Papers

Exploring how matter cycles through the Galaxy, from the birth of stars in dense interstellar clouds to the ejection of matter and energy during a star's final stages-requires a multi-faceted approach. Radio observations are essential to reveal the intricate interactions at play. By studying our Galaxy in detail, we can use it as a model to better understand these processes in galaxies as well. The Square Kilometre Array offers unique capabilities in wide-field, high-sensitivity, high-resolution spectroscopy and precise astrometry to revolutionise Galactic astrophysics. This chapter presents an overview of the science addressed in detail in chapters pertinent to the SKAO Science Working Group Our Galaxy.

Artificial intelligence (AI) models are scaling rapidly, exposing fundamental limitations in conventional computing architectures, where the physical separation of memory and computation imposes substantial energy and latency overheads. Optical neural networks offer a viable solution by enabling high-throughput, low-latency computation through the intrinsic parallelism of light. However, the scalability of photonic computing is constrained by the lack of materials that can provide low-loss, energy-efficient, and nonvolatile control of optical phase. Here, we discuss the emerging role of ferroionic two-dimensional materials as a platform for programmable photonics. Unlike conventional ferroelectrics, where polarization arises from bounded lattice distortions, ferroionic systems enable field-driven ionic redistribution, providing access to a continuum of stable and reconfigurable states. We outline how these material dynamics can be exploited to realize multi-level photonic states and nonvolatile phase control. Furthermore, we highlight a back-end integration strategy that introduces multifunctionality, including tunable optical nonlinearities into pre-fabricated photonic circuits without compromising optical performance. By bridging material-level dynamics with device- and system-level functionality, ferroionic materials provide a pathway toward reconfigurable, low-loss, and energy-efficient photonic computing architectures, opening new opportunities for neuromorphic and adaptive photonic systems.

Quantum materials experiments increasingly rely on microwave, electrical, thermal, optical, and structural probes, but these capabilities are typically assembled from custom hardware that limits reproducibility and scalability. Here we show that a commercial 65-nm CMOS process can be repurposed as a passive, foundry-manufacturable characterization platform by functionally partitioning its metal stack into microwave, thermal, and electrical subsystems within a 1 mm2 footprint. The integrated RF architecture enables cryogenic magnetic susceptibility measurements of Fe3GeTe2 heterostructures at 1.75 K without sample-specific fabrication. We further demonstrate NV-center optically detected magnetic resonance (ODMR) with >20% contrast at 4-9 dBm microwave power, reducing power requirements by 20-25 dB relative to conventional antenna-based approaches while maintaining sensitivities of 2-3 uT/sqrt(Hz). We additionally confirm compatibility with in-situ electron-beam imaging, showing no measurable degradation in image quality upon device operation. These results establish a scalable, foundry-manufacturable platform for multimodal quantum sensing and materials characterization.

Although a complete characterisation of the probability distribution in the phase space of turbulent flows remains elusive, accurately sampling this distribution is essential for both synthetic turbulence generation and turbulent flow reconstruction. Motivated by these applications, we examine to what extent a machine-learned distribution can approximate the physical invariant distribution of turbulent channel flow at $\mathrm{Re}_\tau=180$. We assess three important properties of the approximation: physical ensemble statistics, consistent conditional sampling, and dynamical invariance. To this end, a flow-based generative model is trained on a minimal conditional flow unit, which we define as the smallest domain outside which conditional fields, given a single observation at the domain centre, are indistinguishable from unconditional fields in terms of mean-square discrepancy to other conditional fields. We also introduce a consistent procedure for sampling from the conditional learned distribution. Comparisons with direct numerical simulation show that synthetic turbulent fields reproduce key statistical and dynamical features of turbulence, including intermittency and nonlinear energy transfer. The consistency of conditional sampling is demonstrated in a flow reconstruction problem, and subsequently used to generate synthetic turbulent velocity fields on a large domain. When adopted as initial conditions in direct numerical simulations, these fields yield physical and statistically stationary ensemble statistics, indicating that the learned distribution provides a good approximation to the natural distribution of the turbulent dynamical system.

