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Physics Physics

physics Watch Physics

Friday 17 April

Space Physics · Cross-listed from astro-ph.SR

Solar Cycle Prediction: Challenges, Progress, and Future Perspectives

Bidya Binay Karak

Reliable prediction of the solar cycle is a formidable challenge, yet it is increasingly vital in our technology-dependent society as solar activity drives space weather. Various methods, including precursors, nonlinear curve fitting and extrapolation, statistical and Machine Learning (ML) models, and dynamo and surface flux transport (SFT) models, were implemented to predict past cycles. Analysing about 100 predictions for Solar Cycle 24 and over 130 for Solar Cycle 25, we find that most methods largely failed to predict the peak correctly: Cycle 24 was statistically predicted to be a strong cycle, whereas Cycle 25 was predicted to be a weak cycle. By and large, predictions made only after the cycle began became closer to reality. ML-based models also produced discouraging results. The polar field and its proxy-based predictions are the most physically supported approach to prediction; however, applying them much earlier, before the solar minimum, may yield inaccurate results. Dynamo models are progressively improving both in understanding and in forecasting; however, they need to improve by accurately assimilating the observed polar field data and additional physics, such as meridional flow variations. Solar dynamo theory, complemented by the SFT model and observations, demonstrates that the prediction of a cycle before the time of its previous cycle's maximum is meaningless. The current solar cycle is declining, and the community is now preparing for the prediction of the next cycle. Thus, this review will guide future studies.
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Accelerator Physics

Online optimization of nonlinear lattice using a data-driven chaos indicator

Yongjun Li and Minghao Song

We report the experimental implementation of a Data-Driven Chaos Indicator (DDCI) [Y.~Li et al., Nucl.\ Instrum.\ Methods Phys.\ Res.\ A 1024 (2022) 166060] for online optimization of the National Synchrotron Light Source II (NSLS-II) storage ring. The DDCI quantifies the predictability of electron beam dynamics using turn-by-turn beam position monitor data. A surrogate model of the one-turn map is first trained, and its out-of-sample predictive uncertainty is then employed as a measurable indicator of chaos. By tuning sextupole magnets to mitigate nonlinear effects, a clear enlargement of the dynamic aperture is achieved, accompanied by a corresponding improvement in injection efficiency.
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Fluid Dynamics

Quantum-Inspired Simulation of 2D Turbulent Rayleigh-Bénard Convection

Nis-Luca van Hülst, Mario Guillaume Cecile, Hai-Yen Van et al. (+3 more)

Turbulent thermal convection governs heat transport in systems ranging from stellar interiors to industrial heat exchangers. Two-dimensional Rayleigh-Bénard convection serves as a paradigm for these flows, reproducing key features such as thin boundary layers, large-scale circulation, and sustained plume dynamics. While Matrix Product State (MPS) methods have demonstrated significant compression of isothermal turbulent fields, their application to buoyancy-driven flows with active thermal coupling has remained unexplored. We apply MPS to two-dimensional Rayleigh-Bénard convection with dynamical simulations up to $\mathrm{Ra} = 10^{10}$. An a priori decomposition of DNS snapshots up to $\mathrm{Ra} = 10^{11}$ shows that the bond dimension $\chi$ required to represent the flow fields grows without saturation, in contrast to the plateauing of $\chi$ reported for velocity fields in isothermal 2D turbulence. Crucially, however, dynamical simulations solving the governing equations directly in the compressed MPS format at fixed $\chi$ show that the $\chi$ required to recover statistical observables, such as the Nusselt number, scales significantly more favorably with $\mathrm{Ra}$ than the a priori complexity suggests. At $\mathrm{Ra} = 10^{10}$, a relative error of $1.8\%$ in the mean Nusselt number is achieved with a nearly 9-fold reduction in degrees of freedom, using a $\chi$ comparable to that required at $\mathrm{Ra} = 10^{9}$. Spectral analysis confirms the progressive recovery of spatial and temporal scales with increasing $\chi$. These findings establish MPS as a scalable tool for simulating thermally driven turbulence, suggesting the method may remain viable for investigations of the ultimate regime at substantially higher $\mathrm{Ra}$.
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All authors Nis-Luca van Hülst, Mario Guillaume Cecile, Hai-Yen Van, Tomohiro Hashizume, Eugene de Villiers, Dieter Jaksch

Fluid Dynamics

Early onset of secondary shear instability in Kelvin-Helmholtz braids at high Reynolds number

Emma R. Bouckley, Sam F. Lewin and Adrien Lefauve

We study the onset of two-dimensional secondary shear instability (SSI) in the braid regions connecting primary Kelvin-Helmholtz billows in stratified shear flows. While strain induced by the billows stabilises the braids, it also compresses their tilted isopycnals, enhancing baroclinic shear that enables rapid perturbation growth. By modifying the classical analysis of Corcos & Sherman (J. Fluid Mech. 73, 241-264, 1976) in braid-aligned coordinates and adding an additional stability criterion based on the ratio of strain rate to shear, we develop an inviscid, time-dependent model for the braid and the onset of SSI. We show that the criterion for instability can be achieved significantly earlier than the saturation of the primary billow at sufficiently high initial Richardson number Ri, as increased stratification slows billow growth while accelerating baroclinic shear production in the braid. Two-dimensional direct numerical simulations up to Reynolds numbers Re=10^7 quantify the role of viscosity. At high Re, we find that SSI indeed develops early in the braid, as predicted by the inviscid model, while the primary billow is still growing and before viscosity slows braid thinning. These results provide a mechanistic explanation for field observations of braid-dominated mixing and suggest that, at geophysically relevant Ri and Re, SSI can control the three-dimensional turbulent transition and ensuing diapycnal mixing by preceding and pre-empting both vortex pairing instabilities and secondary convective instabilities in the billow core.
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Plasma Physics · Cross-listed from astro-ph.SR

