Space Physics
Solar Wind Classifications at Mars using Machine Learning Techniques
Catherine E. Regan, Silvia Ferro, Austin M. Smith et al. (+5 more)
Understanding
solar wind variability throughout the heliosphere is essential for fundamental space physics and future exploration of the Moon and Mars. The Mars Atmosphere and Volatile
EvolutioN (MAVEN) spacecraft has provided upstream
solar wind measurements at Mars spanning
Solar Cycles 24 and 25, enabling a statistical investigation of
solar wind regimes at this heliocentric distance. In this work, we apply an unsupervised machine-learning framework combining Principal Component Analysis and K-Means clustering to a normalized, multi-dimensional
solar wind
dataset to identify recurrent
solar wind regimes in a physically interpretable, data-driven manner. The resulting classification reveals distinct slow, fast, intermediate, and compressed
solar wind regimes whose relative occurrence and temporal organization are strongly modulated by
solar activity. This manuscript is part of the Heliophysics Summer School Machine Learning Special Collection.
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All authors Catherine E. Regan, Silvia Ferro, Austin M. Smith, Alvin J. G. Angeles, Nicholas A. Gross, Farzad Kamalabadi, Marco Velli, Jasper S. Halekas
Computational Physics · Cross-listed from cond-mat.str-el
Topological invariant of periodic many body wavefunction from charge pumping simulation
Haoxiang Chen, Yubing Qian, Weiluo Ren et al. (+2 more)
Many-body topological
quantum states host exotic
quantum phenomena and lie at the forefront of developing next-generation
quantum technologies. Recently emerged neural network wavefunction methods have established themselves as a powerful computational framework for accessing these states, enabling the variational machine learning calculation of the system's ground state wavefunction. However, reliable computation of topological invariants remains an open challenge when the whole deterministic energy spectrum is not available. In this work, we introduce a robust approach to determining topological invariant based on simulating the charge pumping process, by monitoring the response of polarization upon flux insertion. By applying this method, we accurately extract the Chern numbers for Abelian fractional Chern
insulators. Our approach also enables the first neural-network-wavefunction-based identification of anomalous composite
Fermi liquid states. Our work resolves a key bottleneck in applying neural network wavefunctions to correlated topological matter, and the method proposed is also generally applicable to other many-body approaches, thereby opening up new avenues for future research in this field.
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All authors Haoxiang Chen, Yubing Qian, Weiluo Ren, Xiang Li, Ji Chen
Applied Physics
Mitigating the contact resistance limitation of cavitated fine line Ag paste by Laser-Enhanced Contact Optimization
Donald Intal, Abasifreke Ebong, Vijay Upadhyaya et al. (+4 more)
Cavitation-assisted Ag paste is a promising route for fine-line, low-silver metallization in silicon
solar cells because it improves paste dispersion, extends shelf life, and reduces Ag consumption, but matching the contact performance of commercial pastes remains a challenge. Here, cavitated paste was evaluated on PERC
solar cells at peak firing temperatures of 720, 740, 750, and 762 C, with and without
laser-enhanced contact optimization (LECO). The results show a clear firing window: 720 and 740 {\deg}C produced high series resistance and reduced fill factor, 750 C gave the best pre-LECO performance, and 762 C showed additional electrical limitations with only limited LECO benefit. LECO selectively recovered the under-activated states, increasing fill factor from 76.8 to 80.2% at 720 C and from 76.7 to 79.8% at 740 C. Electroluminescence and conductive AFM further indicated improved current collection and stronger localized conduction after LECO. These results show that cavitated paste performance is governed primarily by a shifted contact-formation window, and that firing optimization combined with LECO provides a practical route to retain the fine-line advantage while improving electrical performance.
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All authors Donald Intal, Abasifreke Ebong, Vijay Upadhyaya, Brian Rounsaville, Ajeet Rohatgi, Dana Hankey, Marshall Tibbetts
Computational Physics · Cross-listed from quant-ph
Geometry-Induced Long-Range Correlations in Recurrent Neural Network Quantum States
Asif Bin Ayub, Amine Mohamed Aboussalah and Mohamed Hibat-Allah
Neural
Quantum States based on autoregressive recurrent neural network (RNN) wave functions enable efficient sampling without Markov-chain autocorrelation, but standard RNN architectures are biased toward finite-length correlations and can fail on states with long-range dependencies. A common response is to adopt
transformer-style self-
attention, but this typically comes with substantially higher computational and
memory overhead. Here we introduce dilated RNN wave functions, where recurrent units access distant sites through dilated connections, injecting an explicit long-range inductive bias while retaining a favorable $\mathcal{O}(N \log N)$ forward pass scaling. We show analytically that dilation changes the correlation geometry and can induce power-law correlation scaling in a simplified linearized and perturbative setting. Numerically, for the critical 1D transverse-field Ising model, dilated RNNs reproduce the expected power-law connected two-point correlations in contrast to the exponential decay typical of conventional RNN ansätze. We further show that the dilated RNN accurately approximates the one-dimensional Cluster state, a paradigmatic example with long-range conditional correlations that has previously been reported to be challenging for RNN-based wave functions. These results highlight dilation as a simple
geometric mechanism for building correlation-aware autoregressive neural
quantum states.