In astronomical imaging surveys, repeated observations of the same sky patches are taken in order to obtain deeper images and detect new sources. This is the case in the search for many transient phenomena, such as supernovae, gravitational wave (GW) optical counterparts and other cataclysmic variables. In many such surveys some of the images are undersampled, meaning that the pixel size is too large, and the image suffers from aliasing. For undersampled images, both co-addition of the images and background subtraction are done in a non-optimal manner, which leads to reduced sensitivity and an increased rate of false alarms. We present a new method (named Linear Undersampled Transients & Addition (LUTRA)) that performs both processes in a mathematically proven optimal way, which allows improved performance for many scientific applications. It also allows easy and direct performance of measurements such as photometry and astrometry in a simple manner, while providing results in super-resolution. We demonstrate the performance of the method on public ZTF data and show $\times 1.25$ higher SNR compared to current methods. We provide an open source Python implementation.

Polarization-encoded optical-fiber links provide a useful platform for investigating the coexistence of communication and sensing functions in a shared optical channel. In this work, a classical analog of the BB84 polarization-encoding scheme was implemented over a bend-insensitive fiber link to evaluate how temperature, axial strain, and torsion affect the transmitted state of polarization and the recovery of a binary key. Temperature variations from 24 {\deg}C to 35 {\deg}C and axial strain up to 2 m{\epsilon} produced only minor polarization-state variations and did not affect key recovery. In contrast, fiber torsion induced a pronounced retarder-like evolution of the state of polarization, reducing the detector-intensity contrast used for bit discrimination and degrading key recovery. For intermediate torsion angles, the erasure rate reached 50%. The polarization state tended to recover for rotations close to {\Delta}{\theta} = 180{\deg}, consistent with the oscillatory response observed on the Poincaré sphere. These results identify torsion as the dominant impairment in the tested polarization-encoded fiber link and demonstrate its potential use as a sensing mechanism in integrated communication-and-sensing architectures.

In many quantum applications it is important to know whether or not a Bell nonlocal two-qudit state exhibits its nonlocality under correlation scenarios with some given numbers $S_{1},S_{2}\geq1$ of generalized quantum measurements at two sites. In the present article, we find analytically a new general condition sufficient for a nonseparable Werner state with a dimension $d\leq\min\{S_{1},S_{2}\}$ to satisfy all Bell inequalities under every $S_{1}\times S_{2}$-setting correlation scenario with outcomes of an arbitrary spectral type, discrete or continuous $-$ that is, to be $S_{1}\times S_{2}$-setting Bell local, for short. For a variety of measurement settings $S_{1}, S_{2}$, this new general bound is beyond (i) Werner's and Barrett's locality bounds for a nonseparable Werner state and (ii) the related result by Johnson and Viola [Phys. Rev. A 88, 032323 (2013)] on "sharability" of this state. When specialized to $d = 2$ and $\min\{S_{1},S_{2}\} = 2, 3$, our new general bound improves upon the corresponding results by Terhal et. al. in [Phys. Rev. Lett. 90, 157903 (2003)], moreover, for $d=\min\{S_{1},S_{2}\} = 2$, it reduces exactly to the bound derived for this case via the CHSH inequality. We prove also explicitly in operator terms the result of Terhal et. el. that every nonseparable Werner state with a dimension $d >\min\{S_{1},S_{2}\}$ is $S_{1}\times S_{2}$-setting Bell local. The new results presented in this article are important for both the theory of Bell nonlocality and quantum applications based on this fundamental concept.

