We develop a low-order Crouzeix--Raviart--Raviart--Thomas (CR--RT) equilibrated-flux certification workflow for finite element approximations of semilinear diffusion--reaction problems, with particular emphasis on anisotropic mesh settings. Given a computed conforming finite element state $\tilde u_h$, the certification process is reduced to three computable quantities required by a Newton--Kantorovich argument: a dual-norm residual bound, a stability constant for the Fréchet derivative, and a Lipschitz bound for the derivative in a neighborhood of $\tilde u_h$. These components yield an explicit radius $ρ>0$, ensuring that the exact solution exists locally and uniquely within the ball $B(\tilde u_h,ρ)\subset V$. The residual bound is obtained from an $H(\mathrm{div})$-conforming $\mathbb{RT}^0$ certificate flux reconstructed through a Marini-type CR--RT route. The purpose of this route is not to replace general higher-order or local mixed equilibrated reconstructions, but to provide an explicit low-order construction whose algebraic structure is transparent on anisotropic simplicial meshes. Within the certified neighborhood, we further enclose selected quantities of interest $\mathcal J(u)$; the baseline enclosure follows from the verified inclusion, while an adjoint-based correction sharpens the resulting intervals. The numerical experiments report the behavior of the computable certification quantities for monotone semilinear models, including anisotropic mesh tests. Unless interval or outward-rounded scalar post-processing is explicitly used, the reported computations should be understood as floating-point evaluations of the derived rigorous estimators.

We used \texttt{MIST} isochrone fitting and a dedicated grid of stellar evolution models computed with MESA to constrain the ages of the components of the $γ$ Persei binary system. While individual stars can be matched to the models at specific metallicities, no joint isochrone solution reproduces both the observed masses and evolutionary states. The stellar evolutionary tracks calculated by MESA reveal a clear evolutionary mismatch. The primary component of the system is in a post-main-sequence phase consistent with the red giant branch or red clump. In contrast, the lighter secondary component lies near the turn-off point of the main sequence or is in the early phase of the subgiant branch. This discrepancy can be overcome by assuming that the $γ$ Persei system was born as a triple and the primary component is a rejuvenated star formed through a merger of a close-by pair of main-sequence stars. We show that the merger must have occurred no later than a few hundred megaryears after system formation, and the progenitor masses of the merging stars are restricted by a combination of stars that fall within a narrow band in the $(M_{1,a},M_{1,b})$ plane, corresponding to $M_{1,a}\simeq0.9$--$2.1\,M_\odot$ and $M_{1,b}\simeq2.3$--$2.5\,M_\odot$.

Uncrewed aerial vehicles (UAVs) have played an important role in the low-altitude economy and have been used in various applications. However, with the increasing number of UAVs and explosive wireless data, the existing bit-oriented communication network has approached the Shannon capacity, which cannot satisfy the quality of service (QoS) with ultra-reliable low-latency communication (URLLC) requirements for command and control (C\&C) transmission in bit-oriented UAV communication networks. To address this issue, we propose a novel semantic-aware C\&C transmission for multi-UAVs under limited wireless resources. Specifically, we leverage semantic similarity to measure the variation in C\&C messages for each UAV over continuous transmission time intervals (TTIs) and capture the correlation of C\&C messages among UAVs, enabling multicast transmission. Based on the semantic similarity and the importance of UAV commands, we design a trigger function to quantify the QoS of UAVs. Then, to maximize the long-term QoS and exploit multicast opportunities of C\&C messages induced by semantic similarity, we develop a proximal policy optimization (PPO) algorithm to jointly determine the transmission mode (unicast/multicast/idle) and the allocation of limited resource blocks (RBs) between a base station (BS) and UAVs. Experimental results show that our proposed semantic-aware framework significantly increases transmission efficiency and improves effectiveness compared with bit-oriented UAV transmission.

