Geophysics
Towards Open Science: Monitoring Crustal Deformations in North America
Lionel Voirol, Haotian Xu, Yuming Zhang et al. (+3 more)
The study of the Earth's behavior has greatly benefited from the widespread deployment of Global
Navigation Satellite Systems (GNSS), enabling large-scale monitoring of crustal deformation and long-term geophysical trends. In this work, we focus on the North American region, where complex tectonic activity, particularly along the western margin, requires methods capable of processing and analyzing large collections of GNSS time series distributed across extensive spatial domains. Analyzing the full GNSS network provides a coherent view of deformation across multiple scales, allowing detection of long-wavelength signals, subtle intraplate strain and regionally consistent velocity fields that are difficult to capture through local or subsampled analyses. Despite the availability of such data, existing methodologies remain computationally prohibitive for large-scale analyses across this region (or others). To address this limitation, we introduce a highly scalable framework (implemented in open-source software) that enables inference on crustal deformation across the full North American GNSS network using standard computational resources. The proposed method achieves substantial computational gains while maintaining inferential performance comparable to existing approaches and confirms existing tectonic trends, thereby supporting efficient large-scale monitoring and contributing to ongoing efforts toward "Open Science".
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All authors Lionel Voirol, Haotian Xu, Yuming Zhang, Luca Insolia, Roberto Molinari, Stéphane Guerrier
General Physics
Damour-Solodukhin Wormhole as a Black Hole Mimicker: The Role of Observers' Location
K. K. Nandi, R. Kh. Karimov, R. N. Izmailov et al. (+1 more)
It has been recently argued that in semi-classical
gravity, a minimal 2-sphere is not a horizon but a tiny throat of a wormhole, such as the Damour–Solodukhin wormhole (DSWH), with a free parameter $\lambda \neq 0$ separating it from a Schwarxzschild black hole (BH) ($\lambda =0$). As shown by DS, their horizonless WH can mimic many properties of a black hole (BH). Assuming that observing a BH mimicker is equivalent to observing a BH itself, we ask the question as to which identity of the object, a WH or a BH, an observer is likely to observe in a single experiment. To answer this, we introduce Tangherlini's new concept of indeterminacy in the gravitational field by portraying the field as a refractive medium. We then postulate that the identity of the observed object will depend on the probabilistic outcome of
photon motion probing the object. The probabilities will be described by Fresnel reflection ($R$) and transmission ($T$) coefficients derived by Tangherlini on the basis of a non-
quantum statistical indeterminacy of
photon motion in ordinary optical media. By adapting this approach to a gravitational "effective optical medium," we obtain two intriguing results: (i) The Fresnel coefficients at the DSWH throat are independent of mass $M$ but dependent solely on the parameter $\lambda \neq 0$. (ii) Depending on the location of the observer, what is a DSWH to one observer may appear as a BH to another observer for the same value of $\lambda \neq 0$.
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All authors K. K. Nandi, R. Kh. Karimov, R. N. Izmailov, A. A. Potapov
General Physics
On the Special Theory of Relativity and Electromagnetism
O. L. de Lange and R. E. Raab
We present a formulation of the special theory of relativity which bears on F.A. Lindemann's assertion that this theory could have been reached "by pure logic soon after Isaac Newton". We start with the "intuitively plausible" pair of Galilean spatial transformations. These simple relations possess a rich structure of ten properties. From these, one discerns an axiomatic structure (and a synchrony convention) leading to the well-known Lorentz-type transformations which contain a universal constant, $V^2$. Analysis of Fizeau's experiment (1851) shows that $V^2 = c^2$, where $c$ is the speed of light in vacuo. Hence one obtains the Lorentz transformation. Requisites for such a formulation (Galileo's relativity principle, analytical mechanics, the method of changing a postulate, etc.) emerged during the 1600s and 1700s. These observations provide a framework for Lindemann's assertion. We also consider inertially-moving systems of charge, and derive electromagnetic field equations and a force law by applying the Lorentz-type transformations to the theory of electrostatics. The results are independent of any choice of units, and from their dependence on $V^2$ one can infer how certain phenomena manifest in each of the three possible types of space-time.
