Papers

Burning neat hydrogen in aircraft turbines eliminates carbon emissions, yet rapid reaction rates trigger nozzle flashback hazards and high nitrogen oxide emissions across flight throttles. This study investigates aerothermal holding mechanisms, flashback safety margins, and emission pathways in a dual-swirl combustor across equivalence ratios from 0.55 to 1.00. Three-dimensional simulations combine curvature-corrected shear-stress transport turbulence closure, dual-rate finite-rate and eddy-dissipation chemical kinetics, and discrete ordinates radiation, validated against experimental laser benchmarks using ASME grid standards. Advancing engine throttle triggers a topological flame transition from a faceplate-attached M-flame at lean idle to a lifted V-flame above equivalence ratio 0.895, while wall flashback safety indices consistently exceed 3.42. Nitric oxide emissions transition from water-chaperoned nitrous oxide intermediate reactions at lean idle (28.01 ppm, EINOx = 1.85 g/kg), scaling to 319.21 ppm (EINOx = 35.40 g/kg) at takeoff under thermal Zeldovich dominance, governed by a power-law exponent of 4.92. These findings deliver validated operability limits and establish an accessible workstation-based screening methodology for practical zero-carbon aero-engine combustor development.

Equations of state (EoS) for dense matter are commonly provided in tabulated pressure-energy density relations, complicating numerical implementation and potentially compromising thermodynamic consistency. In this work, we propose a piecewise-continuous analytical form with a common parametrization capable of representing a broad class of dense matter EoSs. We validate this parametrization against tabulated EoSs from the CompOSE and LALSimulation repositories. Following the initial deterministic fitting, we employed two distinct Bayesian approaches: one based on synthetic EoSs generated by adding noise to the fitted EoS and another based on multi-messenger measurements of neutron-star masses and tidal deformabilities. In both approaches, the initial best-fit parameters are used as reference values. For the considered EoSs, spanning from very soft to very stiff, the resulting fits reproduce the tabulated EoSs and the associated macroscopic neutron-star observables in the repositories with sufficient accuracy. The inferred parameters exhibit strong correlations arising from the continuity conditions imposed at the segment boundaries. These correlations persist in the low- and intermediate-density segments under multi-messenger inference but become weak in the core, reflecting the limited constraining power of current observations at high densities. The ability of a single functional form to describe EoSs derived from different microscopic frameworks, together with the recurrence of similar parameter correlations, suggests that diverse dense matter EoSs may share a common underlying structure.

In the standard $\Lambda$CDM cosmology, dark matter is assumed to be a pressureless cold fluid with $w_{\rm dm}=0$. However, the microscopic nature of dark matter remains unknown, and whether its equation-of-state parameter strictly vanishes deserves observational scrutiny. In this work, we introduce a free dark matter equation-of-state parameter $w_{\rm dm}$ within the Modified Emergent Dark Energy (MEDE) framework, constructing the MEDE+$w_{\rm dm}$ model. We systematically derive its background evolution and linear perturbation equations, and constrain the model parameters using Planck 2018 cosmic microwave background (CMB), DESI DR2 baryon acoustic oscillation (BAO), and three independent Type Ia supernova datasets: Pantheon+, Union3, and DES5YR. Using the CMB + BAO + DES5YR combination, we find a preference for a positive dark matter equation of state, $w_{\rm dm}=0.00128\pm0.00044$, together with a 3$\sigma$ level preference for quintessence-like dark energy evolution, $\alpha=-0.66\pm0.22$. When the local $H_0$ prior is included, the constraint on $w_{\rm dm}$ remains essentially unchanged, whereas $\alpha$ shifts toward the $\Lambda$CDM limit, yielding $\alpha=-0.18\pm0.18$. Bayesian model comparison favors $\Lambda$CDM over MEDE+$w_{\rm dm}$, although the preference is reduced to the weak level after including the local $H_0$ prior. Overall, current observations exhibit a $2.6\sigma$–$3\sigma$ preference for a nonzero $w_{\rm dm}$ at the parameter-posterior level, but this indication does not yet constitute a robust detection of non-cold dark matter.

