Papers

Attention enables context modeling via query-key scoring with softmax normalization. Driven by industrial long-context demands, mainstream research has converged toward sparsity and efficiency, yet softmax's independence assumption persists. For scientific tasks unburdened by long-token constraints, however, richer structured coupling may often be essential, making tailored attention both viable and more appropriate. To this end, we propose Variational-Ising-Attention (VIA), which augments softmax normalization with an interacting Ising model; attention patterns emerge from learnable pairwise couplings via variational mean-field inference, extending attention from a ranking over isolated items to a collective state over interacting entities. We instantiate VIA on retrosynthesis reaction center prediction and, as a controlled internal ablation, on protein residue contact prediction, two structured prediction tasks governed by cooperative constraints: cooperative bond-breaking for retrosynthesis and inter-residue interactions for protein contact prediction. Comprehensive experiments across model variants, coupled with mechanistic analyses, demonstrate that VIA substantially outperforms standard softmax attention. More broadly, our findings suggest that for scientific problems, the optimal solution is not general-purpose efficiency, but appropriately tailored attention aligned with intrinsic domain structure. This work provides a theoretically grounded and empirically validated instantiation of this paradigm.

Inspired by the Green's function (GF) approach in quantum field theory (QFT) and many body physics, we have developed a mathematical formalism to investigate classical multiplicative stochastic processes. Based on this approach, the interacting GF of any dynamical system subjected to classical stochastic noises, which enter into the system equations of motion in a multiplicative way, can be obtained from the noninteracting (free of noise) GF through an infinite perturbative series which may converge to an exact closed form under special conditions. Using this formalism, we have studied the effects of classical noises of the driving laser on the coherent population trapping (CPT) which have a crucial role in the performance of CPT-based atomic clocks. We have shown that if the bandwidth of the colored noise is sufficiently larger than the system damping rate, the infinite series corresponding to the interacting GF can be approximated by the closed form. The presented formalism enables us to investigate all kinds of homogeneous and inhomogeneous broadening mechanisms on the CPT transmission resonance lineshape, including dephasing due to atomic collisions, power/Doppler broadenings, as well as the broadening mechanisms due to phase and amplitude fluctuations of driving laser and compared their destructive effect with each other. It should be emphasized that the presented formalism is applicable to any dynamical system with multiplicative stochastic noises and the CPT phenomenon is just a prototype for the application of the presented formalism in practice.

Raw-Hermite sensing and collision on a fixed discrete-velocity set can convert a uniform translation into artificial coupling between nominally distinct nonequilibrium orders. We develop a central-Hermite formulation for a D3Q125 kinetic model with order-resolved log-Gaussian relaxation and compare three variants: raw sensing/raw collision (A), central sensing/raw collision (B), and central sensing/central collision (C). In homogeneous translated second-order perturbations, model C preserves third- and fourth-order modal purity to machine precision, whereas A and B develop boost-dependent cross-order content. Across a grid-CFL-boost matrix, model C reduces the post-transport collision frame discrepancy relative to A by 65.342-98.102% (median 81.131%) in the total relative L-infinity measure. Long-time calculations remain positive and conservative to numerical precision, although the accumulated benefit is configuration dependent because transport continually re-injects frame error. A transport study further reveals a clear trade-off: central-Hermite interface reconstruction strongly suppresses the third-order discrepancy but amplifies the fourth-order discrepancy. The fully central-Hermite collision therefore substantially reduces collision-induced cross-order frame discrepancy, while residual dependence remains due to discrete transport and finite velocity-space representation. This moment-space improvement does not by itself establish a comparable reduction in macroscopic Galilean transport error.