Non-perturbative limitations on low-energy effective field theories (EFTs) based on the characteristics of high-energy theory are provided by the analyticity of the flat-space version of the S-matrix. Although the analyticity of the flat-space S-matrix is widely established, it is difficult to apply this framework to de Sitter space because the growing backdrop breaks time-translation symmetry and makes it more difficult to define asymptotic states. The flat-space analyticity imprint on the de Sitter S-matrix is examined in this study. On a certain limit, we derive a comprehensive relationship between the flat-space amplitude and the de Sitter S-matrix. In particular, we demonstrate that the relationship is valid for tree-level amplitude exchanging with arbitrary local derivative interactions with a large scalar field. Next, we contend that this specific limit is more consistent with the definition of EFT since, similar to flat space, the Mandelstam variable may be identified as the unique energy scale because the total energy dependence of the de Sitter S-matrix becomes negligible. Finally, we also find an unexpected connection between the idea of generalized energy conservation of an S-matrix of four-dimensional de Sitter and exceptional EFTs in de Sitter space. We restrict the coupling constants in theories of self-interacting scalars dwelling in the exceptional series of de Sitter representations by requiring that such an S-matrix only has support when the total energies of in and out states are equal. We rediscover the Dirac-Born-Infeld (DBI) and Special Galileon theories, in which a single coupling constant uniquely fixes the four-point scalar self-interactions.

Evolutionary algorithms (EAs) are increasingly executed on graphics processing units (GPUs) to exploit population-level parallelism. This shift changes the resource model under which EAs are designed and evaluated. However, many GPU-based EA studies still focus mainly on implementation-level speedup after porting CPU-oriented algorithms to GPUs, providing limited insight into how algorithmic mechanisms, function-evaluation (FE) budgets, population scales, and hardware utilization jointly affect optimization behavior. In response, this paper goes beyond speedup measurement and studies the scaling behavior of EAs on GPUs from a hardware-aware evaluation perspective. We evaluate 16 representative EAs on 30 benchmark problems across CPU and GPU platforms, covering single-objective optimization, multi-objective optimization, numerical benchmarks, and neuroevolution tasks. The study leads to four findings. First, GPU acceleration is highly heterogeneous across algorithms because different evolutionary mechanisms expose different degrees of batched computation, memory regularity, and synchronization. Second, FE-budgeted evaluation remains useful for measuring sample efficiency, but it provides only a limited observation window under GPU execution; time-budgeted evaluation is therefore necessary for assessing practical time-to-solution and long-horizon search behavior. Third, GPU effectiveness depends on scaling regimes induced by problem dimension and population size, where parallelism may be underutilized, effective, or saturated. Fourth, GPU execution makes very large populations practically affordable, and several evolutionary mechanisms can convert this increased population scale into improved optimization performance. These results indicate that GPU parallelism should not be treated only as a post hoc acceleration tool, but as part of the evaluation and design assumptions of scalable EAs.

Flavor instabilities in dense neutrino media trigger exponential growth of flavor waves, yet their nonlinear saturation remains poorly understood. We examine a simple proxy for this effect in the form of a single-wave solution of an axially symmetric fast flavor system. When the angular crossing is shallow and the growth rate of the instability correspondingly small, the flavor wave primarily affects resonant neutrinos that move in phase with it. The evolution of these resonant neutrinos becomes periodic, undergoing cycles of full flavor reversal. They feed power into the unstable wave, and subsequently return to their initial state, draining power back out. This new flavor pendulum captures the dynamics of weak, nearly monochromatic fast flavor instabilities. Since weakly unstable distributions always exhibit a narrow range of unstable wavenumbers, our model likely describes the earliest development of a flavor instability when it first appears. When the instability is not weak, the linear phase of a single-wave excitation does not connect to a regular nonlinear solution, unless the angle distribution consists of only two beams.

