Papers

Stochastic transport describes physical systems in which an initially structured distribution spreads under unresolved forcing, scattering, or heterogeneous media. Useful surrogates for such systems should be probabilistic, time-resolved, and able to represent non-Gaussian distributional structure. Generative diffusion models, which corrupt data with Gaussian noise and learn a reverse flow back to structured states, have these properties. Their noise schedules, however, are usually chosen heuristically: image and audio generation—the canonical use cases—provide no physical clock. In transport, by contrast, the variance, or mean-square displacement, is often known from macroscopic theory or empirical scaling even when the full distribution is not. Here we prescribe the forward noising rate as the time derivative of this variance, turning generative time into a calibrated transport clock. The variance path is enforced by construction, while the learned score field represents how non-Gaussian structure inherited from entrance data is smoothed along that path, requiring no intermediate-time physical transport data. For ballistic-to-diffusive transport in turbulent plasmas, the surrogate matches test-particle distributions, reproduces the laboratory-measured variance scale, and tracks the simulated kurtosis evolution without schedule tuning, enabling calibrated emulation and likelihood-based inference.

Multidimensional optical microscopy - extracting 3D location, orientation, and spectral information from nanoscale emitters - is key to modern nanoscience. However, this multidimensional capability requires complex instrumental setups, demanding exceptional stability and specialized expertise in optics. Here, we overcome these barriers by introducing Double Refraction Microscopy (DRM), a passive imaging method providing a straightforward pathway to multidimensional super-resolution imaging. Based on bifocal imaging via a birefringent microscope slide, DRM splits nanoprobe light into a characteristic double image encoding 3D location, orientation, and spectral signature, while requiring zero hardware modifications to standard wide-field microscopes. To showcase its robustness, we implement DRM across three distinct slides of varying materials and thicknesses, calibrating 3D localization with 450-nm nanoparticles and demonstrating high orientation sensitivity using polarization-controlled emitters. Furthermore, we confirm spectral readout using a pinhole array acting as a grid of point emitters back-illuminated at various wavelengths to generate distinct spectral signatures. Finally, we showcase practical utility by performing a two-colour 3D localization measurement within a $10\,\mu\text{m}$ gap, utilizing the single optical pathway of a standard epi-fluorescence microscope. Ultimately, DRM provides the missing optical hardware simplicity to complement established computational tools, promising to transfer advanced super-resolution capabilities from specialized facilities to every laboratory bench.

Fluid–structure interaction (FSI) experiments are typically built around mechanical dynamics and constraints imposed by the physical apparatus, so changing mass, stiffness, damping, or allowable motion often requires hardware reconfiguration. Here we present a reconfigurable cyber-physical framework in which these properties are instead assigned through software-defined dynamics. The system provides three translational and one rotational degree of freedom, each independently configurable as prescribed, load-responsive, or locked, with operating roles that can also be reassigned during a running experiment. Measured forces and torques are incorporated into real-time virtual dynamic models, while a common supervisory architecture coordinates multi-axis motion, mode switching, synchronized data acquisition, and diagnostic positioning. The prescribed-motion pathway is validated using a pitching hydrofoil by comparison with published thrust and power scaling trends, while the load-responsive pathway is evaluated using an active-heave/passive-pitch benchmark that reproduces the expected frequency-dependent resonant response over the tested conditions. The same platform is then reconfigured for intra-cycle active–passive pitching, coordinated vertical-axis turbine-surrogate motion, force-driven passive surge, and automated multilayer stereoscopic particle image velocimetry. These results demonstrate that distinct FSI boundary conditions and measurement requirements can be implemented within a common motion, sensing, and control architecture. By treating mechanical roles and constraints as software-defined experimental variables, the framework provides a reusable basis for reconfigurable FSI experiments without redesigning the underlying platform for each application.

