Fluid Dynamics
Conditional Neural Field based Reduced Order Model for Dynamic Ditching Load Prediction
Henning Schwarz, Pyei Phyo Lin, Jens-Peter M. Zemke et al. (+1 more)
Grid-based neural networks such as convolutional autoencoders are widely used in dimension reduction-based surrogate models for computational fluid dynamics. In recent years, the use of coordinate-based approaches like conditional neural fields has emerged. Their independence of the spatial discretization is a beneficial feature for various applications in computational fluid dynamics. This paper discusses the spatio-temporal prediction of aircraft ditching loads using a conditional neural field approach. The model is evaluated using two
datasets for the dynamic loads of the fuselage of a DLR-D150 aircraft, one of which relates to a single fixed spatial discretization and the other that includes data from different discretizations. When paired with a long short-term
memory (LSTM) network in the latent space, the neural field-based model achieves a spatio-temporal prediction accuracy for the first data set that is close to that of grid-dependent convolutional autoencoder-based models, and with significantly less parameters. Results for the second data set demonstrate the ability of the neural field-based approach to reconstruct ditching loads accurately for heterogeneous spatial discretizations. This allows for flexible use of training
datasets generated for different geometries and/or discretizations, as well as the use of the surrogate model to predict loads for different configurations.
Read the full abstract ▾
All authors Henning Schwarz, Pyei Phyo Lin, Jens-Peter M. Zemke, Thomas Rung
General Physics
Observational Constraints and Cosmological Dynamics of Interacting Fractional Holographic Dark Energy in Light of DESI DR2
Qihong Huang, Hao Chen and Qingdong Wu
Based on the fractional
entropy originating from fractional
quantum mechanics, the fractional
holographic dark energy (FHDE) model has been proposed. In this paper, we consider an interaction between the pressureless matter and FHDE and analyze three different interacting FHDE models. Combining the latest observational data including SNIa, OHD, BAO, and CMB, we estimate the model parameters and find that the interaction forms $Q=\gamma H \rho_{de}$ and $Q=\beta H \rho_{m}+\gamma H \rho_{de}$ show some preference from the observational data. Using phase space analysis, we further find that only interacting FHDE model with $Q=\beta H \rho_{m}+\gamma H \rho_{de}$ can describe the full evolutionary history of the universe. The statefinder diagnostic pair reveals that this model deviates from the $\Lambda$CDM model but converges to the $\Lambda$CDM fixed point and the de Sitter expansion fixed point in the future. Finally, we analyze the
evolution of cosmological parameters and demonstrate that this model can drive the late time acceleration of the universe.
Read the full abstract ▾
Chemical Physics
A Data-Driven Parametric Reduced-Order Chemical Kinetics Model Derived from Atomistic Simulations
Michael N. Sakano and Alejandro Strachan
Coarse-grained modeling in molecular simulations serves not only to extend accessible time and length scales beyond atomistic limits, but also to reduce high-dimensional chemical data to low-dimensional representations that expose the underlying latent structure. In the context of energetic materials, reduced-order chemical kinetics models are essential for describing thermally driven decomposition, deflagration, and detonation. Recent data-driven approaches based on machine learning and dimensionality reduction have shown promise for constructing such models directly from atomistic simulations; however, when reaction pathways vary strongly with thermodynamic conditions, these methods can produce latent representations that are difficult to interpret physically or extrapolate reliably. Here, we introduce a parametric, temperature-dependent autoencoder framework that learns a unified reduced-order description of chemical decomposition across a wide range of temperatures within a single model. Physical interpretability is enforced through non-negativity constraints and a softmax activation, enabling the latent variables to be directly associated with additive chemical components and their relative contributions. Reaction kinetics and heat-release parameters are optimized simultaneously within the neural-network architecture, providing a self-consistent coupling between chemical
evolution and energetics. The proposed approach yields significantly improved reconstruction accuracy compared to a state-of-the-art dimensionality-reduction method, as quantified by reductions in mean-squared error, while preserving a physically meaningful latent representation. These results demonstrate that parametric, interpretable machine-learning models can provide robust reduced-order chemical kinetics suitable for multiscale modeling of complex reactive systems.