We present a model for a topological quasicrystalline system which is suitable for realisation in cold-atom experiments. We define the model in terms of complex momentum-space couplings which break time-reversal symmetry (TRS), and detail how it may be experimentally realised using two-photon Raman couplings. In the weak-potential limit, we study the model analytically by calculating the bandstructure over a `quasi-Brillouin zone' (QBZ). We find symmetry-protected Dirac cones, which are gapped by a TRS-breaking term, resulting in a Chern number $\mathcal{C}=1$. This provides a direct analogy to the Haldane model, but now in a quasicrystalline setting. We also infer the number of states below the topological gap from the QBZ area. We verify our analysis with numerical calculations of periodic approximants to our system, constructing a phase diagram in parameter space which shows a topological region extending beyond the weak-potential regime. We also find examples of narrow Chern bands with the potential for hosting strongly-correlated physics. Our work raises questions about the nature of localisation and strongly-correlated states in Chern bands in quasiperiodic systems.

Neutral atoms for quantum computing applications show promise in terms of scalability and connectivity. We demonstrate the realization of a versatile apparatus capable of stochastically loading a 5x5 array of optical tweezers with single $^{88}$Sr atoms featuring flexible magnetic field control and excellent optical access. A custom-designed oven, spin-flip Zeeman slower, and deflection stage produce a controlled flux of Sr directed to the science chamber. In the science chamber, featuring a vacuum pressure of $3 \times 10^{-11}$ mbar, the Sr is cooled using two laser cooling stages, resulting in $\sim 3 \times 10^5$ atoms at a temperature of 5(1) $μ$K. The optical tweezers feature a $1/e^2$ waist of 0.81(2) $μ$m, and loaded atoms can be imaged with a fidelity of $\sim 0.997$ and a survival probability of $0.99^{+0.01}_{-0.02}$. The atomic array presented here forms the core of a full-stack quantum computing processor targeted for quantum chemistry computational problems.

We report temperature-dependent switching between lower and upper polariton condensation in a GaAs/AlGaAs microcavity when both of these species have comparable populations in a mixture. Using angle-resolved photoluminescence, we observe that at low temperatures, condensation occurs in the lower polariton branch, while at elevated temperatures, the upper polariton branch can become favored. At an intermediate temperature, we observe instability in the condensate formation, characterized by metastable correlations of the fluctuations in intensity and linewidth of the lower and upper polariton branches.

In this note we propose a two-layer viscous mechanism for preventing finite time singularity formation in the Moffatt-Kimura model of two counter-rotating vortex rings colliding at a nontrivial angle. In the first layer the scenario is recast within the framework of the study of turbulent dissipation based on a suitably defined `scale of sparseness' of the regions of intense fluid activity. Here it is found that the problem is (at worst) critical, i.e., the upper bound on the scale of sparseness of the vorticity super-level sets is comparable to the lower bound on the radius of spatial analyticity. In the second layer, an additional more subtle mechanism is identified, potentially capable of driving the scale of sparseness into the dissipation range and preventing the formation of a singularity. The mechanism originates in certain analytic cancellation properties of the vortex-stretching term in the sense of compensated compactness in Hardy spaces which then convert information on local mean oscillations of the vorticity direction (boundedness in certain log-composite weighted local bmo spaces) into log-composite faster decay of the vorticity super-level sets.

A dense neutrino plasma can exhibit collective flavor evolution caused by neutrino--neutrino refraction. Recently, a new class of exact nonlinear inhomogeneous solutions was discovered: single-wave (SW) solutions of the fast flavor system. The key property is that the flavor occupation numbers remain homogeneous, whereas the field of flavor coherence varies spatially with a single wave vector. The equations of motion for this structure resemble those of a collection of classical spins, in analogy with the homogeneous slow and fast flavor cases. In contrast, the SW system is not integrable (it does not possess Gaudin invariants) so that, while two-beam pendulum solutions are inevitable, they do not extend to a multi-angle system. We develop a taxonomy of all known nonlinear collective flavor solutions, explaining the overlap between categories and their differences.

