation-belt remediation (RBR).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

LeWRON: Agentic Analysis of Electroweak Phase Transitions

The electroweak phase transition (EWPT) is a central topic in particle physics and cosmology, connecting collider phenomenology, baryogenesis, and gravitational-wave observatories. Its analysis requires a technically demanding, convention-sensitive, and model-dependent pipeline, from constructing the finite-temperature effective potential to tracking thermal histories, computing bubble nucleation rates, and predicting gravitational-wave spectra. We present LeWRON (Learning ElectroWeak phase tRansitiON), an agentic framework that orchestrates this pipeline starting from an input Lagrangian. LeWRON combines audited toolbox construction with an Explorer module that uses the generated model-specific code for further analysis, including scans and plots. Intermediate analytic outputs are checked by auditor agents and stored as structured artifacts, enabling reproducible human inspection and downstream use through both a command-line interface and a public Python API. The framework supports a reproduction mode, which infers conventions from the literature and reproduces published results, and a discovery mode, which guides users through structured checkpoints for new models. We demonstrate LeWRON across representative beyond-the-Standard-Model scenarios and release the code on GitHub.

Wang, Isaac R. [Fermilab] (ORCID:000000030789218X)↗

Relic cosmological vector fields and inflationary gravitational waves

Here we show that relic vector fields can significantly impact a spectrum of primordial gravitational waves in the postinflationary era. We consider a triplet of U(1) fields in a homogeneous, isotropic configuration. The interaction between the gravitational waves and the vector fields, from the end of reheating to the present day, yields novel spectral features. The amplitude, tilt, shape, and net chirality of the gravitational wave spectrum are shown to depend on the abundance of the electric- and magneticlike vector fields. Our results show that even a modest abundance can have strong implications for efforts to detect the imprint of gravitational waves on the cosmic microwave background polarization. We find that a vector field comprising less than 2% of the energy density during the radiation-dominated era can have a greater than order unity effect on the predicted inflationary gravitational wave spectrum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ultracompact hybrid stars consistent with multimessenger astrophysics

In this work, we consider the consequences of phase transition in dense QCD on the properties of compact stars and implications for the observational program in gravitational wave and x-ray astrophysics. The key underlying assumption of our modeling is a strong first-order phase transition past the point where the hadronic branch of compact stars reaches the two-solar mass limit. Furthermore, our analysis predicts ultracompact stars with very small radii—in the range of 6–9 km—living on compact star sequences that are entirely consistent with the current multimessenger data. We show that sequences featuring two-solar mass hadronic stars consistent with radio-pulsar observations are also consistent with the inferences of large radii for massive neutron stars by NICER x-ray observations of neutron stars and the small radii predicted by gravitational waves analysis of the binary neutron star inspiral event GW170817 for our models that feature a strong first-order QCD phase transition.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Verifying raytracing/Fokker–Planck lower-hybrid current drive predictions with self-consistent full-wave/Fokker–Planck simulations

Raytracing/Fokker–Planck (FP) simulations used to model lower-hybrid current drive (LHCD) often fail to reproduce experimental results, particularly when LHCD is weakly damped. A proposed reason for this discrepancy is the lack of ‘full-wave’ effects, such as diffraction and interference, in raytracing simulations and the breakdown of the raytracing approximation. Previous studies of LHCD using non-Maxwellian full-wave/FP simulations have been performed, but these simulations were not self-consistent and enforced power conservation between the FP and full-wave code using a numerical rescaling factor. Here, we have created a fully self-consistent full-wave/FP model for LHCD that is automatically power conserving. This was accomplished by coupling an overhauled version of the non-Maxwellian TORLH full-wave solver and the CQL3D FP code using the Integrated Plasma Simulator. We performed converged full-wave/FP simulations of Alcator C-Mod discharges and compared them with raytracing. We found that excellent agreement in the power deposition profiles from raytracing and TORLH could be obtained, however, TORLH had somewhat lower current drive efficiency and broader power deposition profiles in some cases. This discrepancy appears to be a result of numerical limitations present in the TORLH model and a small amount of diffractional broadening of the TORLH wave spectrum. Our results suggest full-wave simulation of LHCD is likely not necessary as diffraction and interference represented only a small correction that could not account for the differences between simulations and experiment.

