Motivated by observational evidence from JWST and theoretical results from cosmological simulations, we use a simple parametric, phenomenological model to test to what extent bursty star formation with standard Initial Mass Function, no continuous star formation, no mergers, \mr{and no dust} can account for the observed properties in the $M_{UV}$ vs $M_*$ plane of galaxies at redshifts $z>5$. We find that the simplest model that fits the data has a quiescence period between bursts $Δt \sim 100$~Myrs and the stellar mass in each galaxy grows linearly as a function of time from $z=12$ to $z=5$ (i.e., repeated bursts in each galaxy produce approximately equal mass in stars). The distribution of burst masses across different galaxies follows a power-law $dN/dM_* \propto M_*^α$ with slope $α\sim -2$. At $z>9-10$ the observed galaxy population typically had only one or two bursts of stars formation, hence the observed stellar masses at these redshifts (reaching $M_* \sim 10^{10}$~M$_\odot$), roughly represent the distribution of masses formed in one burst.

Recrystallization is a phenomenon in which a plastically deformed polycrystalline microstructure with a high dislocation density transforms into another that has low dislocation density. This evolution is driven by the stored energy in dislocations, rather than grain growth driven by grain boundary energy alone. One difficulty in quantitative modeling of recrystallization is the uncertainty in material parameters, which can be addressed by integration of experimental data into simulations. In this work, we compare simulated static recrystallization dynamics of a Mg-3Zn-0.1Ca wt.% alloy to experiments involving thermomechanical processing followed by measurements of the recrystallization fraction over time. The simulations are performed by combining PRISMS software for crystal plasticity and phase-field models (PRISMS-Plasticity and PRISMS-PF, respectively) in an integrated computational materials engineering framework. At 20% strain and annealing at 350 °C, the model accurately describes recrystallization dynamics up to a mobility-dependent time scale factor. While the average grain boundary mobility and the fraction of plastic work converted into stored energy are not precisely known, by fitting simulations to experimental data, we show that the average grain boundary mobility can be determined if the fraction of plastic work converted to stored energy is known, or vice versa. For low annealing temperatures, we observe a discrepancy between the model and experiments in the late stages of recrystallization, where a slowdown in recrystallization kinetics occurs in the experiments. We discuss possible sources of this slowdown and propose additional physical mechanisms that need to be accounted for in the model to improve its predictions.

We investigate bound states of a non-relativistic scalar particle in a three-dimensional helically twisted (torsional) geometry, considering both the free case and the presence of external radial interactions. The dynamics is described by the Schrödinger equation on a curved spatial background and, when included, by minimal coupling to a magnetic vector potential incorporating an Aharonov--Bohm flux. After separation of variables, the problem reduces to a one-dimensional radial eigenvalue equation governed by an effective potential that combines torsion-induced Coulomb-like and centrifugal-like structures with magnetic/flux-dependent terms and optional model interactions. Because closed-form analytic solutions are not reliable over the parameter ranges required for systematic scans, we compute spectra and eigenfunctions numerically by formulating the radial equation as a self-adjoint Sturm--Liouville problem and solving it with a finite-difference discretization on a truncated radial domain, with explicit convergence control. We analyze four representative scenarios: (i) no external potential, (ii) Cornell-type confinement, (iii) Kratzer-type interaction, and (iv) the small-oscillation regime around the minimum of a Morse potential. We present systematic trends of the low-lying levels as functions of the torsion parameter, magnetic field, and azimuthal sector, and we show that geometric couplings alone can produce effective confinement even in the absence of an external interaction.