To enable flexible and rapid aerodynamic performance evaluation in turbomachinery design, this paper proposes a panoramic performance prediction framework. Unlike most previous prediction models that directly predict the objective functions of interest, our approach first predicts the basic parameters of the Navier-Stokes equations, such as temperature, pressure, and density. Utilizing these basic physical quantities, it subsequently predicts key performance parameters of the turbine stage meridian plane. By adopting this methodology, our proposed panoramic performance prediction framework functions similarly to a CFD simulator, capable of predicting various objective of interest to the designers. To enhance prediction accuracy, a transformer-enhanced neural operator (TNO) is introduced within this framework. Using the Rotor 37 blades as a reference, the proposed TNO is trained to predict the performance of a transonic compressor blade in the meridian plane. The TNO can accurately predict total quantities such as isentropic efficiency, mass flow, and distributions of total pressure ratio. Remarkably, the prediction error of TNO is observed to be smaller than that of state-of-the-art deep learning operators such as the FNO and DeepONet. Furthermore, the TNO is applied to downstream tasks, including sensitivity analysis and optimization of various objective functions. The results confirm that the TNO can operate almost like a CFD simulator, while reducing the computational cost of downstream tasks by four orders of magnitude. The effectiveness and reliability of the proposed TNO for solving different kinds of downstream tasks have been well demonstrated.

This paper uses the ERA5 weather dataset to assess the impact of the wind on an equatorial space elevator. An analytical formulation establishes that the effect of wind on tether inclination and payload capacity can be captured by a single scalar: RMS wind velocity, averaged over air pressure. This formulation clarifies what constitutes excessive wind for a particular elevator and provides a direct link between wind data and elevator design parameters. Analysis of equatorial ERA5 data shows that equatorial wind loading varies strongly with geography with lower values over continents and higher values over oceans, with the majority contribution coming from the lowest 20 km of atmosphere. The data indicate that realistic equatorial winds pose a significant constraint on thin-ribbon elevator designs if align to face the wind. Combining wind and lightning statistics highlights several promising equatorial regions for anchor sites. Finally, the implications of wind loading for elevator design are examined, and several mitigation strategies are discussed to improve survivability and operational payload capacity under realistic wind conditions.

High-throughput calculations using density-functional theory (DFT) are commonly used to explore point defects for applications in power electronics and quantum technologies. There is currently a major shift away from these traditional simulation techniques towards machine learning (ML) methods. We explore a class of physics-guided ML models for predicting defect formation energies and zero-phonon lines (ZPL) to identify point defects for quantum applications. The models are specifically targeted for use in a prescreening step for accelerated high-throughput workflows, and are therefore designed to avoid the costly relaxation step typically present with ML interatomic potentials (MLIPs). We compare performance for single and double point defect systems in 4H-SiC with ridge, kernel ridge, and multilayer perceptron (MLP) models using three different descriptors representing the defect systems. For vacancies and substitutions, the optimized models give mean absolute errors (MAEs) of 0.437 eV for the formation energy and 0.202 eV for ZPLs, which is just above the level at which such predictions can be useful even beyond the targeted prescreening, i.e., in some applications they may completely replace the need for costly DFT calculations. For interstitials the MAEs are larger, 1.101 eV for the formation energy and 0.230 eV for the ZPL, which, while still useful for prescreening, will not generally be useful for more detailed characterization. Hence, while the results may be further improved by model design and optimization, the models presented in this work are already useful for prescreening in high-throughput characterization of point defects.

Foundational machine-learning interatomic potentials (MLIPs) are transforming atomistic simulations by achieving near-ab initio accuracy across large chemical spaces at a fraction of the computational cost. A central challenge in using these tools for high-throughput property calculations is translating high-level scientific intent into adaptive simulation campaigns without compromising workflow rigour. We introduce El Agente Potente, an agentic system that combines typed execution graphs with a complementary coding mode for MLIPs-driven atomistic simulations. Typed execution graphs provide structured and provenance-aware execution for standardized workflows, with large language models (LLMs) restricted to planning and routing while deterministic Python components perform scientific computation and validation. Complementing this structured execution, a coding agent constructs customized workflows for tasks requiring greater procedural flexibility while invoking existing Potente functions for supported calculations. We demonstrate El Agente Potente across computational materials discovery, molecular energy-landscape exploration, adsorption, and catalytic reaction workflows, together with systematic benchmarks of reproducibility and LLM token cost. These results establish typed execution graphs and code-based workflow construction as complementary mechanisms for agentic scientific computing, combining controlled, auditable execution with the flexibility required for customized atomistic simulations