Magnetic switchback formation: a review of proposed mechanisms

Peter F. Wyper, Jonathan Squire, Etienne Pariat et al. (+19 more)

Magnetic switchbacks are large amplitude deflections of the magnetic field within the solar wind. They are Alfvénic in character and so are associated with a spike in velocity and a generally small variation in local plasma density. Early orbits of Parker Solar Probe revealed that the solar wind near the Sun is dominated by these structures, and therefore, they may be playing an important role in the energy budget and acceleration of the young solar wind. In this review, we present an overview of different mechanisms that have been proposed for how switchbacks could be formed. We group the mechanisms by whether they predominantly act in the low solar atmosphere or within the solar wind (in situ). We focus on mechanisms that can create reversals of the ambient magnetic field direction and, thus, account for the most extreme perturbations. The general consensus is that mechanisms in the lower solar atmosphere do not form such reversals on their own but provide the seed perturbations, flows, or particle beams necessary for in situ mechanisms to create switchbacks within the solar wind. Switchback observations thus likely contain an imprint of the coronal source of the seed perturbation or flow, which is evolved further locally by one of several plausible in situ mechanisms. We discuss the strengths and weaknesses of each mechanism and outline future observational and theoretical tests that could help differentiate between them.
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All authors Peter F. Wyper, Jonathan Squire, Etienne Pariat, Oleksiy V. Agapitov, Jim F. Drake, Norbert Magyar, William H. Matthaeus, Lorenzo Matteini, David Ruffolo, Victor Réville, Chen Shi, Munehito Shoda, Marc Swisdak, Marco Velli, Mojtaba Akhavan-Tafti, Bahaeddine Gannouni, Roberto Lionello, Maria S. Madjarska, Mathew J. Owens, Nour E. Rawafi, Alphonse C. Sterling, Durgesh Tripathi

Medical Physics

VQ-Wave: A physics-driven spatio-temporal deep learning approach for non-contrast-enhanced lung ventilation and perfusion MRI

Grzegorz Bauman, Pavlos Panos, Philipp Latzin et al. (+1 more)

Purpose: To develop a robust deep learning framework for non-contrast-enhanced functional lung MRI, overcoming the limitations of spectral decomposition in the presence of physiological non-stationarity. Methods: We introduce VQ-Wave (Ventilation/Q-perfusion Waveform-based Assessment of Variable Evolutions), a physics-driven spatio-temporal inception neural network trained on synthetic signal models to estimate ventilation and perfusion parameters. By processing local spatial context alongside temporal evolution, the network learns to decouple physiological signals from noise. The training generator simulated non-stationary dynamics, including amplitude modulations, frequency drifts, and noise. Performance was validated against matrix pencil (MP) decomposition using numerical phantoms and in-vivo lung MRI acquired in four healthy volunteers and two children with cystic fibrosis (CF) at 1.5T. Results: In numerical benchmarks, VQ-Wave demonstrated superior robustness to non-stationarity, maintaining low global and regional error rates where MP exhibited stochastic instability due to spectral leakage. In-vivo, VQ-Wave accurately captured functional defects in patients with CF yielding ventilation and perfusion maps with high quantitative stability (mean variation < 12%) even when scan time was reduced from 45s to 15s. Conversely, under irregular physiology and short scan lengths, MP decomposition severely degraded, exhibiting systematic amplitude instability, overestimation bias, and regional signal dropouts. Conclusion: VQ-Wave offers a robust, physics-driven neural network-based alternative to spectral decomposition. By effectively handling physiological irregularity and noise, it enables reliable functional lung imaging with substantially shortened acquisition protocols.
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All authors Grzegorz Bauman, Pavlos Panos, Philipp Latzin, Oliver Bieri

Instrumentation and Detectors · Cross-listed from hep-ph

$\delta_{CP}$-free constraints on NSI parameters $\varepsilon_{e\mu}$ and $\varepsilon_{e\tau}$ using high-purity $\nu_\mu$ CC events at IceCube DeepCore

J Krishnamoorthi, Anil Kumar and Sanjib Kumar Agarwalla

Atmospheric neutrinos provide a unique avenue to probe theories beyond the Standard Model (BSM) over a wide range of energies and path lengths. The theory of nonstandard interactions (NSI) of neutrinos is one of the important BSM scenarios, which can modify flavor oscillations of atmospheric neutrinos traveling through the Earth. In this work, we use a high-purity $\nu_{\mu}$ charged-current (CC) sample of atmospheric neutrinos from IceCube DeepCore with a livetime of 7.5 years to search for the NSI parameters $\varepsilon_{e\mu}$, $\varepsilon_{e\tau}$, and $\varepsilon_{ee}-\varepsilon_{\mu\mu}$. The $\nu_{\mu}$ CC events mainly come from the $\nu_{\mu}$ survival channel having no significant dependence on $\delta_{CP}$. Therefore, the constraints on $\varepsilon_{e\mu}$ and $\varepsilon_{e\tau}$ obtained using this $\nu_{\mu}$ CC sample are expected to be free from the $\delta_{CP}$-degeneracy. The data sample is found to be in agreement with the standard neutrino interactions. Therefore, we place bounds on these NSI parameters that are consistent with and comparable to existing experimental constraints. These $\delta_{CP}$-free constraints from IceCube DeepCore are complementary to those from the long-baseline neutrino oscillation experiments, where the appearance channel depends on $\delta_{CP}$.
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Plasma Physics

