This paper examines defending the power grid against load-altering attacks using electric vehicle charging. It proposes to preventively segment the cyber infrastructure that charging station operators (CSOs) use to communicate with and control their charging stations, thereby limiting the impact of successful cyber-attacks. Using real German charging station data and a reconstructed transmission grid model, a threat analysis shows that without segmentation, the successful hack of just two CSOs can overload two transmission grid branches, exceeding the N-1 security margin and necessitating defense measures. A novel defense design problem is then formulated that minimizes the number of imposed segmentations while bounding the number of branch overloads under worst-case attacks. The resulting IP-MILP bi-level problem can be solved with an exact column and constraint generation algorithm and with heuristics for fast computation on large-scale instances. For the near-real-world Germany case, the applicability of the heuristics is demonstrated and validated under relevant load and dispatch scenarios. It is found that the simple scheme of segmenting CSOs evenly by their installed capacity leads to only 23% more segments compared to the heuristic optimization result, suggesting potential relevance as a regulatory measure.

We explore the stability of a high-finesse optical cavity at 493 nm in vacuum for cavity QED with Barium ions. A high-finesse Fabry-Perot cavity is built using mirrors with high-reflectivity (HR) coatings that are implemented by stacking multiple thin films of low-loss dielectrics on substrates. Applications of such HR mirrors in the near ultraviolet (UV) range have been hampered by degradation of coatings in vacuum. Here, we explore the degradation of mirrors with HR coatings at 493 nm in vacuum. We study both vacuum-induced and laser-induced effects on oxide-coated cavity mirrors by probing changes in cavity loss using cavity lifetime measurements. We investigate the role of circulating power in the rate of increase in cavity loss and demonstrate methods of reversal of cavity degradation. While we observe no degradation without long exposure or with short exposures at lower circulating powers, we find evidence of degradation on long exposure to high circulating powers. We discuss potential causes and conclude that laser-induced deposition is the likely cause while ruling out thermally activated processes due to laser-induced heating.

Linearized Reed-Solomon (LRS) codes form an important family of maximum sum-rank distance (MSRD) codes that generalize both Reed--Solomon codes and Gabidulin codes. In this paper we study the equivalence problem for LRS codes and determine the number of inequivalent codes within this family. Using the correspondence between sum-rank metric codes and systems of $\mathbb{F}_q$-subspaces, we analyze the stabilizer of the Gabidulin system and derive a characterization of equivalence between LRS codes. In particular, we prove that two LRS codes are equivalent if and only if the sets of norms that define the codes coincide up to multiplication by an element of $\mathbb{F}_q^\ast$. This description allows us to reduce the classification problem to the action of $\mathbb{F}_q^\ast$ on subsets of $\mathbb{F}_q^\ast$. As a consequence, we derive formulas for the number of inequivalent linearized Reed-Solomon codes and illustrate the results with explicit examples.

Quantum magnets in two dimensions display strong quantum interaction effects even when magnetically ordered. Using the metal-organic framework material CuF$_2$(D$_2$O)$_2$(pyz), we investigate the field-dependent spin dynamics of the $S = 1/2$ square-lattice Heisenberg antiferromagnet by high-resolution inelastic neutron scattering to applied fields beyond one third of saturation. We discover an anomalously sharp, dispersive ``shadow mode'' residing within the two-magnon continuum, which shadows the dispersion of the transverse one-magnon branches across the Brillouin zone at an offset equal to the Larmor energy. We perform cylinder matrix-product-state (MPS) calculations that reproduce the field-induced spectrum quantitatively and apply a spectrally consistent $1/S$ spin-wave theory to deduce that the ``Larmor-shadow mode'' is a composite two-magnon resonance: a dispersing magnon at wavevector ${\bf Q}$ couples to the uniform Larmor precession at $Γ$, its small intrinsic linewidth indicating a non-perturbative effect of attractive magnon-magnon interactions. Another quantum-fluctuation phenomenon, the zero-field $(π,0)$ anomaly, is lost at increasing fields, which tighten the spectral weight into the one-magnon and Larmor-shadow modes. To our knowledge, these results constitute the first observation of a sharp quasi-bound state embedded in the continuum of a gapless two-dimensional antiferromagnet.