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Optics
Increased endurance of nonvolatile photonics enabled by nanostructured phase-change materials
Jayita Dutta, Andrew Tang, Brian Mills et al. (+8 more)
The rapid rise of artificial intelligence, and in-
memory computing has reinvigorated research on scalable, energy-efficient, and reconfigurable photonic hardware. Non-volatile phase-change materials (PCMs) are attractive, as they offer large refractive index contrast, wavelength-scale footprints, and zero static power consumption. However, current PCM-based electrically controlled photonic devices are plagued by high insertion loss and low endurance. One prevalent hypothesis for these material limitations come from electromagnetic scattering in the interface and large programming volumes, respectively. Here, we validate this hypothesis by showing that nano-structuring of PCM minimizes optical loss and enhances the endurance. By tapering both ends of a wide bandgap PCM Sb2Se3 segment on a silicon waveguide, we suppressed the insertion loss by ~94% (resulting in a loss of ~0.1 dB per {\pi} phase shift). Through combining tapering and
segmentation, we achieved high optical modulation amplitude (~70%), low loss (~0.5 dB per {\pi} phase shift), low-voltage (< 5V) actuation, and record high endurance greater than 100 million cycles. This work showcases the substantial advantage of nanopatterning PCMs to attain low loss and high cyclability.
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All authors Jayita Dutta, Andrew Tang, Brian Mills, Rui Chen, Arnab Manna, Gokul Nath SJ, Virat Tara, Dennis Callahan, Cosmin Constantin Popescu, Juejun Hu, Arka Majumdar
Atmospheric and Oceanic Physics · Cross-listed from q-bio.QM
Resolving satellite-in situ mismatches in Net Primary Production using high-frequency in situ bio-optical observations in the subpolar Northwest Atlantic
Kitty Kam, Emmanuel Devred, Stephanie Clay et al. (+5 more)
Net primary productivity (NPP) plays a central role in biological carbon pump (BCP) and global carbon cycling, but NPP estimates in high-latitude regions remain highly uncertain despite their disproportional contribution to the global carbon sink. Previous studies identified discrepancies among satellite and in situ-derived NPP estimates, but the drivers of disagreement remain poorly resolved due to limited high-frequency observations. Here, we present continuous depth-resolved estimates of in situ NPP in the subpolar Northwest Atlantic (56{\deg}N), reconstructed from daily bio-optical profiles collected between May and October 2016, and a 40-years
dataset of photosynthesis parameters derived from ^{14}C photosynthesis-irradiance (P-I) incubation experiments. Comparing with two satellite-based models showed satellite models overestimated NPP by factors of 2.5 to 4 from the study period. Statistical analyses identified the parameterization of the P-I relationship as the primary source of disagreement between satellite and in situ NPP estimates. Given the importance of NPP to estimates of the biological carbon pump, our findings highlight the need for regionally appropriate P-I parameterization in NPP models, particularly in high-latitude regions.
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All authors Kitty Kam, Emmanuel Devred, Stephanie Clay, Mohammad M. Amirian, Andrew Irwin, Dariia Atamanchuk, Uta Send, Douglas W.R. Wallace
Fluid Dynamics
Inverse Energy Cascade in Turbulent Taylor-Couette Flows
Changquan Zhou, Hua-Shu Dou, Lin Niu et al. (+1 more)
The inverse energy cascade in turbulent Taylor-Couette flow is studied in line with the results of the large eddy simulation. The simulation results show that the inverse energy cascade first occurs within the core region of the flow channel of the Taylor-Couette flow at higher Reynolds number. It is uncovered that this phenomenon is induced by the pulsed zero shear stress resulting from the singularities of the Navier-Stokes equation. In the core area between the two cylinders, the shear stress is nearly zero at higher Reynolds number. The
turbulence generated there has high turbulent energy due to discontinuity of the tangential velocity. Since the energy transfer between the fluid layers is inhibited due to the low shear stress, the turbulent energy cannot be transferred along the radial direction, and small-scale
vortices with high turbulent energy are produced. These small-scale
vortices are located with the large-scale
vortices and cannot be dissipated owing to low shear stress. A peak in the energy spectrum at middle frequency (or wave number) is formed due to the concentration of the small-scale
vortices. As the number of the singular points of the Navier-Stokes equation increases with the increasing Reynolds number, the region with zero shear stress expands along the radial direction, intensifying nonlinear instability and energy accumulation. This, in turn, leads to more prominent peaks in the energy spectrum, resulting in a more pronounced inverse energy cascade.
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All authors Changquan Zhou, Hua-Shu Dou, Lin Niu, Wenqian Xu
Optics
Fresnel zone plates for reconfigurable atomic waveguides
A.M. Pike, A. Dorne, L. Pickering et al. (+7 more)
Fresnel zone plates (FZPs), with patterns of $1\,\mu$m resolution, allow the formation of clean, diffraction-limited foci – but have a static phase profile. Spatial light modulators (SLMs) allow dynamic control of spatial beam intensity and phase – but are bulky and currently limited to roughly $10\,\mu$m pixel sizes and $1\,$Mega-pixel formats. Here, we present a new `best-of-both' kind of FZP, scalable to large area rings currently incompatible with direct SLM generation. It is equivalent to a plano-convex donut lens, whereby light's local intensity and global phase at the FZP map directly onto the image plane. The same FZP under different SLM illumination can generate: rings and arcs, double-rings, phase windings and ring
lattices (or dynamic combinations thereof). The smooth and adaptable near-field waveguide this enables will be ideal for Sagnac interferometry with ultracold atoms.