Physics↗

Public perceptions of wave energy development on the west coast of North America: Risks, benefits, and coastal attachment

While solar and wind energy continue to grow as significant sources of renewable energy, a global energy transition away from fossil fuels will require an expanding portfolio of generating resources. Marine renewable energy has the potential to contribute greatly in the coming decades, as the more predictable nature of wave energy can support the resiliency of the power grid and complement solar and inland wind generation. Yet, the broad deployment of marine energy technologies like wave energy will depend on public support, making it critical to identify the relevant factors associated with public attitudes and risk/benefit perceptions. This paper draws on social representations theory to specifically examine perceptions of wave energy on the west coast of North America, a site chosen because of the high suitability for wave energy generation and the fact that one of only three wave energy test sites in the world is under development off the coast of Oregon. Using an online survey in June 2020, we recruited a sample of 2000 respondents from California, Oregon, Washington, and British Columbia. We found a majority of respondents held positive attitudes to wave energy, but respondents also had low familiarity – with a quarter of respondents lacking sufficient information to form an opinion. We used logistic regression to identify factors correlated with wave energy attitudes, finding that respondents who were more supportive of wind and solar energy, more optimistic about new technology, and reported more familiarity with wave energy were significantly more likely to have a positive impression of wave energy. Respondents with higher levels of place attachment to coastal areas were more split, as they perceived higher benefits of wave energy – but also higher risks. Our results indicate broad appeal of wave energy on the west coast, but we caution policymakers and developers to not take initial siting processes for granted. As experience has shown for offshore wind, broad appeal does not guarantee a smooth siting process in a local context. Furthermore, the role of place attachment to coastal areas must be taken seriously or risk alienating local communities.

16 TIDAL AND WAVE POWER↗

Imaging the energy gap modulations of the cuprate pair-density-wave state

The defining characteristic of Cooper pairs with finite center-of-mass momentum is a spatially modulating superconducting energy gap Δ(r). Recently, this concept has been generalized to the pair density wave (PDW) state predicted to exist in cuprates. Although the signature of a cuprate PDW has been detected in Cooperpair tunneling, the distinctive signature in single-electron tunneling of a periodic Δ(r) modulation has never been observed. Here, using a new approach, we discover strong Δ(r) modulations in Bi 2 Sr 2 CaCu 2 O 8+δ that have eight-unit-cell periodicity or wavevectors Q ≈ (2π/a0)(1/8, 0) and Q ≈ (2π/a0)(0, 1/8). Simultaneous imaging of the localdensity- of-states N(r, E) reveals electronic modulations with wavevectors Q and 2Q, as anticipated when the PDW coexists with superconductivity. Finally, by visualizing the topological defects in these N(r, E) density waves at 2Q, we discover them to be concentrated in areas where the PDW spatial phase changes by !, as predicted by the theory of half-vortices in a PDW state. Overall, this is a compelling demonstration, from multiple single-electron signatures, of a PDW state coexisting with superconductivity in the canonical cuprate Bi 2 Sr 2 CaCu 2 O 8+δ .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Relevance of Pion-Exchange Contributions Versus Contact Terms in the Chiral Effective Field Theory Description of Nucleon–Nucleon Scattering

The standard way to demonstrate the relevance of chiral symmetry for the NN interaction is to consider higher partial waves of NN scattering which are controlled entirely by chiral pion-exchanges (since contacts vanish). However, in applications of NN-potentials to nuclear structure and reactions, the lower partial waves are the important ones, making the largest contributions. Lower partial waves are sensitive to the short-range potential, and so, when the short-range contacts were to dominate over the chiral pion contributions in lower partial waves, then the predictions from chiral potentials would have little to do with chiral symmetry. To address this issue, we investigate systematically the role of the (chiral) one- and two-pion exchanges, on the one hand, and the effect of the contacts, on the other hand, in the lower partial waves of NN scattering. We are able to clearly identify the signature of chiral symmetry in lower partial waves. Furthermore, our study has also a pedagogical spinoff as it demonstrates in detail how the reproduction of the lower partial-wave phase shifts comes about from the various ingredients of the theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Counting topological interface modes using simplicial characteristic classes