We present the design, fabrication, and characterization of a monolithic, segmented, three-dimensional linear Paul ion trap for quantum science applications. The trap is fabricated from a single fused-silica block using selective laser-induced etching (SLE) and is subsequently metallized, forming electrodes isolated by self-shadowing trench structures without the need for layer alignment or external shadow masks. The segmented electrodes allow for shaping of the axial potential, enabling the creation of anharmonic potential wells, such as those required for equidistant ion strings. In addition, they enable shuttling and splitting of ion chains. We discuss key design choices and SLE-imposed constraints on achievable feature sizes, and evaluate electron-beam evaporation and magnetron sputtering as metallization approaches. Across two independent experimental setups, we demonstrate stable trapping and control of linear chains of up to 33 $^{40}$Ca$^+$ ions, including approximately equally spaced configurations. The measured secular frequencies in both traps agree with boundary-element simulations at the percent level, with residual deviations attributed to stray electric fields in the presence of anharmonic axial potentials, rather than fabrication imperfections. We measure axial micromotion field strengths on the order of 100 V/m along the trap axis, in approximate agreement with simulations. For radial mode frequencies near 2 MHz and an ion-electrode distance of 300 um, we measure heating rates of the order of 10 quanta/s in all but one motional mode, which is elevated by a technical noise source. The presented trap design is thus suitable for a wide range of quantum science applications and demonstrates the viability of SLE for the fabrication of finely segmented, monolithic, three-dimensional ion traps.

Tornadoes are documented on every inhabited continent, yet the environmental conditions used to anticipate them were developed and validated overwhelmingly on mid-latitude records, leaving tropical regimes largely unexamined. Here, we collected 1,186 combined tornado and waterspout reports in the Philippines spanning the early 1900s to 2025 and paired each with an ERA5 proximity sounding to construct the first baseline climatology and environmental characterization of these events in the archipelago. Activity concentrates in three corridors, mostly flanked by mountain ranges, one in each major island group, and is sharply phased within a May-October window that closely tracks the annual cycle of thunderstorm frequency, peaking in August and lagging into October for waterspouts alongside the tropical cyclone season. These events cluster in the mid-to-late afternoon, consistent with a daytime heating regime rather than nocturnal convection. The environments are thermodynamically permissive but kinematically shallow, with convective available potential energy (CAPE) exceeding typical Great Plains values, while the 0-6 km bulk wind difference (BWD; DLS) remains weak at $\sim$10-14 kt, departing from the mid-latitude covariance in which instability and shear increase together. Although streamwise vorticity is modest in magnitude, nearly all discriminating variance resides in the lowest kilometer, where 68-79% of near-surface horizontal vorticity is streamwise, reaching $>$0.005 s$^{-1}$ and 96% streamwiseness in the most organized profiles, and the hodographs retain low-level curvature. Consequently, composite indices remain low even as tornadoes and waterspouts recur. Mid-latitude-calibrated parameters can therefore misdiagnose tropical-maritime regimes, and recalibration toward shallow-layer, orientation-aware kinematic discriminators may recover the diagnostic signal.

Floor response spectra (FRS) are essential tools for the design of non-structural elements (such as equipment or components). Given the various physical phenomena influencing FRS, high-fidelity (HF) mechanical models of the primary structure may be required to estimate them. Since numerical simulations based on such models are generally computationally expensive, this paper proposes using a multi-fidelity Monte Carlo (MFMC) approach for the efficient estimation of FRS. The method relies on using observations from a fast low-fidelity (LF) model as control variables. If the absolute value of the correlation between LF and HF samples is close to 1, this approach reduces both variance and estimation error compared to a standard Monte Carlo estimate based solely on HF data samples. Through a case study involving the reactor building of the Kashiwazaki-Kariwa nuclear power plant, we demonstrate the suitability of this method for FRS estimation. It effectively reduces variance and estimation error, even when using a LF model as simple as a single-degree-of-freedom system. We also show that the method accounts for modeling uncertainties while maintaining comparable performance. Its ease of use makes it a valuable tool for practitioners.

Relative periodic orbits (RPOs) are solutions of the three-body problem that are periodic in a uniformly rotating reference frame and, in general, quasi-periodic in inertial coordinates. We present a numerical procedure for computing and continuing one-parameter families of RPOs of the planar Newtonian three-body problem. The method exploits consecutive syzygies, understood here as configurations in which the three bodies are aligned and their velocities satisfy the corresponding symmetry conditions. Matching the positions and momenta at two consecutive alignments reduces the computation of RPOs to a low-dimensional nonlinear problem. Its solutions are then numerically continued, and linear stability is determined from the nontrivial eigenvalues of the rotated monodromy matrix after removing the neutral directions associated with conserved quantities and continuous symmetries. The procedure is applied to several mass distributions and initial configurations, producing families of Poincaré, Hill, and binary-type solutions. These families exhibit transitions from nearly circular to highly eccentric motion, changes of stability near resonances and turning points, and absolute periodic solutions when the rotation angle is a rational multiple of 2{\pi}. In the Hill families, the continuation connects satellite configurations with circumstellar motion as the smallest body loses its gravitational binding to the intermediate body. Circumbinary and circumstellar configurations are also obtained in the binary regime. The results illustrate the dynamical diversity of RPOs and provide coherent three-body motions that can be used as prescribed trajectories in restricted four-body models.