Deep convective updraft velocities play a key role in the Earth's climate system, influencing precipitation extremes, lightning, and the planetary energy budget. While Convective Available Potential Energy (CAPE) is widely used to explain maximum updraft velocity ($w_{\max}$), CAPE is an imperfect predictor as updrafts are also influenced by entrainment, boundary layer dynamics, pressure perturbations, and condensate loading. However, the relative importance of these processes and how they interact to set $w_{\max}$ in individual clouds remains unclear. Here, we use equation learning to identify compact, physically interpretable relationships linking environmental and in-cloud conditions to $w_{\max}$ in individual tracked clouds across idealized radiative-convective equilibrium regimes spanning a range of sea surface temperatures and radiative cooling rates. For pre-storm prediction, CAPE and local mean boundary layer vertical velocity ($\overline{w_{\mathrm{bl}}}$) together explain nearly half the variance in $w_{\max}$ across regimes ($R^2=0.47$). While CAPE captures regime-mean differences, it has little predictive value within a single simulation. $\overline{w_{\mathrm{bl}}}$ is essential for capturing cloud-to-cloud variability, including the suppression of $w_{\max}$ even at high CAPE values. At the time of peak intensity, a simple approximate Bernoulli-like invariant combining maximum pressure perturbation and maximum cloud condensate explains 89% of the variance ($R^2=0.89$). The tight link between $w_{\max}$ and pressure perturbation supports the sticky thermals hypothesis and highlights the importance of dynamic pressure effects, often neglected in updraft theories. These results highlight $\overline{w_{\mathrm{bl}}}$ as an important regulator of convective intensity alongside CAPE, and demonstrate that dynamic pressure plays an important role within individual updrafts.

The realization of correlated layered magnets hosting robust ferromagnetism with emergent topological transport remains a key challenge in quantum materials. Here we report the first catalyst-free chemical vapour deposition growth of layered 1T-CrS$_2$, establishing a highly stable vdWs ferromagnet with an out-of-plane easy-axis anisotropy and a Curie temperature above room temperature. Transport measurements reveal a semimetal–insulator crossover near 80 K and pronounced negative magnetoresistance up to 350 K. A topological Hall effect emerges below 30 K, a rare signature of correlated transport in layered transition-metal dichalcogenide ferromagnets. First-principles calculations show that spin–orbit coupling gaps Dirac-like crossings, while electronic correlations reconstruct the Fermi surface by suppressing electron pockets and reducing the carrier density, enhancing momentum-dependent out-of-plane spin polarization. Magnetic measurements, supported by Heisenberg exchange calculations, reveal strong nearest-neighbour ferromagnetic exchange that stabilizes long-range ferromagnetism. Our results establish 1T-CrS$_2$ as a rare correlated 3$d$ layered ferromagnet in which electronic correlations and spin–orbit coupling cooperatively drive emergent topological transport.

We compute the weak-coupling free energy density of pure four-dimensional $\mathcal{N}=2$ supersymmetric Yang-Mills (SYM) theory through second order in the 't Hooft coupling $\lambda$ at finite temperature using effective-field-theory methods. The contribution from the hard scale $T$ is obtained from massless three-loop vacuum diagrams in the full theory, and that from the electric scale $\sqrt{\lambda}\,T$ from a two-loop calculation in the dimensionally reduced three-dimensional effective theory. In contrast to $\mathcal{N}=4$ SYM, the theory is asymptotically free: the coupling-renormalization counterterm, together with the EFT unit-operator counterterm, cancels all $1/\epsilon$ poles. The remaining renormalization-scale dependence is fixed by the one-loop beta function. The expansion reproduces earlier results through order $\lambda^{3/2}$, and the order-$\lambda^2$ term is new.

We show that the inclusion of a dimension-six operator in the Higgs potential has a dramatic impact on the stability of oscillons in the $SU(2)$ bosonic sector of the Standard Model, extending their lifetime by orders of magnitude. This happens for the physical value of the ratio between the Higgs and W boson masses, $m_H/m_W=1.556$ and for the dimension-six operator $O_6 = (\Phi^\dagger \Phi)^3$ whose coupling constant is below the current upper bound.