Experimental evidence for coronal mass ejection suppression in strong stellar magnetic fields

S.N. Chen, K. Burdonov, W. Yao et al. (+10 more)

Solar coronal mass ejections (CME) are routinely observed, but as of yet there exist few convincing detections of stellar CMEs. A reason for this could be the stronger magnetic fields of these stars, compared to that of our Sun, would prevent CME to form and escape. Here we combined astrophysical simulations, measurements of scaled high-energy laser-driven plasma flows, and 3D magneto-hydrodynamic modeling to test this hypothesis. Simulations show that in a 100 G stellar dipole field, low-plasma beta CMEs become magnetically confined. In the laboratory, a laser-produced plasma stream scaled to stellar CME conditions propagates freely at low applied magnetic fields (approximately 30 G stellar equivalent) but becomes unstable and halts entirely when the field is increased to 3e5 G (i.e., a 100 G equivalent). Numerical simulations suggest that the sudden disruption of the flow is induced by a kink instability. These results provide the first laboratory-scale evidence that strong stellar magnetic fields can fully suppress CME propagation, offering a physical explanation for their lack in stellar observations and highlighting the role of magnetic confinement in stellar evolution and exoplanet space weather.
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All authors S.N. Chen, K. Burdonov, W. Yao, J. D. Alvarado-Gómez, C. Argiroffi, J. Béard, S. Bolanõs, R. Bonito, A. Ciardi, O. Cohen, J. J. Drake, S. Orlando, J. Fuchs

Optics

High-yield fabrication of micromirror templates via feedback-controlled laser ablation

Daniel Allepuz-Requena, Jonas Schou Neergard-Nielsen, Alexander Huck et al. (+1 more)

We present a high-yield method for fabricating concave micromirror templates in silica using feedback-controlled CO2 laser ablation with precise in situ positioning. Real-time monitoring of the white-light emission generated during ablation is used to terminate laser exposure, thereby reducing shot-to-shot variability in mirror depth and radius of curvature. To ensure reproducible single-shot processing across different substrates, the sample position relative to the laser focus is calibrated using an in situ phase-scanning interferometric microscope integrated into the fabrication workflow. The method enables reliable fabrication of shallow mirror templates with tunable radii of curvature spanning from approximately 20$\mathrm{\mu m}$ to several hundred micrometers, with relative geometric variances as low as 3%. The suitability of the fabricated mirrors for optical resonators is verified by realizing a compact plano-concave Fabry–Perot microcavity with a finesse of 37000 at telecom wavelengths. The setup provides a simple and automated route to reproducible micromirror fabrication for applications in cavity quantum electrodynamics and cavity optomechanics.
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All authors Daniel Allepuz-Requena, Jonas Schou Neergard-Nielsen, Alexander Huck, Ulrik Lund Andersen

Optics

Dual-Wavelength Cancellation of Dispersion-Induced Phase Noise in Opto-Terahertz Fiber Links

Brendan M. Heffernan, James Greenberg, William F. McGrew et al. (+1 more)

Stable dissemination of terahertz (THz) signals over long distances is important for next-generation synchronization networks, radio astronomy, and high-capacity wireless systems. Optical fiber provides a low-loss platform for coherent frequency transfer; however, when a THz carrier is encoded as the difference between two optical wavelengths, chromatic dispersion introduces differential phase noise that degrades spectral purity. Here, we demonstrate phase-coherent distribution of opto-THz carriers over 38 km of standard single-mode fiber using a dual-wavelength Brillouin laser (DWBL) combined with a dual-channel round-trip noise-cancellation architecture. By extracting the differential phase noise between the two optical lines via a dual-channel round-trip measurement, dispersion-mediated phase fluctuations are compensated, and the intrinsic stability of the source is effectively preserved at the remote end within the measurement sensitivity. Opto-THz carriers at 150, 300, and 600 GHz exhibit sub-femtosecond timing stability and fractional frequency instabilities below 1e-17 at 10,000 seconds of averaging.
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All authors Brendan M. Heffernan, James Greenberg, William F. McGrew, Antoine Rolland

Optics · Cross-listed from quant-ph

Quantum Noise Suppression Beyond the Standard Quantum Limit in a Hybrid Magnonic Optomechanical System

Alolika Roy and Amarendra K. Sarma

We theoretically study how quantum measurement noise can be engineered in a hybrid cavitymagnomechanical platform for precision force sensing. The proposed configuration consists of a driven optomechanical cavity, with a movable mirror on one side plus a fixed semi-transparent mirror on the other side, coupled to a magnon mode, with an OPA placed inside the cavity. We show that the magnon mediated dynamics reshapes the added-noise spectrum leading to improved sensitivity compared to a conventional optomechanical sensor. In particular, by satisfying the coherent quantum noise cancellation (CQNC) criterion, radiation-pressure back-action can be fully suppressed. In addition, a larger OPA pump gain permits operation beyond the standard quantum limit at substantially reduced laser power, thereby mitigating power-related constraints without sacrificing performance. These combined advantages provide a practical pathway to below-SQL weak force detection and can outperform existing approaches based on squeezing in magnomechanics.
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Chemical Physics

Spin-cavity interactions in relativistic Jahn-Teller systems under strong light-matter coupling

