Papers

Dark modes arise when destructive interference prevents selected bosonic degrees of freedom from coupling to environmental channels. We formulate a Hamiltonian criterion for identifying such modes in multimode bosonic systems by separating two requirements: the candidate mode must be invisible to the direct system–environment coupling, and its generated operator space must remain invariant under the intrinsic system dynamics. For linear environment coupling and quadratic system Hamiltonians, the criterion is reduced to the the familiar null-space and invariant-subspace conditions of passive linear dark-mode theory. We then extend the analysis to nonlinear scenarios. For a two-photon conversion channel coupled to an auxiliary environmental mode, interference among nonlinear conversion pathways can reduce the environment coupling to a single collective two-photon channel, leaving a complementary bosonic mode decoupled from the environment. We show that preserving this mode under nonlinear intrinsic dynamics generally requires more than conventional Kerr-type quartic interactions: correlated four-boson conversion processes are needed to cancel mixed nonlinear conversion between the dark and environment-coupled collective modes. Finally, we show that the Bogoliubov dark mode of a parametrically driven optomechanical satisfies the same Hamiltonian criterion through an active canonical transformation. These results provide a unified Hamiltonian framework for identifying and engineering dark modes in linear, nonlinear, and driven bosonic systems.

We propose a mechanism for the generation of intense ultrafast mid-infrared radiation from heavily doped semiconductors. An ultrafast optical pulse transfers a finite impulse to the free carriers, displacing the screening clouds surrounding ionized dopants and inducing coherent plasma-frequency oscillations of the resulting polarization. We derive an exact analytical solution for the corresponding nonequilibrium dynamics and the resulting far-field radiation emitted by a thin semiconductor film. For realistic parameters of heavily doped GaAs, the emitted mid-infrared pulses can reach electric-field amplitudes on the order of $10^7\,{\rm V/m}$ directly in the far field, without relying on optical focusing.

We study the weakly coupled elliptic Anderson model with spatial white noise on the four-dimensional torus, which provides a basic example of a critical SPDE requiring renormalization at arbitrarily high orders. With coupling $\lambda |\log\varepsilon|^{-\frac12}$ where $\lambda>0$ is sufficiently small, we prove that the Green's function of the corresponding random Schrödinger operator, suitably centered and rescaled, converges to a centered Gaussian random field with explicit covariance. The main difficulty is that, for such critical models, one must expand up to order $|\log\varepsilon|$, while the perturbative expansion contains factorially many pairings and a growing number of renormalization terms. To overcome this, we construct a truncated renormalized parametrix and prove sharp high-order bounds for its remainder. A central ingredient is a multiscale analysis based on a new version of Hepp trees, combined with new estimates for summations over permutations. These estimates reveal a precise balance between logarithmic losses from scale summation and factorial gains from the structure of primitive pairings. The methods developed here are intended as a first step toward a general theory for critical SPDEs with weak couplings.

We study a class of diffusion processes on $\mathbb{R}^n$ interacting through a symmetric matrix $X\in\mathbb{R}^{n\times n}$. When eigenvectors of $X$ are Haar-uniform on the orthogonal group, we derive a dynamical mean-field limit for the empirical law of sample paths, extending the classical Sompolinsky–Zippelius characterization for $X\sim\mathrm{GOE}$. The limit takes the form of a generalized Langevin equation with correlated Gaussian noise and memory, whose correlation and response kernels relate to those of the original dynamics through convolution equations involving the free cumulants of the eigenvalue distribution of $X$. For the overdamped Langevin diffusion associated with $\mu(\boldsymbol{\theta})\propto \exp\!\big(\frac12\boldsymbol{\theta}^{\top}X\boldsymbol{\theta}\big)\prod_{i=1}^n\nu(\mathrm{d}\theta_i)$, we analyze the mean-field limit under a rapid-mixing assumption. The correlation and response kernels admit time-translation-invariant approximants satisfying a fluctuation-dissipation relation. The generalized Langevin equation admits a Markovian approximation coupled to an auxiliary multivariate OU process and converges to a replica-symmetric prediction for the empirical coordinate law under $\mu$. This auxiliary correlation structure is characterized through the infinitesimal generator of a Markov semigroup for the lifted path-history process. Consequently, the free energy converges to a replica-symmetric limit under an explicit high-temperature condition, which for an Ising model is $\|X\|_{\mathrm{op}}<1/2$. By recent dynamical universality results, the same free-energy characterization holds for deterministic models without random disorder when $X$ satisfies a set of deterministic delocalization conditions.