We present DualityCert, a symbolic verifier for candidate Seiberg-duality claims in four-dimensional N=1 quiver gauge theories. The verifier evaluates 't Hooft anomaly matching, superpotential R-charge consistency, central-charge matching, and a bounded chiral-ring proxy. A claim that passes receives a consistency certificate, which states that no tested inconsistency was found, not that the duality is proven. We use the verifier as a repair environment for language-model agents, which receive a deliberately broken claim and must edit it until it certifies. On a preregistered benchmark of 145 broken claims, with the analysis fixed before the first confirmatory model call, verifier-gated retry improves final repair success over a single attempt by +8.3 percentage points (pp) on deepseek-chat and +7.1 pp on qwen-plus (Holm-adjusted p<0.002). Under an equal budget of eleven attempts, the stop-first strategy portfolio underperforms independent verifier-filtered resampling by 10.3 percentage points on deepseek-chat but outperforms it by 14.7 points on qwen-plus, reversing the ordering of the two tested verifier-exploitation policies across the two confirmatory models. On qwen-plus, category-level verifier feedback is worth +8.7 pp over content-free retry, and interpretable obligation identities alone are worth +6.4 pp over structurally identical masked feedback. Neither effect is detected on deepseek-chat. Separately, a preregistered MiniMax-M2.5 extension again finds an iteration gain and independent verifier-filtered resampling outperforming the strategy portfolio. Which policy is better thus differs between the two models, while every winning policy uses the same cheap certificate. The verifier, benchmark, protocol, and all per-attempt records are released.

Circumstellar disc dissipation timescales constrain the window available for planet formation. At approximately 9 Myr, IC 2395 lies at a critical epoch in primordial disc evolution, yet no kinematically selected disc census exists beyond the inner cluster core. A wide-field survey of IC 2395, extending to a 2 degree radius, establishes a kinematically selected disc census and evaluates the frequency of planet-forming environments in the outer cluster field. Using a high-purity catalogue of 173 members identified via Gaia DR3 kinematics, mid-infrared excesses are identified using AllWISE photometry. Candidates are classified into two tiers: Crossvalidated (corroborated by Gaia variability) and Single-band detections. Twenty-one disc candidates are identified, 90% of which lie beyond the footprint of prior Spitzer surveys. The candidates are concentrated among low-mass members (0.31-0.68M), with no significant correlation between mass and excess (Spearman rho = +0.07, p = 0.84). A secure disc fraction of 4.0 p/m 1.5% is established by the Cross-validated subsample, independently confirmed by Gaia DR3 YSO variability classification; a photometric 3 sigma significance cut yields a consistent estimate of 2.9 p/m 1.3%. An upper bound of 12.1 p/m 2.5% is derived from all 21 W1-W2 excess candidates, with a background subtracted value of approximately 10.1%. Gaia DR3 epoch photometry reveals diverse variability morphologies, including a dramatic dipper and multiple bursters, confirming ongoing magnetospheric accretion. By extending the survey radius, this work demonstrates that infrared excess sources indicative of inner-disc emission in IC 2395 are more abundant and widely distributed than previously recognised. The survival of these discs in the lower-density outer field provides a well-characterised sample for studying the final stages of disc evolution and planet formation.