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All authors A.M. Pike, A. Dorne, L. Pickering, M. Jamieson, I.T. MacCuish, E. Riis, M.Y.H. Johnson, V.A. Henderson, P.F. Griffin, A.S. Arnold
Fluid Dynamics · Cross-listed from astro-ph.EP
The effect of dust on vortices II: Streaming instabilities
Nathan Magnan and Henrik Nils Latter
One of the main questions in
planet formation theory is how to cross the metre-scale barrier. In this two-part series, we assess the merits of
vortex-based theories by investigating the effect of backreacting
dust on
vortices. Specifically, this second paper focuses on the 'turbulent'
vortex theory, according to which the streaming instability (SI) might be active in
vortices. We re-purpose the dusty
vortex models derived in paper I as background flows for a linear stability analysis. To simplify the perturbation equations, we build an analogue of the shearing box that follows
vortex streamlines instead of Keplerian orbits. This allows us to study the
evolution of small wavelength perturbations. We find that inertial waves and
dust density waves can propagate in
vortices, but that they are not sinusoidal in time. We then extend resonant drag instability theory to these non-modal waves. This allows us to demonstrate that a close cousin of the SI remains active in
vortices, a result that greatly strengthens the case for
vortex-induced planetesimal formation. Our results also complement past simulations - which showed that the
dust's backreaction makes
vortices unstable - by providing insights into the nature of (some of) the unstable modes. The caveat is that our work is restricted to the limit of dilute well-coupled
dust and to the linear phase of the instability. Finally, our '
vortex SI' extends to 2D. We explain the mechanism of this 'zonal flow RDI', but remain unsure whether it is the unknown instability seen in 2D
vortex simulations.
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Fluid Dynamics · Cross-listed from astro-ph.EP
The effect of dust on vortices I: Laminar models
Nathan Magnan and Henrik Nils Latter
One of the main questions regarding
planet formation is how to cross the metre-scale barrier. Several theories rely on the formation of
dust clumps dense enough to collapse under their own
gravity.
Vortices are promising candidate sites of clump formation because they can concentrate
dust 'laminarly' by capturing particles, and 'turbulently' by creating the ideal conditions for the streaming instability. In this two-part series, we assess the validity of both pathways by investigating the effect of backreacting
dust on
vortices. This first paper focuses on the laminar pathway. We use multiple timescale analysis to create two models of
vortex evolution. They differ in their assumptions regarding how much gas crosses the
vortex's boundary: the first one assumes that the
vortex's mass is constant, whereas the second one assumes that the gas density is constant. These two options epitomize the two ways in which
vortices can respond to
dust concentration. Essentially, as
dust gets closer to the
vortex centre, it loses angular momentum. To compensate, the gas must either move away from the
vortex centre or change its vorticity (and therefore its shape). This choice neatly emerges from the conservation of a quantity akin to potential vorticity. Interestingly, we find that
vortices that adjust their vorticity all evolve towards elliptically unstable shapes. And since the elliptical instability destroys the
vortex, we conclude that
dust imposes an upper bound on
vortex lifetimes. If
vortex destruction happens before the
dust reaches the Hill density, the 'laminar'
vortex pathway to planetesimal formation fails.
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Optics
Dynamical control of non-hermitian coupling between sub-threshold nanolasers enables Q-switched pulse generation
Kristian Seegert, Roberto Gajardo, Guillaume Huyet et al. (+2 more)
Non-Hermitian photonics provides a framework to engineer the gain and loss of optical modes in open systems, enabling control of their spectral and dynamical properties. In particular, the ability to dynamically tune modal losses offers a route to implement functionalities traditionally relying on cavity Q-factor modulation, such as Q-switching, within nanophotonic platforms. Here, we demonstrate the generation of short optical pulses in a pair of phase-coupled photonic
crystal nanolasers exploiting non-Hermitian coupling. Two waveguide-coupled nanocavities are operated below their individual lasing thresholds and subjected to asymmetric optical pumping, such that a transient carrier-induced detuning modifies the interference conditions between them. This dynamically controls the gain and loss of the collective modes, and, upon crossing a resonance condition, leads to the rapid release of stored carrier energy as an optical pulse. A rate-equation model captures the interplay between carrier dynamics and modal coupling and reproduces the observed behavior. Experiments performed on an indium phosphide platform show pulse generation from cavities that do not lase efficiently on their own in continuous-wave operation, with temporal characteristics governed by carrier dynamics. These results indicate that non-Hermitian coupling can be used to control the effective cavity losses in time, providing a route to pulse generation in integrated photonic systems.