Read the full abstract ▾
Applied Physics
Lithium Experimental Application Platform (LEAP): Secondary-Containment Architecture for Flowing Liquid Lithium in Fusion Systems
Yufan Xu, Yoichi Momozaki, Michael Hvasta et al. (+2 more)
Flowing
liquid lithium is a promising fusion technology because it can provide a renewable
Plasma-Facing Component (PFC) surface, modify recycling, support power exhaust, and potentially connect
plasma-facing components with fuel recovery. Its deployment, however, is limited by the need to manage chemical reactivity, fire and aerosol hazards, inert gas operation, maintainability, and rapid experimental iteration. This paper develops a semi-quantitative hazard complexity framework for selecting secondary containment architectures for flowing
liquid lithium systems. The framework is applied to six representative containment scenarios and to the Lithium Experimental Application Platform (LEAP) at Princeton
Plasma Physics Laboratory. LEAP is under construction with a modular, room-scale argon gloveroom as an inert secondary containment boundary for a staged flowing lithium program with heating, diagnostics,
magnetic field exposure, and future device interface capability. The analysis shows that an inert, airtight secondary enclosure without scrubbers around a
liquid lithium loop provides a practical balance between hazard reduction and facility complexity, as defined by the design requirements. The resulting architecture offers a deployable path for lithium PFC development and a transferable design logic for other reactive or conductive
liquid metal systems.
Read the full abstract ▾
All authors Yufan Xu, Yoichi Momozaki, Michael Hvasta, Robert Kaita, Egemen Kolemen
Geophysics
Dynamic centrality of headwater sources in river networks: a stochastic approach via ultrametric Laplacians
Ángel Alfredo Morán Ledezma
River networks are hierarchical transport systems in which the timing and position of headwater confluences govern hydrologic response, solute transport, and ecological connectivity. Despite the recognized importance of headwater sources in structuring downstream processes, no mathematically grounded centrality index exists that captures their dynamic role in the transport hierarchy. We apply the dynamic centrality index $C_{\mathrm{CTMC}}$ [Morán Ledezma, arXiv:2603.20922], originally introduced in the context of phylogenetic trees, to the problem of headwater centrality in river networks via the dynamic tree representation of [Zaliapin et al., https://doi.org/10.1029/2009JF001281]. Through a topological analysis of the ultrametric structure induced by the dynamic tree, we show that high-centrality headwaters are the tributaries that most efficiently transmit water into the rest of the network, in the sense that their flows merge earliest and most broadly with surrounding sources as transport proceeds downstream. The index admits a fully explicit closed-form expression computable in $O(n)$ time from the tree structure alone, without simulation. Comparing $C_{\mathrm{CTMC}}$ rankings against the number of downstream junctions reached during transport, a direct measure of hydrological influence, on a
dataset of 49 natural river basins across the United States, we find that top-ranked headwaters consistently reach a disproportionately large number of junctions across all transport times. This indicates that high-centrality headwaters are not merely early contributors but consistently influential throughout the entire transport process. These results suggest that ultrametric spectral analysis provides an interpretable and scalable framework for identifying hydrologically influential headwaters, with potential applications in ecological monitoring and watershed management.
Read the full abstract ▾
Geophysics
Global Waterbody Calculator: A high-resolution global database of lakes and reservoirs depth-area-volume (D-A-V) relationships
Shengde Yu, Yukai Wu, Weikun Liao et al. (+1 more)
The new GLRDAV database assembles key morphometric characteristics for over 1.4 million lakes and reservoirs. By integrating data from HydroLAKES and GLOBathy, more than 17 million
polynomial (orders 1-5) and power functions describing depth-area-volume (D-A-V) relationships at a 0.1 m depth resolution are presented. The D-A-V relationships are validated against existing databases (ReGeom and GRDL) that provide comparable or simplified global bathymetric relationships, as well as in situ measurements for four waterbodies in the Texas Water Development Board (TWDB). The results show that higher-order
polynomial equations (particularly orders 4 and 5) generally yield the lowest RMSE and highest goodness-of-fit (i.e., R^2). Although power functions and lower-order
polynomials can offer reasonable representations for simpler and shallower systems, they typically underperform when applied to large or morphologically complex lakes and reservoirs. Our findings underscore the flexibility and robustness of GLRDAV, offering a globally consistent, high-resolution, and computationally scalable resource for hydrological, ecological, and water resource management applications.