Quantum Krylov diagonalization (QKD) has emerged as a promising hybrid quantum-classical approach for estimating ground-state properties of many-body systems on near-term quantum devices. In this work, we investigate the convergence, stability, and hardware performance of QKD for the one-dimensional Hubbard model with periodic boundary conditions. Building upon our previously developed low-depth Jordan–Wigner implementation, which reduces the number of two-qubit (CNOT) gates required for quantum time evolution, we perform a systematic study of the influence of the Krylov dimension, Hamiltonian evolution parameters, system size, interaction strength, and singular-value truncation (SVT) on the convergence of the method. Our results show that the performance of QKD is governed by a delicate interplay between the low-energy spectral structure of the Hamiltonian and numerical stability. In particular, systems with near-closing energy gaps require longer evolution times to efficiently resolve nearby eigenstates, while the evolution time, Krylov dimension, Trotter number, and SVT threshold must be carefully balanced to avoid numerical instabilities and accumulated time-discretization errors. This analysis provides practical guidelines for selecting algorithmic parameters in QKD. Finally, we demonstrate the algorithm on IBM quantum hardware, where the experimental results reproduce the convergence trends predicted by ideal simulations using only lightweight readout-error mitigation and a modest measurement budget. Together, these results demonstrate that QKD is a practical and hardware-efficient approach for studying strongly correlated fermionic systems on current NISQ quantum processors.

A recently formulated mean-field model of glasses features an equilibrium, zero-temperature Replica-Symmetry-Breaking (RSB) transition in some parameter range. In this range, the model's solution in the Replica-Symmetric phase is expressed in terms of an effective, self-consistent random potential for uncoupled degree of freedoms, where the transition to the RSB phase is characterized by the emergence of spectral-edge localized modes and a pseudogapped quartic vibrational spectrum, resulting in a finite spin-glass susceptibility. These properties are preserved in numerical solutions of the model under non-equilibrium conditions, i.e., upon an instantaneous quench. Inspired by recent advances in computer glasses, we define a micromechanical response function — the linear response to local force monopoles — in the framework of the mean-field model. We establish exact relations between the force monopole stiffness and global susceptibilities, which suggest a close correspondence between the non-equilibrium RSB phase of the model and the above-mentioned effective random potential description. As such, the obtained micromechanical observables constitute a concrete realization of the collective degrees of freedom of the model, offering a bridge between a glassy mean-field model and finite-dimensional glasses. We show that the model's vibrational spectrum can be computed solely from the monopole response statistics and, by employing a marginal stability criterion, we extract a characteristic frequency/stiffness scale of soft glassy modes, which is related to the boson peak in finite-dimensional, laboratory glasses.

We reconstruct the late-time expansion history with a hierarchical Gaussian process (GP) that co-samples the kernel hyperparameters $(\sigma_f,l)$ together with $(\Hzero,\Om,\Ok,\omega_b h^2)$. The data are 37 cosmic-chronometer $H(z)$ points, DESI DR2 BAO, Planck 2018 compressed distance priors, and Pantheon+ supernovae, coupled by a Monte-Carlo effective likelihood. DESI's headline Chevallier–Polarski–Linder (CPL) preference at $2.8$–$4.2\sigma$ uses the full Planck likelihood; we do not reproduce or refute that result. On this compressed-CMB pipeline the baseline posterior is $w(z\simeq 0)=-0.80^{+0.26}_{-0.23}$ (68%~C.L.), less than $1\sigma$ from $w=-1$, with $l=3.79^{+0.81}_{-1.12}$. A CPL fit on the same data improves nested $\lcdm$ by only $\Delta\chi^2\sim 1$; Akaike's criterion prefers nested $\lcdm$ ($\Delta\mathrm{AIC}\simeq 3$), while BIC is quoted only as an indicative check for correlated supernovae. The reconstructed $f_{\rm DE}=1$ lies inside the 68% band at every grid point with $z\le 1.6$. Ablations that fix $(\sigma_f,l)$, drop SN or LRG1/2 BAO, replace the radial-basis kernel by a Matérn family, swap the SN catalogue (Union3, DES-Y5, DES-Dovekie), or nest a residual GP around $\lcdm$ leave the median $w(0)$ within $\lesssim 1\sigma$ of $-1$.

We employ neural control variates to minimize the range of event weights and avoid negative weights for phase-space integration and event generation. A signed control variate, built from two normalizing flows, fulfills both tasks. Combined with neural importance sampling, it significantly reduces the computational cost of LO and NLO predictions. For the NLO case, our conditional neural control variate can be viewed as a trainable subtraction term, complementing the established physics subtraction schemes for enhanced sampling performance.