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All authors Kristian Seegert, Roberto Gajardo, Guillaume Huyet, Fabrice Raineri, Guilhem Madiot
Optics
Dispersion Control in Micromechanical Evanescent Optical Modulators
Karl Johnson, John Hong, Tallis Chang et al. (+8 more)
Efficient, low-loss, and versatile optical modulators are a critical ingredient for practical integrated photonic systems. Modulators based on micro-electromechanical systems (MEMS) have unique advantages over more traditional thermal, electro-optic, or
plasma dispersion modulators. In this work, we show that evanescent MEMS modulators (in which a dielectric slab is mechanically inserted into a waveguide's evanescent field) can exhibit anomalously dispersive modulation. That is, despite positive modulation of a waveguide mode's effective index, the modulator brings about a negative change in group index. We experimentally demonstrate these unique capabilities using a novel MEMS actuator design. The new theory and results here reveal that evanescent MEMS modulators possess a capability for control of wavelength dispersion not accessible to nearly any other type of modulator. These new capabilities may enable on-chip integration of systems for various optical applications, including broadband switching, photonic true time delay, pulse shaping, or phase matching of nonlinear processes.
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All authors Karl Johnson, John Hong, Tallis Chang, Sean C. Andrews, Jean Huang, Leilani Ferguson, Liam McCue, Edward Chan, Bing Wen, Noah A. Rubin, Yeshaiahu Fainman
Applied Physics
Beyond the Static Approximation: Assessing the Impact of Conformational and Kinetic Broadening on the Description of TADF Emitters
Daniel Beer, Jonas Weiser, Tom Gabler et al. (+3 more)
Thermally activated delayed fluorescence (TADF) is a promising route towards high-efficiency, metal-free organic light-emitting diodes (OLEDs). However, the characterization of TADF kinetics in solid-state thin films is often complicated by pronounced multiexponential photoluminescence decays that prevent standard biexponential modeling. In this work, we introduce the 'Gamma-Fit' method, a streamlined analytical framework based on the gamma distribution that accounts for the continuous distribution of decay rates inherent in disordered molecular ensembles. By treating the decay as a result of conformational and kinetic heterogeneity, we accurately extract kinetic parameters for the
benchmark emitters 4CzIPN and 5CzBN, as well as a series of novel diphenylamine (DPA)-based systems. Our results reveal that accounting for the local environment in thin films remains an important part in determining OLED efficiency. The experimental findings are complemented by a semiclassical Marcus-like computational approach. We evaluate the reliability of this conventional single-conformation rate calculation method and highlight the presence of conformational ensembles and multiple RISC-active triplet states as important factors for accurately describing the transition kinetics.
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All authors Daniel Beer, Jonas Weiser, Tom Gabler, Kirsten Zeitler, Carsten Deibel, Christian Wiebeler
Atomic Physics
Relativistic KRCI calculations of symmetry violating interaction constants for YbX (X: Cu, Ag and Au) molecules
Ankush Thakur, Renu Bala and H. S. Nataraj
The present work reports the parity ($\mathcal{P}$)-odd and time-reversal ($\mathcal{T}$)-odd interaction constants for the ground electronic state, X$^2\Sigma^{+}_{1/2}$, of YbX, X: Cu, Ag and Au molecules. The reported results have been calculated using the Kramers-restricted configuration interaction method limited to single and double excitations, in conjunction with relativistic core-valence double-, triple-, and quadruple-
zeta quality basis sets, within a four-component relativistic framework. The computed results for the
symmetry violating properties have been compared with the available results in the literature. Further, the parallel and perpendicular components of the hyperfine structure constants for the constituent atoms in YbX molecules are reported here for the first time.
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Optics
High-efficiency graphene-silicon slot-waveguide microring modulator at 1.5 {\mu}m and 2 {\mu}m wavelength bands
Chao Luan, Deming Kong, Yong Liu et al. (+2 more)
Electro-optic (E/O) modulators are crucial for optical communication but face a trade-off between modulation bandwidth and efficiency. A small footprint could reduce the capacitance and increase the bandwidth, however, this usually results in a low modulation efficiency. Here, we present an integrated E/O modulator that simultaneously achieves wideband large bandwidth and high modu- lation efficiency operation by
embedding a partially overlapped double-layer
graphene on a compact silicon slot waveguide microring resonator. At 1550 nm, the
graphene-silicon slot-waveguide demon- strates a high phase modulation efficiency of V{\pi} L = 220 V {\mu}m, and the corresponding microring modulator has a large bandwidth of over 70 GHz, a compact active length of 10 {\mu}m, and an optical modulation amplitude (OMA) of -1.97 dBm under a 3-V voltage swing. The modulator operates at a data rate of 50 Gbit/s with an open eye diagram under a 2-V Vpp RF drive voltage. The
graphene modulator operation is broadband, and we also characterize its performance at 2 {\mu}m wavelength band. At 2 {\mu}m wavelength band, the microring modulator has a large bandwidth of over 20 GHz, an OMA of -3.36 dBm under a 6-V voltage swing, and an open eye diagram at 20 Gbit/s with a 2-V Vpp RF drive voltage. The difference in performance is caused by the bandwidth limit of the 2 {\mu}m wavelength band measurement setup. The broadband, large bandwidth, compact, highly effi- cient, and energy efficient
graphene E/O modulator has the potential to enable large-scale
graphene photonic integrated
circuits, facilitating a broad range of applications such as optical interconnects, optical neural networks, and programmable photonic
circuits.