Read the full abstract ▾
All authors Shengde Yu, Yukai Wu, Weikun Liao, Philippe Van Cappellen
Instrumentation and Detectors · Cross-listed from quant-ph
Graphs on chip: a silicon photonics platform
H. Girin, X. Chécoury, B. Odouard et al. (+5 more)
We present a versatile photonic waveguide network platform implementing
quantum (wave) graphs, proposed by Kottos & Smilansky [Phys. Rev. Lett. 79, 4794 (1997)] to investigate ray-wave correspondence and
quantum chaos. Realized on a silicon-on-
insulator chip at telecom wavelengths, it enables a unique capability: the direct, non-invasive imaging of individual optical wave functions with unprecedented resolution via third-harmonic generation in silicon, which we use to study the localization of intensity distributions. Furthermore, by investigating two graphs with contrasting classical dynamics – one strongly chaotic, the other one ergodic, but non-mixing – we reveal strikingly different spectral statistics, in quantitative agreement with random
matrix theory and a minimal
unitary quantum-map model. This establishes silicon photonics networks as a versatile and scalable platform for investigating
quantum chaos and non-linear graphs, and paves the way for optical
quantum computing in complex networks.
Read the full abstract ▾
All authors H. Girin, X. Chécoury, B. Odouard, S. Bittner, J.-R. Coudevylle, B. Dietz, C. Lafargue, M. Lebental
Classical Physics
Modeling the Frictional Driving of a Gyroscope Casing by a Spinning Rotor
Vedat Tanr{\i}verdi and Arda Erbasan
The rotation of the casing and rotor of a gyroscope is studied by considering frictional effects. Friction causes the casing to rotate, and over time, air dissipation and friction at the touchpoint gradually stop this rotation. Several models for air friction, friction between the rotor and casing, and friction at the touchpoint are analyzed. Fit results demonstrate that while some of these models can describe the primary motion, certain effects require further study to yield more precise results. These findings can aid in developing improved models for the rotation of satellites.
Read the full abstract ▾
Atmospheric and Oceanic Physics · Cross-listed from stat.AP
Prediction of Drought and Flash Drought in Africa at the Seasonal-to-Subseasonal Scale using the Community Research Earth Digital Intelligence Twin Framework
Stuart Edris, Amy McGovern and Jason Hickey
Droughts and flash droughts (rapidly developing droughts; FDs) remain impactful events that are known to desiccate landscape and destroy crops. In particular, droughts in Africa are often more impactful than in other locations, such as the United States or Europe, due to many regions in Africa heavily depending on local agriculture for sustenance. In recent years, large machine learning (ML) models, such as GraphCast and AIFS, have emerged as effective tools for global weather prediction. However, sparse data observations and few ML studies in Africa have left it unclear if these ML models retain their skill when focused on Africa. As such, this project seeks to examine the predictability of drought and FD in Africa using a CrossFormer model based on the Community Research Earth Digital Intelligence Twin (CREDIT) framework developed by NSF NCAR. Our CrossFormer model, termed DroughtFormer, incorporates variables from the ERA5 and GLDAS2 reanalyses and the IMERG and MODIS satellite observations, and employs dry air mass and moisture conservation, to predict soil moisture, vegetation health, and other drought-related surface variables. While DroughtFormer displayed lower accuracy in predicting precipitation and FD indices, it showed significant skill in predicting the remaining variables, delivering stable and skillful forecasts out to 90-day lead times (either beating out or having comparable skill to climatology). In particular, DroughtFormer skillfully represented
climate anomalies for key variables, such as soil moisture (though it struggled with the magnitude of the anomalies). Thus, DroughtFormer showed significant promise in representing and predicting agricultural level drought in a region that is heavily impacted by drought events.
Read the full abstract ▾
Optics
Scattering-Induced Loss in Ferroelectric Photonic Devices
Jonah Townsend, Enzo Conceição Picinini and Rogério de Sousa
Ferroelectric materials have colossal optical nonlinearities, but their integration into
quantum photonic chips is made challenging by the additional loss mechanisms that they introduce. Here we present a perturbative theory that expresses non-absorptive (elastic)
photon scattering-induced loss as a functional of a general spectral density for spatial fluctuations of electric permittivity. We apply the theory to calculations of attenuation coefficients $\alpha$ in slab waveguides in order to compare two distinct loss mechanisms: Interface roughness and ferroelectric domain disorder. Our theory can account for realistic roughness without special
symmetry considerations, and it demonstrates how to use electron microscopy images of ferroelectric domains to obtain explicit numerical predictions for $\alpha$. Loss is maximum when the mean domain length is comparable to the wavelength of light (Mie regime), indicating that, for telecom wavelengths, sub-micron domains (Rayleigh regime) or single domain waveguides provide equivalent strategies for reducing loss.