The seamless integration of Density Functional Theory (DFT) with quantum variational algorithms is essential for the predictive simulation of strongly correlated materials. In this work, we present an end-to-end computational pipeline - comprising DFT geometry relaxation, non-self-consistent field (NSCF) calculations, and Wannier-based orbital localization - to prepare active-space Hamiltonians for quantum embedding. We utilize the Adaptive Variational Quantum Eigensolver (ADAPT-VQE) framework, significantly enhanced by a Greedy-Operator Commutativity Partitioning (GOCP) approach and a Taylor-expanded O(5) operator evolution strategy to efficiently manage the exponential scaling of the Hilbert space. We demonstrate this framework through a systematic benchmark study of Li-hBN, mapping the system onto qubit registers and investigating the convergence behavior as the active space is expanded from 8 to 14 spatial orbitals. Our results quantify the relationship between active-space size and computational demand, identifying a critical "scaling wall" where classical simulation costs transition from manageable to intractable. This study provides a rigorous performance baseline for the DFT-to-ADAPT-VQE workflow and offers empirical insights into the memory and processing limits currently facing hybrid quantum-classical architectures using advanced co-processing strategies.

The stationary state of a spin Hall bar connected to an external load circuit is investigated through a variational approach based on the principle of minimum power dissipation generalized to the two-spin-channel model. The self-consistent distributions of longitudinal and transverse current densities, alongside the corresponding spin and charge accumulations and dissipation power in the resistance, are derived. Surprisingly, it is shown that the Joule dissipation vanishes when the load resistance is placed at a sufficiently large distance compared with the spin-relaxation length. Such a highly non-trivial global stationary state appears as the most striking characteristic of the injection of pure spin current compared with more usual current injection.

Quantum state tomography provides complete information about a quantum state, but its measurement cost generally grows exponentially with system size. In many-particle quantum simulators, this challenge is further compounded by the limited accessibility of local measurements and controls. Here we develop a tomography protocol for permutation-invariant fermionic many-body states with U(1) particle-number symmetry. We show that any such state is completely determined by the distribution of the total particle number and the occupation of a single collective mode within each particle-number sector, both of which are accessible in current ultracold-atom experiments. The number of required observables scales only linearly with the system size. More generally, the protocol reconstructs the permutation-symmetrized component of arbitrary U(1)-symmetric fermionic states, which can still encode nontrivial many-body and state-level structure beyond conventional few-body observables. We demonstrate this protocol in interacting non-Gaussian states of the complex Sachdev-Ye-Kitaev model and in free-fermion chains across a Lifshitz transition. This framework opens a route toward information-theoretic characterization of strongly correlated itinerant quantum matter in experimentally realistic fermionic quantum simulators.

Multipartite Bell tests provide a correlation-only route to benchmarking quantum processors, but their application at large scales is hindered by the rapid decay of many-body correlators under noise and exponentially many terms in conventional Bell expressions. Here we address these scalability obstacles by introducing a finite-setting generalized Mermin family of state-tailored Bell inequalities with analytic certification bounds, in which the measurement-setting number $m$ provides an additional certification dimension complementary to the system size $n$. We show that, for the powers-of-two setting choices considered here, increasing $m$ leaves the ideal normalized multipartite quantum value unchanged while lowering the relevant classical bounds, thereby strengthening the Bell-violation ratios and yielding an improved noise-robustness scaling compared to the standard Mermin inequality. We test this construction experimentally on a programmable superconducting processor by preparing Greenberger-Horne-Zeilinger (GHZ) states of up to 80 qubits. Using randomized sampling for direct Bell-operator estimation, we observe Bell ratios that grow exponentially with system size, certify a nonlocality depth of 14, and show that increasing $m$ strengthens both the Bell ratio and depth certification. All results are obtained solely from measured correlators and analytical bounds, without readout correction, tomography, or model-based mitigation. Generalized Mermin inequalities therefore provide a sharper Bell benchmark for noisy large-scale GHZ states.