Eric W. Fischer and Michael Roemelt

We extend our recent work on the cavity-modified spin Zeeman effect of an effective spin-1/2-system[J. Chem. Phys. 163, 174307 (2025)] to a relativistic Jahn-Teller scenario under strong light-matter coupling. Here, the effective spin-1/2-system is realized via a single electron or a single hole in a doubly-degenerate molecular orbital system of trigonal symmetric transition metal complexes. Both single-particle and single-hole systems are subject to both vibronic and spin-orbit coupling (SOC) augmented by interactions with a quantized cavity field via the cavity Zeeman interaction. Methodologically, we combine the relativistic $E\times e$-Jahn-Teller model with a recently introduced effective Hamiltonian formalism based on quasi-degenerate perturbation theory, which treats the cavity-spin interaction in leading order beyond the dipole approximation. We derive analytic expressions for Kramers pair energies in weak and strong SOC regimes as well as related cavity-modified effective electronic g-factors. We find cavity-induced modifications of the electronic g-factor to become relevant in the weak SOC regime for both single-particle and single-hole systems while being effectively quenched under strong SOC. Alternating signs of the cavity-Zeeman correction render single-particle and single-hole scenarios distinct in their response to the cavity field from a g-factor perspective.
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Chemical Physics

Geminal wavefunction models in chemistry

Pratiksha Gaikwad, Krisztina Zsigmond and Ramon Alain Miranda-Quintana

Geminal wavefunctions, introduced in the late 1950s, have long been recognized for their ability to compactly capture strong electron correlation. Despite their promise, they were historically overshadowed by more computationally efficient methods. Advances in both computational resources and theoretical frameworks have renewed interest in geminal-based approaches, particularly as researchers seek accurate yet tractable wavefunctions for complex electronic systems. Recent developments highlight their versatility: from serving as efficient starting points for correlated wavefunctions, to hybrid formulations that blend geminal concepts with coupled-cluster theory, to emerging applications in quantum algorithms where orbital-pairing provides a natural structure. In this mini-review, we summarize key advances in geminal wavefunction theory, with a focus on their modern resurgence, new methodological innovations, and potential directions for electronic structure theory and quantum computation.
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Medical Physics

Prompt Gamma Timing for range verification with carbon ion irradiation: first experimental measurements and comparison with Geant4 Monte Carlo simulations

Iram Barbaro Rivas Ortiz, Sahar Ranjbar, Piergiorgio Cerello et al. (+14 more)

Prompt Gamma Timing (PGT) is a promising technique for in vivo range verification in particle therapy, exploiting the time-of-flight between primary particles and prompt gamma rays emitted by nuclear interactions. PGT distribution is highly sensitive to beam energy and target density, which, under controlled detector positioning, enables real-time monitoring of particle range, detection of morphological changes, and support for adaptive treatment strategies. This study investigates for the first time the application of PGT in carbon ion therapy. Measurements were performed using a dedicated detection system composed of a silicon strip sensor for primary ion timing and a LaBr3(Ce) read out by a SiPM for secondary radiation. Carbon ion beams with energies of 166.41, 268.86, and 398.84 MeV/u irradiated a homogeneous 30.0 cm PMMA target at CNAO. The secondary radiation detector was positioned at four off-beam positions to assess the robustness of the PGT technique. Simulations based on Geant4 were conducted for all configurations to evaluate agreement and predictive capability. A bin-by-bin comparison of experimental and simulated PGT intensities demonstrated strong agreement within the 95% confidence interval, with no incompatible bins at 166.41 MeV/u, at most 1% at 268.86 MeV/u, and up to 8% at 398.84 MeV/u, depending on detector position. Photons were identified as the dominant contribution to the detected signals, particularly for detector positions upstream with respect to the primary particle beam, minimizing signal contamination from neutrons and charged fragments. The validated experimental-simulation framework confirms the capability of the proposed PGT system to resolve energy-dependent differences and highlights its potential for detecting clinically relevant changes in the particle beam range, supporting further development toward real-time monitoring in carbon ion therapy.
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All authors Iram Barbaro Rivas Ortiz, Sahar Ranjbar, Piergiorgio Cerello, Emanuele Maria Data, Mohammad Fadavi Mazinani, Miguel David Fernandez Moreira, Veronica Ferrero, Simona Giordanengo, Felix Mas Milian, Diango Manuel Montalvan Olivares, Francesco Pennazio, Marco Pullia, Roberto Sacchi, Roberto Cirio, Simone Savazzi, Anna Vignati, Elisa Fiorina

Chemical Physics · Cross-listed from cs.LG

Tabular foundation models for in-context prediction of molecular properties

Karim K. Ben Hicham, Jan G. Rittig, Martin Grohe et al. (+1 more)

Accurate molecular property prediction is central to drug discovery, catalysis, and process design, yet real-world applications are often limited by small datasets. Molecular foundation models provide a promising direction by learning transferable molecular representations; however, they typically involve task-specific fine-tuning, require machine learning expertise, and often fail to outperform classical baselines. Tabular foundation models (TFMs) offer a fundamentally different paradigm: they perform predictions through in-context learning, enabling inference without task-specific training. Here, we evaluate TFMs in the low- to medium-data regime across both standardized pharmaceutical benchmarks and chemical engineering datasets. We evaluate both frozen molecular foundation model representations, as well as classical descriptors and fingerprints. Across the benchmarks, the approach shows excellent predictive performance while reducing computational cost, compared to fine-tuning, with these advantages also transferring to practical engineering data settings. In particular, combining TFMs with CheMeleon embeddings yields up to 100% win rates on 30 MoleculeACE tasks, while compact RDKit2d and Mordred descriptors provide strong descriptor-based alternatives. Molecular representation emerges as a key determinant in TFM performance, with molecular foundation model embeddings and 2D descriptor sets both providing substantial gains over classic molecular fingerprints on many tasks. These results suggest that in-context learning with TFMs provides a highly accurate and cost-efficient alternative for property prediction in practical applications.
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All authors Karim K. Ben Hicham, Jan G. Rittig, Martin Grohe, Alexander Mitsos