While stellar population synthesis (SPS) models have been widely used for spectral analysis in optical wavelengths, their characteristics remain uncertain in the near-infrared (NIR) due to a relative lack of observed NIR spectra. The spectrophotometric data from SPHEREx are well-suited for investigating the performance of SPS models in the NIR, thanks to its wide wavelength coverage over $0.75-5.0~{\rm \mu m}$. In this work, we compare the observed SPHEREx data of SDSS compact galaxies, including 2,726 non-emission-line galaxies and 1,163 emission-line galaxies, to the NIR SEDs predicted from the full spectrum fitting of SDSS optical spectra. We use four different SPS models that extend into the NIR: E-MILES, Bruzual & Charlot (BC03), Charlot & Bruzual (CB19), and FSPS. We find that all four models tend to overpredict the stellar continuum at $2.4-5~{\rm \mu m}$ by $0.1-0.3~{\rm mag}$. This trend is particularly prominent for intermediate-age stellar populations ($\sim1-5~{\rm Gyr}$), suggesting a systematic bias in the NIR SED predictions of current SPS models. For stellar populations older than $5~{\rm Gyr}$, E-MILES shows relatively smaller offsets at $3.8-5~{\rm \mu m}$ compared to other models. Meanwhile, for emission-line galaxies, the SPS models underestimate the SED by up to $\sim0.5~{\rm mag}$ at longer wavelengths due to the contribution of non-stellar emission. Overall, these results highlight the necessity of refining the NIR stellar spectral features in SPS models, such as emissions from thermally pulsating asymptotic giant branch stars or molecular absorptions from cool stars.

We consider repulsive Euler-Poisson equations in both one-dimensional space and in the multidimensional case with radial symmetry, assuming a power-law velocity-dependent damping coefficient. We show that under this assumption, in the one-dimensional case the set of initial data corresponding to a globally time-smooth solution expands, whereas in other dimensions (except for dimension 4) the damping does not influence on improving of smooth properties of the solution. Namely, any arbitrary small perturbation of the steady state blow up, despite of its amplitude of oscillations decays.

We prove full replica symmetry breaking for the zero-field Sherrington-Kirkpatrick model at zero temperature: the Parisi minimizer is absolutely continuous, has a smooth density, and has support $[0,1)$. At inverse temperature $\beta>1$, [arxiv.org/abs/2607.11756v3] recently proved that the Parisi measure has support $[0,q_\beta]$. Here, we show $q_\beta$ converges to $1$ as $\beta\to\infty$.

We revisit the problem of real-time quantum dynamics of the paradigmatic two dimensional transverse-field Ising model using the recently developed fuzzy sphere regularization scheme. By linearly ramping the transverse field from the paramagnetic phase to criticality, we study the finite-time scaling behavior of the squared order parameter $\langle m_z^2 \rangle$, the excitation energy density $Q$, and the two-point correlation function of $m_z$. We establish numerically that, at intermediate quench rate, $\langle m_z^2 \rangle$ follows the conventional Kibble-Zurek prediction set by the critical exponents of the $3$D Ising universality class, and the correlation function exhibits the expected exponential decay whose correlation length can be used to estimate the non-universal scaling coefficient in the freeze-out time/length. In contrast, the excitation energy density $Q$ does not reach the same scaling regime at available system sizes due to large effective finite-size gap from symmetry-enforced level sparsity in the energy spectrum. At slow quench rates the universal quasi-adiabatic scaling for both $\langle m_z^2 \rangle$ and $Q$ is recovered. Since the fuzzy sphere construction can realize not only the Ising conformal field theory (CFT), but a broad family of $(2+1)d$ CFTs, our results establish a route to the real-time critical dynamics of strongly coupled CFTs that are otherwise computationally challenging to study.

We study the cosmological core-halo relation in vector dark matter using three-component Schrödinger-Poisson simulations. Starting from cosmological vector-field initial conditions, which due to the evolution of the vector field during inflation are enhanced on small scales, we find that nonlinear evolution begins almost immediately following matter-radiation equality and produces compact self-gravitating Proca-star condensates at the centers of halos. After confirming the central condensates through their radial density profiles, we find the empirical relation \(\widetilde M_\star\propto \widetilde M_{\rm h}^{0.6403}\) between the Proca star mass and halo mass, although interestingly we find that we are only able to confirm Proca stars in $\mathcal{O}(10\%)$ of halos. This serves as important input for future studies of the abundance and merger rates of Proca stars in models of vector dark matter. We also examine the vector-field structure of the objects through global longitudinal and transverse polarization fractions and local spin density inside halos, which increases over cosmic time.