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All authors Chao Luan, Deming Kong, Yong Liu, Yunhong Ding, Hao Hu
Computational Physics · Cross-listed from math.NA
Hard-constrained Physics-informed Neural Networks for Interface Problems
Seung Whan Chung, Stephen T. Castonguay, Sumanta Roy et al. (+3 more)
Physics-informed neural networks (PINNs) have emerged as a flexible framework for solving partial differential equations, but interface problems remain challenging because continuity and flux conditions are typically imposed through soft penalty terms, leading to imperfect interface enforcement and degraded accuracy near interfaces. We introduce two ansatz-based hard-constrained PINN formulations for interface problems that embed the interface physics into the solution representation, decoupling interface enforcement from PDE residual minimization. The windowing approach constructs the trial space from compactly supported windowed subnetworks so that interface continuity and flux balance are satisfied by design. The buffer approach discretely hard-constrains subnetworks with additive buffer functions that enforce boundary and interface constraints at sampled points through a lightweight correction. We study both formulations on one- and two-dimensional
elliptic interface
benchmarks against soft-constrained baselines. A statistical study in one dimension shows that the windowing approach occasionally attains very high accuracy (as low as $O(10^{-9})$) on simple structured cases, but its rigid ansatz makes training stiff, so its median errors are often worse than the baselines. In contrast, the buffer approach achieves the smallest median error (as low as $O(10^{-5})$) across a wider range of source terms and interface configurations. In two dimensions, the buffer formulation is more robust for general geometries, while the windowing construction is more sensitive to overlap and corner effects and over-constrains the problem. These results position the buffer method as a straightforward and promising approach for interface problems, with the search for an optimal buffer function form left for future work.
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All authors Seung Whan Chung, Stephen T. Castonguay, Sumanta Roy, Michael S. Penwarden, Yucheng Fu, Pratanu Roy
Instrumentation and Detectors
ML for the hKLM at the 2nd Detector
Rowan Kelleher and Anselm Vossen
The present research applies Graph Neural-Networks (GNNs) for energy measurement and particle identification tasks for a proposed second detector at the future Electron Ion
Collider (EIC). In particular, an iron-scintillator sampling calorimeter would provide neutral
hadron ($K_L$ and
neutron) energy measurements and identification, as well as separation of
muons from
hadrons. Using detector simulations, particle hits in the detector are represented as graphs, and a GNN is trained for either classification or prediction. Furthermore, we developed a parameterization of the scintillator optical
photon simulation that yields a 20-fold speed up compared to the default simulation. We find that the GNN method outperforms classical methods at the same tasks, and we report projections for the energy and timing resolution, and identification accuracy of the calorimeter. We also present an integration of the GNN method into a Multi-Objective Optimization framework, enabled by an automated pipeline of data generation, GNN training, and detector performance evaluation. We utilize the optimization to quantify the tradeoffs between different performance metrics at high and low energies when changing the detector design parameters, such as the iron/scintillator thickness.
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Atmospheric and Oceanic Physics
Ecohydrological Controls on Moist Convection and Long-Term Rainfall Feedback
Elizabeth Cultra, Jun Yin, Mark Bartlett et al. (+1 more)
To elucidate how land surface state and soil moisture dynamics regulate moist convection, and how convective rainfall subsequently reshapes surface and root-zone hydrology, we develop a
stochastic dynamical model that couples soil moisture, vegetation hydraulics, atmospheric boundary layer
evolution, and convective available potential energy (CAPE). We show that CAPE depends not only on the free-tropospheric environment but also on soil moisture, through its control of surface fluxes, boundary-layer growth, and the timing of the intersection between the atmospheric boundary layer and the lifting condensation level (LCL). Soil texture and plant properties strongly modulate convective potential during dry-down. Loamy sand favors convection at relatively high soil moisture and maintains the largest CAPE at the time of LCL-ABL crossing across drying conditions. In contrast, sandy soils exhibit high CAPE when wet but lose convective potential rapidly as they dry. As matric potential becomes more negative, convection is increasingly suppressed in finer, loamy clay textures. Plant functional type further shapes dry-down dynamics: water-use-maximizing strategies can enhance dry persistence via stomatal closure during drying, whereas more conservative strategies can sustain convection for longer periods. On longer timescales,
stochastic rainfall forcing with CAPE-dependent precipitation intensity produces persistent wet and dry soil moisture regimes, with switching times that depend on soil hydraulic properties, plant physiological traits, and atmospheric conditions.
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All authors Elizabeth Cultra, Jun Yin, Mark Bartlett, Amilcare Porporato
Atomic Physics
Nuclear forward scattering of Bessel beams in $^{229}$Th:CaF$_2$
Alexander Franz, Tobias Kirschbaum and Adriana Pálffy
The coherent pulse propagation of a Bessel beam resonant to the 8.4 eV
nuclear clock transition in $^{229}$Th-doped
crystals is investigated theoretically. Due to the
magnetic dipole character of the clock transition, Bessel beams which present non-uniform transverse profiles and carry orbital angular momentum might enhance excitation channels or offer new control degrees of freedom compared to standard plane waves. We model the
nuclear forward scattering of a resonant Bessel beam pulse propagating through the
crystal, extending an formalism based on the iterative wave equation for plane waves. Thereby we take into account the
nuclear quadrupole splitting in the
crystal, considering the possibility of multiple quantization axes and present results for scenarios involving a single
nuclear transition and multiple simultaneously driven transitions, analyzing temporal and spatial intensity patterns. Our findings show that the propagation of Bessel beams can be used to determine the relative distribution of different directions of quantization axes inside the
crystal.