For an abelian type Shimura variety and an odd prime $p$ of good reduction, we characterize the regularity in codimension one of Zariski closures of Ekedahl--Oort strata in terms of the Frobenius action on the root datum. We give an algorithm that detects codimension one singularities for arbitrary Ekedahl--Oort strata. When the Shimura datum is of split type, we relate the singularities of Ekedahl--Oort strata to a stack of $G$-zips over the complex numbers. We study the existence of generalized Hasse invariants on this stack.

Parallel-wound no-insulation (PW-NI) high-temperature superconducting (HTS) coils significantly reduce charging delay while maintaining excellent self-protection capability, demonstrating great potential for high-field applications. Existing models that couple the T-A formulation with equivalent circuits have demonstrated high accuracy in electromagnetic analysis of PW-NI coils. However, eliminating the computational overhead caused by frequent variable mapping and data exchange between electromagnetic and circuit modules is important for improving computational efficiency, particularly in long-duration transient simulations of large-scale magnets. To address this issue, an extended T-A formulation based on potential-chain recursion, termed PCR-TA, is proposed. By directly embedding inter-tape current sharing and radial current bypass behaviors into the finite-element framework, this method computes the transient electromagnetic response of PW-NI coils without requiring an explicit equivalent circuit model. Building upon it, a multi-scale approach is further developed for large-scale PW-NI coils. The validity of the proposed method and its multi-scale extension is verified through comparisons with experimental measurements and field-circuit coupled modeling results. Comparative analyses demonstrate that the PCR-TA method achieves a speedup of approximately 2.4 over the field-circuit coupled method, whereas its multi-scale extension further increases this speedup to roughly 5.8. Furthermore, the PCR-TA method is extended to model the continuous transition of PW-NI coils from power-supply charging to closed-loop operation. This work provides an efficient method and tool for the electromagnetic modeling of PW-NI coils under both driven and closed-loop operating conditions.

The cosmic dipole in galaxy number counts is traditionally described by the Ellis--Baldwin (EB) formula under simplifying assumptions of power-law source counts and flux-limited selection. We reformulate the EB dipole as a symmetry response of observed counts to a Lorentz boost, leading to the general expression $D=βR$, where $R=\partial\ln N/\partial\lnβ$ encodes the underlying population and selection effects. The classical EB formula is recovered as a limiting case. We show that this response framework extends beyond one-point statistics: Lorentz boosts induce a dipole component in the two-point correlation function and, more generally, a hierarchy of responses in $n$-point statistics. We further clarify the relation to redshift-space distortions and relativistic galaxy clustering, and provide a unified description in which observer- and source-induced dipoles contribute to the same multipole component. This establishes the cosmic dipole as a symmetry response of finite-sample point-process statistics, offering a new perspective on dipole anisotropies and their observational interpretation.

Production of the leptophilic Z' boson at future colliders was proposed as one of the benchmark Beyond the Standard Model (BSM) scenarios for the Physics Briefing Book prepared for the 2026 update of the European Strategy for Particle Physics. Presented in this contributions are results on the sensitivity of the experiments at the International Linear Collider (ILC) and at the Linear Collider Facility (LCF) at CERN to the considered scenario. Studied as a function of the Z' boson mass is the expected signal in the di-muon decay channel, which is expected to have the highest sensitivity. Signal and background simulation in WHIZARD includes effects of multi-photon emission and initial state radiation (ISR), with proper matching between ISR and matrix element domains. Expected limits on the Z' couplings to SM leptons are presented for ILC and LCF running at 250 GeV and LCF running at 550 GeV.

Open quantum walks (OQWs) constitute a class of quantum walks whose dynamics are entirely driven by interactions with the environment. It is well known that OQWs provide a general framework for implementing dissipative quantum computation. In this work, we demonstrate the feasibility of running the previously proposed quantum distance-based classifier within the open quantum walk computation model, and we show that its expected runtime remains finite even in the slower regime.