We prove that, over an arbitrary field and whenever $q$ is not a root of unity, the Baseilhac–Kolb root vectors form a PBW basis of the $q$-Onsager algebra for every total order on the positive roots of $\widehat{\mathfrak{sl}}_2$. This removes the previous transcendence hypothesis. We establish twelve PBW bases in the alternating generators and show that they persist under arbitrary scalar central specialisation of the alternating central extension. We determine the centraliser of the negative alternating subalgebra and that of the first imaginary alternating generator, and deduce that the four single-family alternating polynomial subalgebras are maximal commutative. Together, these results settle four conjectures of Terwilliger and, in characteristic different from $2$, a conjecture of Baseilhac and Belliard.

This work investigates nonlinear uncertainty propagation in perturbed astrodynamics, focusing on the rapid characterization of non-Gaussian distributions and the construction of three-dimensional "banana-shaped" confidence boundaries. To bridge the gap between computationally intensive high-fidelity methods and inaccurate linear approximations, this paper introduces a fully analytical, sample-free framework for higher-order moments extraction. Leveraging Differential Algebra to bypass repeated numerical integration, statistical moments are extracted analytically via Isserlis' theorem and a monomial-to-Hermite basis transformation. A pair-product projection strategy is exploited to overcome the severe computational bottleneck of full fourth-order tensor contractions and compute only relevant terms via efficient polynomial algebra. The extracted skewness and kurtosis components directly parameterize non-elliptical confidence geometries that capture spatial bending and out-of-plane coupling of typical non-Gaussian distributions in astrodynamics. The approach is validated in high-fidelity environments including a cislunar Near-Rectilinear Halo Orbit and close-proximity trajectories around Apophis during Earth's flyby, where the analytical approach achieves geometric accuracy comparable to expensive Monte Carlo simulations while reducing computational runtime by orders of magnitude.

Nonrelativistic spin splitting (NRSS) in collinear antiferromagnets, including altermagnets and compensated ferrimagnets, offers a route to high-frequency spintronics immune to stray fields, but its dynamic control has remained elusive. We demonstrate, using density functional theory (DFT) and nonlinear phononics, that THz laser pulses can achieve ultrafast, reversible control of NRSS on picosecond timescales in antiferromagnets. We derive two mode-selection criteria, accounting for phonon and magnetic wavevector compatibility and inversion parity, to identify which phonon modes can activate NRSS. Our calculations illustrate the creation of NRSS in spin-degenerate NiO and the enhancement of existing splitting in LaFeO$_3$. While practical implementation depends on excitation conditions, lattice dynamics, and mode coupling, these results establish design principles for identifying materials with stronger and more accessible responses. Limitations imposed by driving fields, phonon damping, and anharmonic detuning motivate further materials screening based on accessible excitation strengths, lattice stability, resonance frequency matching, and favorable anharmonic coupling.

Modelling rarefied gas flow using the Boltzmann equation is vital in many areas. Because of the high dimensionality and coexistence of multiple characteristic scales, conventional solution strategies for this equation incur prohibitively high computational costs and are inadequate for rapid response in engineering design simulations. Based on proper generalised decomposition (PGD), we propose an a priori, asymptotic-preserving reduced-order method for the high-dimensional parameterised Shakhov kinetic model equation. Separated representations reduce the kinetic problem to a set of low-dimensional problems. We incorporate synthetic equations into the PGD iteration so that, in the hydrodynamic limit, the iteration reduces to solving the Navier-Stokes equations, whose solution naturally exhibits a low-rank structure. Furthermore, treating the rarefaction parameter as an additional coordinate yields a solution over the whole range of rarefaction in one offline computation. It enables fast online queries to any point in the parameter space. Numerical examples using this method show reasonable precision and a significant reduction in computational cost.