Odd viscosity is a nondissipative component of the viscosity tensor that arises in fluids with broken time-reversal symmetry. Despite conserving energy, we show that odd viscosity can qualitatively alter hydrodynamic stability by generating exponentially growing modes that are absent in conventional fluids. For plane Poiseuille flow, we derive the odd-viscous generalization of the Orr–Sommerfeld–Squire equations and find a new instability that first emerges for spanwise perturbations and extends to oblique modes through the amplification of odd-viscous forces in critical layers. The instability originates from the non-normal dynamics of shear flows: conventional fluids support transiently growing disturbances through the lift-up mechanism, while odd viscosity provides a feedback between wall-normal velocity and vorticity that converts this transient growth into a self-sustaining exponentially growing mode. More generally, we show that an energy-conserving perturbation can destabilize a non-normal dynamical system only when the unperturbed system supports transient growth. Our results establish a direct connection between transient growth, non-normality, and instability induced by nondissipative forces, with implications extending beyond odd-viscous hydrodynamics.

We study the inverse energy cascade of two-dimensional turbulence by means of high-resolution numerical simulations forced at intermediate wavenumbers. To clarify the role of vortices generated near the forcing scale, we decompose the vorticity and velocity fields into vortex and background components. Although the vortex component carries only a small fraction of the total energy, it has a clear effect on the energy spectrum and produces deviations from dimensional Kolmogorov scaling, which is realized by the background flow. We derive a generalized von Karman–Howarth balance for the decomposed fields and obtain a relation involving the third-order correlation between vortex and background velocity increments. The simulations support this prediction, which we interpret as a constant inertial-range flux associated with vortex-background correlations.

A central question in physical inference is whether strongly constrained dynamical systems can realize accurate input–output maps through their own finite-time evolution. We study this question in Kuramoto phase networks, whose deterministic dynamics form an input-conditioned gradient flow and whose predictions are read directly from output oscillators. As a constructive training approach, we develop a two-stage teacher–student procedure. A neural teacher is first converted into an explicit phase trajectory whose terminal oscillator activations reproduce the teacher outputs, and the Kuramoto parameters are trained by matching the student vector field along this prescribed path. Because accurate teacher-forced path matching does not ensure accurate autonomous inference, we then differentiate through the autonomous finite-time rollout and directly align its terminal output with the neural target. The resulting oscillator system, with $74$ oscillators, reaches mean test accuracies of $96.711\%$ on MNIST and $86.399\%$ on Fashion-MNIST. This capability persists across neural-teacher architectures, matched system sizes, thermal perturbations, and integration-grid refinement. Together, these results provide a constructive demonstration that a strongly constrained, small-sized Kuramoto gradient-flow system can be trained for high-accuracy finite-time inference through a direct oscillator readout.

High-purity germanium (HPGe) detectors with low capacitance, low electronic noise, and stable high-voltage operation are important for high-resolution gamma-ray spectroscopy and rare-event searches. We report the fabrication and characterization of two compact p-type inverted coaxial point-contact (ICPC) HPGe detectors, AK01 and AK02, produced from crystals grown at the University of South Dakota. Both devices use lithium-diffused $n^{+}$ outer contacts together with amorphous-Ge/Al point-contact electrodes. The principal advance is the implementation of this hybrid contact process on two independently fabricated USD-grown ICPC prototypes and the demonstration of stable electrical and spectroscopic operation. Both detectors exhibited picoampere-level leakage currents, operational depletion-voltage ranges of approximately 200–250~V (AK01) and 240–260~V (AK02), and estimated effective plateau capacitances of approximately 0.84 and 0.87~pF, respectively. Measurements with a $^{137}$Cs source yielded archived full-energy-peak FWHM values of 1.71 and 1.62~keV near 662~keV for AK01 and AK02, while AK02 yielded 1.04~keV FWHM at 59.5~keV with $^{241}$Am. Electric-field calculations reproduce the expected ICPC field configuration for the measured detector geometry. A Geant4 model of AK02 is used as a qualitative response study; its 0.8-mm Li-diffused inactive layer is an illustrative model assumption rather than a measured thickness, and its Gaussian broadening is constrained by the experimental resolution. The work therefore establishes the fabrication and operation of compact lithium-diffused ICPC prototypes while identifying quantitative inactive-layer characterization as an important next step.