We establish the existence of smooth solutions for the LYZ equation at the critical phase $θ=(n-2)\fracπ{2}$, thereby solving the critical case of a problem posed by Collins-Jacob-Yau and Li concerning the solvability for phase $θ\leq (n-2)\fracπ{2}$. As applications, we solve the 3D Hessian equation $σ_2 = 1$ and the 4D Hessian quotient equation $σ_3 = σ_1$ under weaker assumptions than previously required.

In this note we give formulas for cup product in Tate cohomology in terms of inhomogeneous cochains. Using one of these formulas, for a torus T defined over a non-archimedean local field K and splitting over a cyclic extension of K, we compute explicit cocycles representing all cohomology classes in H^1(K,T).

Extended warm and cold gas nebulae, with complex morphologies and kinematics, have been observed in the centres of cool-core galaxy clusters. Their origin within the hot intracluster medium (ICM) is still puzzling, and among many mechanisms, positive feedback from the central active galactic nucleus (AGN) has been proposed. In this work, we performed a suite of very high-resolution hydrodynamic simulations of a Perseus-like cool-core galaxy cluster subject to self-regulated AGN jet feedback, which leads to realistic ICM properties. By explicitly following warm ionized, neutral, and molecular gas phases, we studied the complex interplay between AGN activity and the multi-phase ICM. While AGN feedback globally heats the ICM, we find that during the individual AGN jet bursts, hot material is also injected laterally to the jet axis, within the turbulent mixing layer. This material, as it expands, compresses the surrounding hot ICM, reducing the local cooling time, and leads to the formation of cold clumps on a characteristic timescale of $\sim 30$ Myr. By employing tracers, we explicitly track cooling within the affected regions, finding that very hot gas identified in high-compression, low-vorticity zones condenses in situ to form cold clumps. A statistical analysis reveals that the condensation of cold gas is highly promoted once the local turbulent Mach number, $σ_{hot}/c_{s,hot}$, in the hot gas component ($T \geq 10^7$ K) takes values around ~0.3. The presented process is a further important step in understanding the physical mechanisms that lead to the formation of cold gas in the cluster core. Our measured values of the characteristic turbulent Mach number, together with detailed multi-phase gas kinematics predictions, provide important theoretical tools to interpret future X-ray spectroscopy and deep radio data, ultimately to constrain the origin of cool-core cluster nebulae.

Learning, inference, memory, and emergence in biological and artificial systems are often described using disparate theoretical frameworks. Here we develop a cognitive field theory in which cognition is described as a collective nonequilibrium phenomenon governed by the geometry and relaxation spectrum of a learned cognitive manifold. Starting from a stochastic cognitive-field equation on an adaptive Riemannian cognitive manifold, we derive a memory-dressed cognitive field equation incorporating nonlocal memory kernels and retarded self-energy feedback. We show that the local stability structure of learned cognitive geometry generates a spectrum of collective relaxation modes whose distribution is characterized by a time-scale density of states (TDOS). The TDOS provides a fundamental dynamical descriptor of cognition and determines the emergent memory kernel, collective response, and infrared temporal organization of the cognitive field. The accumulation of weakly damped collective modes suppresses the cognitive forgetting gap, enhances collective susceptibility, and drives the system toward a protected near-critical regime characterized by long-time contextual persistence and collective cognitive coherence. The resulting framework provides a unified dynamical description of learning, memory, inference, selfhood, and emergent cognition in terms of the collective organization of a memory-dressed cognitive field.

Variational counterdiabatic (CD) driving is a disciplined and widely used method to robustly control quantum many-body systems by mimicking adiabatic processes with high fidelity and reduced duration. Central to this technique is a universal structure of the adiabatic gauge potential (AGP) over a parameterized Hamiltonian. Here, we reveal that introducing a new degree of freedom into the theory of the AGP can significantly improve variational CD driving. Specifically, we find that the algebraic characterization of the AGP is not unique, and we exploit this nonuniqueness to develop the weighted variational method for deriving a refined driving protocol. This approach extends the conventional method in two aspects: it assigns customized weights to matrix elements relevant to specific problems, and it effectively incorporates nonlocal information into local driving coefficients. We also develop an efficient numerical algorithm to compute the refined driving protocol using computer algebra. Our framework is broadly applicable and, in principle, it can replace any previous use of variational CD driving. We demonstrate its practicality by applying it to adiabatic evolution along the ground state of a parameterized Hamiltonian. This proposal outperforms the conventional method in terms of fidelity, as confirmed by extensive numerical simulations on quantum Ising models.