We study scalar waves on subextremal Kerr-de Sitter spacetimes in a compact slow-rotation regime and at a fixed overtone index. Working initially at a fixed cosmological constant $Λ>0$ and uniformly for $(M,a)$ in a compact slow-rotation set, using the meromorphic/Fredholm framework for quasinormal modes and a semiclassical equatorial labeling proved in a companion paper, we establish a quantitative two-mode dominance theorem in an equatorial high-frequency package: after exact azimuthal reduction, microlocal equatorial localization, and analytic pole selection by entire localization weights constructed from equatorial pseudopoles, the $k=\pm\ell$ sector signals are each governed by a single quasinormal exponential, up to an explicitly controlled tail and an $\mathcal O(\ell^{-\infty})$ contribution from all other poles. We then develop a fully deterministic frequency-extraction stability estimate based on time-shift invariance, and combine it with the two-mode dominance result and the companion paper's inverse stability theorem to obtain an explicit parameter bias bound for ringdown-based recovery of $(M,a)$. Finally, using the companion paper's three-parameter inverse theorem and a damping observable based on the scaled imaginary part of one equatorial mode, we propagate the same deterministic error chain to a local bias bound for recovery of $(M,a,Λ)$ on compact parameter sets with $|a|$ bounded away from $0$. As a further consequence, we obtain a localized pseudospectral stability statement for the equatorial resolvent package, quantifying how large microlocalized resolvent norms enforce proximity to the labeled equatorial poles. The resulting estimates clarify the conditioning mechanisms (start time, window length, shift step, and detector nondegeneracy) and provide a rigorous PDE-to-data interface for high-frequency black-hole spectroscopy.

We study the interaction of a kaon with the $f_1(1285)$ resonance, assuming that the $f_1(1285)$ is a molecular state generated by the $K \bar K^*, \bar K K^*$ interaction, evaluating the scattering amplitude, the scattering length and effective range of the $K f_1$ system. The scattering amplitude develops a resonant structure approximately $10$ MeV below the $K f_1$ threshold, with a width of around $15$ MeV. The corresponding correlation function has the distinctive shape of a system with a bound state close to threshold. We also show that the interaction of the $K f_1$ system is differs significantly from the one obtained assuming that the $f_1(1285)$ is an elementary particle. This provides motivation to continue the search for these observables, already initiated by the measurement of the $p f_1(1285)$ correlation function by the ALICE collaboration.

Intermodal quantum key distribution at telecom wavelengths provides a hybrid interface between fiber connections and free-space links, both essential for the realization of scalable and interoperable quantum networks. Although demonstrated over short-range free-space links, long-distance implementations of intermodal quantum key distribution remain challenging, due to turbulence-induced wavefront aberrations which limit efficient single-mode fiber coupling at the optical receiver. Here, we demonstrate a real-time intermodal quantum key distribution field trial over an 18 km free-space link, connecting a remote terminal to an urban optical ground station equipped with a 40 cm-class telescope. An adaptive optics system, implementing direct wavefront sensing and high-order aberration correction, enables efficient single-mode fiber coupling and allows secure key generation of 200 bit/s using a compact state analyzer equipped with room-temperature detectors. We further validate through experimental data a turbulence-based model for predicting fiber coupling efficiency, providing practical design guidelines for future intermodal quantum networks.

We present high-angular resolution ($\simeq 0\rlap.{''}06$) VLA and ALMA observations of Orion South separated by 15.52 years. The purpose of this study was to search for orbital motions in three close ($\simeq 0\rlap.{''}1$) binary systems in the region. We do not detect changes in the position angle of the binaries but in two of the cases we detect significant changes in their separation in the plane of the sky. We use these changes to estimate that the total mass of the binaries is in the $\simeq$1-2 $M_\odot$ range. We also estimate the disk masses from the mm emission. The dust-to-stellar mass ratio is in the range of 0.04 to 0.18, values consistent with those expected for very early stellar evolution (Class 0) protostars.

This study investigates how target geometry and material influence pion and muon production from an 8 GeV proton beam, in support of target-system design for a muon collider demonstrator. A 2 m long, 0.7 m radius solenoid with a 5 T peak magnetic field is used to capture secondary particles, with the target positioned at its center. We examine how variations in target radius, length, and material affect secondary-beam yield and emittance at the solenoid exit. In parallel, we evaluate temperature rise within the target to assess material limitations and guide future work on thermal and structural survivability. The results provide initial intuition for optimizing both particle yield and target durability in muon collider front-end systems.