Read the full abstract ▾
Biological Physics · Cross-listed from q-bio.PE
Genotype specificity and spatial arrangement govern the direction and magnitude of selection in variable environments
Hossein Nemati, Kamran Kaveh, Jakub Svoboda et al. (+2 more)
Spatial environmental variation can either amplify or suppress the fixation of beneficial mutants in structured populations, yet the interplay of ecological factors and spatial structure in determining which outcome occurs remains theoretically unresolved. Here, we develop a unified framework for selection on
lattice graphs with environmental heterogeneity, in which mutant and resident fitness depend on the local environmental state. Across three common classes of genotype-environment interactions and a wide range of spatial arrangements of environmental states, we identify two governing principles. Genotype specificity determines the direction of the effect: heterogeneity amplifies selection when it modulates resident fitness, but suppresses selection when it modulates mutant fitness, with genotype-symmetric modulation producing weaker amplification. Spatial arrangement determines the magnitude: intermixed versus clustered environments tune the strength of amplification or suppression without reversing the direction of the effect. Together, these principles reconcile disparate theoretical results and provide predictive criteria for adaptation in heterogeneous landscapes, from microbial communities to somatic
evolution and cancer.
Read the full abstract ▾
All authors Hossein Nemati, Kamran Kaveh, Jakub Svoboda, Mohammad Reza Ejtehadi, Krishnendu Chatterjee
Optics · Cross-listed from quant-ph
Robust certification of high-dimensional quantum devices
Javier Fernández, Albert Rico, David Viedma et al. (+6 more)
Certifying
quantum behavior from classically accessible data is essential for secure communication and scalable
quantum technologies. While powerful certification methods such as Bell nonlocality and
quantum steering exist, their implementation typically requires
entanglement or additional assumptions, and experimental demonstrations mainly focus on low-dimensional systems. In minimal prepare-and-measure scenarios, where a sender encodes information into
quantum states and a receiver performs a single measurement, robust certification becomes particularly challenging, especially in the presence of noise and in higher-dimensional
Hilbert spaces. Here, we propose, design, and experimentally implement a protocol that certifies quantumness between two distant parties without the need for preshared resources or measurement incompatibility. The experiments are carried out using the orbital angular momentum degrees of freedom of single
photons, chosen for providing increased dimensionality that is scalable. We demonstrate the robustness of the protocol through rank-stability analysis of the observed correlations, which enables the certification of non-classicality even in the presence of noise. Our results provide a practical route to validate high-dimensional
quantum communication systems and open new possibilities for secure and dimension-efficient
quantum information processing.
Read the full abstract ▾
All authors Javier Fernández, Albert Rico, David Viedma, Evelyn A. Ortega, Valerio Pruneri, Adam Vallés, Verònica Ahufinger, Anna Sanpera, Some S. Bhattacharya
Computational Physics
GPU-Accelerated Simulations of Moving Boundary Problems and Fluid-Structure Interaction at Extreme Scales
Sushrut Kumar, Joshua Romero, Jung-Hee Seo et al. (+2 more)
Computational fluid dynamics and fluid-structure interaction simulations involving moving and deforming bodies is extremely hard. In this work, we present a graphical processing unit (GPU) optimized implementation of the sharp-interface immersed boundary method. The method allows performing simulation around complex stationary as well as moving bodies on a Cartesian grid. We base our implementation on the ViCar3D framework and make use of OpenACC, CUDA, NCCL and MPI. We test the implementation across grid sizes ranging from O(10million) to O(1billion) points and achieved a 20X speedup compared to existing CPU implementation. We next present our multi-GPU implementation by utilizing CUDA streams and NCCL communicators. This enables us to obtain a >90% strong and weak scaling efficiencies. Next we demonstrate the capability of the developed software to simulate a turbulent fluid flow and coupled fluid-structure interaction in flapping bat wing in flight at Re=5000.