Historically, retrieving rainfall data from satellite imagery has been the domain of space agencies. However, in recent years, the development of cheaper, more compact satellites (SmallSats) capable of detecting rainfall proxies has led to a significant increase in private-sector initiatives for satellite launch and surface precipitation products. This rapid growth has yet to be matched by data validation efforts. Consequently, the need for a robust tool to detect anomalies in near-real-time data before it is disseminated to the public has become critical. In this paper, we present the development of an anomaly-detection system to identify artifacts in global satellite-based rainfall products. The developed framework leverages pre-trained computer vision models and incorporates scarce human-labeled data to detect specific anomalies. Our proposed anomaly detection strategy is tested on data from the Special Sensor Microwave Imager (SSMI) and the Special Sensor Microwave Imager/Sounder (SSMIS). Results demonstrate the efficacy of our approach at separating regular orbits from artifact-containing orbits for each satellite, with performance comparable to state-of-the-art in-place methods. Additionally, the framework offers explainability and the capacity for iterative refinement following false-positive or false-negative classifications.

We investigate the refractive index $n$ of LiF using DFT+G$_0$W$_0$+BSE, with ionic-temperature effects included through QMD. We calculate photon-energy dispersions $n(\omega)$ and $k(\omega)$ at ambient pressure and $n(\rho,T)$ at 532 and 1550 nm under shock compression, where $\rho$ and $T$ vary together. Quasiparticle band structures at ambient and compressed conditions and the ambient-pressure orbital-projected density of states connect the optical response to the electronic structure. At ambient pressure, G$_0$W$_0$ yields a quasiparticle gap of 14.25 eV, close to the experimental 14.2 eV, while BSE reproduces the main excitonic feature at 12.5 eV, close to the observed 12.6 eV. Quasiparticle and excitonic effects are thus essential for accurate optical dispersion; the hybrid HSE functional does not reproduce the optical spectra. Along the principal Hugoniot up to 140 GPa, $n(\rho)$ agrees closely with shock data at 1550 nm and acceptably at 532 nm, and agrees better overall than earlier first-principles calculations. Above approximately 110-120 GPa, QMD produces a downturn relative to cold $n(\rho)$ curves, suggesting that ionic dynamics may contribute to deviations from the linear $n$-$\rho$ Gladstone-Dale relation. QMD-sampling and finite-k-grid uncertainties are estimated, and transition-peak broadening is assessed using a recently proposed criterion. The gap increases under pressure, with a transition to a $\Gamma\to\mathrm L$ indirect gap near 50 GPa. An exploratory calculation at approximately 1400 GPa finds a gap of about 24 eV, disfavoring gap-closure metallization. Structural and elastic benchmarks of the underlying models are also provided.

The primary purpose of the parliamentary discussion is to present and debate legislative drafts. Mentions of other Members of the Parliament (MPs) and interruptions of them represent the structure of the political discourse. Name mentions can be automatically recognised in speech transcripts and linked to the relevant MPs. We construct networks of MPs based on name mentions in 96753 speeches delivered during the electoral terms 2015-2018 and 2019-2022 in the Finnish Parliament to study the structures of interaction within parliamentary discussion. The results show that the networks are not polarized, although there is slight bias towards mentioning one's own party members. Activity on the parliamentary floor, political seniority and minister status have a positive correlation with higher centrality scores of MPs. Our analysis is generalizable to different political arenas and is an interesting basis for comparison across regional assemblies or countries.

We investigate the feasibility of precision counting experiments based on laser-electron beam interactions to verify strong-field quantum electrodynamic effects, with particular emphasis on the stochastic nature of photon emission, photon polarization, and spin asymmetry. A precise Monte-Carlo model is developed using photon packets with multi-dimensional phase-space weighting, hierarchical-mesh cumulative distribution functions, and a variable time-step method. This model quantitatively reproduces the highest edge of the photon energy spectrum and the positron yield in the previous SLAC E-144 experiment. The quantized radiation back-reaction determines the highest edge tail and thus the positron yield for higher laser intensities. The spin asymmetry in photon emission and spin flip determines photon polarization in the high-energy tail, while that in pair production can be observed through the large-angle positron scattering. Our simulations predict that these effects depend on the combination of the electron-beam energy and the laser intensity, and that they could be verified in future ELI-NP experiments using sub-GeV electron beams and optical lasers with intensities ~10^22W/cm2.