We introduce a compact operator-based technique that solves the paraxial wave equation for a broad class of structured light fields. Using the spatial evolution operator to propagate two families of physically apodized inputs, Gaussian apodized Whittaker integrals and Gaussian apodized Helmholtz fields, we derive closed form expressions that retain the Gaussian width and therefore describe finite energy beams. The method unifies and extends the Helmholtz Gauss families and readily generalizes to nonseparable nondiffracting architectures. Experiments on superposed Bessel Gauss beams confirm the predicted transverse rotations, demonstrating that this operator approach is a fast, transparent, and practical alternative to standard diffraction ntegral treatments

p-spin glasses, characterized by frustrated many-body interactions beyond the conventional pairwise case (p>2), are prototypical disordered systems whose ground-state search is NP-hard and computationally prohibitive for large instances. Solving this problem is not only fundamental for understanding high-order disorder, structural glasses, and topological phases, but also central to a wide spectrum of hard combinatorial optimization tasks. Despite decades of progress, there still lacks an efficient and scalable solver for generic large-scale p-spin models. Here we introduce PLANCK, a physics-inspired deep reinforcement learning framework built on hypergraph neural networks. PLANCK directly optimizes arbitrary high-order interactions, and systematically exploits gauge symmetry throughout both training and inference. Trained exclusively on small synthetic instances, PLANCK exhibits strong zero-shot generalization to systems orders of magnitude larger, and consistently outperforms state-of-the-art thermal annealing methods across all tested structural topologies and coupling distributions. Moreover, without any modification, PLANCK achieves near-optimal solutions for a broad class of NP-hard combinatorial problems, including random k-XORSAT, hypergraph max-cut, and conventional max-cut. The presented framework provides a physics-inspired algorithmic paradigm that bridges statistical mechanics and reinforcement learning. The symmetry-aware design not only advances the tractable frontiers of high-order disordered systems, but also opens a promising avenue for machine-learning-based solvers to tackle previously intractable combinatorial optimization challenges.

We use large-scale density-matrix renormalization group simulations with bond dimensions up to $20\ 000$ to determine the magnetization curves of spin-1 and spin-$\tfrac{3}{2}$ pyrochlore Heisenberg antiferromagnets. Both models exhibit a robust half-magnetization plateau, and we find that the same 16-site state (quadrupled unit cell) is selected in both cases on the largest 64-site cubic cluster we consider for the plateau state. This contrasts sharply with the effective quantum dimer model prediction which favors the ``R'' state, and demonstrates the breakdown of the perturbative mechanism at the Heisenberg point. These results provide a nonperturbative characterization of field-induced phases in pyrochlore magnets and predictive guidance for spin-1 and spin-$\tfrac{3}{2}$ materials.

The nearly scale-invariant primordial power spectrum provides the standard initial conditions for cosmological perturbations. However, the largest scales remain only weakly constrained by CMB observations, leaving room for deviations such as an infrared (IR) cut-off. This possibility is further motivated by the persistence of large-scale CMB anomalies, most notably the low quadrupole power. In this work, we revisit several broad classes of phenomenologically motivated IR cut-off scenarios using parametrised functional forms of the primordial power spectrum. We confront these models with the latest CMB, BAO, and supernova data and derive updated constraints on the cut-off scale and associated features. Our results remain consistent with earlier studies, showing that although such models suppress power at low multipoles, the improvement in fit is marginal and does not overcome the associated parameter penalties. We therefore find no statistically significant evidence favouring IR cut-off models over the standard power-law spectrum with current data. We further explore the interplay between IR cut-off features and a possible increase in the reionisation optical depth, motivated by the recent CMB-BAO tension highlighted by DESI DR2 within the $Λ$CDM framework. We show that the additional freedom introduced by large-scale suppression is generally insufficient to support a substantial increase in optical depth, owing to the weak statistical preference for suppressed large-scale temperature power. Finally, we examine the implications of IR cut-off models for large-scale CMB anomalies by analysing the corresponding anomaly statistics within a Bayesian framework.

We study the mean-field dynamics of a system of $N$ interacting bosons starting from an initially condensated state. For a broad class of mean-field Hamiltonians, including models with arbitrary bounded interactions and models with unbounded interaction potentials, we prove that the probability of having $n$ particles outside the condensate decays exponentially in $n$ for any finite evolution time. Our results strengthen previously known bounds that provide only polynomial control on the probability of having $n$ excitations.