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Space Physics · Cross-listed from eess.SP
Earth-baseline VLBI restores the observability of a lunar surface station in joint orbit-and-clock determination
Chakshu Baweja
Lunar positioning,
navigation, and timing (PNT) is moving from concept to hardware, ESA's Moonlight/LCNS, NovaMoon reference stations, LunaNet, and Coordinated Lunar Time, all reducing to one estimation core: fix the orbits and clocks of the lunar infrastructure and tie them to an Earth/inertial frame. We ask which measurements make a surface station's absolute position observable, and prove the answer. In a snapshot batch fit, the internal observables (station-to-satellite and inter-satellite ranging plus clock-sync) constrain only relative geometry and leave a six-dimensional rigid-body datum defect: three translations and three rotations of the cluster. The clocks are fully observable, so the defect is purely positional, and closing it needs a tie to the Earth frame. Two such ties exist and are not interchangeable. An indirect tie (Earth-to-satellite ranging through the constellation) reaches the station only when the satellite geometry is rich; a direct tie (an Earth-baseline VLBI delay to the station beacon) fixes it regardless. This gives a conditional design law, not a single number: VLBI restores absolute observability when the constellation cannot supply it, and merely sharpens the bound when it can. For a sparse three-satellite constellation the station lies in the null space of the Fisher information until VLBI is added, reaching a Cramer-Rao bound of 20.1 m; for a rich six-satellite constellation VLBI tightens the bound from 23.2 m to 9.7 m. A single-epoch baseline informs at most two of three axes, so the datum closes at three non-collinear Earth stations. The Gauss-Newton
estimator attains the bound (efficiency 1.02), with a 91x median station-error improvement in the sparse regime. The FIM/CRLB engine is validated against NumPy and published closed forms; the lunar application stays modelled, every figure deterministic and reproducible.
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Plasma Physics
An Enhanced RPA-LDA Model for Ion Stopping Power from Cold Matter to High-Energy Density Plasmas: A Unified, Open-Source Framework
Thomas A. Mehlhorn, Ming Feng Gu and Igor Golovkin
We present an enhanced random-phase-approximation–local-density-approximation (e-RPA-LDA) model for the stopping power of ions that is valid over a wide range of conditions, from cold solids through warm dense matter to high-energy-density
plasmas. The electronic stopping is computed from the RPA dielectric response in the local-density approximation over an average-atom electron density obtained in a muffin-tin potential with the Flexible Atomic Code, augmented by four corrections to the earlier RPA-LDA model of Wang et al.: a strong-collision correction for large-momentum-transfer events, a static local-field correction for electron correlations, an electron-binding correction, and the higher-order Barkas and Bloch terms. The resulting
proton stopping powers agree with the NIST PSTAR and IAEA databases across the periodic table and for compounds – providing a physics-based alternative to semi-empirical codes such as SRIM – and reproduce the limited published
plasma data, including charged-particle transport-workshop
benchmarks, time-dependent DFT calculations, and the first measurements of enhanced light-ion stopping in
plasmas. We further extend the model to a complete total stopping power for
protons and alpha particles by adding
nuclear and ionic (elastic ion-ion) stopping to the electronic term, yielding a continuous, self-consistent description of energy deposition from cold matter to hot dense
plasmas. Because the average-atom treatment includes contributions from all electrons – unlike Kohn-Sham DFT – while remaining computationally efficient and applicable to low- and high-Z targets at arbitrary temperature and degeneracy, the model is well suited to inertial fusion and high-energy-density science. The computational framework is available on GitHub (https://github.com/dedx-erpa/dedx), with tabulated stopping powers and ranges in the data/ subdirectory.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Computed materials proposals depart from the structural memory of experimental discovery
Dan Nguyen, Karen Cao, Brian Chu et al. (+3 more)
Generative AI and high-throughput DFT pipelines propose millions of inorganic
crystal structures, but lack a calibrated reference frame against experimentally realized chemistry. Here we embed 167,500 Inorganic
Crystal Structure Database entries in a continuous structural-similarity space, partition it into graph communities, and replay them in time. Experimental discovery shows strong structural
memory: 82.9% of new formulas enter pre-existing communities; new-community formation falls from 40.2% (1930s) to 2.6% (2010s). The communities are chemically meaningful, positively identifying nine textbook field-defining renaissances, including cuprates, colossal-magnetoresistance manganites, MAX phases, and Li-ion battery cathodes. Projecting GNoME, MatterGen-public, Materials Project, JARVIS-DFT, and Alexandria-PBE into frozen historical maps yields a cutoff-robust ordering: held-out ICSD > MatterGen > {GNoME ~ MP-theoretical} > JARVIS > Alexandria. Structural departure from experimental basins is not specific to generative AI but general across the tested computed sets. Combining structural proximity with reduced-formula precedent defines a historical synthesizability prior for triaging computed materials.