We revisit the holographic proposal relating the growth rate of spread complexity to the radial momentum of a bulk probe, aiming to identify its underlying assumptions and clarify how classical probe dynamics emerges from quantum dynamics. By quantizing AdS probes directly and using the extrapolation dictionary, we provide a more general derivation of the proposal. In particular, we interpret it as a concrete realization of a classical complexity observable and its quantization in the “complexity=anything” framework. Since probe dynamics is not intrinsically tied to the AdS/CFT correspondence, we also examine the proposal in flat and de Sitter spacetimes. In flat spacetime, the physical Hamiltonian does not preserve the coherent-state structure, and spread complexity measures the dispersive broadening of the wave packet rather than classical momentum. In de Sitter space, generic semiclassical wave packets in the static-patch energy representation show the same dispersive behavior. By contrast, coherent states adapted to the principal-series representation can exhibit exponential growth of spread complexity, with a growth rate that has the same time dependence as the classical radial momentum. These examples indicate that a semiclassical limit alone is not sufficient for a momentum–complexity relation.

The semileptonic and nonleptonic decays of the $\Upsilon(nS)$ with $n=1,2,3,4$ are investigated within the covariant light-front quark model (CLFQM). Using the form factors of the transitions $\Upsilon(nS) \to B_{(c)}$ obtained from the CLFQM, we calculate the branching ratios of the decays $\Upsilon(nS)\to B_{(c)}\ell\nu_\ell$ and $\Upsilon(nS)\to B_{(c)}M$ with $\ell=e,\mu,\tau$ and $M$ referring to $\pi(\rho),K^{(*)},D^{(*)},D^{(*)}_s$. One can find that the branching ratios of the decays $\Upsilon(3S)\to B_c\ell\nu_\ell$ are the largest among those of considered semileptonic decays and can amount to $10^{-9}$; As to the nonleptonic decays, $\Upsilon(3S)\to B_c\rho$ and $\Upsilon(3S)\to B_cD^{(*)}_s$ have the largest branching ratios, which reach up to $10^{-10}$. Given the identification and detection efficiency of final states, searching for these weak decay modes should be fairly challenging in future experiments. The forward-backward asymmetry $A_{FB}$ and the longitudinal polarization fraction $f_L$ are also calculated for those semileptonic decays.

Statistical testing for signal discovery and signal-strength estimation in high-energy physics increasingly relies on machine-learning models trained on simulated data. We present a synthetic dataset for $t\bar t H$ multilepton signal–background classification and perform a systematic evaluation of machine-learning models ranging from the widely used XGBoost for tabular data to LorentzNet, which processes events with built-in Lorentz symmetry. Existing studies often differ in feature definitions, training procedures, and evaluation metrics, making it difficult to isolate the impact of model architecture on performance. To address this, we apply standardized training and hyperparameter-optimization procedures, construct a controlled hierarchy of feature sets, and perform a comprehensive comparison of the models. In addition to the analysis-driven metric of signal-strength uncertainty, we report the commonly used ROC AUC metric and show that under realistically weighted training, it correlates well with the uncertainty-based ranking of models. We further investigate model performance as a function of input feature set, training-set size, and the choice between channel-specific and unified multi-channel training. Our results establish the superiority of Particle Transformer and LorentzNet within the considered setup. We also identify potential avenues for further improvement, including more expressive architectures, joint training across additional analysis channels, and larger simulated datasets. Although this study focuses on a specific Higgs-boson analysis, we expect the main conclusions to generalize to a broader class of searches and measurements at the LHC and HL-LHC.

Critical rare earth elements, lithium, copper, and coal underpin global clean energy transitions and advanced manufacturing, yet China faces persistent supply volatility and resource security risks amid fragmented cross-border mineral trade with Outer Mongolia. This paper constructs a dynamic partial equilibrium Stackelberg supply chain model spanning ten years, integrating three geographic nodes: Outer Mongolia's mineral extraction sector, Baotou's rare earth processing hub in Inner Mongolia, and residual demand from the Rest of the World (RoW). The model endogenizes core mechanisms including mineral supply curves constrained by infrastructure stock, lagged capital accumulation, Leontief processing production functions, profit-driven investment, and optimal export tax policy maximizing China's discounted social welfare. Three comparative scenarios are calibrated and simulated: a baseline status-quo trade framework, deep Sino-Mongolian resource integration, and a delayed cross-border infrastructure counterfactual.