We consider the phenomenon of string breaking in the context of the spatial Wilson loops using the gauge/string duality. In particular, we discuss the impact of light flavors on the pseudopotential. We also introduce the notion of the spatial string breaking distance and estimate it for $SU(3)$ gauge theory in the temperature range $0\,\text{-}\,3\,T_c$.

We consider the amplification of bosonic interactions through parametric control that implements squeezing along orthogonal quadratures. We show that bosonic interactions described by certain classes of quadratic and quartic Hamiltonians can be enhanced in this way while simultaneously overcoming noise and decoherence. In general, the amplification method enhances both desired and undesired interactions present in the system. Depending on the case, however, detrimental processes can be less amplified than the desired couplings. We leverage this observation to improve the fidelity for preparing Bell-type entangled states between two bosonic modes in the presence of noise and losses. We also investigate noise models for which the protocol either fails or partially achieves a loss-tolerant state preparation speedup. Our work facilitates faster preparation of complex quantum states and implementation of entangling gates in the presence of decoherence mechanisms.

Turbulence in the magnetized plasma is well understood to be the consequence of wave interactions. When the Hall effect is added to the minimum magnetohydrodynamics (MHD), the MHD waves become dispersive and different nonlinear interactions are expected. The emergent turbulent state will thus be expected to be different. For incompressible Hall MHD we develop a reduced model for wave-wave interactions concentrating on those processes that will lead to phase coherent modifications to the linear dispersion of a given wave. We show that these special interactions provide an amplitude-dependent contribution to the linear dispersion relation, which yields nonlinear frequency shifts. The resonance-driven frequency shifts are dominant and add damping or growth to the linear dispersion. The damping/growth rates represent the nonlinear time scales for energy redistribution and can be used in conjunction with a conjecture like the "critical balance" to estimate the energy spectral content.

The redshifted 21-cm signal emitted by neutral Hydrogen (HI) is a promising probe to understand the evolution of the topology of ionized regions during the Epoch of Reionization (EoR). The topology of ionized regions allows us to infer the nature and properties of ionizing sources, i.e., early galaxies and AGNs. Traditional Fourier statistics, such as the power spectrum, help us quantify the strength of fluctuations in this field at different length scales but do not preserve its phase information. Analyzing the 21-cm brightness temperature field in the image domain retains its non-Gaussian characteristics and morphological information. One such approach is to track the coalescence of multiple ionized regions to form one contiguous ionized region spanning the universe. This is referred to as percolation, and its onset is quantified by a sharp rise in the value of the Largest Cluster Statistic (LCS) approaching unity. In this work, we carry out a percolation analysis of 21-cm brightness temperature fields by studying the redshift evolution of the LCS along a lightcone to distinguish between several simulated reionization scenarios. We have extended previous results on reionization model comparison from the analysis of coeval 21-cm maps to understand how the lightcone effect biases the observed percolation behavior and affects the distinguishability of the source models. We estimate the LCS of subvolumes of different sizes in the 21-cm lightcone maps and study their redshift evolution for different reionization scenarios using a moving volume approach. We find that the percolation transition inferred from a lightcone approaches that from the coeval box as we increase the bandwidth of the moving volume in all but one reionization scenario.

Fluid molecular ferroelectrics are a new class of organic materials where ferroelectricity is found in conjunction with 3D fluidity whilst still retaining spontaneous polarization values comparable to their traditional solid state counterparts. One of the major challenges for soft condensed matter physics is predicting whether a fluid molecular material will form ferroelectric phase with nematic or smectic order. Through the synthesis of forty five systematically varied molecules, and by analogy to solid molecular ferroelectrics, is it shown that subtle hydrogen fluorine substitution allows for tuneable syn-parallel pairing motifs resulting in either specific pairings leading too geometrically constrained lamellar order or diversified pairings stabilising nematic ordering. Large-scale, fully atomistic molecular dynamics simulations reveal that smectic ferroelectricity emerges from discrete lateral pairing modes, whereas nematic phases arise from a multiplicity of equivalent polar configurations. Together, these findings establish experimentally validated design principles for fluid molecular ferroelectrics and provide a predictive framework for engineering functional polar fluids.