We present a unified overview of recent progress in the study of QCD radiation in heavy-quark jets, focusing on the dead-cone effect. Using precision data from LEP at $\sqrt{s}=91.2$~GeV, we demonstrate strong momentum-space suppression in charm and bottom quark jets, supported by Monte Carlo simulations with \textsc{Pythia}8, and provide a quantitative interpretation within the Modified Leading Logarithmic Approximation (MLLA) of perturbative QCD. We then extend the analysis to top-quark jets at $\sqrt{s}=1$~TeV, where finite lifetime effects and decay radiation introduce new conceptual challenges. A new method is presented to isolate the top-quark dead cone by separating production and decay radiation, and it is validated at both parton and hadron level using \textsc{Pythia}8. Together, these results establish a coherent framework for testing QCD radiation dynamics across all three heavy quarks.

This paper introduces a boundary integral equation for time-harmonic electromagnetic scattering by composite dielectric objects. The formulation extends the classical Müller equation to composite structures through the global multitrace method. The key ingredient enabling this extension is the use of the Stratton-Chu representation in complementary region, also known as the extinction property, which augments the off-diagonal blocks of the interior representation operator. The resulting block system is composed entirely of second-kind operators. A Petrov-Galerkin (mixed) discretization using Rao-Wilton-Glisson trial functions and Buffa-Christiansen test functions is employed, yielding linear systems that remain well conditioned on dense meshes and at low frequencies without the need for additional stabilization. This reduces computational costs associated with matrix-vector multiplications and iterative solving. Numerical experiments demonstrate the accuracy of the method in computing field traces and derived quantities.

We show that quantum search can be used to compute the hardness to round an elementary function, that is, to determine the minimum working precision required to compute the values of an elementary function correctly rounded to a target precision of $n$ digits for all possible precision-$n$ floating-point inputs in a given interval. For elementary functions $f$ related to the exponential function, quantum search takes time $\tilde O(2^{n/2} \log (1/δ))$ to return, with probability $1-δ$, the hardness to round $f$ over all $n$-bit floating-point inputs in a given binade. For periodic elementary functions in large binades, standalone quantum search yields an asymptotic speedup over the best known classical algorithms and heuristics. We then estimate the resources required for a fault-tolerant implementation of the proposed algorithm for the $\sin$ and $\cos$ functions in double precision. We find that, although the algorithm can in principle compete with the fastest known practical method for computing the hardness to round over all binades in the format, it requires qubit coherence times that are unrealistically long for present technology.

The Internet of Underwater Things (IoUT) supports marine sensing, environmental monitoring, subsea inspection, and autonomous underwater operations. However, IoUT communication is constrained by limited bandwidth, long propagation delay, time-varying underwater channels, intermittent connectivity, and strict energy budgets. Semantic Communication (SC) offers a promising alternative by transmitting task-relevant meaning rather than raw data, thereby improving communication efficiency in resource-constrained underwater networks. This paper presents a critical and feasibility-aware survey of SC for IoUT, focusing on opportunities, challenges, limitations, and future research directions. We first review the fundamentals of SC-enabled IoUT systems, including semantic representations, layered architectures, semantic channel modeling, and task-oriented evaluation metrics. We then examine learning-driven approaches based on machine learning (ML), knowledge graphs (KGs), vision-language models (VLMs), generative models, and federated learning (FL), with emphasis on their feasibility under underwater edge constraints. Representative applications, including environmental monitoring, marine ecology, subsea infrastructure inspection, disaster response, and autonomous underwater vehicle (AUV) coordination, are analyzed from an SC perspective. Finally, we identify key research directions involving standardized semantic models, reproducible testbeds, compute--communication trade-offs, trustworthy reconstruction, hybrid underwater links, energy-aware edge intelligence, semantic security, digital twins (DTs), and cross-domain interoperability. This survey provides a structured foundation for developing reliable, efficient, and meaning-driven IoUT communication systems.