We present a unified, geometry-resolved framework for analyzing absorption, resonance fluorescence, entanglement negativity, and phase-space quasiprobability in Doppler-broadened four-level atomic vapor. Using a density-matrix formalism with thermal velocity averaging and exact dressed-state diagonalization, we show that these observables constitute complementary projections of a common coherence-driven phase-space structure governed by multiphoton interference. Central to this framework is the Stratonovich-Weyl (SW) Wigner function, which provides a unified phase-space representation incorporating both populations and coherences. Direct comparison reveals a near one-to-one correspondence between SW quasiprobability distributions and entanglement landscapes, with geometry-dependent features, including hyperbolic dispersion asymptotes and split resonance ridges, consistently preserved. Furthermore, isolating the Doppler-odd component yields an eigenvalue-free proxy that captures the coherence geometry underlying entanglement negativity, providing a non-invasive quantum correlation witness. At the same time, resonance fluorescence emerges as a thermally robust observable: unlike susceptibility-based absorption, its additive pole weighting preserves sharp Autler-Townes spectral features under strong driving. This robustness enables fluorescence to accurately track bright dressed states and entanglement extrema despite severe Doppler dephasing, establishing its dual role as a sensitive electrometry probe and correlation witness. By combining a coherence-resolved description with a Doppler-sensitive phase-space representation, the proposed framework offers an experimentally accessible, eigenvalue-free approach to quantum state characterization, enabling Doppler-resilient fluorescence-based quantum sensing and precision field electrometry in warm atomic media.

We introduce a unified entropic framework for real fluids that encompasses the van der Waals, Berthelot, Redlich Kwong, and Peng Robinson equations of state within a common thermodynamic description. The corresponding microscopic interactions are then explored using Geometrothermodynamics, GTD, through the scalar curvature $mathcal{R}$ of the equilibrium manifold. We show that curvature singularities accurately reproduce macroscopic critical phenomena, while vanishing curvature $\mathcal{R}=0$ identifies specific thermodynamic states where attractive and repulsive intermolecular forces effectively balance. Furthermore, we introduce a set of dimensionless critical-amplitude ratios $Q^i_{j}$, which reveal universal geometric features of the critical regime. Although individual critical amplitudes exhibit a logarithmic dependence on the system size, these invariant ratios organize different molecular species according to the strength of criticality and encode universal scaling features, suggesting their potential as robust classification parameters. Finally, employing Bayesian inference and Markov Chain Monte Carlo, MCMC methods, we statistically reconstruct the zero-curvature curves. The posterior distributions support the consistency of the geometric scaling behavior, demonstrating that the GTD manifold encodes non-trivial information about the underlying thermodynamical models.

Stochastic simulations can be generated from deterministic reaction-diffusion equations by discretising in space and time and interpreting coefficients in the resulting system of discretised equations as probabilities governing movement and reaction events. In this paper, we present a novel variant of this approach for nonlinear reaction-diffusion equations that employs an exponential integrator when discretising in time. The proposed method yields valid probabilities, defined by the entries of appropriate matrix functions, without the strict conditions on the time step required by a commonly-employed time discretisation scheme. Simulation results presented for one and two dimensional Porous-Fisher type models demonstrate the veracity of the method across several test problems.

Bismuth monolayer is the first two-dimensional elemental ferroelectric and an appealing platform for coupling polar order to spin-orbit-driven topology. However, its microscopic switching mechanism remains elusive. Here, using first-principles lattice dynamics and symmetry-adapted mode analysis, we identify a previously overlooked rotational pathway for in-plane polarization switching. Its energy barrier is more than four times lower than that of direct reversal, naturally explaining the vortexlike domain textures observed in molecular dynamics simulations. Remarkably, this polarization rotation also drives a spin-topological transition, changing the spin Chern number from $C_s=-2$ to $0$. Directional uniaxial strain further steers the polarization orientation and tunes the associated topological transition. These results establish polarization rotation as the switching mechanism of ferroelectric Bi monolayer and as an efficient route to electrically and mechanically programmable topology in two-dimensional ferroelectrics.