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All authors Dan Nguyen, Karen Cao, Brian Chu, Nick Lemoff, Paul Kienzle, William Ratcliff II
Chemical Physics
ElemeNet: Multiscale Molecular Machine Learning with Uncertainty Quantification Across the Periodic Table
Jacob W. Toney, Samir Darouich, Yiran Wang et al. (+3 more)
Advances in deep learning architectures and representations have enabled ML-driven chemical property prediction, but state-of-the-art (SOTA) models have remained largely confined to independent codebases and lack support for diverse chemical species. This work introduces ElemeNet, a unified, general-purpose software package for molecular machine learning. The ElemeNet software package enables the training of advanced ML models for diverse properties and
datasets with an enlarged range of elemental compositions. We define molecular representations compatible with elements 1-100, supporting diverse organometallic and biological systems in addition to organic chemistry already well-served by the Chemprop ML toolkit. As well as more common atom-, bond-, and molecule-level predictions, we introduce moiety predictions. We also natively define optional conditioning on charge and
spin states. Advanced E(3)-equivariant and
transformer architectures are supported, as well as classical 2D models, with all classes including built-in uncertainty quantification through deterministic and statistical measures. We
benchmark our protocols for ML model training against representative
datasets from organic, inorganic, coordination, and biological chemistry, achieving competitive and SOTA performance relative to literature baselines and favorable scaling to millions of molecules. The entire workflow is exposed through a concise command-line interface, lowering the barrier to entry for non-expert users. We anticipate ElemeNet will empower non-computational researchers to leverage modern deep learning methods across the chemical and physical sciences.
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All authors Jacob W. Toney, Samir Darouich, Yiran Wang, Aaron G. Garrison, Johannes Kästner, Heather J. Kulik
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Prebiotic Chemistry Assemblies of L-Cysteine on Defect-Free Pyrite Terraces
Adriana E. Candia, Sindy J. Rodríguez, Vanina G. Franco et al. (+3 more)
Wächtershäuser's theory proposes iron-sulfur minerals as key platforms for molecular synthesis and supramolecular organization in prebiotic environments. However, defects have been traditionally considered at the center of such assemblies, thereby underestimating the contributions of regular and pristine interfaces. Here, we combine scanning tunneling microscopy and spectroscopy (STM/STS) with density functional theory (DFT) to investigate the fundamental prebiotic chemistry system of L-Cysteine (L-Cys) on defectless FeS$_2$(100) terraces. To do so, we first achieved atomically ordered, defect-free terraces that act as support of two distinct supramolecular phases of L-Cys: one compact, highly ordered supramolecular network and another less packed, labile supramolecular network. We unveil trimer-based intermolecular interactions to be at the origin of these pattern formations. These results demonstrate that L-Cys self-assemblies can be hosted on flawless FeS$_2$ terraces due to the cooperative interplay between substrate electronic structure and intermolecular interactions, without the participation of dominant defects. Therefore, the autocatalytic activity of pyrite could have triggered the on-surface polymerization process of these non-static self-assembled structures under
primordial conditions, thereby endorsing Wächtershäuser's postulates on the origin of life.
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All authors Adriana E. Candia, Sindy J. Rodríguez, Vanina G. Franco, Mario C. G. Passeggi, Jorge Lobo-Checa, Myriam H. Aguirre
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Role of polarity in the growth of cubic GaN within silicon inverted pyramids
David Lister, Melissa Radford, Sara Fortin et al. (+4 more)
A lack of spontaneous internal polarization makes cubic GaN (c-GaN) a well-suited material for emerging micro-LED-based short-range communication, where c-GaN promises increased speed over conventional hexagonal GaN (h-GaN). Although c-GaN is metastable, there are well-established methods for growing it in Si V- or U-grooves; the logical step is to truncate these grooves to wedges or inverted pyramids for small devices. There are limited reports of GaN grown in inverted pyramid templates, and the results are contradictory. To study this process, we perform selective area growth of GaN using organometallic vapor phase epitaxy (OMVPE) on Si inverted pyramidal templates and analyze our samples by cross-sectional TEM. We find that polarity is critical to understanding the growth of c-GaN in this four-fold geometry, in contrast to the growth in long grooves. This effect fits within the broader set of challenges of polar-on-nonpolar heteroepitaxy; the c-GaN inside the four-fold symmetric template has its
symmetry reduced by polarity to be two-fold. In typical growth conditions – where the underlying h-GaN polarity is uniform – we find this implies that two h-GaN to c-GaN grain boundaries will have a polarity inversion. We observe two different structures at these inverting boundaries, including a previously unreported inversion domain boundary along the basal plane of the undoped h-GaN. These findings show that for small devices – such as micro-LEDs – the polarity-inverting interfaces must be prevented, for example by suppressing the growth of h-GaN on two facets of the template or by locally controlling the h-GaN polarity.