Chemical Physics · Cross-listed from quant-ph

Entanglement and photoelectron holography in dissociative photoionization: molecular quantum eraser

Sebastian Hell, Paul Winter, Martin Gärttner et al. (+6 more)

In a double-slit experiment with a bipartite system, the visibility of interference fringes depends on the availability of which-way information. Here, we report a Bell-like state of photoelectron and residual ion in the multiphoton dissociative ionization of the D$_2$ molecule. Evidence for entanglement is provided by the correlated emission directions of photoelectron and ion, which is observed using a COLTRIMS reaction microscope. In the presence of this correlation, the holographic interference fringes contained in the photoelectron momentum distributions are suppressed, indicating the existence of which-way information. The interference pattern persists when a single ionic state is populated and thus no which-way information is available. The experimental observations and conclusions are supported by the numerical solution of the electronic-nuclear time-dependent Schrödinger equation. Our work demonstrates that coincidence spectroscopy of ions and electrons is a powerful method for studying fundamental concepts of quantum information science within the context of ultrafast light-matter interactions.
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All authors Sebastian Hell, Paul Winter, Martin Gärttner, Julian Späthe, Saurabh Mhatre, Dejan B. Milošević, Gerhard G. Paulus, Manfred Lein, Matthias Kübel

Chemical Physics · Cross-listed from astro-ph.EP

Machine learning isotope shifts in molecular energy levels

Marco G. Barnfield, Oleg L. Polyansky, Sergei N. Yurchenko et al. (+1 more)

Recent advances in the use of High-Resolution Cross-Correlation Spectroscopy (HRCCS) to detect molecular species in exoplanet atmospheres, presents a new challenge for the accuracy of reference spectroscopic line lists. While parent isotopologues of key atmospheric tracers are often well-characterized, minor isotopologues, crucial for diagnosing planetary formation histories and evolution, suffer from a scarcity of experimental data, often leading to reliance on less accurate theoretical predictions. In this work, a comprehensive machine learning framework is designed to mitigate these inaccuracies by modelling the residual errors of the isotopologue extrapolation (IE) method used within the ExoMol project. A fully connected neural network architecture for carbon dioxide (CO$_2$) is shown to predict energy corrections with high fidelity, reducing the mean absolute error (MAE) relative to the original IE approach for more than 87% of the levels when benchmarked against empirical (\Marvel) energies. Furthermore, development of a novel hybrid, molecule-aware transfer learning architecture is presented that successfully propagates correction patterns from the data-rich CO$_2$ system to the data-poor carbon monoxide (CO) system. This transfer learning approach yields MAE improvements in over 93% of CO samples, demonstrating that physical correction factors related to isotopic substitution can be generalized across chemically related molecular systems. Updated and improved line lists are presented for 11 CO$_2$ isotopologues and energy levels for excited states of CO isotopologues are predicted. The methodology establishes a scalable, data-driven paradigm for refining molecular line lists, helping to bridge the gap between theoretical calculations and experimental precision.
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All authors Marco G. Barnfield, Oleg L. Polyansky, Sergei N. Yurchenko, Jonathan Tennyson

Biological Physics · Cross-listed from q-bio.PE

Phase transitions in microbial lineage trees

Kaan Öcal, Syrine Ghrabli and Michael P.H. Stumpf

Microbial populations exhibit high cell-to-cell variability, which fundamentally shapes population behavior. A striking consequence is the existence of phase transitions, where small genetic or environmental changes trigger abrupt shifts in population dynamics. While biological phase transitions have often been proposed, connecting observed behavior to the underlying physics has remained challenging. We combine population genetics with statistical physics to show how phase transitions arise naturally in microbial populations. We highlight the existence of a first-order transition in a model of bacterial plasmid engineering and find a strict lower bound on the number of plasmids that can be stably maintained in a population.
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Accelerator Physics

Controlling external injection in laser-plasma accelerators with terahertz frequency bunch manipulation

Aras Amini, Lewis R. Reid, James K. Jones et al. (+6 more)

Laser-plasma wakefield acceleration (LWFA) offers ultrahigh accelerating gradients in compact setups, but the complex non-linear nature of the process makes it challenging to generate high-quality beams. Injection of electron bunches from an external source into a plasma accelerator provides a promising route to improved performance; however, electron bunches from conventional radio-frequency (RF)-based injectors suffer from non-linear compression and laser-beam asynchrony, leading to energy jitter and emittance growth. We present a fundamental concept of terahertz-controlled electron bunches for external injection into LWFA. This terahertz-frequency approach provides temporal locking between the electron beam and the drive laser, and enables the compression of high-quality beams to sub-10-fs durations before injection into the LWFA. Numerical simulations demonstrate that GeV-scale acceleration with excellent beam quality and stability – energy jitter and energy spread around 0.2% – can be achieved using this method. This concept opens new opportunities for stable, multi-stage laser-driven accelerators and supports the development of next-generation applications such as free-electron lasers (FELs).
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All authors Aras Amini, Lewis R. Reid, James K. Jones, Morgan T. Hibberd, Laura Corner, Darren M. Graham, Steven P. Jamison, Graeme Burt, Robert B. Appleby