We uncover a continuous phase transition in a quantum Hall ferromagnet (QHF) at filling factor $\nu=1$, driven by vacuum fluctuations of a cavity. Our analysis starts with a Landau level projection in dipole gauge, where we find the states to be well-represented by a tensor product of the electronic and photonic degrees of freedom. Through analytic spin wave calculations, mean-field theory and density matrix renormalization group (DMRG) simulations, we show that for a spatially antisymmetric cavity field, the uniform QHF state is stable only for weak light-matter coupling and gives way to states of inhomogeneous electron density above a critical coupling. These states involve "flanks" of uniform QHF fluids, separated by a "compact core" of doubly occupied orbitals with the core size being the order parameter, which we dub as "compact-core phases". While the fully spin polarized electronic states are product states, entanglement builds up between the uniform QHF flanks across the compact core in the $S_z=0$ magnetic sector, motivating an ansatz for the compact-core electronic states. The transition boundary is exactly derived for product electronic states in terms of matter and cavity parameters, and numerically confirmed by DMRG. We also study the thin-cylinder limit near the critical point where quantum fluctuations are enhanced, and the many-body excited states in both phases by focusing on the entanglement spectrum degeneracies. Remarkably, the photon number is found to probe the order parameter of the transition, providing a possible experimental signature of the electronic transition and the compact-core states. Our study offers a rare example of a phase of electrons stabilized solely by coupling to the enhanced vacuum fluctuations of a cavity mode.

Continuous unitary transformations repeatedly evaluate the same operator algebra as the coefficients of a Hamiltonian and its observables evolve. We compile these algebraic relationships once into a numerical operation graph that can be saved and reused for new coefficient sets, additional operators, derivatives, and forward and reverse calculations on CPUs and GPUs. Reuse is demonstrated by applying the same compiled graph to hydrogen and deuterium parameterizations of a reduced molecular model without regenerating the operator equations. The main computational challenge is construction: generated many-body algebra can contain hundreds of millions of contributions before numerical propagation begins. We address this by determining the required storage in advance and writing contributions directly into the final disk-backed representation. In a deliberately large diagnostic-enabled stress test containing more than 350 million generated contributions, peak host memory remains only about 7% above the final stored size. Cross-checks show that CPU and GPU implementations, forward and reverse operations, and repeated loading of the compiled graph reproduce the tested operations to numerical precision. This compile-once representation separates expensive operator-algebra generation from the numerical transformations that reuse it.

Observations have established that the circumbinary discs formed around post-asymptotic giant branch (post-AGB) binaries have striking similarities to protoplanetary discs around young stars. In this study, we examine the feasibility of the different stages of growth in the core accretion framework of planet formation in post-AGB discs, in order to assess whether planet formation is possible in these systems. We find that dust coagulation up to mm sizes is possible within the lifetimes of post-AGB discs, consistent with observations. We then investigate the subsequent growth of planetesimals through pebble and planetesimal accretion. If the streaming instability operates in these discs, the resulting planetesimals formed in higher-mass post-AGB discs ($M_{\rm disc}\sim0.1M_\odot$) can enter rapid pebble accretion and reach their isolation mass within the estimated disc lifetime. By contrast, in lower-mass post-AGB discs ($M_{\rm disc}\sim0.01M_\odot$), planetesimal accretion is too inefficient to produce substantial further growth. We also show that the larger aspect ratios of post-AGB discs compared to protoplanetary discs around young stars imply high pebble isolation masses and therefore potential formation of rocky planets with masses extending up to Jupiter masses. After assessing gas accretion and concurrent migration in these discs, we conclude that second generation planet formation in post-AGB discs is theoretically possible within their estimated lifetimes ($10^4$–$10^5$yr) provided that local dust-to-gas ratio enhancements and sufficiently high disc masses are achieved.