Power-law spectra are a central prediction of shock acceleration and are commonly associated with asymptotic scale invariance under diffusive transport. In finite relativistic shocks, strong anisotropy and limited residence times may restrict the number of effective shock crossings before the many-cycle diffusive limit is established. This work develops a reduced finite-cycle framework in which particle energization is described by discrete shock-crossing mappings, while downstream transport is encoded through an energy-dependent return probability. In this formulation, the local spectrum is controlled by the competition between the mean energy gain per cycle and the probability of surviving to the next cycle. A systematic decrease of the return probability with energy then produces intrinsic spectral curvature as a consequence of transport-limited cycle survival. The energy dependence of the return probability is estimated from the competition between magnetic deflection, downstream advection, and finite shock lifetime, yielding a characteristic steepening scale determined by macroscopic source parameters. For fiducial parameters relevant to compact blazar emission regions, the steepening scale lies below the ultimate acceleration cutoff, so that curvature can appear before the terminal maximum energy is reached. These results point to a pre-asymptotic finite-cycle limit of relativistic shock transport in which non-power-law spectra can arise from the limited survival of repeated shock-crossing cycles.

Color codes are promising alternatives to surface codes for universal fault-tolerant quantum computing due to their simpler lattice-surgery protocols and the transversal implementation of logical Clifford gates. However, their practical deployment has been limited by slower decoding algorithms and worse logical failure rates and thresholds compared to surface codes. Although AI-based logical-flip decoders have recently been proposed to address these challenges, no clear framework currently exists for implementing such decoders within the parallel block-wise decoding schemes in both space and time required for large-scale fault-tolerant computation. AI-based pre-decoders offer a scalable alternative due to their local nature. By performing spacelike corrections on physical qubits and timelike corrections on stabilizer measurements, pre-decoders are naturally compatible with parallel block-wise decoding schemes and lattice-surgery protocols. In this work, we introduce AI-based pre-decoders for triangular color codes. We present a novel neural-network architecture for their implementation and develop methods to simplify the complex training data generated by color-code syndrome-extraction circuits containing feedforward operations. Remarkably, we find that both logical failure rates (LERs) and runtimes improve relative to raw Chromobius decoding as the code distance increases. For example, at code distance d=31 and physical error rate $p=0.3\%$, our pre-decoder + Chromobius pipeline improves the logical failure rate by a factor of 347x while reducing runtime by 7.33x compared to raw Chromobius decoding alone. These results demonstrate that AI-based pre-decoding can substantially narrow the performance gap between color codes and surface codes, bringing color codes closer to practical large-scale fault-tolerant quantum computation.

Can AI agents visually comprehend quantum circuit diagrams and generate verified executable code–and at what cost? We present Quantum Circuit Vision, a cost-aware evaluation framework for multimodal AI agents on quantum circuit visual understanding. We construct a 132-circuit benchmark spanning 13 categories ($1$–$10$ qubits) with executable Amazon Braket code and unitary-fidelity verification. Evaluating three frontier Claude-family models at different capability-cost tiers with $n=5$ repeated trials, we find that the mid-tier model (Sonnet 4.6, $1.30\times$ credits) offers the most favorable balance on the cost-accuracy frontier: 91% pass rate on the core subset at 18% of the per-call cost of the strongest model (Opus 4.6), whose accuracy advantage is not statistically significant (paired $t$: $p=0.083$). Logistic regression confirms that circuit depth–not qubit count–is the primary predictor of failure ($p<0.001$). Chain-of-thought prompting shows no statistically significant effect (all $p>0.18$, $n=5$), suggesting that visual pattern recognition outweighs explicit reasoning strategy for structurally coupled diagrams. We propose a cascade routing strategy (cheap $\rightarrow$ expensive models) that achieves 84% accuracy at 38% of single-model cost, demonstrating that model routing dominates prompt engineering as a cost lever. We release QCV-Dataset (132 circuits, 5 modalities, 1,931 files) on Hugging Face Hub as an open evaluation infrastructure with structured metadata for discoverability, interoperability, and responsible AI documentation, and all evaluation code, cost logs, and verification scripts on GitHub for full reproducibility.