Nonadiabatic coupled electron-nuclear dynamics upon electronic excitation underpin the microscopic mechanism and rational modulation of diverse photoinduced functional phenomena in materials, yet their direct first-principles simulations remain computationally demanding. Here we develop a framework for nonadiabatic excited-state machine-learning molecular dynamics (EMLMD) simulations, where the nonequilibrium electronic information upon photoexcitation such as electron temperature is rigorously calibrated from high-precision real-time time-dependent density functional theory (rt-TDDFT) benchmark simulations, enabling accurate reconstruction of excited-state potential energy surfaces (PES). This framework natively incorporates the excited-state electron-phonon couplings and intrinsically captures photoinduced phonon anharmonicity, both of which are missing in standard machine learning molecular dynamics, thus delivering first-principles-level accuracy for excited-state atomic evolutions. Large-scale EMLMD simulations resolve time- and momentum-resolved phonon dynamics in photoexcited materials, directly uncovering the competition between photogenerated coherent phonons and thermal phonons during photoinduced phase transition of bismuth. It also simultaneously resolves elusive atomic-scale microscopic dynamics and global structural rearrangement for selenium photoamorphization. Balancing high accuracy and efficiency, EMLMD offers a versatile paradigm to tackle key challenges in the study of complex excited-state molecular dynamics.

Experiments on a flexible plate horizontally submerged in a wave tank are reported in this paper. The plate is held at a fixed depth at its upstream end, while its downstream end is free to move. The wave field is measured using a synthetic Schlieren technique, giving access to an estimate of the fractions of the incoming wave energy that are transmitted and reflected after encountering the region where the plate is submerged. Part of the incoming wave energy is shown to be dissipated by the plate. Flow field measurements in a vertical plane parallel to the wave propagation are performed to examine the wave-plate interaction. A jet-like flow is produced at the free end of the plate, with strong vortex activity similar to that produced by a flapping fin. The kinetic energy present in this jet-like flow is computed from the velocity field measurements, and the external dissipation produced by jet creation is estimated. Results highlight the efficiency of flexible plates in reflecting and attenuating waves. This study also showcases a change in jet direction, in particular the observation of a jet going upward toward the free surface for certain frequencies. Such a configuration, could be of great interest for wave energy conversion applications, while preventing harmful phenomena such as seabed erosion.

Concept inventories are widely used in Physics Education Research to uncover student misconceptions and measure the effectiveness of instruction. Two questions in the widely used multiple-choice Force Concept Inventory concern a car that is pushing a truck, as the car is accelerating and then when a steady speed has been reached. We investigate the premise that correct answering of these questions is because of good conceptual understanding of Newton's Third Law, by analyzing responses to a modified inventory that randomly offers students multiple-choice or free-text versions of the questions and follows these with questions in which students select the physical principle(s) they used. The results from 674 attempts from students at six universities show a similar pattern of results for multiple-choice and free-text versions, also comparable with Force Concept Inventory results from one of the universities in the preceding five years, but with marked differences relative to early published Force Concept Inventory data. Free-text responses and the law-selection sub-questions can reveal more about conceptual understanding than can be seen in multiple-choice responses alone. For the accelerating system (Question 15), correct responses are usually attributed to Newton's Third Law and incorrect responses are usually attributed to Newton's Second Law. When speed is constant (Question 16), around 90% of responses are correct, but a significant number of these are attributed to Newton's First Law or the Superposition Principle rather than Newton's Third Law, especially pre-instruction. We conclude that students are confusing balanced forces on a single object moving at constant speed with the correct equal-and-opposite interaction pair between two objects, and correct responses to Question 16 may be concealing an underlying misconception.

Presented here is an exploratory conceptual framework with the aim of describing electromagnetic and thermal energy transport and transfer in collisionless plasmas in a coherent way, starting from an arrow-of-time perspective. That is, arguments about the transport of energy are fundamentally based on the idea that systems tend to fill the phase space available to them. First, we describe electric fields, magnetic fields, and plasma particles as interacting subsystems that are thermodynamically linked in specific ways. Second, we discuss the importance of the stochastic electric field in the transport of plasma particles down energy density gradients until the energy flux contributions from so-called electrothermodynamic (ETD) interactions become sufficiently uniform. Third, the logic of ETD transport is extended to a magnetized system invoking 2 types of magnetothermodyamic (MTD) transport: 1) transport of electromagnetic energy through stochastic Poynting flux and 2) plasma energy transport through stochastic drift energy fluxes associated with local ExB drift motion. The magnitudes of the ETD and MTD mechanisms are tied to local characteristic scales of the electric field fluctuations and critical scales are derived beyond which ETD mechanisms dominate MTD mechanisms. Finally, we discuss the interplay between electrothermodynamic and magnetothermodynamic equilibria (ETE and MTE), dynamics in the small critical scale (MTD) limit, and the potential relevance of this type of description to the problem of reconnection onset and scale coupling.