This paper introduces an online evolve–filter–relax (EFR) strategy for long-term stability of Operator Inference (OpInf) reduced-order models (ROMs) of complex fluid flow simulations. The main novelty of the new EFR-OpInf strategy is the use of online (i.e., at the learned ROM online evaluation level) spatial filtering inspired from large eddy simulation to significantly improve long-term stability and predictive performance of standard OpInf. Furthermore, the EFR-OpInf strategy reduces, and in some cases even eliminates, the need for standard $L^2$ regularization, while providing physical interpretability for the OpInf hyperparameters. The EFR-OpInf framework is modular, readily integrated into existing OpInf workflows, and accommodates a user-selected ROM filtering strategy. We demonstrate the EFR-OpInf's effectiveness using a fully non-intrusive projection-based ROM filter, a ROM differential filter, and a hybrid projection-differential ROM filter. The new EFR-OpInf models are evaluated on a high-Péclet-number convection–diffusion–reaction problem that embeds the variation in one parameter and two unsteady Navier–Stokes problems that focus on predictions beyond a training horizon: a transitional two-dimensional flow past a cylinder and a three-dimensional turbulent minimal channel flow. Across these three scenarios, EFR-OpInf can reduce prediction errors by up to an order of magnitude relative to standard OpInf. Moreover, EFR-OpInf remains stable over long prediction horizons in cases where standard OpInf diverges. Depending on the ROM filter used, EFR-OpInf's computational cost is comparable to that of standard OpInf.

The CPT theorem, combined with S-matrix unitarity, imposes nontrivial constraints on CP asymmetries in B-meson decays ~\cite{Marshak1969}. A long-standing question is whether these constraints apply in an inclusive manner—globally across all final states—or exclusively, within a final state interaction (FSI) as argued by Wolfenstein ~\cite{Wolfenstein1991}. We present the theoretical framework underlying this relationship between CP violation and the CPT theorem (CPV/CPT), deriving the CP-violating rate differences through the S-matrix formalism with final-state interactions (FSI). We propose that a precise measurement of the integrated CP asymmetry in $B^+ \to \pi^+\mu^+\mu^-$ can unambiguously discriminate between the two mechanisms.

Scientific autoformalization turns verbal accounts into executable mathematics, but executable code does not settle which model has been constructed. We examine two sources of structural uncertainty: the formalizer that generates a response law, and the recurrence that turns that law into trajectories. In secondary analyses of an openly archived crossed experiment, we studied 320 response maps generated by two pinned language-model formalizers from five engineered cognitive accounts within one sparse quadratic grammar and 16 randomized blocks. With whole blocks held out, source-account identity was recovered at 78.8% accuracy (chance 20.0%) and formalizer identity at 96.3% (chance 50.0%; both p < 0.001). Program size was the stronger single feature family; a pre-specified exploratory comparison found no stable source-account predictive gain from local geometry beyond size. Holding every response map fixed, we then evaluated five recurrence families spanning 33 configurations and 1,013,760 finite-horizon trajectories. Added feedback, projection and leak produced sharply different outcome distributions. The consequential distinction was which comparisons survived: median cross-recurrence rank concordance was 0.73 for endpoint magnitude but 0.05 for settling, among the configuration pairs with defined rankings. Thus a common mathematical language did not erase translation provenance, and robust ordering under one observable did not transfer to another. Scientific autoformalization is usefully studied as model-space construction: the generated ensemble and its dynamical embedding are both part of the specification supporting a scientific claim.

The LUX-ZEPLIN experiment has reported a single nuclear recoil candidate at $E_R = 248 \pm 23(\mathrm{stat}) \pm 23(\mathrm{sys})$~keV, disfavouring the background-only hypothesis at a global significance of $2.6\sigma$. The difficulty such an event poses is not the recoil energy itself but the absence of any accompanying excess at low energy as elastic scattering of halo dark matter yields a monotonically falling spectrum, and supplying the required momentum transfer $q \simeq 246$~MeV already demands $m_\chi \gtrsim 79$~GeV. We confront the event with the two kinematically distinct mechanisms that evade this limitation, endothermic inelastic dark matter, in which a mass splitting $\delta \sim \mathcal{O}(100)$~keV forbids low-energy recoils and boosted dark matter, in which a light relativistic flux supplies the momentum, treating both with the same model-independent scalar–scalar, pseudoscalar–scalar and pseudoscalar–pseudoscalar effective operators. The two scenarios prove spectrally distinguishable. The inelastic spectra sit near the observed energy for every operator, placing only $6$–$17\%$ of events below 150~keV, whereas the boosted spectra depend critically on the operator: the scalar and pseudoscalar–scalar interactions place $99\%$ and $92\%$ of their events below 150~keV, while the pseudoscalar–pseudoscalar interaction places $75\%$ above it. Momentum dependence is thus essential to the boosted interpretation, but in the inelastic case it trades against the splitting, the preferred $\delta$ decreasing monotonically from $\mathcal{O}_{ss}$ to $\mathcal{O}_{ps}$ to $\mathcal{O}_{pp}$. Because the scenarios differ across the whole high-energy window, a handful of additional events would separate them, placing the question within reach of the full LZ exposure.