We propose that the superconducting diode (SD) efficiency can be significantly enhanced near the transition between two superconducting states by choosing parameters where, before the system goes normal with increasing supercurrent, it switches into a different superconducting order for one direction of the current but not for the other. This mechanism for producing high SD efficiency relies on the expectation that the critical current depends sensitively on the superconducting order. We demonstrate this explicitly by performing detailed calculations for a bilayer superconductor with an in-plane magnetic field, which admits the standard Bardeen-Cooper-Schrieffer (BCS) and the orbital Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) orders as a function of the strength of the magnetic field. We predict a sharp peak in the SD efficiency in the FFLO state close to the transition, which arises from a complex interplay between the two superconducting orders. An implication of our study is that the measurement of the SD efficiency can provide fundamental insight into the nature of the BCS-FFLO transition both as a function of the magnetic field and the supercurrent.

Context. Characterization of warm giants is crucial to constrain giant planet formation and evolution. Measuring the mass and radius of these planets, combined with their moderated irradiation, allows us to estimate their planetary bulk composition, which is a key quantity to comprehend giant planet formation and structure. Aims. We present the discovery of two transiting warm giant planets orbiting solar-type stars from the Transiting Exoplanet Survey Satellite (TESS), which were characterized by further spectroscopic and photometric ground-based observations. Methods. We performed a joint analysis of photometric data with radial velocities to confirm and characterize TOI-883 b and TOI-899 b, two sub-Saturns orbiting solar-like stars. Results. TOI-883 b and TOI-899 b have masses of $0.123 \pm 0.012$ $M_J$ and $0.213 \pm 0.024$ $M_J$, radius of $0.604 \pm 0.028$ $R_J$ and $0.991 \pm 0.044$ $R_J$, periods of $10.06$ d and $12.85$ d and equilibrium temperature of $1086 \pm 19$ K and $1040 \pm 19$ K, respectively. Conclusions. While having similar masses, orbital periods and stellar host properties, these planets seem to have different internal compositions, which could point to distinct formation histories. Both planets are suitable targets for atmospheric studies to further constrain formation scenarios of planets in the Neptune-Saturn mass range

Most cold atoms experiments in microgravity platforms or in Space are achieved using atom chips, leading to limitations in terms of optical access and inhomogeneous magnetic fields. Optical dipole traps do not have these drawbacks but have difficulties producing atomic samples with a large number of atoms at ultra low temperature in the absence of gravity. Here, we report on an efficient evaporative cooling in two-crossed laser beams during parabolic flights. Time-averaged potentials combine the advantages of large capture volume and trap compression, increasing the initial phase space density and collision rate to favor the evaporative process. With this technique we demonstrate the production of an ultra cold gas of $2.5\times 10^4$ rubidium atoms at a temperature below 100 nK in less than 4 seconds. Our experiment paves the way for the development of quantum sensors applied to fundamental physics and geodesy as well as the study of ultracold atomic physics in Space.

The RNA inverse folding problem aims to identify nucleotide sequences that preferentially adopt a given target secondary structure. While various heuristic and machine learning-based approaches have been proposed, many require a large number of sequence evaluations, which limits their applicability when experimental validation is costly. We propose a method to solve the problem using a factorization machine with quadratic-optimization annealing (FMQA). FMQA is a discrete black-box optimization method reported to obtain high-quality solutions with a limited number of evaluations. Applying FMQA to the problem requires converting nucleotides into binary variables. However, the influence of integer-to-nucleotide assignments and binary-integer encoding on the performance of FMQA has not been thoroughly investigated, even though such choices determine the structure of the surrogate model and the search landscape, and thus can directly affect solution quality. Therefore, this study aims both to establish a novel FMQA framework for RNA inverse folding and to analyze the effects of these assignments and encoding methods. We evaluated all 24 possible assignments of the four nucleotides to the ordered integers (0-3), in combination with four binary-integer encoding methods. Our results demonstrated that one-hot and domain-wall encodings outperform binary and unary encodings in terms of the normalized ensemble defect value. In domain-wall encoding, nucleotides assigned to the boundary integers (0 and 3) appeared with higher frequency. In the RNA inverse folding problem, assigning guanine and cytosine to these boundary integers promoted their enrichment in stem regions, which led to more thermodynamically stable secondary structures than those obtained with one-hot encoding.