Fluid Dynamics

Implicit Velocity Correction Schemes for Scale-Resolving Simulations of Incompressible Flow: Stability, Accuracy, and Performance

Henrik Wüstenberg, Alexandra Liosi, Spencer J. Sherwin et al. (+2 more)

Scale-resolving simulations of high-Reynolds-number incompressible flow are often limited by the Courant–Friedrichs–Lewy (CFL) restriction of explicit time-stepping schemes, leading to small steps and long times-to-solution. We systematically compare two implicit formulations of the velocity correction scheme – a linear-implicit approach and a sub-stepping (semi-Lagrangian) method – with a standard semi-implicit formulation in a high-order spectral/hp element framework. The schemes are assessed in terms of stability limits, temporal accuracy, and computational performance for implicit large-eddy simulation of the Imperial Front Wing benchmark, a complex high Reynolds number geometry with curved surfaces that imposes strict CFL constraints. The sub-stepping scheme extends the stable time step size by a factor of 20, and the linear-implicit scheme by up to a factor of 100 when equal-order velocity and pressure spaces are used. While increasing the cost per time step, the linear-implicit scheme reduces the time-to-solution by up to a factor of 8.7 at this largest step, whereas the sub-stepping scheme reduces it by only 12%. With application targets of 1% for mean lift and 5% for mean drag, the fastest accepted linear-implicit case reduces time-to-solution by a factor of 1.53 at ten times the CFL-limited step. The main-plane separation bubble is already substantially shortened at this step, showing that force agreement can mask changes in transition-sensitive flow structure. The results quantify the trade-off between stability, accuracy, and computational cost for implicit velocity correction schemes on complex geometries and provide guidance for selecting time integration strategies in large-scale scale-resolving simulations.
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All authors Henrik Wüstenberg, Alexandra Liosi, Spencer J. Sherwin, Joaquim Peiró, David Moxey

Atmospheric and Oceanic Physics · Cross-listed from cond-mat.soft

Discharge at the Microscale: Using Optical Tweezers to Observe Muon-Induced Discharges of a Levitated Microparticle in Air

Andrea Stoellner, Isaac C.D. Lenton, Caroline Muller et al. (+1 more)

Electrical discharge at the smallest possible length and charge scales is not well understood. Using optical tweezers, we investigate spontaneous discharges of a single micron-scale particle levitated in air. These “microdischarges” have a typical size of $\sim$40 $|e|$, but can be as small as a few $|e|$ and as large as several hundred. The absence of a well-defined trigger charge and the weak dependence on particle size suggest events are not classical gaseous breakdown. Instead, we show that microdischarge events arise from the rapid capture of ions left in the tracks of nearby passing ionizing radiation. Our results highlight the role of natural ionizing radiation in initiating micron-scale discharges and provide a platform for studying discharge physics in electrode-free environments and at the smallest scales.
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All authors Andrea Stoellner, Isaac C.D. Lenton, Caroline Muller, Scott Waitukaitis

Data Analysis and Statistics · Cross-listed from cs.CV

Ranking XAI Methods for Head and Neck Cancer Outcome Prediction

Baoqiang Ma, Djennifer K. Madzia-Madzou, Rosa C.J. Kraaijveld et al. (+1 more)

For head and neck cancer (HNC) patients, prognostic outcome prediction can support personalized treatment strategy selection. Improving prediction performance of HNC outcomes has been extensively explored by using advanced artificial intelligence (AI) techniques on PET/CT data. However, the interpretability of AI remains a critical obstacle for its clinical adoption. Unlike previous HNC studies that empirically selected explainable AI (XAI) techniques, we are the first to comprehensively evaluate and rank 13 XAI methods across 24 metrics, covering faithfulness, robustness, complexity and plausibility. Experimental results on the multi-center HECKTOR challenge dataset show large variations across evaluation aspects among different XAI methods, with Integrated Gradients (IG) and DeepLIFT (DL) consistently obtained high rankings for faithfulness, complexity and plausibility. This work highlights the importance of comprehensive XAI method evaluation and can be extended to other medical imaging tasks.
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All authors Baoqiang Ma, Djennifer K. Madzia-Madzou, Rosa C.J. Kraaijveld, Jin Ouyang

Plasma Physics

The virial expansion of plasma properties: benchmarks for numerical results

Gerd Röpke

Expressions for the thermodynamic and transport properties of plasmas are derived from quantum statistics in the form of equilibrium correlation functions. These can be evaluated using analytical methods or numerical approaches such as DFT-MD or PIMC simulations. Virial expansions are obtained using the Green's function method. They provide benchmarks for numerical simulations and are useful in the low-density range. The results for the equation of state are discussed for the uniform electron gas and the hydrogen plasma. Transport properties such as the dielectric function are also of interest. Virial expansions are considered for the electrical direct current conductivity as a special case of the dielectric function. Examples are given and it is explained where further work is needed to obtain a consistent description of the properties of hot and dense plasmas.
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Chemical Physics