Empirical evidence shows that wealthy households have substantially higher saving rates and markedly lower marginal propensity to consume (MPC) than other groups. Existing theory cannot account for this pattern without jointly imposing restrictive assumptions on returns, discounting, and preferences. In this paper, we develop a general theory of optimal savings with preference shocks and identify a novel mechanism through which stochastic risk preferences reshape the asymptotic consumption and saving behavior. Specifically, the mere possibility of becoming less risk averse next period raises the value of carrying wealth forward, since future selves may be more willing to convert wealth into consumption. Unlike the classical precautionary saving motive, which typically arises from resource risks and weakens as wealth increases, this force remains operative even at arbitrarily high wealth levels, generating a persistent incentive to defer consumption and driving the asymptotic MPC to zero (i.e., a 100% asymptotic saving rate). As a result, vanishing MPCs emerge as a generic implication of risk preference dynamics, rather than an artifact of restrictive assumptions, offering a theoretically robust and empirically consistent account of the persistently high saving rates and low MPCs observed among wealthy households.

This paper develops a generalized finite horizon recursive solution to the discrete time stage bound disturbance attenuation regulator (StDAR) for state feedback control. This problem addresses linear dynamical systems subject to stage bound disturbances, i.e., disturbance sequences constrained independently at each time step through stagewise squared two-norm bounds. The term generalized indicates that the results accommodate arbitrary initial states. By combining game theory and dynamic programming, this work derives a recursive solution for the optimal state feedback policy. The optimal policy is nonlinear in the state and requires solving a tractable convex optimization for the Lagrange multiplier vector at each stage; the control is then explicit. For systems with constant stage bound, the problem admits a steady-state optimization expressed as a tractable linear matrix inequality (LMI) whose empirical computational cost is approximately cubic in $n$. Numerical examples illustrate the properties of the solution. This work provides a complete feedback solution to the StDAR for arbitrary initial states. Companion papers address the signal bound disturbance attenuation regulator (SiDAR): the finite horizon solution in Part~I-A and convergence properties in Part~I-B.

Time-to-event endpoints are central to evaluating treatment efficacy across disease areas. In clinical trials with time-to-event endpoints, the information available for interim and final analyses is largely determined by the number of observed events rather than by the number of enrolled patients. Interim monitoring therefore requires assessing how many additional events are expected to accrue by scheduled future analysis dates. Quantifying uncertainty around these counts is essential for assessing whether planned information levels are likely to be reached, anticipating delays or event overrunning, and supporting operational decisions while the trial is ongoing. This is especially relevant in pediatric oncology trials, where event accrual is often uncertain. Although methods for predicting time to endpoint maturation are well established, interval prediction for event counts at fixed calendar times remains less developed. We propose a patient-level framework for constructing such intervals at interim analyses of time-to-event trials. Conditionally on the interim data, the future count follows a Poisson--binomial law with patient-specific event probabilities; we estimate this law using a conditional parametric bootstrap. Under standard regularity conditions, the bootstrap is consistent and yields asymptotically calibrated prediction intervals. The framework accommodates staggered entry, patient-level covariates, administrative censoring, random loss to follow-up, and possible dependence between entry dates and loss to follow-up before conditioning on the realised interim data. We study its operating characteristics in simulation studies and illustrate it using a real-world phase III trial in childhood acute lymphoblastic leukaemia.