We consider physics behind the FLASH modality of cancer radiation treatment where extremely short treatment times are achieved with ultra high dose rates maintaining the conventional antitumor effectiveness and yet substantially reducing damage to normal tissues (sparing effect). The difference in responses between normal and tumor tissues is attributed here to different recombination rates related to their structure morphologies: ordered in normal vs disordered in the tumor tissues. Correspondingly different are their charge densities under ionizing radiation. In normal tissues it is high enough to form electron-hole liquid (EHL). Because of low EHL diffusivities, the chemical reaction and generation of free radicals are suppressed; hence, sparing effect. To the contrary, a disordered tumor tissue renders efficient energy relaxation channels forming antitumor free radicals. We describe the FLASH thresholds for doses and dose rates.

JWST is beginning to uncover a population of extremely metal-poor galaxies (EMPGs, $Z < 1\%~\mathrm{Z}_\odot$) at $z > 3$, mostly through serendipitous NIRSpec discoveries and blind slitless spectroscopy. To accelerate our understanding of pristine star formation, we further develop a methodology to identify EMPG candidates from photometry, using the extensive deep medium-band imaging from JADES. Our EMPG candidates at $2.5 < z < 6.5$ exhibit strong photometric boosts by H$α$, yet correspondingly weak boosts by [O III] + H$β$, likely indicating extremely low metallicity to explain their lack of [O III] emission. We further demand our EMPG candidates to have strong Balmer jumps, as revealed by medium-band imaging, to ensure that they are young starbursts, as opposed to broad-line AGN/LRDs, though contamination by dusty/dense-gas starbursts and highly-obscured AGN remains a concern. SED-fitting with near-pristine models (${\sim}0.1$-$1\%~\mathrm{Z}_\odot$) indicates that our 22 EMPG candidates are low-mass (median $M_* \approx 10^{6.7}~\mathrm{M}_\odot$), faint dwarf galaxies ($M_\mathrm{UV} \approx -16.6$), with high ionizing photon production efficiencies ($\log\, (ξ_\mathrm{ion, obs}/\mathrm{(Hz\ erg^{-1})}) \approx 26.0$). Hence these are plausible sites of near-pristine star formation, comprising ${\sim}0.04$-$0.6\%$ of $2.5 < z < 6.5$ galaxies at $-19 < M_\mathrm{UV} < -16$. We discuss this extremely metal-poor extension to the mass-metallicity relation. We forecast that deep (${\sim}28$ h) NIRCam slitless spectroscopy can identify bright EMPGs through strong H$β$ but lack of [O III] emission, or secure the redshifts of fainter systems through H$α$ detections. Highly-multiplexed NIRSpec spectroscopy offers an alternate route to discovering the faintest pristine galaxies out to $z=10$, without requiring deep medium-band/MIRI imaging to identify secure candidates.

Cooperative multi-robot missions often require teams of robots to traverse environments where traversal risk evolves due to adversary patrols or shifting hazards with stochastic dynamics. While support coordination--where robots assist teammates in traversing risky regions--can significantly reduce mission costs, its effectiveness depends on the team's ability to anticipate future risk. Existing support-based frameworks assume static risk landscapes and therefore fail to account for predictable temporal trends in risk evolution. We propose a forecast-aware cooperative planning framework that integrates stochastic risk forecasting with anticipatory support allocation on temporal graphs. By modeling adversary dynamics as a first-order Markov stay-move process over graph edges, we propagate the resulting edge-occupancy probabilities forward in time to generate time-indexed edge-risk forecasts. These forecasts guide the proactive allocation of support positions to forecasted risky edges for effective support coordination, while also informing joint robot path planning. Experimental results demonstrate that our approach consistently reduces total expected team cost compared to non-anticipatory baselines, approaching the performance of an oracle planner.

First of a kind comprehensive full-f drift-kinetic (DK) and $δ$-f gyrokinetic (GK) turbulent simulations are carried out in a linear plasma device. We self-consistently derive an electrostatic model including large-scale slowly-varying DK-ordered fields coupled to small-scale rapidly-fluctuating GK-ordered fields. By relying on the critical balance ordering, we show that the electrons are described by a drift-reduced Braginskii model while we rely on a Hermite-Laguerre spectral expansion for describing both the DK and GK parts of the ion distribution function. Global simulations are carried out using the parameters of the linear device LAPD, showing that the DK part of the ion distribution function is approximately a bi-Maxwellian. Fast spectral convergence both for the DK and GK Hermite-Laguerre expansion coefficients is observed, and that the GK fields do not affect the DK fields at the physical LAPD collisionality. Only when the collisionality is reduced and the source term is amplified for the GK fluctuations, an amplification of small-scale turbulent structures is observed. The findings are supported by linear results that show that the simulations are dominated by turbulent fluctuations that are Kelvin-Helmholz driven. Additionally, a GK Kelvin-Helmholz-like mode is observed in the low-GK-collisionality regime which can non-linearly drive small-scale structures.