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All authors David Lister, Melissa Radford, Sara Fortin, Bilal Janjua, Mohsen Asad, Karen Kavanagh, Simon Watkins
Atmospheric and Oceanic Physics
Conditional Tropical Cyclogenesis Rates via Rare-Event Sampling in a Neural Weather Emulator
John S. Schreck, William Chapman, Charlie Becker et al. (+1 more)
We couple Forward Flux Sampling (FFS), a non-
equilibrium rare-event technique from statistical mechanics, to a neural weather emulator (SDL-WXFormer, 1{\deg} grid spacing) to estimate conditional tropical cyclogenesis rates, or how often a tropical cyclone achieves a hurricane-level central pressure, without modifying model dynamics. Tropical cyclogenesis rates vary by orders of magnitude across regimes, yet direct ensemble sampling cannot resolve this variability at operationally feasible ensemble sizes. FFS decomposes the rare disturbance to mature cyclone intensification path into a flux through an initial interface pressure and a product of conditional crossing probabilities across four intermediate interface pressures. We use the 1{\deg} emulator because FFS requires O(10^4) model trajectories per initial condition, and because the model's calibrated
stochastic layers provide the necessary exploratory spread. Applied to 98 Atlantic basin initial conditions spanning 21 August - 8 October 2022, FFS resolves genesis rates spanning nearly three orders of magnitude, capturing a seasonal cycle qualitatively consistent with observations. A self-consistency check comparing FFS rates to independent direct-sampling rates yields a mean ratio of 1.03 +/- 0.15 across all initial conditions. Computational enhancement factors range from 3X (most active environment) to 140X (most suppressed), with a
geometric mean of 14X. Three case studies illustrate the physical diagnostics the method provides: the rate-limiting step is initial tropical organization for the Earl environment, uniformly high crossing probabilities for the Fiona precursor environment, and a compound barrier at the final intensification stages for the Ian environment. More efficient emulators would enable application of FFS to finer resolutions.
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All authors John S. Schreck, William Chapman, Charlie Becker, David John Gagne II
Optics
A Unified Perspective on Causality and One-Sided System Responses in Time and Space Across Physical and Fourier Domains
Mohammadreza Salehi and Francesco Monticone
The principle of causality has long been mathematically associated with the frameworks of Titchmarsh's
theorem and the Kramers–Kronig relations. While these relations arise naturally in the context of temporal system responses – ensuring that the effect of an applied field or force does not precede its cause – they have recently been shown to provide a pathway for realizing one-sided system responses in a variety of physical settings. In particular, one-sided frequency responses and one-sided wavevector responses have been successfully studied and engineered, enabling the prospect of numerous applications based on the complete suppression of backward scattering. In this work, we present a brief review of causality and its connection to these
Fourier-domain analogs. We then turn our
attention to the only remaining setting in which a one-sided system response may be explored: one-sided spatial nonlocality. We specifically investigate the possibility of realizing a one-sided spatial response within the widely used framework of nonlocal flat optics, where we uncover fundamental obstacles that hinder the achievement of such functionality in these structures. This, in turn, raises an intriguing open question: is one-sided spatial nonlocal response merely incompatible with the specific platform of nonlocal flat optics, or is it fundamentally forbidden by nature itself?
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Optics
Spectral DiffuserScope: a compact snapshot hyperspectral microscope
Neerja Aggarwal, Eric Markley, Kyung Chul Lee et al. (+12 more)
Hyperspectral fluorescence microscopy enables important biological and clinical applications, but conventional systems are bulky or require scanning, limiting temporal resolution and throughput. We introduce a computational snapshot hyperspectral microscope that uses compressed sensing to achieve higher spatial-spectral resolution than traditional snapshot systems. Our device is compact (~15 cm x 6 cm x 6 cm) and easily attaches to standard fluorescence microscopes. We
benchmark our system against existing snapshot methods through simulations to evaluate its spatial and spectral performance. Experimental imaging of fluorescent beads, labeled
cells, and lanthanide hydrogel beads demonstrates a practical, high-throughput solution for hyperspectral microscopy in biological and clinical applications.