Understanding mechanisms of ion transport in bulk materials is central to designing next-generation ion conductors for energy storage devices, yet studies employing all-atom molecular dynamics (MD) have largely been limited to reporting overall transport coefficients without a quantitative, spatiotemporally resolved breakdown of \emph{how} charge is carried. We present a computational framework that analyzes MD trajectories to quantitatively interpret macroscopic transport by decomposing it into additive contributions from physically motivated events. They are defined either through heuristically identified microscopic transitions, capturing events such as single-ion hops, multi-ion hops, and vehicular motion, or through transitions between chemically interpretable coordination macrostates. The construction guarantees that attributed contributions sum exactly to the Onsager transport coefficients estimated via the Green-Kubo/Einstein formalism, while scanning the sampling window exposes characteristic temporal scales at which distinct transport mechanisms emerge and dominate. Applied across three prototypical electrolytes-inorganic crystals, liquids, and polymers-the framework quantitatively resolves long-standing debates (e.g., the role of concerted motion and exchange), identifies dominant mechanisms and rate-limiting steps, quantifies their frequencies and effectiveness, and extracts activation energies for distinct transport modes, thereby distilling design rules for fast conduction. This general and reproducible analysis tool turns MD trajectories into quantitative mechanism maps, enabling the ion-conductor community to adjudicate mechanistic hypotheses and accelerate discovery.

The rare-event sampling problem has long been the central limiting factor in molecular dynamics (MD), especially in biomolecular simulation. Recently, diffusion models such as BioEmu have emerged as powerful equilibrium samplers that generate independent samples from complex molecular distributions, eliminating the cost of sampling rare transition events. However, a sampling problem remains when computing observables that rely on states which are rare in equilibrium, for example folding free energies. Here, we introduce enhanced diffusion sampling, enabling efficient exploration of rare-event regions while preserving unbiased thermodynamic estimators. The key idea is to perform quantitatively accurate steering protocols to generate biased ensembles and subsequently recover equilibrium statistics via exact reweighting. We instantiate our framework in three algorithms: UmbrellaDiff (umbrella sampling with diffusion models), $Δ$G-Diff (free-energy differences via tilted ensembles), and MetaDiff (a batchwise analogue for metadynamics). Across toy systems, protein folding landscapes and folding free energies, our methods achieve fast, accurate, and scalable estimation of equilibrium properties within GPU-minutes to hours per system -- closing the rare-event sampling gap that remained after the advent of diffusion-model equilibrium samplers.

Twinning is a primary deformation mechanism in Mg alloys. This study focuses on tension twins during uniaxial compression of Mg-Y alloys, with three key aspects: the orientation specificity of twin grains, the relative evolution of CRSS with increasing Y content, and the local stress and strain evolution at twin sites. Experimental characterization and crystal plasticity modeling were performed. In Mg-7wt.%Y, TT2-{112-1} tension twins were observed in addition to the common TT1-{101-2} twins. Increasing Y suppressed TT1 formation while promoting TT2 activity. A previously unreported group of crystallographic orientations with a higher global Schmid factor for <c+a> slip was identified, which exhibited TT1 twinning with increasing compression strain. To elucidate Y effects on twin activity and local mechanical fields, both TT1 and TT2 tension twin modes were incorporated into PRISMS-Plasticity, an open-source, finite element-based crystal plasticity solver. Four binary Mg-Y alloys were modeled under compression, and statistical analysis was conducted to correlate initial orientations, stress-strain distributions, and twin activities as functions of Y concentration. The plasticity analysis revealed that increasing Y decreases the CRSS ratio of prismatic and pyramidal slip relative to TT1 twinning, while the slip-to-twin CRSS ratio for TT2 increases, thereby serving as a potential indicator of differential twin activity with Y addition in Mg alloys. Additionally, despite their small volume fraction, TT2 twin sites were predicted higher local strain accumulation locally, relative to the representative volume element and TT1 twins, suggesting their potential influence on localized phenomena such as recrystallization or twin nucleation. These findings provide insight into local mechanical behavior in Mg alloys and support alloy design for advanced engineering applications.