The limited extrapolative power of structure-based machine learning (ML) models is a critical bottleneck in chemical discovery, particularly for industrial R&D, where navigating uncharted chemical space to find next-generation materials or drugs is paramount. These models, reliant on structural descriptors or graph neural networks (GNNs), often fail when predicting properties for molecules with novel chemotypes. Here, we introduce a physics-augmented ML framework that overcomes this limitation. Our approach replaces conventional structural inputs with thermodynamic properties such as cohesive energy, heat of vaporization, and density, derived directly from molecular dynamics (MD) simulations. While performing comparably to structure-based models on known organic compounds, our method uniquely maintains low error when extrapolating to dissimilar chemical spaces. Crucially, it accurately predicts boiling points for entire chemical classes absent from the training set, including inorganic compounds, salts, and molecules with elements such as Si, B, and Te. By learning from the intermolecular forces that govern phase transitions, our framework provides a more fundamental and generalizable strategy for molecular property prediction, enabling chemical exploration beyond established structural domains.

Equations of ideal magnetohydrodynamics (MHD) play an important role in the studies of turbulence, astrophysics, and plasma physics. These equations possess remarkable geometric structures and symmetries. Indeed, they admit a geodesic formulation in the sense of Arnold, as a Lie--Poisson flow on the dual of an infinite-dimensional Lie algebra. Zeitlin's model, previously developed for MHD on the flat torus and the two-sphere, is a matrix approximation of MHD consistent with the underlying geometric structures. In this paper, we derive the reduced model of axially symmetric magnetohydrodynamics on the three-sphere and give its Hamiltonian formulation. We further extend finite dimensional Zeitlin's matrix model for MHD from 2D to axially symmetric 3D flows of magnetized fluids, yielding the first discrete model for 3D magnetohydrodynamics compatible with the underlying Lie--Poisson structure.

Planetary atmospheres cannot remain hydrostatic at all altitudes because they approach finite density at infinite radius, implying infinite mass. Classical treatments address this in two directions: either retain a hydrostatic structure while allowing particles in the high-velocity tail to decouple and escape in a Jeans-type manner, or promote the gas to a continuum outflow to obtain a transonic Parker-type solution. The usual criterion compares the local mean free path to the sonic point radius. If the mean free path is shorter, the atmosphere is hydrostatic with an imposed Jeans escape flux; if it is longer, the gas is hydrodynamic with Jeans escape neglected. Here, we show that hydrogen-rich atmospheres do not separate cleanly into hydrodynamic and Jeans-escape regimes. At any radius, some particles still collide and behave as a fluid, while others have already experienced their last collision and move collisionlessly on ballistic trajectories. The relative importance of these two behaviors changes smoothly with radius rather than switching at a single boundary. The hydrodynamic channel accelerates and passes through a sonic point, whereas the collisionless channel decelerates under gravity and grows with altitude, removing mass and momentum from the collisional flow. As the collisionless component grows, the bulk flow speed reaches a maximum and then decelerates thereafter, producing profiles similar to Parker breeze solutions even though escape is carried by the collisionless channel. This two-channel framework provides a first step toward a self-consistent treatment that unifies hydrodynamics and kinetics in atmospheric loss models.

This paper demonstrates that adopting out-of-place writes is essential for database systems to fully leverage SSD performance and extend SSD lifespan. We propose a set of out-of-place optimizations that collectively reduce write amplification across both the DBMS and SSD layers. We redesign the in-place, B-tree-based LeanStore to write out-of-place and support these optimizations, and evaluate it on diverse OLTP benchmarks, dataset sizes, and SSDs. The final design improves throughput by 1.65-2.24x and reduces flash writes per operation by 6.2-9.8x on YCSB-A. On TPC-C with 15,000 warehouses, throughput improves by 2.45x while flash writes decrease by 7.2x. Finally, we show that the architecture can seamlessly support novel SSD interfaces such as ZNS and FDP.