We develop and implement a two-step location-scale analysis for repeated physical measurements when the underlying distribution is not known. For a chosen substitute distribution, stationarity of population Kullback-Leibler information loss at fixed scale motivates the location score, which we apply to the observed measurements through empirical cross-entropy. Steiner's curvature rule then defines a companion scale separately. We place Gaussian, Cauchy, and logistic substitutes in one common construction and implement them reproducibly on a physics benchmark. For the logistic substitute, we pair the established bounded location score with a scale defined by the curvature rule rather than by a fitted tuning constant or a scale-likelihood equation. For Gaussian measurements with different quoted uncertainties, an experiment-level curvature convention and a stated variance mapping give an exact algebraic connection to a standard residual-based variance estimate for a weighted fit. Applied to a published 21-measurement neutron-lifetime compilation, the inverse-variance weighted, most frequent value, and logistic locations are 878.689, 881.164, and 882.835 s, respectively. These values are benchmark results of the compared constructions and are not proposed as a new recommended neutron lifetime.

The dispersion of an excitation is commonly used to infer its microscopic character: dispersive modes are associated with propagation, whereas nondispersive features are often interpreted as localized. This distinction becomes less straightforward for composite excitations, whose spectral maxima can remain nearly dispersionless even when they are built from propagating quasiparticles. Here we use momentum- and temperature-dependent resonant inelastic X-ray scattering (RIXS) to reveal the origin of multimagnon excitations in antiferromagnetic LaCrO$_3$. Whereas the single magnon disperses strongly, the two- and three-magnon features remain nearly flat. On approaching the Neel temperature, thermal population of the magnon band produces an anti-Stokes branch and opens an additional three-magnon channel involving the creation of two magnons and annihilation of one. Its energy and momentum dependence are reproduced by a thermally weighted multimagnon joint density of states calculations. These results establish thermal population as a means of exposing the propagating constituents hidden within nondispersive composite excitations, and position RIXS as a probe of multimagnon dynamics and, ultimately, magnon-magnon interactions.

The construction of multiqubit unextendible product bases (UPBs) has been a long-standing problem. We give a systematic construction of multiqubit UPBs by studying their unextendible orthogonal matrices (UOMs) with graph-theoretic methods. Row decompositions of small UOMs produce the main intervals. Com- pletion graphs settle the remaining small UPB sizes, except for one size obtained from a good column structure. Nonexistence of the other UPB sizes follows from counts of fibres and row pairs. The computer is used only for a few finite UOM checks, whose exact tests are stated in the certificate appendix. These arguments determine the complete multiqubit UPB size spectrum in every dimension.

Droplet-laden cloud dynamics emerge from coupled phase transitions and turbulent mixing. Combining experiments and mean-field theory, we establish scaling laws for steam-injected clouds in unsaturated air seeded with condensation nuclei. Depending on whether the cloud is confined to the initial momentum-dominated zone of the jet or extends into the buoyancy-dominated plume, two asymptotic regimes arise. In the momentum regime, cloud dimensions scale with the injector radius. In the buoyancy regime, size follows a \(\dot{m}^{2/5}\) scaling, where \(\dot{m}\) is the injected steam mass flow rate. Assuming inter-droplet air remains humidity-saturated, our mean-field analysis predicts cloud persistence governed by enthalpy and humidity mixing. These findings bridge microphysical processes and macroscale dynamics, offering a quantitative framework for atmospheric cloud evolution.

We propose a variational shortcut-to-adiabaticity scheme for the fast dynamical control of one-dimensional quantum droplets in ultracold Bose-Bose mixtures. The control is implemented through time-dependent mean-field (MF) and beyond-mean-field (BMF) nonlinearities, which can be adjusted by tuning intra- and interspecies scattering lengths near Feshbach resonances. Using a bright-droplet variational ansatz, together with inverse engineering, we derive time-dependent interaction protocols that connect prescribed initial and target self-bound states while suppressing residual excitations. We analyze three representative settings: simultaneous control of the MF and BMF terms, control with fixed BMF nonlinearity and time-dependent MF interaction, and control with fixed MF nonlinearity and time-dependent BMF interaction. For the constrained cases, additional variational degrees of freedom are introduced to optimize the protocols while respecting the imposed restrictions. Direct numerical simulations of the extended Gross-Pitaevskii equation confirm final fidelities exceeding $0.99$ on short time scales, and show that the optimised protocols are robust against finite calibration errors of the nonlinear control strength. Our results provide a route toward fast state-to-state manipulation of self-bound quantum fluids and may be useful for controlled matter-wave engineering in ultracold mixtures.