A Diagrammatic Route to Multi-Reference GW for Strongly Correlated Molecules

Yuqi Wang, Wei-Hai Fang and Zhendong Li

The GW approximation is a cornerstone of many-body perturbation theory for computing single-particle excitations, yet it can fail qualitatively in strongly correlated systems where the single-reference picture becomes inadequate. To overcome this limitation, we develop a diagrammatic route to multi-reference GW (MR-GW) from an interacting active-space reference, treating strong correlation nonperturbatively and the residual interaction through dynamical screening at the multi-reference random phase approximation level. Because the conventional diagrammatic self-energy expansion no longer applies, we define a practical one-shot MR-GW approximation within a generalized diagrammatic framework, recovering standard GW as a special case. Applications to prototypical correlated atoms and molecules show that the interacting active-space reference captures multiconfigurational satellite structures poorly described by single-reference GW, while dynamical screening generally improves the satellite energies as well as the leading ionization and electron-attachment energies. This work opens a diagrammatic route to Green's-function methods that combine nonperturbative strong correlation with dynamical screening.
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Geophysics · Cross-listed from cs.CV

Breakout-picker: Reducing false positives in deep learning-based borehole breakout characterization from acoustic image logs

Guangyu Wang, Xiaodong Ma and Xinming Wu

Borehole breakouts are stress-induced spalling on the borehole wall, which are identifiable in acoustic image logs as paired zones with near-symmetry azimuths, low acoustic amplitudes, and increased borehole radius. Accurate breakout characterization is crucial for in-situ stress analysis. In recent years, deep learning has been introduced to automate the time-consuming and labor-intensive breakout picking process. However, existing approaches often suffer from misclassification of non-breakout features, leading to high false positive rates. To address this limitation, this study develops a deep learning framework, termed Breakout-picker, with a specific focus on reducing false positives in automatic breakout characterization. Breakout-picker reduces false positives through two strategies. First, the training of Breakout-picker incorporates negative samples of non-breakout features, including natural fractures, keyseats, and logging artifacts. They share similar characteristics with breakouts, such as low acoustic amplitude or locally enlarged borehole radius. These negative training samples enables Breakout-picker to better discriminate true breakouts and similar non-breakout features. Second, candidate breakouts identified by Breakout-picker are further validated by azimuthal symmetry criteria, whereby detections that do not exhibit the near-symmetry characteristics of breakout azimuth are excluded. The performance of Breakout-picker is evaluated using three acoustic image log datasets from different regions. The results demonstrate that Breakout-picker outperforms other automatic methods with higher accuracy and substantially lower false positive rates. By reducing false positives, Breakout-picker enhances the reliability of automatic breakout characterization from acoustic image logs, which in turn benefits in-situ stress analysis based on borehole breakouts.
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Fluid Dynamics

Towards PR-DNS of scour around a wall-mounted cylinder in turbulent open channel flow

Leo Bürk, Artjom Hermann, Markus Weyrauch et al. (+1 more)

Particle-resolved direct numerical simulation (PR-DNS) is performed for turbulent open channel flow over a smooth horizontal wall with a vertical cylinder and a dilute set of mobile, heavy, spherical particles. At the chosen parameter point (which matches a previous study without a cylinder) the particles are mostly translating in the horizontal plane while remaining in contact with the wall. It is shown that the presence of the cylinder leads to the generation of intense vortical structures, enhanced turbulence intensity in the wake region, and to strong modifications of the local wall shear stress. These cylinder-induced perturbations have direct consequences for the average particle concentration: preferential accumulation/depletion in different parts of the wake region occurs, while the wall-normal transport of particles (against gravity) is significantly enhanced. A second simulation which adds roughness elements on the wall reveals an additional effect upon the wall-normal distribution of particles. It turns out that the configuration with wall-roughness and a wall-mounted cylinder features the largest fraction of entrained particles, even far from the wall.
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All authors Leo Bürk, Artjom Hermann, Markus Weyrauch, Markus Uhlmann

Chemical Physics

Reweighting Estimators for Density Response in Path Integral Monte Carlo: Applications to linear, nonlinear and cross-species density response

Pontus Svensson, Thomas Chuna, Jan Vorberger et al. (+5 more)

We present density response estimators for Monte Carlo simulations that are based on a reweighting procedure, where the samples of an unperturbed system are used to estimate the properties of a system perturbed by an external harmonic potential. This allows the linear and nonlinear static density response to be estimated purely from simulations of the unperturbed system. The method is demonstrated for the uniform electron gas under warm dense matter and strongly coupled conditions using ab initio path integral Monte Carlo simulations. The performance of the method with respect to the number of particles and the number of imaginary time slices is investigated. The scheme is generalised to consider multiple external perturbations, acting on different species and with different wavenumbers, giving one access to additional cross-species density response functions and the complete quadratic response function resolved for both wave number arguments through mode coupling. The flexibility of the methodology opens the possibility to investigate numerous new density response properties to further advance our understanding of interacting quantum many-body systems across a broad range of applications.
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All authors Pontus Svensson, Thomas Chuna, Jan Vorberger, Zhandos A. Moldabekov, Paul Hamann, Sebastian Schwalbe, Panagiotis Tolias, Tobias Dornheim

General Physics

Fluctuations in Aharonov-Bohm Electrodynamics

F. Minotti and G. Modanese

We consider the application of the Fluctuation Dissipation Theorem (FDT) to the electrodynamics of Aharonov-Bohm (ABE), which differs from Maxwell's in that it allows for local non-conservation of charge. For the case of a system of non-conserved charges at thermal equilibrium we obtain the same spectral distribution of energy of the electromagnetic field as in Maxwell electrodynamics. However, the electric field contribution to that energy doubles that in Maxwell case, while the magnetic contribution is the same as in Maxwell theory, the electric excess energy is compensated by a negative contribution arising form the Aharonov-Bohm (AB) scalar field. For a conductor with local non-conservation of charge described by the $\gamma$ model, we derive the spectrum of current correlation at first order in $\gamma$, which results in a violet noise contribution added to the classical Johnson-Nyquist white noise result for the voltage fluctuations in a conductor.
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Instrumentation and Detectors