Nonlinear optimisation techniques are commonly employed to minimise complex cost functions, with their effectiveness determined largely by the structure of the underlying error landscape. These methods require initial parameter values, and in the presence of multiple local minima, they are prone to becoming trapped in suboptimal regions. The likelihood of locating the global minimum increases substantially when the initialisation lies within its corresponding basin of attraction. Consequently, high-quality initial parameters are critical for successful optimisation. This technical report outlines a new strategy for selecting suitable initial parameters for a trigonometric model and unevenly sampled data, ensuring that the optimisation procedure starts sufficiently close to the global minimum. The proposed parameter estimation approach is strictly NI-based, interpretable, and explainable. It targets at complicated cases which include: samples with strong random noise, samples with only few covered periods, and samples which cover only a fraction of one period. Special attention is put on the frequency estimation. It can be shown that an estimation of initial parameters with sufficient accuracy is possible down to a signal-noise-ratio of 1.4 dB at much lower computational costs than the Lomb-Scargle-periodogram method requires.

We study regression problems with distribution-valued responses and mixed distributional and Euclidean predictors. In quadratic cost, the negative gradient of the Kantorovich potential represents, at each source location, the displacement to its matched location under the optimal transport map. By constructing potentials from the Wasserstein barycenter to individual distributions, the proposed Kantorovich regression model approximates the response displacement field as a sum of predictor displacement fields, each adjusted by a functional parameter. Owing to the linear structure, Euclidean predictors can enter as scaling coefficients of $c$-concave parameter potentials. We characterize functional parameter classes ensuring the intrinsic structure of the model, establish asymptotic theory through uniform convergence of the empirical Wasserstein loss, and derive Gâteaux derivatives leading to first-order optimization algorithms. Real data applications include a mixed-predictor analysis of housing price distributions and an analysis of two-dimensional temperature distributions, demonstrating the flexibility and interpretability of the proposed framework.

In life insurance, life tables are used to estimate the survival distribution of individuals from a given population. However, these tables only provide survival probabilities at integer ages but no information about the distribution of deaths between two consecutive integer values. This incompleteness is particularly relevant for modern insurance products such as variable annuities, whose payoffs depend jointly on lifetime uncertainty and financial market performance. The valuation of such contracts must therefore be carried out in a joint actuarial-financial framework, as their values depend not only on the full information about mortality rates but also on the interaction between mortality risk, asset dynamics, and embedded guarantees. One frequent solution to this incompleteness is to postulate fractional age assumptions or mortality rate models, but it turns out that the results of the computations strongly depend on these restrictive assumptions. We hence derive upper and lower bounds of hybrid functionals of the lifetime with respect to mortality rates, which are compatible with the observed life table at integer ages and the given financial market. We derive two sets of results under distinct assumptions. In the first, we assume that each mortality trajectory is almost surely consistent with all the given one-year survival probabilities from the table. In the second, we consider a relaxed formulation that allows for deviations of the mortality rates while still being consistent in expectation with the given one-year reference survival probabilities. These distinct yet complementary approaches provide a new robust joint actuarial-financial framework for managing mortality risk in life insurance. They characterize the worst- and best-case contract values over all mortality processes that remain compatible with the observed life-table information and the financial market.

The space of Kähler potentials can be quantized through the classical Fubini-Study map, relating infinite-dimensional geometric structures to finite-dimensional symmetric spaces. We prove (exactly) when the Fubini-Study image of a geodesic line in the space of positive definite Hermitian matrices gives rise to a quasi-geodesic in the space of Kähler potentials. Furthermore, we introduce a quantization procedure for geodesics between potentials on normal Kähler varieties and show how this construction extends to the Sasaki setting.

READMEs shape first impressions of software projects, yet what constitutes a good README varies across audiences and contexts. Research software needs reproducibility details, while open-source libraries might prioritize quick-start guides. Through a design probe, LintMe, we explore how linting can be used to improve READMEs given these diverse contexts, aiding style and content issues while preserving authorial agency. Users create context-specific checks using a lightweight DSL that uses a novel combination of programmatic operations (e.g., for broken links) with LLM-based content evaluation (e.g., for detecting jargon), yielding checks that would be challenging for prior linters. Through a user study (N=11), comparison with naive LLM usage, and an extensibility case study, we find that our design is approachable, flexible, and well matched with the needs of this domain. This work opens the door for linting more complex documentation and other culturally mediated text-based documents.