A computational approach for predicting the number of topological interface modes (TIMs) in hermitian systems using the spectral flow—monopole correspondence is presented. The number of TIMs is determined by calculating the Chern number of a complex line bundle of local polarisation vectors over a phase space sphere surrounding a Weyl point. The Chern number is computed by constructing the simplicial first Chern class of a discrete vector bundle on a simplicial mesh. This approach is gauge invariant, derivative free, structure preserving, and robust to noise. The algorithm is shown to reproduce the expected number of TIMs for the case of equatorial fluid waves and the topological Langmuir cyclotron wave. The possibility of using this algorithm to analyse experimental measurements of bulk wave polarisations and predict the associated number of TIMs is explored in a synthetic example.

discrete vector bundles↗

Photometric detection of internal gravity waves in upper main-sequence stars

Massive stars are predicted to excite internal gravity waves (IGWs) by turbulent core convection and from turbulent pressure fluctuations in their near-surface layers. These IGWs are extremely efficient at transporting angular momentum and chemical species within stellar interiors, but they remain largely unconstrained observationally. In this work, we aim to characterise the photometric detection of IGWs across a large number of O and early-B stars in the Hertzsprung–Russell diagram, and explain the ubiquitous detection of stochastic variability in the photospheres of massive stars. Furthermore, we combined high-precision time-series photometry from the NASA Transiting Exoplanet Survey Satellite with high-resolution ground-based spectroscopy of 70 stars with spectral types O and B to probe the relationship between the photometric signatures of IGWs and parameters such as spectroscopic mass, luminosity, and macroturbulence.

79 ASTRONOMY AND ASTROPHYSICS↗

Gravitational Waves from Primordial Black Hole Dark Matter Spikes

The origin of the binary black hole mergers observed by LIGO–Virgo–KAGRA remains an open question. We calculate the merger rate from primordial black holes (PBHs) within the density spike around supermassive black holes (SMBHs) at the centers of galaxies. We show that the merger rate within the spike is comparable to that within the wider dark matter halo. We also calculate the extreme mass ratio inspiral (EMRI) signal from PBHs hosted within the density spike spiralling into their host SMBHs due to gravitational-wave emission. We predict that LISA may detect ∼10 4 of these EMRIs with a signal-to-noise ratio threshold of 20 within a 4 yr observation run, if all dark matter is made up of ∼30 M ⊙ PBHs. Uncertainties in our rates come from the uncertain mass fraction of PBHs within the dark matter spike, relative to the host central SMBHs, which defines the parameter space LISA can constrain.

dark matter↗

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗

Gravitational Wave Eigenfrequencies from Neutrino-driven Core-collapse Supernovae

Abstract Core-collapse supernovae (CCSNe) are predicted to produce gravitational waves (GWs) that may be detectable by Advanced LIGO/Virgo. These GW signals carry information from the heart of these cataclysmic events, where matter reaches nuclear densities. Recent studies have shown that it may be possible to infer the properties of the proto-neutron star (PNS) via GWs generated by hydrodynamic perturbations of the PNS. However, we lack a comprehensive understanding of how these relationships may change with the properties of CCSNe. In this work, we build a self-consistent suite of over 1000 exploding CCSNe from a grid of progenitor masses and metallicities combined with six different nuclear equations of state (EOS). Performing a linear perturbation analysis on each model, we compute the resonant GW frequencies of the PNS, and we motivate a time-agnostic method for identifying characteristic frequencies of the dominant GW emission. From this, we identify two characteristic frequencies, of the early- and late-time signal, that measure the surface gravity of the cold remnant neutron star, and simultaneously constrain the hot nuclear EOS. However, we find that the details of the CCSN model, such as the treatment of gravity or the neutrino transport, and whether it explodes, noticeably change the magnitude and evolution of the PNS eigenfrequencies.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of THz generation by multicolor laser pulses with various frequency ratios

Here, terahertz (THz) generation in a gas medium is simulated by quantum calculations with multicolor intense laser pulses of various frequency ratios. By correlating THz radiation with the above-threshold-ionization photoelectron spectrum, we confirm that our previously proposed free-free transition model for the generation of THz radiation is also applicable to multicolor pulses. THz photon emissions can proceed through transitions between continuous states with similar energies that have opposite parities. This mechanism predicts that THz waves can be efficiently generated at special two-color laser frequency ratios when the multiphoton mixing condition is satisfied. Applying this model to multicolor fields (sawtooth wave shape), we provide a quantum-mechanical interpretation for the reason for THz radiation enhancement. A scheme combining multiple lasers to raise THz radiation satisfying multiphoton mixing conditions is also proposed.