Quantum measurement is a key resource for quantum generative learning, providing intrinsic stochasticity for generating diverse quantum samples. However, in measurement-assisted state-ensemble resampling, repeated measurements can also induce overconcentration: under a fixed measurement trajectory, distinct input states progressively converge toward similar output states, suppressing input-dependent diversity. To diagnose this effect, we introduce three complementary metrics: accuracy, generative power, and input sensitivity. For Haar-random monitored circuits, we prove that one-step models retain input sensitivity up to dimension-suppressed corrections, whereas sequential monitored circuits exhibit a depth-dependent loss of input sensitivity. Motivated by this diagnosis, we propose a truncated quantum denoising diffusion probabilistic model (QuDDPM), which restricts the temporal depth of both the forward diffusion and reverse denoising processes. Numerical benchmarks show that truncated QuDDPM preserves stronger input sensitivity while maintaining accuracy and generative power comparable to the original model. These results identify measurement-induced overconcentration as a dynamical limitation of deep monitored quantum generative models and establish temporal depth as a design parameter for balancing measurement-induced randomness with input-dependent diversity.

Two-dimensional topological insulators (2D TIs) have emerged as a cornerstone of next-generation spintronic technologies due to their robust, dissipationless edge states protected by time-reversal symmetry. Initial realizations of 2D TIs have primarily focused on materials with strong intrinsic spin-orbit coupling capable of driving band inversion, an approach that significantly constrains the accessible materials landscape. More recently, a paradigm shift has occurred toward engineering topological phases in van der Waals (vdW) heterostructures, where nontrivial band topology can arise from interfacial coupling rather than relying solely on intrinsic material properties. This framework provides an exceptionally versatile platform with multiple tunable degrees of freedom, including stacking configuration, twist angle, and chemical functionalization, allowing systematic manipulation of the band topology. Furthermore, external stimuli, such as electric fields, strain, and light-matter coupling, enable dynamic and reversible control of the topological character. The combined use of vdW interface engineering and external modulation allows the realization of 2D TI phases even in otherwise topologically trivial systems, substantially expanding the accessible materials landscape. This Research Update reviews key milestones in the development of vdW-engineered 2D topological quantum materials, critically assesses outstanding theoretical and experimental challenges, and outlines promising directions for future breakthroughs.

A detailed analysis of the impulsive C2.8 solar flare SOL2023-03-19T02:12 is presented, focusing on the microwave (MW) and X-ray domains. The flare was selected because of its impulsive nature, the relatively simple magnetic morphology of its parent active region (AR) NOAA 13256, its confined evolution, its moderate intensity, pronounced non-stationary temporal behaviour, and the availability of a unique multi-wavelength dataset. This dataset includes MW spectral observations in the frequency range 2.8-12 GHz obtained with the new Solar Radio Spectropolarimeter (SOLARSPEL), together with MW images from the Siberian Radioheliograph (SRH). The flare was also observed by two imaging X-ray telescopes, Solar Orbiter/STIX and ASO-S/HXI. Nonlinear force-free field extrapolations are used to reconstruct the three-dimensional magnetic configuration of the AR. We present evidence for a direct coupling between the thermal plasma and the non-thermal electron population in the frame of collisionless plasma during the initial flare stage. Some simple relationships about electron acceleration process are presented and discussed. Analysis of the extrapolated magnetic field indicates that the flare onset was associated with a system of low-lying sheared magnetic loops located along the polarity inversion line (PIL). Given the confined nature of the event and the reconstructed magnetic configuration, we infer that magnetic reconnection most likely occurred within current sheets possessing a substantial guide-field component. The observed non-stationary QPPs in the non-thermal emission, with periods decreasing from approximately 15 to 9 s, are interpreted as signatures of a sequence of magnetic reconnection episodes occurring in different magnetic structures and triggered quasi-periodically by a process that remains uncertain, but which may involve propagating slow magnetoacoustic waves.