Gausslets are among the few electronic-structure bases that permit the four-index electron–electron interaction to be replaced by an accurate two-index integral diagonal approximation (IDA). Near a many-electron nucleus, however, the nuclear attraction and core-electron Hartree field are individually large and substantially cancel. Treating the first as a full finite-basis matrix while treating the second with IDA leaves an avoidable imbalance. We introduce reference-density Hartree screening: the Hartree field of a chosen reference density is represented accurately, and IDA is applied only to density fluctuations about it. Tests on He, Ne, atomic F, F$_2$, and Cr$_2$ show large reductions in direct Hartree errors, including transfer of fitted neutral-atom fields to molecules. For Cr$_2$, atomic-core screening prevents the spurious HF collapse found with the unscreened $q=5$ and $q=7$ Hamiltonians, whereas finite-reference matching without screening does not. Screening leaves exchange and residual correlation unchanged. We therefore also introduce a low-rank one-particle correction that uses an accurate conventional Gaussian-basis Hartree–Fock calculation to match either occupied-space exchange information or the complete occupied Fock vectors. In F$_2$ and Cr$_2$, $X_{\rm HF}$ reproduces the finite-reference energy and occupied Fock vectors to numerical precision and the selected states return after orbital perturbations. For Cr$_2$, the corrected $q=5$ basis uses one quarter as many functions as the $q=7$ control while retaining sub-mHa mean-field accuracy. Screening provides the physical improvement to the direct field; the state-specific correction then restores the remaining accuracy of the Gaussian-basis mean-field reference.

Numerical simulation of dynamic wetting processes remains challenging due to the multiscale feature of the moving contact line. This paper presents a finite element method for two- or three-dimensional dynamic wetting problems within the framework of the lubrication equation and the precursor film model. By reconstructing the disjoining pressure formulation, a mesoscopic precursor film model is implemented to enable a relatively thick precursor film to reproduce the intermediate-region interfacial behavior of a physically thin precursor film. The proposed model reduces the requirement for excessive spatial resolution near the contact line, thereby significantly reducing the computational cost while preserving the macroscopic flow dynamics. This method does not incorporate any moving boundary and easily handles topological changes. Its capability and accuracy are validated through various simulations, including the spreading, retraction, sliding, and coalescence of drops, as well as the breakup of liquid ridges. Numerical results (with the mesoscopic precursor film model adopted) show good agreement with the available exact solutions and asymptotic theories.

The chaotic dynamics of a large one-dimensional lattice of nonlinear maps with a spatial coupling of increasing extent is explored using the covariant Lyapunov vectors (CLVs). A theoretical approach is developed that predicts the spectral variation of the CLVs and the spectrum of Lyapunov exponents. The theoretical approach is independent of the details of the mapping function and requires only a description of the lattice coupling. The general structure of the spatial power spectrum of the CLVs is determined using only the eigenvectors of the coupling matrix. This yields a decomposition of the CLVs into two regimes. The first regime, corresponding to the largest Lyapunov exponents, contains highly entangled CLVs with significant contributions from large scale spatial structures and aligns with the sorted eigenvectors, which occur in pairs with wavenumbers that increase linearly with their index. The second regime contains significant mixing of length scales with increasing index. The index separating these two regimes is approximately equal to the fractal dimension of the dynamics.

The nature of turbulent energy cascade of simple two-dimensional fluid models of ion temperature gradient driven turbulence is studied in detail. Notably, it is observed that a minimal two-field model of toroidal ITG, behaves qualitatively differently with or without the diamagnetic nonlinearity. In its absence, the zonal flows always dominate and the system never reaches a high-transport state. In contrast, when this term is included, zonal flows dominate only near marginality, while away from it, an inverse cascade with high levels of transport is observed, requiring large-scale dissipation (hypoviscosity) to saturate and hyperviscosity to regularize small scale instability associated with this nonlinear term. However introducing such a term, together with the existence of the curvature term, breaks potential vorticity conservation, which is one of the key symmetries of drift-wave turbulence. This can be remedied by considering a more complete model that retains higher-order terms in the pressure equation. This form of the model, with four nonlinearities, conserves potential vorticity and behaves similarly to the original model, requiring hyperviscosity to saturate since the added nonlinearity generates small scale instability also for the pressure equation. To characterize the roles of potential vorticity conservation and higher-order terms in the pressure equation, the behavior of both the standard ITG system, and the potential vorticity conserving system, is studied by analyzing their spectra, turbulent cascades, and sensitivity to viscosity. Finally, the direction of turbulent cascade due to the different nonlinearities (i.e. the diamagnetic nonlinearity in particular) is investigated by examining their contributions to the spectral energy transfer and by considering the triadic instability assumption for each of these nonlinearities separately.