Electroluminescence Yield Measurements in Xenon Gas with the NEXT-DEMO++ Detector

NEXT Collaboration: J. Renner, J.D. Villamil, N. López-March et al. (+110 more)

The NEXT-DEMO++ detector, a high-pressure xenon gas time projection chamber serving as a prototype for the NEXT-100 experiment, was used to measure the electroluminescence (EL) yield as a function of reduced electric field ($E/p$) across pressures from 2.0 to 9.4 bar, utilizing the 41.5 keV de-excitation peak of $^{83m}$Kr. These measurements were made to examine the pressure dependence of the slope of the reduced EL yield $Y/p$, which has shown inconsistencies in the literature. The reduced yield was fitted with a linear model, revealing a modest ($\sim$5%) change in slope, beginning around 5 bar and increasing with pressure up to 9.4 bar.
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All authors NEXT Collaboration: J. Renner, J.D. Villamil, N. López-March, K. Mistry, P. Novella, A. Simón, V. Álvarez, J.M. Benlloch-Rodríguez, M. Cid, C. Cortes-Parra, R. Esteve, F. Kellerer, J. Martín-Albo, A. Martínez, G. Martínez-Lema, M. Martínez-Vara, M. Querol, P. Saharia, M. Sorel, S. Teruel-Pardo, H. Almazán, L. Arazi, I.J. Arnquist, F. Auria-Luna, S. Ayet, Y. Ayyad, C.D.R. Azevedo, F. Ballester, J.E. Barcelon, M. del Barrio-Torregrosa, F.I.G.M. Borges, A. Brodoline, N. Byrnes, A. Castillo, E. Church, X. Cid, C.A.N. Conde, F.P. Cossío, R. Coupe, E. Dey, P. Dietz, C. Echeverria, M. Elorza, R. Felkai, L.M.P. Fernandes, P. Ferrario, P. Ferrero Mancheño, F.W. Foss, Z. Freixa, J. García-Barrena, J.J. Gómez-Cadenas, J.W.R. Grocott, R. Guenette, J. Hauptman, C.A.O. Henriques, J.A. Hernando Morata, P. Herrero-Gómez, V. Herrero, C. Hervés Carrete, Y. Ifergan, A.F.B. Isabel, B.J.P. Jones, L. Larizgoitia, A. Larumbe, P. Lebrun, F. Lopez, R. Madigan, R.D.P. Mano, A. Marauri, A.P. Marques, R.L. Miller, J. Molina-Canteras, F. Monrabal, C.M.B. Monteiro, F.J. Mora, K.E. Navarro, D.R. Nygren, E. Oblak, I. Osborne, J. Palacio, B. Palmeiro, A. Para, I. Parmaksiz, A. Pazos, J. Pelegrin, M. Pérez Maneiro, I. Rivilla, C. Rogero, L. Rogers, B. Romeo, C. Romo-Luque, E. Ruiz-Chóliz, F.P. Santos, J.M.F. dos Santos, M. Seemann, I. Shomroni, A.L.M. Silva, P.A.O.C. Silva, S.R. Soleti, J. Soto-Oton, J.M.R. Teixeira, J.F. Toledo, C. Tonnelé, S. Torelli, J. Torrent, A. Trettin, P.R.G. Valle, M. Vanga, P. Vázquez Cabaleiro, J.F.C.A. Veloso, L.M. Villar Padruno, J. Waiton, A. Yubero-Navarro

Chemical Physics

Host-guest co-amorphous structure revealed by the suppression of the first sharp diffraction peak in isotactic poly(4-methyl-1-pentene)

Tomoki Ogihara, Yusuke Hiejima and Ayano Chiba

While host-guest co-crystals are well established, and co-amorphous solids are recognized in materials science, the concept of a host-guest co-amorphous structure remains largely unexplored. A potential analogue is seen in SiO2 glass under high pressure with helium as a pressure medium; the drop in compressibility in this system is ascribed to helium atoms occupying internal voids. In this study, we investigated a semicrystalline polymer, isotactic poly(4-methyl-pentene-1) (P4MP1), which shares key characteristics with SiO2 glass, particularly regarding the first sharp diffraction peak (FSDP). The FSDP in P4MP1 is attributed to internal voids, as evidenced by its suppression under pressure and recovery upon decompression for molten P4MP1. Notably, the response to helium as a pressure medium is also known to parallel the behavior observed in SiO2 glass. Here, we analyzed two-dimensional X-ray diffraction (2D-XRD) patterns of stretched P4MP1 and found a suppression of FSDP when P4MP1 is immersed in decane. The use of stretched samples enabled the clear isolation of the amorphous FSDP from overlapping crystalline diffractions. Our findings reveal the existence of a host-guest co-amorphous system at room temperature and atmospheric pressure, in which decane molecules occupy the amorphous host matrix of P4MP1. Unlike conventional co-amorphous mixtures, this structure is defined by the specific accommodation of guests within the host's inherent voids. Intriguingly, the signature of this structure in diffraction measurements, manifested as changes in the FSDP intensity ratio, may be regarded to parallel the variations in Bragg peak intensity ratios in host-guest co-crystals. Since selective sorption and guest exchange are well-known in co-crystals, hosts capable of forming co-amorphous structures will be promising materials for molecular sieves, or more generally, liquid-phase molecular sieves.
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