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Optics
Small-scale photonic Kolmogorov-Arnold networks using standard telecom nonlinear modules
Luca Nogueira Calçado, Sergei K. Turitsyn and Egor Manuylovich
Photonic neural networks promise ultrafast inference, yet most architectures rely on linear optical meshes with electronic nonlinearities, reintroducing optical-electrical-optical bottlenecks. Here we introduce small-scale photonic Kolmogorov-Arnold networks (SSP-KANs) implemented entirely with standard telecommunications components. Each network edge employs a trainable nonlinear module composed of a Mach-Zehnder interferometer,
semiconductor optical amplifier, and variable optical attenuators, providing a four-parameter transfer function derived from gain saturation and interferometric mixing. Despite the constrained functional form of these optical nonlinearities, SSP-KANs comprising only a few optical modules achieve strong nonlinear inference performance across classification, regression, and image recognition tasks, approaching software baselines with significantly fewer parameters. A four-module network achieves $94.3$% (IQR: $90.3$–$97.4$%, 10~seeds) accuracy on nonlinear classification
benchmarks; a seven-module network attains $R^2 = 0.986 \pm 0.015$ on six-input regression. Performance remains robust under realistic hardware impairments, maintaining high accuracy down to 6-bit input resolution and 14 dB signal-to-noise ratio. By using a fully differentiable physics model for end-to-end optimisation of optical parameters, this work establishes a practical pathway from simulation to experimental demonstration of photonic KANs using commodity telecom hardware.
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Physics and Society · Cross-listed from q-bio.PE
Analysis of non pharmaceutical interventions with SIR epidemic models: decreasing the infection peak vs. minimizing the epidemic size
Eric Rozán, Marcelo N Kuperman and Sebastián Bouzat
This study investigates the influence of different types of non-pharmaceutical interventions (NPIs) on epidemic progression using SIR compartmental models. We analyze the optimization of two distinct targets: the final epidemic size and the infection peak, particularly how they respond to variations in the initiation time of the NPIs. We derive analytical approximations for the critical points of the infection curve of the standard mean-field SIR model with NPIs, and for the epidemic size, enabling a systematic comparison. The analytical results reveal the existence of six different allowed scenarios for the
evolution of the epidemic with a single NPI. Furthermore, by employing degree-based mean-field network models, we distinguish between NPIs that decrease the transmission rate (individual and environmental measures) and those that reduce social contacts (lock down measures). We find that, when assuming equal effects on the reproductive number, the former are more efficient in reducing the final epidemic size. Meanwhile, the effectivities of both types of NPIs differ in reducing primary and secondary peaks. The results for all models consistently confirm that minimizing the infection peak requires earlier implementation of the NPI than minimizing the epidemic size, offering new insights for strategic public health timing.
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Fluid Dynamics
Elastic and Viscous Effects in Viscoelastic Flows: Elucidating the Distinct Roles of the Deborah and Weissenberg Numbers
Luis G. Sarasúa, Daniel Freire Caporale and Arturo C. Marti
The interpretation of the parameters appearing in constitutive models for viscoelastic fluids is essential for analyzing theoretical predictions and understanding the origin of phenomena observed in experiments. In this work, we examine the physical significance of the Deborah ($De$) and Weissenberg ($Wi$) numbers, along with other key parameters commonly used in these models. The central objective is to clarify the extent to which these dimensionless groups effectively characterise the competition between elastic and viscous effects in complex flows. While these parameters are ubiquitous in theoretical and experimental research, their interpretation is often context-dependent and prone to ambiguity. To address this, we analyse two representative scenarios: an analytical solution for unsteady planar flow and a numerical simulation of viscoelastic flow between rotating coaxial cylinders, governed by the Oldroyd-B constitutive equations. Our findings elucidate the distinct roles of these dimensionless numbers, offering guidelines for their rigorous interpretation in both analytical and numerical studies.
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Optics
Closing the Loop in Epitaxy with Machine Learning: Joint Optimization of Growth and Geometry in On-Chip Lasers
Mihir R. Athavale, Stephen A. Church, Wei Wen Wong et al. (+4 more)
Achieving device-to-device reproducibility is a critical bottleneck for scalable photonic integrated
circuits, as subtle variations in bottom-up epitaxial growth and fabrication severely limit yield. We present a machine learning workflow for III-V multi-
quantum well microring
lasers that first optimizes growth and geometry parameters via multi-objective
Bayesian optimization, then leverages variational autoencoders (VAEs) to attribute residual device-to-device variability to its underlying sources. By explicitly targeting threshold variance alongside absolute performance, we demonstrate 100% lasing yield across all designs. The optimized multi-
quantum well microring
laser fields achieved a median lasing threshold of $16~\mu\mathrm{J}\,\mathrm{cm}^{-2}\,\mathrm{pulse}^{-1}$, a $73\%$ reduction in threshold variance relative to the previously reported best values, and a median emission wavelength of $1333~\mathrm{nm}$, in the telecommunications O-band. Furthermore, to diagnose residual performance dispersion under nominally identical conditions, VAEs were used to isolate the key components of device morphology that impact performance. This analysis successfully decoupled
geometric from material disorder, quantitatively linking previously unmeasured morphological variations to population-level threshold fluctuations. This data-driven workflow bridges the gap between fundamental epitaxy and reliable manufacturing, establishing a generalizable blueprint for designing and yield-optimizing complex, non-linear optoelectronic devices.