Hyperbolic Floquet codes use only weight-2 measurements and can be implemented directly on hardware with native pair measurements. We construct hyperbolic and semi-hyperbolic Floquet codes from $\{8,3\}$, $\{10,3\}$, and $\{12,3\}$ tessellations via the Wythoff kaleidoscopic construction with the Low-Index Normal Subgroups (LINS) algorithm. The $\{10,3\}$ and $\{12,3\}$ families are new to hyperbolic Floquet codes. We evaluate these codes under four noise models. Under ancilla-based Entangling Measurement (EM3) noise, all three families achieve a threshold of ${\sim}1.5\%$. With a native pair-measurement depolarizing model (SDEM3), thresholds are ${\sim}1.0$--$1.2\%$. For heralded photon loss, the $\{8,3\}$ family achieves ${\sim}8.5$--$9\%$, exceeding the planar honeycomb threshold of ${\sim}6.3\%$. In the multi-parameter SPOQC-2 noise model, the $\{8,3\}$ codes achieve a 2D fault-tolerant area $2.2\times$ that of the surface code compiled to pair measurements. We present the first photon loss and SPOQC-2 thresholds for hyperbolic Floquet codes.

We present ViSTAR, a Virtual Skill Training system in AR that supports self-guided basketball skill practice, with feedback on balance, posture, and timing. From a formative study with basketball players and coaches, the system addresses three challenges: understanding skills, identifying errors, and correcting mistakes. ViSTAR follows the Behavioral Skills Training (BST) framework-instruction, modeling, rehearsal, and feedback. It provides feedback through visual overlays, rhythm and timing cues, and an AI-powered coaching agent using 3D motion reconstruction. We generate verbal feedback by analyzing spatio-temporal joint data and mapping features to natural-language coaching cues via a Large Language Model (LLM). A key novelty is this feedback generation: motion features become concise coaching insights. In two studies (N=16), participants generally preferred our AI-generated feedback to coach feedback and reported that ViSTAR helped them notice posture and balance issues and refine movements beyond self-observation.

We present a method to characterize the distribution of length-scales of finite, disordered patterns with, on average, radial symmetry. This method makes it possible to quantify the distribution of characteristic length scales in cases where the conventional "linear" chord method does not work. We show that the method can clearly distinguish regular patterns, patterns that are formed by diffusion-limited aggregation, and patterns that form during the slow drying of confined, colloid-laden droplets, explained by Beechey-Newman et al.1 We also introduce a method to find the centre-point of these finite patterns, without assuming a full connectivity in the pattern. The method should be widely applicable to other, finite quasi-two-dimensional patterns like dendritic structures, viscous fingering, liquid crystal patterns and bacterial growth.

Webs and Springer fibers are separately important objects in representation theory: webs give a diagrammatic calculus for tensor invariants of $\mathfrak{sl}_k$, and the cohomology group of Springer fibers can be used to construct the irreducible representations of the symmetric group. Fung's 1997 thesis gave the first evidence of a connection between $\mathfrak{sl}_2$ webs and Springer fibers, showing that webs naturally index and describe the components of certain "two row" Springer fibers. However, this case is known to be far from generic. This paper deepens this connection with a similar correspondence in the substantially more complicated "two column" case. In particular, and building on works of Fresse, Melnikov, and Sakas-Obeid, we use webs to give a clean characterization of the smooth components of two column rectangle Springer fibers and a simple description of the geometry of these smooth components. We also show that the Poincaré polynomial of the smooth components is invariant under the natural dihedral action on the corresponding webs.