Cerium hydride has a variety of interesting properties, including a known lattice contraction and densification with increasing hydrogen content. However, precise stoichiometric control is not experimentally straightforward and {\it ab initio} approaches are not computationally feasible for many properties such as melting and low temperature diffusion. Therefore, we develop a machine-learned interatomic potential for cerium hydride that is valid for H to Ce ratios from 2.0 to 3.0. A query-by-committee active learning approach is used to develop the training set. Leveraging classical molecular dynamics simulations, we assess a range of properties and provide fundamental mechanisms for the trends with stoichiometry. A majority of the properties follow the trend of lattice contraction, being governed by the stronger lattice binding induced by adding octahedral atoms.

We develop the theoretical model that describes dynamic non-equilibrium effects of external inertial and axion fields in a system of particles with spin. The possibility of using the spin density and the current density of non-relativistic quantum particle systems for the detection of the hypothetical axion-like dark matter is discussed. The resulting closed system of dynamic equations encompasses the continuity equation, the momentum balance equation, and the spin density evolution equation, accounting for the influence of the spin-rotation coupling and the external axion fields. The new formalism opens up new perspectives for an experimental search of dark matter axions.

The self-modulation (SM) instability transforms a long charged particle bunch traveling in plasma into a train of microbunches that resonantly drives large-amplitude wakefields. We present the first determination of the saturation length of SM using experimental and numerical results. The saturation length is the distance over which wakefields reach their maximum amplitude along the plasma. By varying the plasma length and measuring the radius of the transverse distribution of the bunch, we find that the saturation length of SM decreases with plasma density and initial field amplitude, e.g., when seeding. The saturation length is a fundamental parameter of the instability, and these results are key for understanding SM and designing plasma wakefield accelerators driven by long bunches, such as AWAKE, or by long laser pulses for radiation production.

Particle-stabilised emulsions are a cornerstone of soft matter science due to their broad application and fundamental relevance. Computer simulations provide key insights into the formation and behaviour of these emulsions, yet current methods are limited by the spatiotemporal scales accessible for study. The principal issue is that particles are resolved individually. In this work, an alternative strategy is introduced based on phase-field theory, for which we establish the framework. By evolving continuous fields, large-scale dynamics can be simulated in a computationally efficient manner. Our approach is then applied to model the complex formation of a bicontinuous interfacially jammed emulsion gel (bijel) via solvent-transfer induced phase separation (STrIPS). By resolving the coupled dynamics of liquid phase separation and nanoparticle adsorption, the model allows for the characterisation of the influence of nanoparticles on the morphology. Higher concentrations of nanoparticles are found to reduce the average domain size of STrIPS bijels, in line with previous experimental evidence. The presented phase-field model thus represents a promising approach for the morphological investigation of complex particle-stabilised emulsions.

Experimentalists often use wind tunnels to study aerodynamic turbulence, but most wind tunnel imaging techniques are limited in their ability to take non-invasive 3D density measurements of turbulence. Wavefront tomography is a technique that uses multiple wavefront measurements from various viewing angles to non-invasively measure the 3D density field of a turbulent medium. Existing methods make strong assumptions, such as a spline basis representation, to address the ill-conditioned nature of this problem. We formulate this problem as a Bayesian, sparse-view tomographic reconstruction problem and develop a model-based iterative reconstruction algorithm for measuring the volumetric 3D density field inside a wind tunnel. We call this method WindDensity-MBIR and apply it using simulated data to difficult reconstruction scenarios with sparse data, small projection field of view, and limited angular extent. WindDensity-MBIR can recover high-order features in these scenarios within 10% to 25% error even when the tip, tilt, and piston are removed from the wavefront measurements.