Hyperuniform materials occupy an intermediate regime between periodic order and conventional disorder, characterized by a suppression of long-wavelength density fluctuations, commonly quantified by the structure factor. This characterization, however, relies on the statistical properties of an extended configuration or supercell representation and does not directly describe the resonant response of a finite structure, as typically encountered in scattering experiments. Here, we introduce the quasi-normal-mode spectrum as a complementary framework for characterizing the wave properties of finite stealthy hyperuniform materials. We analyze the complex eigenfrequencies of both periodic and stealthy hyperuniform structures over a range of the stealthiness parameter ($\chi$), and investigate how the spatial organization of scatterers is encoded in both frequency and spatial profiles of their quasi-normal modes. We find systematic changes in the quasi-normal modes spectrum as the degree of hyperuniformity is varied, revealing signatures that are not captured solely by the structure factor. In particular, the evolution of the resonant states provides a direct connection between structural correlations and the scattering response of finite systems. Our results establish quasi-normal modes as a real-space and open-system characterization of hyperuniformity and provide a unified framework for comparing discrete heterogeneous materials from the perspective of their scattering and resonant dynamics.

Asymmetric cell division – in which a mother cell divides into two daughter cells of unequal size – is a fundamental problem in biology. It is believed that the asymmetry originates from the prior polarization of the mother cell. Here we show that division asymmetry can occur spontaneously even in unpolarized mother cells. Specifically, curvature-dependent active stresses in the cell cortex can lead to this symmetry breaking without any molecular polarity cue if the mother cell is confined within a restricted space. Either reducing the cell size or tightening mechanical confinement triggers the same spontaneous symmetry-breaking instability, in which the contractile ring slips off the equator to yield daughters of unequal volume. In the presence of a polarity cue, this instability cooperates with the cue to program the division asymmetry. The model prediction is compared with the imaging data of C. elegans embryogenesis, in which successive cell divisions in a confined eggshell lead to smaller and smaller cell sizes. The measured division asymmetry indeed increases as the cells shrink, and is further amplified when the embryo is mechanically compressed, both in agreement with the model prediction.

Advances in several physics domains open up novel paths to smaller scale, higher energy density opportunities to advance small systems for nuclear fusion. Here we survey both legacy and several novel “table-top” approaches which attract current interest. We furthermore address a few related practical and challenging nuclear science topics arising in the context of magnetic confinement and inertial confinement fusion. The contents emphasis includes: By example of solar fusion cycles we draw attention to aneutronic fusion reaction chains. Considering the natural isotopic abundances we assess more carefully the meaning of the term “limitless energy” in the context of actual fusion power realizations. We describe achievements in laser-driven proton-boron fusion, and extensions to a self-sustaining and nearly fully aneutronic proton-boron-nitride reaction cycle. We propose another aneutronic option, where the target is a mix of beryllium and light helium isotope; this 3-helium is arguably the most mentioned fusion component in this article. We look in depth at the plasmonic opto-electric field-enhancement for fusion, and at the particle (muon) catalyzed fusion option. We describe problems in harnessing the dt fusion for civilian use. We introduce space travel as forthcoming application of aneutronic fusion.