Read the full abstract ▾
All authors Sushrut Kumar, Joshua Romero, Jung-Hee Seo, Massimiliano Fatica, Rajat Mittal
Chemical Physics · Cross-listed from cond-mat.soft
Macromolecular tribology at flowing solid/liquid interfaces
Malo Velay and Jean Comtet
Molecular-scale interactions between solvated macromolecules and solid surfaces govern a large number of processes, from biology to engineering. Yet, despite extensive characterization at the macroscopic level, our molecular understanding of
polymer/surface interactions remains limited, particularly under out-of-
equilibrium conditions. Here, we combine wide-field single-molecule microscopy with microfluidic transport to directly track the nanoscale dynamics of individual fluorescently tagged macromolecular PEG adsorbates, and investigate their subtle couplings with interfacial hydrodynamic flows. At
equilibrium, we evidence marked surface dependence, with macromolecular dynamics switching from heterogeneous non-Brownian
diffusion on hydrophilic glass to bidimensional Brownian-like transport in an interfacial physisorbed state on hydrophobic self-assembled monolayers. While for hydrophilic glass, the effect of the flow is restricted to an advective contribution during solvent-mediated flights, we uncover for the hydrophobic surfaces a peculiar regime of mixed macromolecular friction, whereby the adsorbed chain rubs on the solid wall while being continuously dragged by the near-surface hydrodynamic flow through interfacial slippage. Through joint analysis of
equilibrium and out-of-
equilibrium transport, we finely disentangle these molecular level frictional interactions with both the solid surface and the interfacial
liquid. Beyond population-averaged dynamics, we further unveil a broad distribution of friction coefficients associated to individual chains, which we attribute conformational heterogeneities with sluggish reorganization timescale. By enabling direct observations of molecular-scale interfacial dynamics, our approach provides a novel molecular picture of macromolecular friction and adsorbate/surface interactions at flowing solid/
liquid interfaces.
Read the full abstract ▾
Geophysics · Cross-listed from cond-mat.mtrl-sci
Hydrogen-induced volume expansion in hexagonal close-packed iron: Effects of pressure and temperature
Yuichiro Mori, Masahiro Takano, Hiroyuki Kagi et al. (+4 more)
Hydrogen is a promising candidate for the light element in terrestrial planetary cores. Its incorporation into iron causes significant volume expansion, leading to a substantial density deficit. Although extensive studies have been conducted on iron hydride (FeH$_{x}$) with the fcc structure, the thermoelastic properties on FeHx with hcp structure (hcp-FeH$_{x}$) remain unconstrained because of the experimental difficulties to control hydrogen content. Here, we synthesized hcp-FeH$_{x}$ with controlled hydrogen contents under high-pressure and high-temperature conditions. We carried out in situ X-ray diffraction measurements on hcp-FeH$_{x}$ at 10–25~GPa and 300–900~K using a Kawai-type mutilanvil apparatus and constructed their equations of state. By combining our results with previously reported equations of state for hcp-Fe and experimental determinations of hydrogen content in hcp-FeH$_{x}$, we demonstrated that the discrepancies in the hydrogen-induced volume expansion coefficient can be clearly explained by its pressure and temperature dependence. Our results revealed that the hydrogen-induced volume expansion of hcp-Fe exhibits a strong temperature dependence at low pressures, but its temperature effect significantly weakens with increasing pressure. We also showed that the density reduction of Fe by hydrogenation depends on its
crystal structure. These findings demonstrate that estimates of hydrogen content in iron at planetary interior conditions based on hydrogen-induced volume expansion need to be revised by properly accounting for its $PT$-dependence and
crystal structure.
Read the full abstract ▾
All authors Yuichiro Mori, Masahiro Takano, Hiroyuki Kagi, Katsutoshi Aoki, Sho Kakizawa, Noriyoshi Tsujino, Yuji Higo
Plasma Physics
A physics-informed neural network approach to solve the spatially inhomogeneous electron Boltzmann equation
Ihda Chaerony Siffa, Detlef Loffhagen, Markus M. Becker et al. (+1 more)
The accurate determination of electron properties is fundamental to low-temperature
plasma simulations, necessitating precise solutions to the spatially inhomogeneous electron Boltzmann equation (EBE). This work explores the use of physics-informed neural networks (PINNs) for obtaining solutions to the spatially one-dimensional (1D) EBE subject to a uniform electric field in atomic gases. Employing the two-term approximation, the resulting equation for the isotropic distribution is solved directly in kinetic energy space without the conventional transformation to total energy. This approach demonstrates the flexibility of the PINN framework in handling diverse equation formulations. To address the convergence difficulties associated with this class of kinetic equations, a new neural network architecture is introduced. It features a
Fourier-feature input layer, adaptive activation functions, and a scaled multiplicative gating mechanism. It is demonstrated that this formulation preserves robust gradient flow throughout the network, which is critical for learning physically correct solutions. Benchmarking against reference data reveals that the present architecture achieves excellent agreement across both microscopic and macroscopic properties of the electrons. Furthermore, the architecture exhibits strong generalization across different gas types and a defined range of electric field strengths without requiring case-specific hyperparameter tuning. Ultimately, the excellent accuracy achieved here validates the applicability of the present PINN method.