Many of the most luminous extragalactic transients originate from the accretion of material onto a black hole (BH) via core-collapse, stellar mergers, or the tidal disruption of a star. Some produce energetic multi-wavelength emission, displaying short, blue optical flares and bright, long-lived radio afterglows. In rare cases, these have also launched powerful relativistic jets almost exclusively detected on-axis via high-energy emission. Here we report AT 2019ijn, a radio transient discovered in the Very Large Array Sky Survey, associated with a powerful relativistic jet viewed off-axis and accompanied by a luminous ($\nu L_{\nu, opt} \sim 10^{44}$ erg/s) optical transient. Originating from a star-forming dwarf galaxy at z = 0.273, AT 2019ijn's optical flare exhibited a fast rise ($t_{rise, rest} \sim 7$ d) and shallow decline ($t_{dec, rest} > 38$ d), followed a year later by an energetic ($E \sim 2\times10^{52}$ erg) radio counterpart persisting for $>6$ years. These combined properties are unprecedented and preclude known classes of stellar explosion powered by core-collapse. Instead, the implied accretion onto a BH and associated off-axis jet invokes an exotic BH-stellar merger or a jetted tidal disruption event (TDE) by a $10^4 - 10^6 M_\odot$ black hole. Favoring a TDE, this work determines the jet-launching occurrence, with the low redshift allowing constraints on the late-time evolution in contrast to prior events. Upcoming radio sky surveys will offer an unprecedented new window for further discovery of AT 2019ijn-like off-axis relativistic transients.

We develop an entropy-based formulation of gravitational focusing in Lorentzian geometry by associating a scalar entropy functional to timelike geodesic congruences. Rewriting the Raychaudhuri equation as an entropy production law, we show that entropy accumulation governs the evolution of the expansion scalar and drives finite-time focusing. We prove that when the integrated entropy exceeds a critical threshold set by the initial expansion, geodesic incompleteness necessarily follows. This result provides a quantitative refinement of the classical singularity theorems, replacing qualitative geometric conditions with an explicit entropy criterion. Our approach offers a thermodynamic interpretation of gravitational collapse and suggests that singularities arise as endpoints of irreversible entropy growth in spacetime.

A general expectation in quantum gravity is that quantum properties of spacetime manifest themselves as fuzziness, causing an irreducible uncertainty in the measurement of spacetime-related observables. In this work, we derive the time-of-flight fuzziness for free particles within a noncommutative spacetime model with $\kappa$-Poincaré deformed relativistic symmetries. To retain the full quantum structure of the theory we work in the corresponding noncommutative space of worldlines. This provides a convenient framework for constructing quantum states and deriving the probability distributions for the parameters characterizing particle trajectories, allowing us to obtain the probability distribution of particle times of flight. Our results reproduce the well-known systematic time-of-flight correction, leading to energy-dependent departures from the special-relativistic expectation, and simultaneously predict a novel stochastic contribution to the time of flight. While the systematic contribution scales with the ratio between the particle energy and the quantum-gravity energy scale and is amplified by the propagation distance, the stochastic contribution scales as the square root of the product of the quantum-gravity length scale and the travel time, multiplied by a prefactor which depends on the particle velocity.

The current tension between early and late-Universe determinations of the Hubble constant motivates the development of independent high-redshift distance tracers. Quasars, as luminous active galactic nuclei - AGNs, provide a promising route through the empirical relation between their X-ray and ultraviolet luminosities.We construct a joint Type Ia supernova-quasar Hubble diagram and investigate whether a statistically selected quasar subsample can define a preliminary golden sample for future AGN standardization. We combine calibrated Type Ia supernovae with SDSS DR14 quasars and infer the cosmological parameters from the posterior distribution of a joint model. Posterior medians and credible intervals are obtained from the marginalized distributions. We further define redshift-dependent quasar pools from SDSS queries and select the most representative sources in each bin using a multivariate statistical-distance criterion based on redshift, optical magnitudes, and SDSS colors. The posterior analysis yields $H_0 = 71.76^{+1.67}_{-1.31}\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$ and $\Omega_m = 0.294^{+0.014}_{-0.012}$. The statistically selected quasar candidates reproduce the reference Hubble diagram with small residual dispersion across multiple redshift intervals and remain broadly distributed across the SDSS angular footprint without evidence of strong artificial clustering induced by the selection procedure.