Achieving sub-cycle waveform control with attosecond-level precision while reaching shot-noise-limited amplitude stability in the mid-infrared spectral range remains a central challenge for ultrafast and precision optical science. Here, we demonstrate a fully stabilized, ultra-stable optical frequency comb (OFC) based on a Kerr-lens mode-locked Cr:ZnS laser operating at 2.3 $\mu$m. The oscillator delivers 40 fs pulses at a 25 MHz repetition rate, which are spectrally broadened to cover two octaves and compressed to a 1.4-cycle, 11 fs duration. Pumped by a custom low-noise erbium-doped fiber amplifier, the laser exhibits an integrated relative intensity noise (RIN) of 0.0026% over 10 Hz–1 MHz, while the noise of the few-cycle output is further suppressed to 0.0017% and reaches the shot-noise limit for Fourier frequencies above 5 kHz. It represents the lowest amplitude noise reported to date for any mode-locked laser. This unprecedented amplitude stability enables carrier-envelope phase (CEP) stabilization with a residual integrated phase noise of only 1.5 mrad (10 Hz–12.5 MHz), corresponding to a CEP jitter of 1.8 as, the highest phase stability for any laser system ever reported. The long-term performance of the fully stabilized OFC is measured over 24 hours, with a power stability of 0.01% and a residual CEP noise of 17 mrad. By combining few-cycle mid-infrared pulses with shot-noise-limited intensity noise and attosecond-level phase stability, the reported OFC provides access to new regimes of quantum-limited metrology and control of ultrafast light-matter interactions.

This article presents a machine-learning, particle-identification algorithm for electrons and positrons in the CLAS12 experiment. The main objective was to minimize charged-pion contamination for both experimental and simulated data. We developed, evaluated and validated two BDT models with different input features, both trained on simulated samples, and conducted rigorous validation using both simulated and experimental data to ensure reliability. Our results show the effectiveness of the applied models in mitigating background contamination. By retaining more than 90% of leptons in the simulated samples, the charged-pion background is largely reduced. Performance was evaluated on experimental data, providing a framework to validate such approaches at CLAS12 and future electron-beam facilities.

Sensory adaptation provides a concrete setting in which low-order system identification can fail qualitatively. We show that one fixed higher-order adaptive system composed entirely of real first-order relaxation modes can be reduced to opposite sides of the second-order pole boundary: low-frequency moment matching gives $\rho_{\rm moment}=4.50$, whereas finite-window fitting gives $\rho_{\rm window}=3.31$, and the inferred pole class changes further with sampling protocol. Thus the real-versus-complex classification of a reduced model is not itself reduction invariant. We then use the general two-state spectrum to connect stochastic identifiability to adaptation: for nontrivial coupling and one-state observation, cross diffusion drops out of the scalar spectrum when the hidden state has no self-relaxation. In the adaptive model, this condition is precisely the integral-memory limit that produces exact adaptation, while leaky memory restores spectral sensitivity. For the exact-adaptation model, the Gaussian path-space irreversibility nevertheless depends on the hidden cross-diffusion channel. Hence $\{H,S_x\}$ does not determine the irreversibility rate. Independently, for a specified all-even reduced two-state drift with $\rho<4$, the drift-only lower bound is $\sigma \ge \tau_x^{-1}(4/\rho-1)$. Published E.~coli and C.~elegans responses provide biological examples of these limits. The distinction established here between transfer-function invariants, reduction-dependent properties, and hidden-state quantities provides a concrete framework for evaluating the limitations of low-dimensional models of adaptive biological dynamics.

Carbon capture, utilization and storage (CCUS) is a key approach for reducing anthropogenic CO2 emissions. Currently the vast majority of CO2 stored is injected into depleted hydrocarbon reservoirs. Reactive transport in hydrocarbon-bearing carbonate reservoirs is controlled not only by the balance between reactant delivery and surface reaction, but also by the heterogeneous pore-scale flow field created by pore structure and fluid distribution. Here, we used time-resolved micro-CT imaging, pore-network analysis, and direct numerical simulation to investigate channelized dissolution during injection of CO2-saturated brine into oil-bearing Ketton limestone at 0.5 mL/min. The system remained in a high Pe, low Da regime throughout the 180 min injection. Despite the advection-dominated flow regime, dissolution became strongly localized. Preferential flow pathways were already present originally because the heterogeneous pore structure and remaining-oil occupancy restricted brine flow to a subset of the connected pore space. Dissolution progressively amplified these pathways. The associated reduction in hydraulic resistance further focused flow, producing a continuous tortuous channel by 180 min. Meanwhile, the effective reaction rate was only 1.6*10^5 mol/m2s,, approximately one order of magnitude lower than the batch reaction rate, showing that rapid advective transport did not translate directly into rapid overall dissolution under multiphase conditions. These results demonstrate that channel formation arose from the coupling between strong reactant delivery and pore-scale flow-field heterogeneity, rather than from the bulk Pe Da regime alone. Accounting for flow-field heterogeneity is therefore important for predicting reactive transport and pore-structure evolution during CO2 injection into hydrocarbon-bearing carbonate reservoirs.