Tunable low-noise lasers are crucial components employed in modern metrology. Advances in photonic integrated circuit technology have provided a new platform for compact integrated lasers with large output powers, frequency-agile tuning, and narrow linewidths. For instance, lithium niobate extended-DBR lasers can yield output powers in the tens of mW, GHz-level tuning ranges, and tuning rates in the hundreds of MHz. However, noise levels achievable in other integrated laser designs remain challenging to reach. Here, we address this challenge by implementing extended-DBR lasers in lithium tantalate, thereby achieving intrinsic linewidths as low as 24 Hz, output powers of 10 mW, with tuning features on par with those of lithium niobate. The extended-DBR laser is assembled with modern packaging solutions to improve its robustness and demonstrate long-term stability with a free-running frequency drift within a range of 232 MHz over 19 hours. These benefits, in conjunction with lithium tantalate's suitability for volume manufacturing, promise to considerably expand accessibility to a new generation of widely tunable and low-noise integrated lasers.

The hypothesis of strange quark matter (SQM) and the possible existence of strange stars have been extensively investigated within the thermodynamic bag model, typically employing the free Fermi gas approximation with or without perturbative QCD corrections at zero temperature, where quark confinement is modeled by the bag pressure. In this work, based on the perturbative inclusion of quark mass effects, we develop a thermodynamically consistent equation of state (EOS) for SQM at finite temperature, incorporating perturbative corrections up to $\mathcal{O}(\alpha_s)$ in the strong coupling constant $\alpha_s$ while ensuring full adherence to the Maxwell relations. These corrections are essential for accurately describing hot quark stars potentially formed during core-collapse events. We present results for both fixed and running couplings, using a phenomenological model to include the breakdown of the perturbative running of $\alpha_s$ at low momenta. Our results demonstrate that incorporating finite-temperature perturbative QCD corrections leads to SQM configurations that fall within the absolute stability window, with equilibrium energies per baryon lying below that of iron, the most tightly bound nucleus. Our EOS supports compact stars with masses exceeding $1.4\,M_\odot$ (and above $2\,M_\odot$ for some values of the bag constant), in agreement with current astrophysical constraints from pulsar and gravitational-wave observations.

In the conventional theory of quantum computation, universality is discussed in terms of properties of unitary gate sets. In many experimental setups, however, we instead have access to a parametrized set of Hamiltonians, which can be exponentiated for any desired time. Accordingly, we formulate a continuous analogue of universality, where adding one expensive Hamiltonian control to a cheap set of local control operators allows for universal computation. We find several concrete sets of 1- or 2-local Pauli generators $S$ and $n$-qubit “magic" Hamiltonians $H$ that together generate the full Lie algebra $\mathfrak{su}(2^n)$, with a special focus on the Ising Hamiltonian $J$. We propose a method to directly implement any unitary by exponentiating these generator sets, and give bounds on the needed time of application of the magic Hamiltonian $H$. We find that the number of applications of $H$ needed to approximate any unitary up to accuracy $\epsilon$ scales exponentially in the number of qubits as expected from the standard application of the Solovay-Kitaev theorem. We also find phase transitions in the size of the generated Lie algebras as the parameters of the Ising Hamiltonian are varied. We find an algorithmic application of the Chow/Rashevskii technique to implement unitaries corresponding to iterated commutators.

We study whether orbital redistribution in a self consistent spherical Einstein–Vlasov environment can change the asymptotic normalization of a black hole horizon while the horizon mass, particle rest mass and ADM mass are all held fixed. The matter variable is the occupation of regular bound orbital actions, so the stress tensor, orbital energies and gravitational field are determined by the same distribution. Linearization of the spherical mass constraint gives a kinetic variation law in which orbital energy is conjugate to occupation and the inner lapse ratio multiplies the horizon mass variation. On a locally regular equilibrium branch, mixed variations imply an integrated reciprocity relation between the central mass derivative of orbital energy and the directional response of the horizon normalization. We construct finite mass populations and trace constant mass redistribution curves. For the reference rest mass ratio $0.30$, the calculated endpoint surface gravity shifts are approximately $+15.37$ and $-15.33$ parts per million. The constrained response cancels at simultaneous dilute and Newtonian order, is nonzero for exact Schwarzschild orbits, and is further modified by self gravity. Independent balance, integral, derivative and refinement tests resolve the response well below its reported magnitude.