Hydrogen cyanide (HCN) is a key molecule in prebiotic chemistry, and its availability in water is limited by hydrolysis. In this work, we estimate the hydrolysis rates of \ce{HCN}, particularly the errors associated with the rates as a function of temperature, pH and in the presence of salts containing sulfite, sulfide and phosphate. For pure water, we find an acid-catalyzed hydrolysis rate constant at ${\rm 0 ^{\circ}C}$ of $\ln (k^+_{273}/1\,{\rm M^{-1} s^{-1}}) = -12.7 \pm 1.12$ with an activation energy of $67.1 \, {\rm kJ \, mol^{-1}}$. We find a base-catalyzed rate constant of $\ln (k_{273}^-/1\,{\rm M^{-1} s^{-1}}) = -9.0 \pm 1.27$ at ${\rm 0^{\circ}C}$ with an activation energy of $89.5 \, {\rm kJ \, mol^{-1}}$. These values are consistent with estimates from the literature within our uncertainties at ${\rm pH} > 8$ but diverge from literature values at lower pH. In the presence of salts, hydrolysis is accelerated under acidic conditions to 6–14$\times$ the acid-catalyzed rate without salts. However, at ${\rm pH \gtrsim 8}$ hydrolysis rates become $2.5\times$ times slower with sulfite and sulfide. These results demonstrate the importance of estimating uncertainties associated with rates when constraining the maximum concentrations of prebiotic molecules attainable in natural waters on the Earth and other planets.

We develop the mathematical and physical formulation of cognitive cost optimization that underlies the path-integral model of consciousness. The goal-directed cognitive process is modeled as imaginary-time evolution (ITE) under a projector Hamiltonian that rewards configurations consistent with a target concept. We establish three results. First, this ITE coincides with a double-bracket flow and is therefore the Riemannian gradient flow of a Hilbert–Schmidt cost whose unique minimum is the solution. Second, a Wick rotation re-expresses this non-unitary descent as an equivalent unitary evolution on the same Hilbert space, which admits an exact discrete path-integral representation in which the oracle and the initial-state diffusion projector play the roles of potential and kinetic energy. Third, we identify the continuum from unconscious to conscious processing with the strength of the unitary interaction between the cognitive system and a neural-environment probe, recovering the Gorini–Kossakowski–Sudarshan–Lindblad (GKSL) decoherence model of Asano et al. in the Markovian weak-coupling limit, and the projective, reportable fixation of an optimized state in the strong-coupling limit, an insight-like “Aha” endpoint. Both regimes share the same ITE and path-integral structure, and only the measurement-interaction strength varies. The Wick rotation is therefore a technique of re-description, not a physical regime change.

The management of cash replenishment in Automated Teller Machine (ATM) networks requires scheduling recharges in order to minimize operational costs while maintaining high service levels and avoiding cash-outs, under uncertain and time-varying withdrawal demand. This work formulates the ATM cash replenishment problem through a Quadratic Unconstrained Binary Optimization (QUBO) model, which naturally captures nonlinear cost interactions, while incorporating operational constraints through penalty terms. The objective function combines fixed and variable replenishment costs with co-location discounts, as well as penalties for a late replenishment that could cause a service interruption. The resulting QUBO instances are solved using MegaQUBO, a GPU-accelerated QUBO solver. An empirical evaluation on a real dataset of 276 ATMs located in Italy, covering four representative months of 2022 (April, May, October, and November), benchmarks the proposed approach against a threshold-based operational policy. Results show consistent cost reductions of approximately 15%-18% while maintaining an excellent average service level (around 99.8%-99.9). Overall, the study demonstrates that QUBO-based optimization, coupled with GPU-based solving, can provide a practically deployable decision-support tool for large-scale ATM cash logistics.