Searches for stochastic gravitational wave backgrounds generated by first-order phase transitions offer a powerful probe of hidden sectors, but quantitative predictions in gauge theories are obstructed by the gauge dependence of the finite-temperature effective potential and the associated tunneling action. We study a minimal gauged $U(1)$ dark sector containing a dark Higgs and a dark photon, optionally supplemented by a vectorlike dark fermion, coupled to the Standard Model through the Higgs portal or kinetic mixing. Using the Nielsen identity together with a controlled derivative expansion and power counting, we construct a gauge-independent effective action in the high- and low-temperature limits, enabling model-intrinsic nucleation dynamics and robust gravitational wave predictions. We perform dedicated Monte Carlo scans in both limits and map viable microscopic parameters to detector-facing peak frequencies and amplitudes, spanning bands relevant to pulsar timing arrays and planned space-based interferometers. In our scans, supercooled phase transitions typically produce much stronger signals and are more likely to fall within the sensitivity range of current and future gravitational wave detectors, whereas parametrically high-temperature phase transitions generally yield weaker signals. We further connect the phase transition phenomenology to viable dark matter candidates within the same minimal field content, providing benchmark targets for dark photon dark matter and dark fermion dark matter, and highlighting their complementarity with gravitational wave observables. Overall, our results provide an end-to-end, gauge-independent pipeline from a minimal hidden sector Lagrangian to gravitational wave spectra and cosmologically viable dark matter benchmarks, yielding the most reliable and concrete predictions to date for a minimal gauged $U(1)$ dark sector.

This review paper comprehensively examines the influence of spatial torsion on quantum fluctuations from the perspectives of Metric-Affine Gravity (MAG) and the Stochastic Variational Method (SVM). We first outline the fundamental framework of MAG, a generalized theory that includes both torsion and non-metricity, and discuss the geometrical significance of torsion within this context. Subsequently, we summarize SVM, a powerful technique that facilitates quantization while effectively incorporating geometrical effects. By integrating these frameworks, we evaluate how the geometrical structures originating from torsion affect quantum fluctuations, demonstrating that they induce non-linearity in quantum mechanics. Notably, torsion, traditionally believed to influence only spin degrees of freedom, can also affect spinless degrees of freedom via quantum fluctuations. Furthermore, extending beyond the results of previous work [Koide and van de Venn, Phys. Rev. A112, 052217 (2025)], we investigate the competitive interplay between the Levi-Civita curvature and torsion within the non-linearity of the Schrödinger equation. Finally, we discuss the structural parallelism between SVM and information geometry, highlighting that the splitting of time derivatives in stochastic processes corresponds to the dual connections in statistical manifolds. These insights pave the way for future extensions to gravity theories involving non-metricity and are expected to deepen our understanding of unresolved cosmological problems.

Amontons' law postulates a monotonic relationship between frictional force and the normal load applied to a sliding contact. This empirical rule, however, fails in systems where internal degrees of freedom - such as structural or electronic order - play a central role. Here, we demonstrate that friction can emerge entirely from magnetically driven configurational dynamics in the absence of physical contact. Using a two-dimensional array of rotatable magnetic dipoles sliding over a commensurate magnetic substrate, we observe a pronounced non-monotonic dependence of friction on the interlayer separation, and thus on the effective load. The friction peaks at an intermediate distance where competing ferromagnetic and antiferromagnetic interactions induce dynamical frustration and hysteretic torque cycles during sliding. Molecular dynamics simulations and a simplified two-sublattice model confirm that energy dissipation is governed by collective magnetic reorientations and their hysteresis. Our results establish the occurrence of sliding-induced changes in collective magnetic order, which has a strong impact on friction, and thus open new possibilities for contactless friction control, magnetic sensing, and the design of reconfigurable, wear-free frictional interfaces and metamaterials.

We extend the circuit-level erasure noise model and Wang et al.\ quadratic expansion fitting of Chang et al.\ from planar surface codes to hyperbolic CSS surface codes. Under Chang et al.'s noise models, the $\{8,3\}$ Bolza fine-grained family threshold reaches $3.6\%$ under the general-Pauli models (which coincide at temporal resolution $η= 1$) and $4.7\%$ under the tailored spatially perfect model at $R_e = 1$ (pure erasure). The corresponding erasure-to-Pauli ratios ($5.0\times$ and $6.5\times$) match the surface code values to within $5\%$. Per-observable crossing-point analysis at $R_e = 1$ (Models 1--3) independently yields an erasure-to-Pauli ratio of $5.3\times$. These results establish that the erasure advantage extends to hyperbolic codes.