Sociology emerged from Comte's ambition to study society as a form of "social physics" and was later refined by Durkheim's concept of the social fact a collective regularity that cannot be reduced to any single individual's behavior. This essay argues that a structurally similar problem is now emerging in a new domain: interactions among artificial intelligence agents. Drawing on recent empirical work showing that populations of large language model agents can spontaneously develop shared conventions and collective biases through repeated interaction, the essay proposes a new field of inquiry the Sociology of Artificial Agents dedicated to studying the relational, normative, cultural, and organizational patterns that emerge among AI agents themselves, independent of direct human involvement. It introduces the concept of the "artificial social fact" as an analytical bridge between classical sociology and this new research terrain, while cautioning against anthropomorphizing AI systems. The claim is not that artificial agents form societies in the human sense, but that their interactions already produce measurable collective patterns worthy of systematic sociological study.

Wetterich showed that certain 1+1D probabilistic cellular automata are equivalent to fermionic QFTs and posed the 3D construction as an open problem. We construct one: a layered automaton ("coincube") whose conversion blocks form the real quaternion representation of Cl(0,3), controlled by binary environment fields whose streaming outruns the carrier ("fresh tape") – no bit is consulted twice, and the single-particle ensemble propagator equals the annealed Bloch operator at every time. Exact results: the step operator is unitary for an explicit complex structure; the local Grassmann action is extracted mechanically; the single-carrier excitation is a Weyl fermion with an isotropic leading cone (slope ratios 1 within errors, factorized transport excluded by >=10 error bars); at finite momentum the node carries a parity-odd anisotropy c(q)kx ky kz/|k|, cancelled on the Dirac branch whose gap is 2 arctan[qm/(1-qm)], while off-resonant spectators stay massless; media-mediated interaction obeys Ug = (1-2gq^2) U. Obstructions: ballistic transport admits only finite velocity sets; Abelian sign gauges leave the factorized surface; no protected 2-component node survives an exhaustive search. Finally, a dichotomy for the quaternionic event class: an isotropic cone forces overdamping – Q = w_0/Gamma <= pi/(2 ln 2) at all densities, 0.66 at working density – while in-state unitarity forces factorized transport. Postselected two-boundary amplitudes evade this, exactly unitary at all times under the fresh tape, with induced weight positivity open: the relativistic object here is an amplitude whose probabilistic reading is unsettled.

Hamiltonian and Lagrangian mechanics are powerful frameworks for analyzing physical systems. Previous work has extended these formalisms to ecological systems, such as the predator-prey Lotka-Volterra (LV) system. In this Article, we derive a canonical Lagrangian for the two-dimensional LV model directly from its Hamiltonian representation. We find that the two-dimensional LV system admits a standard canonical Lagrangian formulation with one degree of freedom and a non-quadratic kinetic structure. This formulation admits a mechanical interpretation in terms of a particle moving in a potential well, where the non-standard kinetic structure produces a position-dependent damping term that can instead act as "revving." The derivation provides a direct connection between predator-prey dynamics and a canonical formulation of mechanical dynamics. As a verification of the construction, we apply Noether's procedure to the explicitly time-independent derived Lagrangian and reveal that the well-known Hamiltonian of the LV system is the corresponding conserved quantity. We also uncover a subtle redundancy associated with the choice of canonical momentum and its identification with the original population variables.