Schrödinger symmetry has been shown to emerge in a ``fluid limit" from the full superspace to several mini-superspace models. To investigate one aspect of the robustness of this emergent symmetry, we consider two spherically-symmetric static mini-superspace models with matter fields at the classical level: (i) a Maxwell field with a cosmological constant and (ii) $n$ massless scalar fields. By developing a method based on canonical transformations, we demonstrate that for model (i), 3D Schrödinger symmetry emerges, and the solution is the (anti-)de Sitter Reissner-Nordström spacetime, and for model (ii), $(2+n)$D Schrödinger symmetry appears, and the solution is a generalized Janis-Newman-Winicour spacetime and its ``interior", a Kantowski-Sachs type closed universe. Furthermore, for the vacuum model, we find that 2D Schrödinger symmetry holds with different lapse functions and mini-superspace coordinates, suggesting the potential, yet unconfirmed, covariance of the symmetry. Finally, we propose a physical interpretation of the symmetry under the Hamiltonian constraint $H$: symmetry generators commuting with $H$ map a solution to another one, while those non-commuting with $H$ generate a new theory with the Schrödinger symmetry and the transformed configuration is a solution to the new theory. These results reinforce the robustness of the emergent Schrödinger symmetry and open new frontiers for exploring dynamics of matter and gravity.

Optically pumped atomic magnetometers (OPAMs) offer high sensitivity at room temperature and are increasingly considered for portable magnetic sensing in geomagnetic-field environments. Here we report a handheld-scale, single-beam scalar $^{87}$Rb OPAM with a sensor-head volume of approximately 110~mL. The device operates in an all-optical Bell-Bloom configuration and uses digital lock-in, dispersive tracking of the $^{87}$Rb Larmor resonance, implemented with a hybrid electronics stack that combines in-house control hardware with commercial modules. A single frequency-modulated laser beam performs both pumping and probing without RF coils. All signal processing is realized in Python on a single-board computer paired with a commercial off-the-shelf (COTS) data-acquisition module, enabling immediate deployment without dedicated signal-processing hardware. The magnetometer has an intrinsic in-band field sensitivity of approximately 21~pT/$\sqrt{\mathrm{Hz}}$, estimated from the lock-in dispersion slope, over a 0.1--30~Hz closed-loop in-band region with a digital-output rate of 200~samples/s. In an unshielded Earth-field deployment, we detect repeatable transient magnetic signatures from a controlled elevator motion sequence and quantify standoff observability over sensor-elevator distances from 1.25~m to 10~m. These results show that compact scalar OPAMs can provide bandwidth and range-resolved event sensitivity suitable for field-deployable magnetic anomaly detection and infrastructure monitoring in realistic geomagnetic environments.

The recent exceptional growth in special issues has led to the largest delegation of editorial power in the history of scientific publishing. Has this power been used responsibly? We provide the first systematic analysis of endogeny, the practice of publishing articles in ones own special issue. While moderate levels of endogeny are common, excessive endogeny constitutes scientific misconduct, as it stems from a clear conflict of interest. We define special issues containing more than 33% endogeny as SI-hacked. We build a dataset of over 100,000 special issues published in 2015-2025 by five leading publishers. The large majority of guest editors engage in endogeny responsibly, if at all. Nonetheless, despite endogeny policies by publishers and indexers, SI-hacking is endemic. All journals heavily relying on special issues host SI-hacking; more than 1,000 hacked SIs are published each year, hosting tens of thousands of endogenous articles. Egregious SI-hacking is rare, editors exceeding endogeny thresholds mostly to the extent that publishers allow them to. This is not good news, as it reflects a widespread normalisation of guest editor conflicts of interests. Fortunately, SI-hacking can be solved by enforcing existing common sense policies. We provide data and analyses needed for indexers and regulators to act.