Quantum metrology promises sensitivity beyond classical strategies, yet it remains unsettled how quantum-enabled precision should scale with physical resources and how to interpret quantum advantage. We provide a physically grounded resource accounting that clarifies the true Heisenberg limit and resolves apparent super-Heisenberg paradoxes. We demonstrate that the Heisenberg limit is best viewed as an information-theoretic manifestation of the quantum speed limit. We illustrate these ideas with a simple, super-resolving phase-estimation protocol based on Rabi oscillations in two-level atoms driven on an $m$-photon resonance. In this setting, the phase error scales as $n^{-m/2}$, where $n$ is the average photon number. Recasting metrological sensitivity through quantum dynamical speed limits yields operational bounds that reconcile such super-resolution strategies with the standard Heisenberg interpretation and identify the relevant resources in the norm of the generator. We also revisit the common attribution of the NOON state's $1/n$ scaling to quantum entanglement. We show that such an attribution is not generic and the Heisenberg $1/n$ scaling does not, by itself, certify entanglement as the enabling resource.

Building upon the pioneering framework of Vu (2026), we construct a probabilistic representation for three-state discrete-time quantum walks on integer lattices and validate it through empirical examples. Furthermore, we establish that this representation converges to the continuum solution of multi-state Dirac partial differential equations. Broadly, our findings demonstrate that this probabilistic paradigm serves as a robust alternative for simulating higher-dimensional quantum walks, opening new theoretical avenues to analyze quantum dynamics using classical stochastic processes.

Traditional human marking in upper-secondary STEM education creates a structural bottleneck that restricts the frequency of formative mock examinations. This quasi-experimental, mixed-methods longitudinal study (N = 142) investigates the efficacy of deploying a fully automated, handwritten assessment marking platform to remove this bottleneck. Students preparing for STEM A-levels (Mathematics, Further Mathematics, Biology, Chemistry, Physics) were divided into control (N = 70, human marking) and intervention (N = 72, automated marking) groups over a 16-week term. Results indicate that the intervention group achieved a statistically significant improvement in final mock A-level marks (p < .01), scoring on average 16.8% higher than the control group. Furthermore, assessment turnaround time dropped from 11.2 days to < 0.1 days, enabling a fourfold increase in practice volume. The automated system's capacity for granular marginalia, specifically its Error Carried Forward (ECF) logic, accelerated the correction of procedural misconceptions and significantly boosted student self-efficacy. Practically, these findings validate that automated marking systems serve as high-speed formative loop accelerators, providing international schools with a highly scalable, low-cost intervention to elevate institutional exam outcomes without necessitating increases in staff headcount.

We investigate ghost dark energy (GDE) in a cosmological framework derived from Kaniadakis entropy. By applying the first law of thermodynamics to the FRW apparent horizon, we obtain modified Friedmann equations that include a correction term characterized by the Kaniadakis parameter $\lambda$. We then study the evolution of a flat universe containing pressureless matter and interacting GDE within this modified gravity setup. Our numerical analysis reveals that the Kaniadakis correction mildly affects the dark energy equation of state and shifts the transition to cosmic acceleration. Stability analysis via the squared sound speed shows the model remains generally unstable, though the instability is moderated for larger $\lambda$. Statefinder diagnostics indicate that the model approaches the $\Lambda$CDM fixed point in the future, with deviations decreasing as $\lambda$ increases.

We present an analytical theory for the flash temperature for viscoelastic solids sliding on rigid and randomly rough surfaces. The theory takes into account the surface roughness on all relevant length scales.