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All authors Neerja Aggarwal, Eric Markley, Kyung Chul Lee, Seung Ah Lee, Junghyun Bae, Nakkyu Baek, Wook Park, Min Sung Cho, Youngbin Lim, Polly Fordyce, Stephanie Eberly, Lydia L. Sohn, William D. Houck, Kristina Monakhova, Laura Waller
Fluid Dynamics
Dripping-onto-droplet rheometry of sodium alginate solutions
Nada Nazzal, Martin Drahé, Ricardo El Khoury et al. (+7 more)
In this experimental and theoretical study, we assess the extensional relaxation time of sodium alginate solutions by using dripping-onto-droplet capillary breakup rheometry (DoD), e.g., the capillary thinning and breakup of viscoelastic filaments formed following the coalescence of a millimetric-nozzle-generated pendant drop with a lower droplet cap of the same fluid contained in a millimetric pool in ambient air. Hence, we extend the analyses conducted by El Khoury et al. (2026) from Newtonian to viscoelastic fluids. Our approach relies on experiments recorded with a high-speed camera using sodium alginate in deionised water, with alginate concentrations ranging from 0.1% to 9% by weight. The results are depicted by considering the dynamics of fluid filament thinning, stress balances, and scaling laws. Extensional relaxation times are resolved from the filament diameter
evolution. Three flow regimes are highlighted: capillary-inertial, capillary-elastic, and mixed capillary-inertio-elastic. The findings are summarised in a two-dimensional diagram that correlates the filament breakup time with different flow regimes using the important dimensionless parameter of the problem, e.g., the intrinsic Deborah number (which relates the extensional relaxation time to the characteristic capillary-inertial time). This diagram can be used to quantify both the solution's extensional relaxation time and the
liquid/air surface tension solely from filament breakup times.
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All authors Nada Nazzal, Martin Drahé, Ricardo El Khoury, Irineu Lopes Palhares Junior, Cassio Oishi, Roney Leon Thompson, Loren Jørgensen, Cécile Monteux, Edith Peuvrel-Disdier, Anselmo Pereira
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Bridging electrode preparation and electrocatalyst performance with physics-based causal AI
Evelyna Wang, Linda Hung, Sam Witty et al. (+2 more)
State-of-the-art artificial intelligence (AI) and Machine-Learning (ML) tools have not yet enabled rapid design of next-generation materials. Detailed physical understanding of how material properties affect device performance is required to advance materials development. For example, optimization of ink parameters for electrocatalysts has no known physical mathematical model and thus insights are difficult to translate from material studies to device studies. Herein, we demonstrate how to use the emerging AI tool, physics-based structural causal models (SCMs), to extract quantitative causative insights from complex heterogeneous electrochemical systems with small (n < 10), but multi-modal
datasets (modes > 10). Our SCM quantitatively separates the role that varying the support-to-catalyst ratios and total material loadings plays on catalytic performance. The proof of concept model developed in this work enables root-cause-analysis on the cyclic voltammograms of manganese-antimony
oxide oxygen reduction electrocatalysts on Vulcan carbon supports tested in alkaline media using a rotating disc electrode device configuration. Our preliminary causal analyses quantitatively disentangle how the catalyst performance is affected by the number of active sites versus the thickness of the electrode. To the best of our knowledge, this is the first demonstration of physics-based SCMs applied to electrochemical materials and their performance.