Early thermal-mechanical lattice requirements are knowledge-intensive and often jointly unsatisfiable: an engineer asks for a cell that is light, stiff, laterally conducting and cheap, and no cell in the library satisfies it. A design system should say so, and say which requirement to loosen and by how much, rather than return the nearest row. A generative model can return a candidate even when the library holds none. This work applies established conflict diagnosis to a catalogue of homogenised properties. Search over 1,397 homogenised unit cells and 19 base materials (26,543 combinations) returns a catalogue row that a second solver can rebuild, or, for an empty feasible set of at most eight constraints, inclusion-minimal unsatisfiable subsets (MUS) and the slack of a repair, not a neighbour. One registry declaration generates the prompt and the evaluator, so undeclared parsed keys cannot reach search. On a frozen suite of 64 typed queries, retrieve-or-refuse matches min-repair on every feasible query (48/48) and refuses every empty one (16/16) with MUS and slack. Constraint-ignoring nearest-neighbour and penalty search violate stated cost or density limits. On 216 empty queries, repairs printed at three significant figures and rounded outward stay feasible in every case (216/216). When density and cost must be kept, a list of minimum-cardinality repairs keeps them on 209 of 211 queries; a protection-first repair keeps them on all 211, the same as full diagnosis. A 308-request parse benchmark is a template-text check, not unconstrained engineer prose.

Within the entire gamut of magnetostrictive, piezomagnetic, and ferromagnetic shape memory alloy systems, the striction effect is found to vary from a few tens of parts per million to a few percent. Here, we report the observation of an unprecedentedly large magnetic-field-induced lattice strain along the $c$ axis (more than 60-100% at 90 kOe field) in single crystals of orthorhombic $R$FeO$_3$ ($R$ = Dy, Ho) below their spin-reorientation transition temperature $T_{SR}$. However, the striction effect is two orders of magnitude smaller along the $a$ and $b$ axes. Like magnetostriction, the magnetodielectric effect is highly anisotropic and very large along the $c$ axis. Such gigantic striction and dielectric effects along the $c$ axis arise as a result of a magnetic-field-induced first-order structural phase transition which possibly stems from large spin-orbit coupling (and, thereby, enormous magnetocrystalline anisotropy). The observed colossal striction in rare-earth orthoferrites could open new opportunities for applications requiring large, reversible magnetic-field-induced strain.

In this work, we derive phenomenological constraints on a symmetric black-bounce geometry supported by an anisotropic fluid. We investigate the effects of the bounce parameter and the matter parameter on classical and strong-field observables, considering the perihelion advance, light deflection, Shapiro time delay, and black-hole shadow. In the weak-field regime, we obtain analytical corrections to the corresponding general-relativistic predictions and use Solar-System measurements to constrain the parameter space. We find that the matter parameter is generally constrained more strongly than the minimum-radius scale, reflecting the suppressed dependence of weak-field observables on the bounce parameter. In the strong-field regime, we show that the asymptotic shadow radius depends directly on the matter parameter, whereas the bounce parameter enters through the existence condition of the outer unstable photon orbit rather than through an independent correction to the shadow size. These results highlight the distinct roles played by the matter and bounce parameters in weak- and strong-field observables and provide complementary constraints on the parameter space of the symmetric black-bounce geometry.

Magnetic hyperthermia integrated with magnetic resonance imaging (MRI) requires nanoparticles that combine strong heating, T2 contrast, and hemocompatibility after systemic administration. Here, we prepared citrate-stabilized ferrite nanoparticles (Fe3O4, Co0.6Fe2.4O4, Zn0.3Fe2.7O4, and Zn0.35Mn0.25Fe2.4O4) in spherical (8-10.5 nm) and quasi-cubic (9-12.5 nm) forms, along with 35 nm Fe3O4 cubes. By coupling morphology engineering with spinel-lattice cation substitution, we tuned saturation magnetization, coercivity, T2-weighted signal attenuation, and heat dissipation in ovarian tumor-mimicking phantoms under clinically compatible alternating magnetic fields. The 35 nm Fe3O4 cube and quasi-cubic Zn0.35Mn0.25Fe2.4O4 generated the highest phantom temperature rises, whereas smaller spherical particles produced softer heating. All formulations were cytocompatible in SKOV3 cells, with >96% viability at 24 h. However, hemocompatibility distinguished the leading candidates: 35 nm Fe3O4 cubes induced red blood cell deformation despite minimal hemolysis, while 9 nm quasi-cubic Zn0.35Mn0.25Fe2.4O4 showed no change versus PBS up to 1,000 {\mu}g mL-1. Perfusable GelMA models under physiological flow further confirmed biocompatibility. MRI phantoms showed that Fe3O4 cubes produced extended signal voids that may obscure boundaries. Overall, 9.5 nm quasi-cubic Zn0.35Mn0.25Fe2.4O4 is the leading intravenous candidate, combining strong heating, T2 contrast, and hemocompatibility, whereas large Fe3O4 cubes are better suited for localized intratumoral hyperthermia.