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All authors Mihir R. Athavale, Stephen A. Church, Wei Wen Wong, Andre KY Low, Hark Hoe Tan, Kedar Hippalgaonkar, Patrick Parkinson
Physics and Society · Cross-listed from cond-mat.stat-mech
Harmonic morphisms and dynamical invariants in network renormalization
Francesco Maria Guadagnuolo, Marco Nurisso, Federica Galluzzi et al. (+2 more)
Renormalization of complex networks requires principled criteria for assessing whether a coarse-graining preserves dynamical content. We prove that discrete harmonic morphisms – surjective maps preserving harmonic functions – provide the minimal condition under which random walks on a fine-grained network project exactly onto random walks on its coarse-grained image, through an appropriate random time change. We formalize this via the harmonic degree, a diagnostic quantifying how closely any network coarse-graining approximates a harmonic morphism. Applying this framework to
geometric,
Laplacian, and GNN-based renormalization across real-world networks, we find that each method produces a distinct dynamical fingerprint encoding its underlying physical assumptions. Most strikingly,
Laplacian renormalization spontaneously yields exact harmonic morphisms in several networks, achieving exact preservation of first-exit random-walk transition structure at specific scales, a property that entropic susceptibility fails to detect. Our results identify a discrete analog of
diffusion-preserving conformal maps for irregular network
topologies and provide quantitative tools for designing and evaluating multi-scale network descriptions.
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All authors Francesco Maria Guadagnuolo, Marco Nurisso, Federica Galluzzi, Antoine Allard, Giovanni Petri
Optics · Cross-listed from cond-mat.mes-hall
Valley-controlled many-body exciton interactions in monolayer WSe$_2$ phototransistors
Daniel Vaquero, Cédric A. Cordero-Silis, Daniel Erkensten et al. (+6 more)
Many-body
exciton interactions shape the optoelectronic response of atomically-thin transition metal dichalcogenides, yet optical control of these interactions remains largely unexplored. To date, modulation of
exciton-
exciton interactions has primarily relied on electrical gating or van der Waals engineering. Here, we demonstrate all-optical control of many-body
exciton interactions in monolayer WSe$_2$ via valley-selective excitation using polarization-resolved pulsed-
laser photocurrent spectroscopy. Circular excitation selectively populates
excitons in a single valley, whereas linear excitation populates both valleys, inducing a valley-dependent nonlinear photoresponse. We observe helicity-dependent
exciton renormalization, alongside a two-fold enhancement of sublinear photocurrent scaling under circular excitation, reflecting single-valley population of interacting
excitons. A microscopic model incorporating intervalley-exchange and
exciton-
exciton annihilation mediated by dark and bright
exciton populations reproduces the nonlinear valley-selective response. These results establish the valley degree of freedom as an all-optical control parameter for tuning many-body excitonic effects and, exploring correlated
exciton states and valleytronic applications in two-dimensional
semiconductors.
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All authors Daniel Vaquero, Cédric A. Cordero-Silis, Daniel Erkensten, Roberto Rosati, Martijn H. Takens, Kenji Watanabe, Takashi Taniguchi, Ermin Malic, Marcos H. D. Guimarães
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Theory-Guided Discovery of Pressure-Induced Transitions in Fast-Ion Conductor BaSnF4
Robin Turnbull, Zhang YingLong, Claudio Cazorla et al. (+6 more)
Fast-ion conductors such as BaSnF4 are of significant interest for next-generation solid-state battery technologies due to their high ionic conductivity and chemical stability. However, the behaviour of these materials under extreme conditions remains poorly understood, despite the relevance of pressure-induced modifications for tuning functional properties. In this study, we combine density functional theory (DFT) calculations with high-pressure experiments to investigate the structural
evolution of BaSnF4 up to 40 GPa. DFT predicts two pressure-induced phase transitions: from the ambient-pressure tetragonal P4/nmm phase to a monoclinic P21/m-I structure at 10 GPa, and subsequently to a denser monoclinic P21/m-II phase at 32 GPa. The first transition is experimentally confirmed via angle-dispersive X-ray diffraction, Raman spectroscopy, and electrical resistivity measurements, all performed at ambient temperature. The second transition is supported by distinct changes in high-pressure Raman modes and resistivity behaviour, consistent with a further structural reorganization. These findings not only clarify the high-pressure phase diagram of BaSnF4, but also shed light on the potential for pressure-tuned ionic transport in fluorostannate-based solid electrolytes.