We draw a structural analogy between quantum error correction (QEC) and error handling in neural circuits, with respect to their redundant encodings and constraint-based inferences. In QEC, logical information is embedded in a protected codespace within a larger Hilbert space. A set of commuting checks (e.g. stabilizer constraints) is repeatedly evaluated to produce an error syndrome that identifies which constraints were violated without directly revealing the logical state. A decoder then maps the syndrome to a recovery operation that returns the system to the codespace and suppresses logical failure below a threshold. Neural circuits exhibit error-control strategies that can be viewed through a related biological error correction (BEC) pattern: information is distributed across multiple neurons (redundant encoding), yielding reliable collective activity from error-prone unit operations of individual neurons. The structural analogy with QEC raises the question whether collective activity may be constrained on lower-dimensional manifolds (a biological codespace), allowing recurrent circuit dynamics and mismatch signals to function as syndrome-like indicators of constraint violations, driving fast corrective dynamics and slower adaptive updates. Our structural analogy also suggests that new insights into brain-inspired algorithms for collective information processing may inform novel QEC approaches. We perform numerical experiments using simplified models of qubit and neural population dynamics to illustrate the analogy.

We have experimentally realized a parabolic potential barrier for surface gravity water waves. The analogy between the resulting wave equation and the Schrodinger equation for the inverted harmonic oscillator (IHO) enables us to study the propagation of quantum-mechanical wave packets with different average energies in this iconic scattering model. We observe a clear boundary in the phase-space dynamics, namely the separatrix, which distinguishes wave packets with energies below the maximum of the IHO potential from those with energies above it. In the former case, the wave packet is blocked, whereas in the latter case, it is transmitted. We also measure the corresponding variation in momentum during this process.

Epoxy-based materials are inherently hygroscopic, absorbing moisture from the environment, which can significantly alter their short and long-term performance. The presence of graphene is often considered as a potential candidate to act as a microscopic barrier, mitigating the adverse effects of hydration on the matrix. This study investigates the impact of hydration on the glass transition and elastic mechanical properties of epoxy resins and their graphene nanocomposites, focusing on water content up to 5 %wt. Using large-ensemble molecular dynamics simulations, we analyze the temperature-driven glass transition and mechanical response of both neat epoxy and epoxy-graphene systems under varying hydration levels. Our results reveal a distinct threshold at 3 %wt water content: below this, hydration primarily reduces the glass transition temperature, while mechanical properties remain unaffected. Beyond 3 %wt, however, the mechanical properties deteriorate, highlighting a non-linear sensitivity to water uptake. Furthermore, we emphasize the critical role of ensemble size in ensuring the reliability of molecular dynamics predictions for such heterogeneous systems. Our simulations demonstrate that ensembles substantially larger than current state-of-the-art standards are necessary to achieve converged distributions of the predicted mechanical properties, particularly in highly heterogeneous hydrated epoxy-graphene nanocomposites. These findings provide novel insights into the hydration behavior of epoxy-based materials and underscore the potential of graphene to enhance their environmental resistance. This work also advances the understanding of structure-property relationships in polymer nanocomposites, offering guidance for the design of more robust materials in humid environments.

Particle charts are useful teaching tools, but the usual quark-model multiplet diagrams emphasize symmetry labels more than mass ordering. This paper presents a compact “scarab chart” for light hadrons that keeps the familiar isospin and hypercharge information while adding a mass-sensitive ordering. The chart is intended for modern physics or introductory particle physics teaching. Each tile represents a light meson or baryon, with columns labelled by isospin projection, rows ordered by an integer pion-anchored mass count, tile colour identifying hypercharge, and border colour corresponding to the pseudoscalar nonet, vector-meson nonet, baryon octet, or baryon decuplet. The chart is proposed as a pedagogical visualization. The result gives students a single visual diagram in which quark content, multiplet, strangeness, and approximate mass scale can be compared.

Thermal rectification (TR) typically relies on structural asymmetry or material heterogeneity. Here, we show that gravity alone can induce and modulate TR in gaseous systems. Using a minimal model of a single gas particle confined in a two-dimensional channel between heat baths at different temperatures, we analytically demonstrate that gravitational fields generate TR, enabling perfect unidirectional heat conduction across broad gravitational parameter ranges. This effect exhibits an intrinsic trade-off between rectification efficiency and heat power. Extending beyond the single-particle limit, numerical simulations confirm that gravitationally induced TR persists in interacting many-particle systems. Notably, in interacting gas mixtures, the rectification direction can be reversed. Gravity-mediated control of heat currents thus provides new fundamental insights into thermal transport and suggests design principles for gaseous thermal diodes.