Read the full abstract ▾
All authors Ihda Chaerony Siffa, Detlef Loffhagen, Markus M. Becker, Jan Trieschmann
Optics
High-Sensitivity, High-Throughput Double Sagnac Lateral Shearing Quantitative Phase Microscopy and Tomography with Pseudo-Thermal Illumination
Pawel Goclowski, Maciej Trusiak, Balpreet S. Ahluwalia et al. (+1 more)
Quantitative phase microscopy (QPM) enables label-free measurement of local optical path length variations, providing critical insight into the structure and dynamics of transparent biological specimens. Here, a highly sensitive lateral shearing QPM (LS-QPM) system is presented, based on a novel double Sagnac common-path interferometric configuration combined with pseudo-thermal illumination. The pseudo-thermal light source plays a central role in enhancing spatial phase sensitivity by suppressing coherent noise and speckle artifacts, while maintaining sufficient temporal coherence to generate high-density interference fringes, thereby enabling robust single-shot phase
retrieval. In addition, the double Sagnac architecture introduces an inherently stable common-path geometry, significantly enhancing temporal phase stability. Unlike conventional quadriwave lateral shearing interferometry (QWLSI)-based QPM systems, which typically suffer from a trade-off between spatial resolution and field of view (FOV), the proposed approach enables simultaneous achievement of diffraction-limited resolution and a large FOV. Experimental validation using calibrated polystyrene beads demonstrates accurate and spatially uniform phase reconstruction across the entire imaging area. Further, the system's capability for biological imaging is demonstrated through experiments on fixed and live HeLa
cells, where subcellular features and dynamic processes are captured in a label-free manner. Furthermore, volumetric imaging of embedded bead samples highlights the potential of the approach for three-dimensional phase
tomography. The lateral shearing mechanism, analogous to differential interference contrast (DIC), improves robustness to multiple scattering, indicating strong potential for future applications in imaging thick and heterogeneous samples.
Read the full abstract ▾
All authors Pawel Goclowski, Maciej Trusiak, Balpreet S. Ahluwalia, Azeem Ahmad
Space Physics
Transport of electrons in tangled magnetic fields
Daniel Verscharen, Natasha Jeffrey, Anton Artemyev et al. (+6 more)
Cosmic magnetic fields are typically inhomogeneous and often highly tangled due to large-scale
plasma flows,
turbulence, and instabilities. If the variations in the
magnetic field occur on scales that are large compared to the gyro-radius of the
plasma electrons, the electrons are primarily confined to gyro-centre trajectories along the field lines. Therefore, in-situ electron measurements help us map out the connectivity of the
magnetic field in space
plasmas. Gyro-centre drifts, wave-particle interactions, trapping, and cross-field
diffusion are processes related to field inhomogeneities and fluctuations; they have the potential to modify or even disrupt the transport of electrons along field lines. We introduce the basic principles of electron transport in tangled
magnetic fields and review the creation of tangled fields through
turbulence and instabilities as well as the modulation of parallel electron transport through kinetic instabilities. We then describe trapping and de-trapping effects in inhomogeneous
magnetic fields, as well as electron
diffusion and energisation across the
magnetic field. The transport of electrons in tangled fields results from a complex interplay of
plasma processes that occur on a broad range of scales. A combination of in-situ
plasma measurements, remote-sensing
plasma observations, and
plasma theory and simulations is required to resolve this contemporary challenge to the fields of heliophysics and astrophysics.