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All authors Evelyna Wang, Linda Hung, Sam Witty, Michaela Burke Stevens, Kevin Tran
Chemical Physics
Extension of openCOSMO-RS Into a Full Open-Source Equation of State: Implementation, Parameterization, and Benchmarking
Jan Markgraf, D. G. Lisboa Girardi, Irina Smirnova et al. (+1 more)
The COSMO-SAC-Phi model developed by Soares et al. extends the COSMO-SAC activity-coefficient framework into a full equation of state by explicitly accounting for pressure effects. In this approach, pure substances and mixtures are represented as pseudo-mixtures consisting of the actual number of moles and an additional pseudo-component that describes free volume, or holes. In this work, we implement this extension within the openCOSMO-RS framework and evaluate it using a large and diverse set of molecules and binary systems. The resulting equation of state includes an extensive open-source parameter set with around 1800 pure-component entries, made freely available to the academic community. The four pure-component parameters were fitted to vapor-pressure and
liquid-molar volume data for each substance. Model performance was assessed against two
benchmark equation-of-state databases, one for pure compounds and one for binary mixtures, without introducing any binary interaction parameters. The resulting openCOSMO-RS-Phi model reproduces the accuracy of the original COSMO-SAC-Phi formulation while providing a fully open-source and accessible implementation for the scientific community. Beyond its immediate utility, it also establishes a foundation for future development of predictive EoS for electrolyte solutions.
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All authors Jan Markgraf, D. G. Lisboa Girardi, Irina Smirnova, Simon Müller
Optics · Cross-listed from math.OC
Optimal Design of Tubular Perfectly Conducting Objects in Electromagnetic Chirality
Tilo Arens, Roland Griesmaier, Marvin Knöller et al. (+1 more)
This work is about the shape optimization of long tubular objects in electromagnetic chirality (em-chirality). Em-chirality is a property of individual scattering objects or metamaterials describing their qualitatively different response to electromagnetic waves of opposite polarization handedness. The optimization is performed by a Newton-type iterative maximization of a regularized em-chirality measure with respect to the scatterer's shape. In this context, the differentiability of the object-to-far field operator map is analyzed rigorously, thereby extending previously known results on the domain derivative to the far field operator setting. Our optimal design
algorithm is based on the electric field integral equation, which is employed both for the evaluation of scattered fields and for the computation of the domain derivative. Our implementation is done via the boundary element method. The numerical examples presented in this work yield strongly em-
chiral scattering objects capable of exciting higher-order modes beyond the dipole regime with nonintuitive shapes that expand the known set of highly em-
chiral scattering objects.
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All authors Tilo Arens, Roland Griesmaier, Marvin Knöller, Raphael Schurr
Data Analysis and Statistics · Cross-listed from astro-ph.HE
Multipolar Magnetic-Field Inference for PSR J0740+6620 with Neural-Network-Accelerated NICER Pulse-Profile Modeling
Farhana Taiyebah, Constantinos Kalapotharakos, Greg Olmschenk et al. (+6 more)
We investigate the multipolar surface
magnetic-field structure of the high-mass millisecond
pulsar PSR J0740+6620 using the 32-bin bolometric NICER pulse profile of Dittmann et al. (2024). Building on the neural-network surrogate framework of Olmschenk et al. (2025), we model the emitting regions as open-field-line footpoints of an offset dipole plus axisymmetric quadrupole static
vacuum field, rather than as prescribed
geometric hotspots. We fix the
stellar mass, radius, observer inclination, and hotspot temperature ratio to the Dittmann et al. (2024) maximum-likelihood values and explore the resulting 11-dimensional
magnetic-field space. To make this feasible, we train convolutional neural-network surrogates on $5.12\times10^7$ synthetic bolometric light curves and use them in a parallel ensemble Markov Chain Monte Carlo calculation on 4000 CPU cores, accelerating likelihood evaluations by a factor of $\gtrsim 400$. We perform independent inferences for two calibrated temperature-weight prescriptions, Tw=1.31 and Tw=1.41, encoding the relative bolometric weight associated with the hotspot temperature difference. The posteriors, posterior-predictive light curves, and maximum-likelihood values are very similar, indicating weak sensitivity to this choice. The offset model reproduces the observed double-peaked profile and yields broad,
multimodal posteriors, reflecting both the background-dominated data and degeneracies of the multipolar parameterization. The hotspot-density map shows that pulse phases constrain the approximate azimuthal placement of the emission, while latitude, surface extent, and morphology remain weakly constrained. A restricted zero offset run is disfavored within the adopted field basis. This work extends neural-network-accelerated
magnetic-field inference to PSR J0740+6620 and motivates future energy-dependent, force-free, and joint X-ray/$\gamma$-ray extensions.
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All authors Farhana Taiyebah, Constantinos Kalapotharakos, Greg Olmschenk, Wendy F. Wallace, Soumi De, Abu Bucker Siddik, Diane Oyen, Thibault Lechien, Zorawar Wadiasingh