Fermi surface nesting is key to understanding the origin of the itinerant antiferromagnetic spin density wave in chromium. This magnetic order is accompanied by a charge-density wave, and both density waves disappear above the critical pressure $P_c \approx 10$ GPa at low temperatures, defining a quantum critical point. Whether this pressure-induced quantum phase transition is accompanied by a phonon instability remains an open question. Here, we use inelastic x-ray scattering to track the room-temperature acoustic phonon dispersions at pressures up to $P=15.6$ GPa, well above $P_c$. We focus on the Kohn anomalies near the $H$ and $N$ points of the Brillouin zone, with the $H$ point anomaly lying close to the incommensurate spin-density-wave ordering vector. The phonon branches harden smoothly under pressure, while the positions and wave-vector extents of both anomalies remain essentially unchanged across $P_c$, with no additional critical softening. Ab initio calculations likewise show that Fermi surface nesting remains robust above $P_c$. These results indicate that the pressure-induced quantum phase transition is not driven by a phonon instability and support a primarily spin-density-wave-driven mechanism in presence of a robust Kohn anomaly.

We introduce a physics-informed neural network (PINN) approach for designing phase profiles in flat optics that reshape an incident beam into a prescribed target intensity distribution. The method solves Monge–Ampère beam-shaping equations associated with energy-conserving ray mappings generated by a phase-only optical element. We treat both finite-distance and far-field targets using a generalized-Snell-law formulation. The learned phase profiles are validated by scalar diffraction simulations and compared with conventional phase-retrieval methods such as Gerchberg–Saxton. To our knowledge, this is the first time a PINN has been used for beam shaping problems in flat optics.

In general relativity, cosmic acceleration is timelike defocusing of the comoving congruence and requires a negative total active gravitational mass density, $\mathcal{M}_{\rm tot}=\rho_{\rm tot}+3p_{\rm tot}<0$. The criterion $w\equiv p/\rho<-1/3$ diagnoses sector repulsion only for $\rho>0$: the inequality reverses for $\rho<0$, and ratio variables are ill-defined at $\rho=0$ even when the stress-energy tensor is finite. For sign-changing effective dark energy (DE), as in $\Lambda_{\rm s}$CDM-type histories, we instead use the signed density $\rho_{\rm de}$ and two branch-independent combinations. The regular null energy condition (NEC) boundary $\mathcal{I}_{\rm de}=\rho_{\rm de}+p_{\rm de}=0$ replaces the phantom divide $w_{\rm de}=-1$, while $\mathcal{M}_{\rm de}=\rho_{\rm de}+3p_{\rm de}<0$ governs sector-level Raychaudhuri repulsion. For a separately conserved DE sector with a smooth negative-to-positive density crossing of finite odd order $n$ at $z_\dagger$, we prove that $\mathcal{I}_{\rm de}$ and $\mathcal{M}_{\rm de}$ are negative in a punctured neighborhood and non-positive at the crossing, while $w_{\rm de}$ develops a kinematic pole with universal residue $n(1+z_\dagger)/3$. If $\mathcal{M}_{\rm de}>0$ at some sufficiently high redshift, continuity requires at least one repulsion boundary $z_{\rm rep}>z_\dagger$: the sector is already repulsive while $\rho_{\rm de}<0$. We derive the exact range of $\rho_{\rm de}'(z_\dagger)$ for acceleration at the crossing with the total NEC satisfied. Under the stated single-impulse and stationary-point assumptions, the deceleration parameter has one or three sign-changing zeros. A smooth $\Lambda_{\rm s}$CDM profile, an exponential infrared $f(T)$ model, and the minimal phantom brane illustrate the results. These results motivate organizing late-time inference around $(\rho,p,\mathcal{I},\mathcal{M})$ rather than around $w$ alone.