74 ATOMIC AND MOLECULAR PHYSICS↗

Mirror neutron stars

The fundamental nature of dark matter is entirely unknown. A compelling candidate is twin Higgs mirror matter, invisible hidden-sector cousins of the Standard Model particles and forces. This predicts mirror neutron stars made entirely of mirror nuclear matter. Here we find their structure using realistic equations of state, robustly modified based on first-principle quantum chromodynamic calculations, for the first time. This allows us to predict their gravitational wave signals, demonstrating an impressive discovery potential and ability to probe dark sectors connected to the hierarchy problem.

79 ASTRONOMY AND ASTROPHYSICS↗

Sensitivity Analysis of Tunable Equation of State Material Model In Pulsed Mercury Target Simulation

A pulsed neutron spallation target is subjected to very short but intense loads from repeated proton pulses. Approximately 60% of the energy from each proton pulse is deposited into the mercury target material and the stainless-steel target structure, leading to a high-pressure region in both the stationary target structure and the flowing mercury. The high-pressure region propagates and leads to fluid-structure interaction. The resultant loading on the target structure containing liquid mercury is difficult to predict, although various simulation approaches and material models for the mercury have been tried. To date, the best match of simulation to experimental data is obtained by using an equation of state (EOS) material model with a specified tensile cutoff pressure, which simulates the cavitation threshold. The inclusion of a threshold to represent cavitation is key to the successful predictions of stress waves triggered by the high-energy pulse striking the mercury and vessel. However, recent measurements of target structure strain show that significant discrepancies remain between the measured and simulated strain values in the EOS mercury model. These differences grow when noncondensable helium gas is intentionally injected into the flowing mercury to reduce the loading on the structure. An EOS-based proportional–integral–derivative (PID) mercury model has been proposed to reduce the gap between the measured and simulated vessel strain responses for targets with gas injection. The conceptual and numerical description and initial investigation of the PID model are presented in previous work. Further studies of this PID model — including the sensitivity of the structure’s strain response to model parameters (the tensile cutoff, PID parameters Kp, Ki, and Kd) — are reported in this article. Results show the strain response is more sensitive to changes in the tensile cutoff value than to changes in the model parameters Kp, Ki, and Kd. These results will aid in future work where the model parameters will be optimized to match simulation data to strain measurements.

Lin, Lianshan↗

GloPW

This model predicts global plasma wave activity, with a focus on electromagnetic ion cyclotron (EMIC) waves in Earth’s magnetosphere.

Noh, Sung Jun↗

Multi-Level Structural Damage Characterization Using Sparse Acoustic Sensor Networks and Knowledge Transferred Deep Learning

Standard structural health monitoring techniques face well-known difficulties for comprehensive defect diagnosis in real-world structures that have structural, material, or geometric complexity. This motivates the exploration of machine-learning-based structural health monitoring methods in complex structures. However, creating sufficient training data sets with various defects is an ongoing challenge for data-driven machine (deep) learning algorithms. The ability to transfer the knowledge of a trained neural network from one component to another or to other sections of the same component would drastically reduce the required training data set. Also, it would facilitate computationally inexpensive machine learning based inspection systems. In this work, a machine-learning-based multi-level damage characterization is demonstrated with the ability to transfer trained knowledge within the sparse sensor network. A novel network spatial assistance and an adaptive convolution technique are proposed for efficient knowledge transfer within the deep learning algorithm. Proposed structural health monitoring method is experimentally evaluated on an aluminum plate with artificially induced defects. It was observed that the method improves the performance of knowledge transferred damage characterization by 50% during localization and 24% during severity assessment. Further, experiments using time windows with and without multiple edge reflections are studied. Results reveal that multiply scattered waves contain rich and deterministic defect signatures that can be mined using deep learning neural networks, improving the accuracy of both identification and quantification. In the case of a fixed sensor network, using multiply scattered waves shows 100% prediction accuracy at all levels of damage characterization.

36 MATERIALS SCIENCE↗