Complex dynamical systems often undergo transitions from periodic to chaotic behaviour as bifurcation parameters vary, making timely detection of these changes essential. Conventional approaches based on the maximal Lyapunov exponent (MLE) generally require either knowledge of the governing equations or sufficiently long, uniformly sampled time series. Their performance degrades when the available data are scanty or contain missing observations, making reliable phase-space reconstruction difficult. We propose a methodology that combines Topological Data Analysis (TDA), specifically 0-D sublevel persistence, with Machine Learning (ML) classifiers to distinguish periodic and chaotic regimes directly from time series. Sublevel persistence extracts topological features by analysing the evolution of minima and maxima, revealing repeating signatures for periodic dynamics and more scattered patterns for chaotic dynamics. These features are used to train logistic regression, support vector machine, and k-nearest neighbour classifiers. Hyperparameters are validated using K-fold cross-validation, yielding average classification accuracies exceeding 90%. The trained classifiers provide binary predictions, identifying periodic and chaotic behaviour in previously unseen data. The proposed methodology is evaluated on the Duffing, Rössler, and Lorenz systems, where the detected transitions closely agree with those identified using the MLE, demonstrating the reliability of the approach. It is further applied to real-world ECG signals to classify normal and abnormal heartbeats, producing encouraging performance across standard statistical metrics. The proposed framework provides an effective alternative for analysing sparse or incomplete time series and is particularly useful in experimental settings where conventional nonlinear time-series methods are limited.

We present the simulated performance of the coronagraph (CORO) module for ANDES, the Extremely Large Telescope (ELT) high-resolution spectrograph. ANDES aims to address a broad range of science cases, including the characterization of the atmosphere of exoplanets. With a first light envisioned by 2035, the instrument baseline features a modular fiber-fed echelle spectrograph with visible and near-infrared ultra-stable spectral arms to provide a simultaneous spectral range of 0.4-1.8\,$\mu$m with a spectral resolving power up to 100,000. ANDES also includes an Integral Field Unit (IFU) mode-fed by a single-conjugate adaptive optics (SCAO) module and an insertable CORO module, enabling the combination of high-contrast imaging and high-dispersion spectroscopy (R=100,000) for the study of exoplanet properties. In this contribution, the ANDES CORO design, its main features and its simulated performance are detailed in the presence of SCAO residual errors to probe exoplanet atmospheres with the spectro-imager mode at high-spatial resolution and with unprecedented angular resolution. We show the preliminary simulation results on the predicted contrast and the expected detection performance with ANDES performance unfolded (APU), the simulation tool to determine the yield of exoplanets that will be detected in emitted and possibly reflected light. The characterization operation of the instrument will be discussed to assess the ANDES ability to detect atomic and molecular signatures connected to the exoplanet atmosphere characteristics.

An additional term of the form $\lambda \mathbf{T} \cdot \mathbf{C} \cdot \mathbf{T}$ in the Einstein-Hilbert Lagrangian was introduced to explain the interaction between matter and pure gravitational field [H. W. Lee and A. Qadir, Motion of test particle for Weyl-interaction gravity, Int. Jour. Mod. Phys. D 28(16) (2019) 2040014], the modified relativistic dynamics (MORD). In this paper, we estimate the shadow parameters of black hole in a spherically symmetric static spacetime within the MORD framework. As a first approximation, we assume that the black hole is surrounded by a constant-density baryonic matter halo. The analysis is then extended by introducing a homogeneous plasma background. We compute the shadow radii for various black hole masses and analyze their dependence on the WIG coupling parameter $\lambda$. In addition, we compute the fundamental quasi-normal mode (QNM) frequencies under test-field approximation, and perform a time-domain integration analysis.