Read the full abstract ▾
All authors Daniel Verscharen, Natasha Jeffrey, Anton Artemyev, Jesse T. Coburn, Matthew W. Kunz, Oreste Pezzi, Mario Riquelme, Ida Svenningsson, Lynn B. Wilson III
Optics
2D Optical Beam Scanning using Integrated Acousto-Optics and a Frequency Comb
Shucheng Fang, Qixuan Lin, Fengyan Yang et al. (+5 more)
Optical beam steering is an essential technology for free-space optical communication, reconfigurable optical networks and
quantum information systems. Yet conventional steering methods either require bulky mechanical mechanisms, or rely on complex arrays of individually controlled light emitting elements. Integrated acousto-optic beam steering (AOBS) offers non-mechanical, continuous one-dimensional steering on-chip by using traveling acoustic waves with variable frequency to deflect light. In this work, we combine AOBS with an optical frequency comb and optical gratings to enable two-dimensional beam steering from a single aperture. Azimuthal scanning is controlled via acoustic frequency while polar coverage is realized by dispersing frequency comb lines with the gratings. We demonstrate this architecture by sequentially selecting and steering 11 comb lines spanning 1540-1570 nm, achieving a field of view of 18.2 by 4.3 degrees. Validation with a tunable
laser extends polar coverage to 11.4 degrees. Both components are realized on the same thin-film lithium niobate platform, providing a pathway toward monolithic integration.
Read the full abstract ▾
All authors Shucheng Fang, Qixuan Lin, Fengyan Yang, Yue Yu, Guangcanlan Yang, Bingzhao Li, Hong X. Tang, Mo Li
Plasma Physics
Three dimensional, spherically polarized magnetic fields
Anna Tenerani and Marco Velli
Turbulence in the
solar wind is characterized by Alfvénic fluctuations that exhibit spherical polarization, a
geometric condition resulting in the nearly constant magnitude of the
magnetic field. This property persists even during the largest field fluctuations, sometimes leading to local polarity reversals known as switchbacks. A longstanding question is whether three-dimensional smooth
magnetic fields can simultaneously satisfy the constant-$|{\bf B}|$ constraint, and how such fields can be constructed analytically or numerically. Here we propose a new numerical method that allows to construct a
magnetic field that is exactly spherically polarized, reproducing key features of
solar wind fluctuations. Using this framework, we find evidence that discontinuities are unavoidable for generic three-dimensional configurations. Fundamentally, this implies that field rotations cannot maintain exactly constant $|{\bf B}|$ in an arbitrarily large spatial domain. Rather, field rotations with constant magnitude can exist in limited regions of space. We argue that these finite spatial domains are separated by discontinuities where a local departure from constant $|{\bf B}|$ is expected. These results provide insights into the structure of
solar wind
turbulence and more generally into the nature of nonlinear
magnetic fluctuations in
plasmas.
Read the full abstract ▾
Atomic Physics
Nuclear Charge Radii of Sr Isotopes: Reevaluation based on Transition Frequency Measurements in the $5s-5p-4d$ manifold in Sr$^+$
J. Palmes, K. König, B. K. Sahoo et al. (+10 more)
High-precision quasi-simultaneous collinear and anticollinear
laser spectroscopy was performed on the $5s\,^2S_{1/2}\rightarrow 5p\,^2P_{1/2}$ (D1), $5s\,^2S_{1/2}\rightarrow 5p\,^2P_{3/2}$ (D2), and three $4d\rightarrow 5p$ transitions in the naturally abundant Sr$^+$ isotopes. Absolute transition frequencies were determined with uncertainties as low as $600$ kHz, while common-mode rejection enabled the extraction of isotope shifts with uncertainties down to $200$ kHz, one order of magnitude smaller than previously achieved. The uncertainties of the hyperfine-structure constants of the $5p$ states and the $4d\,^2D_{3/2}$ state in $^{87}$Sr were also improved. A King-plot analysis yielded a field-shift ratio of the D2 and D1 lines of $F_{\mathrm{D2}}/F_{\mathrm{D1}}=1.004(5)$, which lies within the theoretically allowed region and provides a
benchmark for atomic-structure calculations. Using data from all stable isotopes and investigated transitions, we compare field- and mass-shift constants obtained using several established approaches, ranging from King plots based entirely on experimental input to state-of-the-art ab initio atomic-structure calculations. We show that, above $N=50$, the extracted charge radii depend strongly on the approach used.