We consider a system of non-interacting fermions prepared in the many-body ground state of an isotropic trapping potential in any dimension, and investigate the ballistic expansion of the fermionic cloud after the potential is suddenly released. Using semi-classical techniques, we derive the full late-time profile of the expanding cloud in the regime when the fermion number is large. We thus obtain explicit expressions for power-law potentials with arbitrary exponent $a$ and in all dimensions $d$. The momentum distribution and the spatial profile of the cloud exhibit a universal edge exponent $d/a$, thus generalizing the Wigner semi-circle law and the Thomas-Fermi distribution.

We investigate the ergodicity of star formation in simulated galaxies from the FIRE-2 (Feedback In Realistic Environments) project. We restrict ergodicity considerations to being related to deviations from the star-forming main sequence (SFMS), and in turn whether ensemble averages across populations match time-averaged star formation histories (SFHs) based on simulated observable properties. We find that in these high-resolution simulations the deviations of individual galaxies from the SFMS tend to approach ergodic behavior over time, regardless of the SFMS definition adopted and the star formation estimator used. This trend persists when galaxy morphology, as traced by Sérsic index, is considered despite the spheroid-dominated morphologies showing a smaller range of SFMS deviations than the disk-dominated morphologies. Unsurprisingly, we find more rapid convergence to ergodic behavior for star formation estimators based on shorter time scales ($10^{7}$ years) as opposed to longer ($10^{9}$ years). We caution that these findings should be considered in the context of the current sample and that further studies, particularly of high redshift evolution and the impact of active galactic nuclei should be investigated.

Susceptible-infected-susceptible (SIS) epidemic models on networks are governed by hierarchical moment equations where the dynamics of smaller subsystems depend on the state of larger ones. Moment closure approximations, which truncate this hierarchy by expressing higher-order state probabilities in terms of lower-order ones, are essential for obtaining tractable reduced systems. Higher-order networks, which extend the pairwise structure to include group interactions, introduce a combinatorial explosion of closure configurations, making systematic derivation harder. Consequently, existing higher-order SIS models are derived heuristically, where structural and dynamical assumptions underpinning their closures are not always apparent from the formulation alone. We develop a bottom-up derivation of higher-order SIS dynamics, building systematically from node-level equations to pairs, triplets, and three-body interactions. Central to our approach is a network-dependent closure operator that generates topologically appropriate approximations from local pairwise and triadic structure. Using this framework, we recover three existing higher-order SIS models–Burgio et al.'s maximal clique, Malizia et al.'s pair-based and inter-order models–as special cases, each arising under specific topological and dynamical assumptions. Our derivation reveals assumptions that are invisible from heuristic approaches: for instance, Malizia et al.'s inter-order overlap parameter is insufficient alone to express the model within our framework despite performing well against simulations, with the original derivation implicitly invoking additional structural assumptions. Our framework offers both a foundation for higher-order epidemic modeling and a constructive pathway for understanding the assumptions implicit in heuristically derived mean-field closures and provides a principled method of generating new models.

Altermagnetism combines compensated magnetic order with nonrelativistic spin splitting, yet established mechanisms predominantly rely on spin-reversing rotations in Néel-order antiferromagnets. Here we establish stripe-order altermagnetism governed instead by a spin-reversing mirror, placing it outside the usual rotation-based $l$-wave classification. Using two-orbital models, we show that the interplay between stripe spin and orbital orders can yield a stripe altermagnet with mirror-constrained nematic spin splitting or a stripe anti-altermagnet with spin-degenerate bands. The latter can support ferroelectric-like electrical control of spin splitting in suitable buckled structures. Random-phase-approximation (RPA) calculations show that stripe-order altermagnetism is favored near half filling under strong hopping anisotropy. The spin-reversing mirror further enforces a purely transverse Drude spin current for an electric field parallel or normal to the mirror plane, while spin-resolved mirror and rotation probes distinguish this response from that of rotation-governed $l$-wave altermagnets.