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All authors Robin Turnbull, Zhang YingLong, Claudio Cazorla, Akun Liang, Rahman Saqib, Miriam Pena-Alvarez, Catalin Popescu, Laura Pampillo, Daniel Errandonea
Data Analysis and Statistics · Cross-listed from astro-ph.HE
Reginald Christian Bernardo
Langevin
stochastic differential equations provide a dynamical description of
pulsar timing noise and gravitational wave background (GWB) signals. They are also central to state space
algorithms that have gained traction in
pulsar timing array analysis due to their linear computational scaling with the number of observations. In this work, we utilize established methods in
diffusion theory to derive analytical time-domain solutions (means, covariances, and probability density functions) to Langevin equations relevant to red noise and the GWB signal in
pulsars. The solutions give direct physical insight on the dynamics of
pulsar timing signals. As a canonical example, we show that the
pulsar spin frequency modeled as an Ornstein-Uhlenbeck process is mathematically inconsistent with a stationary GWB signal when the timing residual is the direct observable. The nonstationarity can be partially dealt with by marginalizing over long time deterministic trends in the data. Then, we show that a random process based on an overdamped harmonic oscillator supports both a stationary
spin frequency and phase residuals, consistent with a stationary GWB signal. We also turn our
attention to a phenomenological model of a
neutron star – a two-component model with
spin wandering – that has been motivated to explain observed timing noise in
radio pulsars. We derive analytical expressions for the means, covariances, and cross-covariances of the crust and superfluid rotational states driven by white noise. The associated constant deterministic torques are linked to the quadratic
spin-down of
pulsars. The solutions reveal the physical origin of nonstationarity in the residual model: the coexistence of damped and diffusive eigenmodes of the system.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Comparative high-pressure study on rare-earth entropy fluorite-type oxides
Pablo Botellaa, David Vie, Leda Kolarek et al. (+6 more)
We report a comparative high-pressure study of two fluorite-type rare-earth
oxides with increasing configurational
entropy, (CePr)O$_{2-{\delta}}$ and (CePrLa)O$_{2-{\delta}}$. Synchrotron-based powder X-ray diffraction and Raman spectroscopy were carried out up to 30 GPa and 20 GPa, respectively. Both compounds retain the cubic fluorite structure throughout the pressure range explored, although an anomaly is observed between 9-16 GPa, characterized by a compressibility plateau and changes in vibrational modes. This behavior is attributed to local
lattice distortions and a progressive bond angle bending rather than abrupt phase transitions. In (CePrLa)O$_{2-{\delta}}$, the onset of amorphization is observed above 22 GPa, highlighting its reduced structural stability. The bulk modulus of both systems shows a slight decrease after the onset of the anomaly, suggesting subtle
lattice softening. Raman spectroscopy reveals suppression of the F$_{2g}$ mode intensity with increasing cationic disorder, and under compression, partial reordering is evidenced by an increase in the RE-O mode intensity. Our results highlight the complex interplay between configurational
entropy, cation size, and pressure in determining the structural stability and vibrational properties of rare-earth high-
entropy oxides and provide insight into the mechanisms governing their resilience and local disorder under extreme conditions.
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All authors Pablo Botellaa, David Vie, Leda Kolarek, Neha Bura, Peijie Zhang, Anna Herlihy, Dominik Daisenberger, Catalin Popescu, Daniel Errandonea
Fluid Dynamics · Cross-listed from cond-mat.soft
Axial forces in capillary liquid bridges of polymer solutions
Sreeram Rajesh, Riley S. Tinianov, Jooyeon Park et al. (+1 more)
Liquid bridges form between particles during wet mixing with binders or by condensation due to ambient humidity. The consequences of capillary bridges can be quite drastic, creating macroscopic cohesion, as seen in sandcastles and in the formation of particulate agglomerates. Bulk effects in cohesive particles arise from forces generated by capillary bridges, so particle-scale measurements are needed to develop predictive models. Most existing studies at the particle scale assume Newtonian
liquids. Yet many binders in industry and in the environment can exhibit viscoelastic behavior. In this study, we measure the axial force generated by
liquid bridges of viscoelastic
polymer solutions between two spherical beads during controlled uniaxial separation. We vary the
polymer concentration, separation velocity, and particle size, and track the force as the bridge thins and ruptures. At quasi-static rates, the axial force remains dominated by capillarity and is not significantly affected by
polymer rheology. However, increasing the stretching rate increases the peak force through viscous dissipation and promotes the formation of a viscoelastic filament, thereby delaying rupture. The peak axial forces collapse when rescaled by a capillary number and particle size, while the effective rupture distance collapses with a Weissenberg number. These results provide a simple first-order particle-scale force law for polymeric binders.
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All authors Sreeram Rajesh, Riley S. Tinianov, Jooyeon Park, Alban Sauret
Optics
A beat wave approach to harmonic generation in chiral media
Raoul Trines, Holger Schmitz, Robert Bingham et al. (+4 more)
We extend the beat-wave framework for
laser harmonic generation - where spectra form regular
lattices in
Fourier space - to the nonlinear response of isotropic
chiral media driven by locally
chiral light. We represent the enantio-sensitive response of the medium by a
chiral zero-frequency (DC) mode derived from the transverse
spin density induced by structured or focused fields. Beating between this DC mode and the driving electromagnetic modes yields alternating
chiral and achiral contributions on a regular harmonic
lattice. We derive a general criterion for when
chiral and achiral pathways overlap at the same harmonic and generate enantio-sensitive interference that survives spatial or angular integration (global chirality), versus when enantio-sensitivity remains confined to spatially varying patterns (local chirality). We apply the criterion to published configurations of synthetic
chiral light, including OAM-carrying bicircular fields and crossed multicolour beams, and show that it reproduces and clarifies their reported global-chirality and beam-bending regimes.
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All authors Raoul Trines, Holger Schmitz, Robert Bingham, Martin King, Paul McKenna, David Ayuso, Laura Rego