Read the full abstract ▾
All authors J. Palmes, K. König, B. K. Sahoo, H. Bodnar, A. Candiello, A. Dorne, R. de Groote, P. Imgram, I. Lopp, P. Müller, W. Nörtershäuser, B. Ohayon, R. Van Duyse
Optics
Seeing the forbidden: overcoming optical selection rules through nanophotonic integration
Alex H. Rubin, Vytautas Žalandauskas, Pranta Saha et al. (+7 more)
Optically addressable
spin defects in silicon carbide, including the neutral divacancy (VV$^0$) and the negative nitrogen-vacancy (NV$^-$), are among leading building blocks of solid-state
quantum technologies. Integrating these defects into photonic structures such as nanopillars improves
photon collection efficiency, but the consequences extend further. We show that the sub-wavelength geometry of nanopillars drastically modifies the local electromagnetic environment, providing optical access to defect transitions that are otherwise suppressed by selection rules in bulk material. Using low-temperature photoluminescence spectroscopy, we observe that emission from the PL3 divacancy, which is nearly absent in planar devices, becomes pronounced in nanopillars owing to a polarization transformation of the excitation field within the pillar. We further leverage the orientation-dependent collection of nanopillars to resolve the origin of previously ambiguous spectral lines. In particular, the NV4$'$ feature displays the signal enhancement expected for axially oriented NV$^-$ centres, consistent with assignment to a higher excited state of the $kh$ defect configuration. Our results establish nanophotonic integration as a
symmetry-sensitive probe that can both activate nominally dark transitions and identify the dipole character of poorly understood defect states.
Read the full abstract ▾
All authors Alex H. Rubin, Vytautas Žalandauskas, Pranta Saha, Rubek Poudel, Aurora Teien, Liam Hofmann, Nathan R. Gonzalez, Scott Dhuey, Marianne Etzelmüller Bathen, Marina Radulaski
Optics
High Frame-Rate Mid-Infrared SPAD Camera
Ziv Abelson, Daniel Beitner, Ziv Livne et al. (+4 more)
Single-
photon avalanche diode (SPAD) arrays have transformed optical imaging by enabling
photon-counting sensitivity, picosecond resolution, and high frame-rate operation. These capabilities, however, have remained confined to the visible and near-infrared, leaving the mid-infrared, the spectral region hosting the fundamental vibrational signatures of most molecules, largely inaccessible. Here, we demonstrate the first mid-IR SPAD camera by integrating broadband adiabatic frequency upconversion with a 512x512 Silicon SPAD array. This architecture transfers full SPAD functionality to the mid-IR, enabling room-temperature, low-noise, broadband
photon-counting imaging. We achieve spectrally resolved mid-IR imaging at frame rates of up to 60,000 frames per second and capture nanosecond-scale
laser-induced thermal dynamics via weak mid-IR blackbody emission, revealing spatial-temporal behavior inaccessible to existing technologies. These results establish a scalable platform for
photon-resolved, ultrafast thermal and chemical imaging in a spectral range previously inaccessible to high-speed low-light detection.
Read the full abstract ▾
All authors Ziv Abelson, Daniel Beitner, Ziv Livne, Eyal Hollander, Moshe Cohen Erner, Edoardo Charbon, Haim Suchowski
Plasma Physics
Synthetic model of gamma-ray emission during DT experiments on the SPARC tokamak
E.Panontin, R.A. Tinguely, J.L. Ball et al. (+10 more)
In thermonuclear
plasmas,
plasma ions undergoing
nuclear reactions emit gamma-rays with energies in the MeV range. Their spectroscopy can convey much
plasma information, such as the DT fusion power, the spatial and velocity distributions of the fast ions, and the
plasma heating performance. In the present work, we simulate the gamma-ray emission expected in the SPARC tokamak during a primary reference discharge, when the tokamak is expected to generate $140$ MW of fusion power and reach an energy gain factor of $Q\approx11$. We focus particularly T(D, $\gamma$)He-5, B-10(He-4, p $\gamma$)C-13 and D(He-3, $\gamma$)Li-5 reactions. We use realistic
plasma profiles calculated with the TRANSP code and simulate radiofrequency heating of the
plasma with CQL3D and TORIC. Possible locations for gamma spectrometers based on lanthanum bromide inorganic scintillators are suggested. For each, the signal-to-noise ratio of gamma-rays over
neutrons is evaluated using the ray-tracing code ToFu and high fidelity Monte Carlo models (MCNP and OpenMC) to solve radiation transport in SPARC. A dedicated
neutron attenuator made of high density polyethylene is scoped to allow gamma-spectroscopy during high
neutron yield experiments. And finally, the performance of LaBr$_3$ detectors in reconstructing the fusion power generated by SPARC is discussed.
Read the full abstract ▾
All authors E.Panontin, R.A. Tinguely, J.L. Ball, A. Grieve, S. Mackie, L. Nichols, P. Raj, A.A. Saltos, L. Singh, D. Vezinet, X. Wang, J.C. Wright, J. Rice