Interstellar objects (ISOs), particularly those with cometary activity, provide unique insight into the primordial physical and chemical conditions present during the formation of the planetary system in which they originated. Observations in the sub-mm regime allow for direct measurements of several parent molecules released from the comet nucleus into the coma. Here we present observations of the third ISO, 3I/ATLAS, with the `Ū`ū heterodyne receiver on the James Clerk Maxwell Telescope (JCMT), which targeted emission from HCN($J = 3 - 2$) and CO($J = 2 - 1$). Our observations, taken between 16 July 2025 and 21 July 2025 (UT), when 3I/ATLAS was at a heliocentric distance between 4.01 and 3.84 au, provide the earliest sub-mm constraints on its activity. We do not detect HCN or CO in these epochs, with 3$σ$ upper-limits on the production rates of $Q(HCN) < 1.7 \times 10^{24}$ s$^{-1}$ at $r_h = 4.01 - 3.97$ au and $Q(CO) < 1.1 \times 10^{27}$ s$^{-1}$ at $r_h = 3.94 - 3.84$ au, respectively. We combine this HCN limit with later JCMT observations of HCN to constrain its temporal evolution. Fitting the HCN detections with a $Q(HCN) \propto r_h^{-n}$ model and accounting for the upper-limits yields $n = 12.7^{+6.9}_{-2.5}$. This slope is steeper than those of typical Solar System comets, but consistent with the production rate slopes measured for other species in the coma of 3I/ATLAS.

Evolution occurs in populations of reproducing individuals. In stochastic descriptions of evolutionary dynamics, such as the Moran process, individuals are chosen randomly for birth and for death. If the same type is chosen for both steps, then the reproductive event is wasted, because the composition of the population remains unchanged. Here we introduce a new phenotype, which we call a replacer. Replacers are efficient competitors. When a replacer is chosen for reproduction, the offspring will always replace an individual of another type (if available). We determine the selective advantage of replacers in well-mixed populations and on one-dimensional lattices. We find that being a replacer substantially boosts the fixation probability of neutral and deleterious mutants. In particular, fixation probability of a single neutral replacer who invades a well-mixed population of size $N$ is of the order of $1/\sqrt N$ rather than the standard $1/N$. Even more importantly, replacers are much better protected against invasions once they have reached fixation. Therefore, replacers dominate the mutation selection equilibrium even if the phenotype of being a replacer comes at a substantial cost: curiously, for large population size and small mutation rate the relative reproductive rate of a successful replacer can be as low as $1/e$.

In this short note, we provide an explicit sufficient condition for non-explosion of Crump--Mode--Jagers branching processes with pure birth reproduction. It shows that the standard sufficient condition for explosion, namely the convergence of the series of reciprocals of the birth rates, is -- at least for rate sequences without excessive oscillations -- remarkably close to being necessary. At the same time, it is not necessary in full generality: we construct a counterexample which also yields a general preferential attachment tree without fitness with an infinite path and no vertices of infinite degree, thereby answering an open question previously raised in the literature.

This paper formalizes a widely used dynamical class--replicator-mutator dynamics and Price-style selection-and-transmission--and makes explicit the modeling choices (scale, atomic unit, interaction topology, transmission kernel) that determine how this class instantiates across domains. The backbone is known; we do not claim to have discovered selection. The novel contributions are threefold: (i) a scale-relative kernel parameterization where atomic units are themselves parameters, enabling systematic instantiation across physics, biology, economics, cognition, and social organization; (ii) a consent-friction instantiation for political philosophy, where friction is the primitive, legitimacy functions as survival probability, and belief-transfer functions as mutation kernel; and (iii) a derivation path from social contract theory rather than from biology or physics, arriving at the same formal structure via an independent route. We provide a bridge principle connecting descriptive dynamics to instrumental normativity: if agents prefer lower expected friction, then "ought" claims are shorthand for policies that reduce expected friction under the specified dynamics. This conditional structure avoids the is-ought fallacy while grounding normative discourse in empirically tractable dynamics. We address pathological cases (authoritarian stability, suppressed friction) through explicit modeling of latent versus observed friction. The framework generates testable predictions through operationalization of friction, legitimacy, and belief-transfer dynamics, and is falsifiable at the level of measurement apparatus rather than formal structure.