The phenomenon of frustration greatly enriches the accessible physics of quantum magnets. With this in mind we study the magnetism of \NC using a combination of bulk properties measurements and neutron scattering techniques. The low-temperature heat capacity reveals two magnetic transitions at $T_{N1}$ = 270 mK and $T_{N2}$ = 180 mK. However, much of the magnetic entropy is released above $T_{N1}$, manifesting as a broad peak centered at $T^{*} \approx$ 450 mK. A similar broad peak is observed in the magnetic susceptibility, which possesses a clear anisotropy; this data can be well fit using a 1-dimensional XXZ model, yielding an antiferromagnetic nearest-neighbor exchange $J_{NN}$ = -0.962(2) K and exchange anisotropy close to the Ising limit. Single crystal elastic neutron scattering reveals highly anisotropic magnetic diffuse scattering above $T_{N1}$, confirming that quasi-one-dimensional, short-range, antiferromagnetic order is the origin of the broad peak in the heat capacity and magnetic susceptibility. Magnetic Bragg peaks characterized by a $\vec{k}$ = ($0$ $0$ $\frac{1}{2}$) propagation vector emerge below $T_{N1}$. Interestingly, the magnetic diffuse scattering persists for $T_{N2} < T < T_{N1}$, indicating a regime of coexisting short and long-range order. The magnetic Bragg peaks exhibit an additional increase in intensity below $T_{N2}$ with no change in $\vec{k}$. Concomitantly, the diffuse scattering disappears indicating the attainment of full long-range order. While the precise nature of the ordered magnetic ground state remains unresolved, the observed magnetic scattering indicates predominate $c$-axis moments with a small $ab$-plane component. We propose that the quasi-one-dimensional behavior and the coexistence of short and long-range order are driven by frustration of exchange interactions with significant anisotropy.

Microwave frequency combs constitute promising resources for quantum technologies, cryogenic electronics, and multiplexed sensing architectures. In this work, we propose a frequency-comb generator based on a Josephson field-effect transistor operated in a relaxation-oscillation regime. The device comprises a gate-tunable ballistic superconductor-semiconductor-superconductor junction embedded in a resistively shunted circuit, in which electrostatic control of the carrier density enables in situ tuning of both the critical current and the Josephson inductance. Time-domain circuit simulations indicate that the resulting oscillator produces coherent voltage pulses whose Fourier spectrum forms a microwave frequency comb. In contrast to conventional Josephson-based comb architectures, the proposed platform provides direct electrical control of the comb spacing, emission frequencies, and modal power distribution via a gate electrode. For a representative Al/InAs implementation, we demonstrate continuous frequency coverage in the technologically relevant 1-10 GHz range. Furthermore, the concept is shown to be compatible with higher-$T_c$ superconductors, underscoring its potential as a compact and scalable microwave source for cryogenic quantum information and sensing applications.

The recently discovered twist-bend nematic NTB and ferroelectric nematic NF phases are distinct examples of spontaneous symmetry breaking in liquid crystals. Here, we report the occurrence of both type nematic phases within the same homologous series of dimers consisting of two strongly dipolar mesogenic units linked by a flexible spacer. The NF phase, observed for dimers having spacer with even number of atoms, exhibits the strong polar order; in the NTB phase, observed for dimers with odd number of atoms in the spacer, short-pitch heliconical director structure develops.

In the two-dimensional limit, the intrinsic magnetic topological insulator MnBi2Te4 provides a compelling platform for exploring thickness-dependent quantum states and their evolution under external perturbations. Using first-principles calculations and classical Heisenberg Monte Carlo simulations, we demonstrate that electrostatic gating and surface chemical functionalization can drive a systematic crossover from the topological to the conventional anomalous Hall regime. This transition is governed by the simultaneous shift of the Fermi level away from the topological gap and a reversal of interlayer coupling from antiferromagnetic to ferromagnetic order. Results reveal that hole doping drives the Fermi level into the valence bands, inducing an exceptionally high anomalous Hall conductivity of 1127 S/cm arising from Berry curvature hot spots. In contrast, surface chemical doping drives a topological state where intrinsic $\sigma_{xy}$ is reduced from $e^2/h$ to $\sim 0.86\ e^2/h$ by the spectral coexistance of chiral edge mode with metallic bulk states of the two-dimensional film. Furthermore, we show that both tuning routes significantly enhance in-plane exchange interactions, leading to a substantial increase in the magnetic ordering temperature relative to the pristine bilayer. These results establish a versatile framework for the simultaneous engineering of topological, magnetic, and transport properties in ultrathin MnBi2Te4, offering direct implications for the development of reconfigurable quantum devices.

Symmetry-governed magnetic materials have emerged as a promising platform for spintronic functionalities without net magnetization or stray magnetic fields, motivating the exploration of how lattice dynamics couple to symmetry-derived spin-polarized electronic states. Understanding spin-phonon coupling in these systems is therefore essential for uncovering the microscopic origin of spin-lattice interactions and for enabling their control in quantum materials. However, this mechanism remains poorly understood because spin polarization originates from crystal symmetry rather than conventional magnetic order. Here, we address this issue in the g-type altermagnet CoNb4Se8 using temperature- and polarization-resolved Raman spectroscopy, complemented by measurements on a structurally analogous Co-deficient compound lacking well-defined long-range magnetic order. We observe pronounced symmetry-selective phonon renormalization across the magnetic transition in CoNb4Se8, while related phonon anomalies persist in the Co-deficient system, demonstrating that the lattice response cannot be explained solely by conventional exchange-striction associated with coherent magnetic ordering. First-principles calculations reveal that spin-orbit coupling establishes a symmetry-dependent interaction channel between lattice vibrations and symmetry-governed electronic states. Our results identify an alternative mechanism for spin-phonon coupling in symmetry-governed magnetic materials and demonstrate that phonons provide a sensitive probe of symmetry-driven spin polarization even without robust magnetic order. More broadly, this work provides a framework for understanding and engineering spin-lattice functionality in symmetry-driven quantum materials, offering design principles for coupling lattice dynamics to spin-polarized electronic states.

We present RuNNer 2.0, the "Ruhr University Neural Network energy representation", a highly optimized software suite for training and evaluating high-dimensional neural network potentials (HDNNPs) of the second, third, and fourth generation. Long-range electrostatics and charge equilibration (QEq) for the description of non-local charge transfer in fourth-generation (4G) HDNNPs are accelerated by quasi-linear-scaling plane-wave methods, reducing QEq computational complexity from $\mathcal{O}(N^3)$ to $\mathcal{O}(N\log^2 N)$ such that linear or quasi-linear scaling is achieved across all HDNNP generations. An optimized memory management strategy eliminates the training overhead traditionally associated with long-range interactions, allowing 4G-HDNNPs to be trained with the same efficiency as their local counterparts. Developed in modern Fortran (2003/2008 standards), combined with a hybrid MPI/OpenMP parallelization scheme, RuNNer 2.0 has been designed to run efficiently in any CPU environment, from cost-effective local workstations to massive HPC clusters. Its modular library architecture facilitates straightforward binding to external simulation software; native interfaces to LAMMPS and the Atomic Simulation Environment (ASE) provide full access to all its features, including built-in committee-based uncertainty quantification. The high efficiency and scalability of the RuNNer 2.0 ecosystem are demonstrated through detailed benchmarks.

AI Phe is an eclipsing binary star with an orbital period of 24.6 days for which the surface gravity and effective temperature are known from direct measurements to very high precision and accuracy. We have obtained high-quality spectroscopy of the K0IV star during the total eclipse of the F7V companion, and also obtained spectra with a very high signal-to-noise ratio for this star and its F7V companion using the spectral disentangling technique. We have used these spectra to measure the abundances of iron and magnesium for both stars. We compare the values of [Fe/H] and [Mg/H] for the F7V star and the K0IV star to stars in M67, an open cluster of similar age and metallicity to AI Phe. We find that our [Fe/H] and [Mg/H] measurements clearly show the signature of elemental diffusion in the F7V star. This suggests that AI Phe can be used to test models of single stars that include diffusion and mixing of elements.