We present an interactive web platform that unifies the construction Feynman ribbon diagrams (FRDs), the evaluation of higher-rank Chern–Simons knot invariants, and the identification of FRD-like knots at higher crossing numbers. These tree-structured diagrams naturally represent arborescent knots, which we refer to throughout as FRD-like knots. Within a single visual environment, users can construct an FRD as a tensor network, evaluate its associated Chern–Simons invariants, and use the resulting invariant data to distinguish and identify the corresponding knot. To our knowledge, this is the first platform to combine diagrammatic construction, tensor-network evaluation, invariant computation, and knot identification within a unified workflow.

By appropriately perturbing a critical transverse-field Ising chain away from its critical point, the system can develop a finite correlation length with a characteristic purely massive spectrum, whose ratios and correlations are precisely described by an integrable field theory and an infinite set of integrals of motion corresponding to the $E_8$ Lie algebra. In this work, we report on experimental observation of a characteristic massive spectrum close to transverse field-induced dimensional reduction in a quasi-two-dimensional quantum magnet Cu$_2$(OH)$_3$Br, providing evidence for an emergent $E_8$ symmetry and the corresponding excitations of bound states in the sublattice of its ferromagnetic chains. These results demonstrate the power of integrable field theory in describing emergent many-body quantum critical phenomena in condensed matter systems.

We give an explicit shuffle algebra model for the loop-nilpotent cohomological Hall algebra (CoHA) of a tripled quiver with canonical cubic potential. As consequences, we (1) relate the loop-nilpotent CoHA to the quantized Coulomb branch algebra of the corresponding quiver gauge theory, (2) show that the loop-nilpotent CoHA is supercommutative after specialization at $\hbar=0$, (3) give generators for both the loop-nilpotent CoHA and the full preprojective CoHA, and (4) obtain an explicit characterization of the BPS Lie algebra of the full preprojective CoHA via certain degree and divisibility conditions. This gives a new formula for the Kac polynomials of the quiver in terms of the dimensions of certain vector spaces of polynomials. We also prove a conjecture on the spherical generation of the localized shuffle algebra and show that for ADE quivers, the loop-nilpotent CoHA is the positive half of Drinfeld-Gavarini dual of the Yangian.

Current climate policies are targeted at slowing down the global warming rate, or the global mean surface air temperature (SAT) change ({\Delta}Tmean), which is measured by the arithmetic mean approach under the assumption that SAT changes are symmetrically distributed. However, in reality, the SAT change is asymmetric in nature and its influence on the {\Delta}Tmean interpretation seldom received attention in previous research about climate change. This study theorizes, based on the image histogram approach, that while {\Delta}Tmean measures the Earth's overall SAT change, it yields a value larger than the global-scale SAT change ({\Delta}Tgs) because of the asymmetrical distribution of SAT change. Results show that {\Delta}Tmean is greater than that based on {\Delta}Tgs by 0.19-0.23{\deg}C from 2000-2019, relative to the global SAT in 1979. In future climate projections, where more significant inhomogeneous warming is expected, the disagreement between {\Delta}Tmean and {\Delta}Tgs reach 0.27-0.54{\deg}C by the end of the 21st century (2080-2099) under different emission scenarios. The large difference between {\Delta}Tmean and {\Delta}Tgs implies that there is a net positive regional-scale warming effect over the globe which is mainly contributed by Arctic Amplification. This paper constitutes a warning that extreme regional warming effects could have large impacts on the interpretation of {\Delta}Tmean, which is often considered in climate assessments and policies making, and illustrates the limitations and cautions inherent in using {\Delta}Tmean as the only indicator of the global warming rate.

The temperature-redshift relation, $T(z)=T_0(1+z)$, is a cornerstone of the standard cosmological model, but it is violated in many physically motivated extensions thereof, e.g. when photon number is not conserved. We apply the methodology of cosmography, a model-independent approach to cosmology, to this observable, and use astrophysical Sunyaev-Zeldovich and high-resolution spectroscopic measurements spanning the redshift range $0\le z\le6.34$, to constrain violations of the standard relation. We explore the impact of different cosmographic approaches and expansion variable choices and also compare the cosmographic constraints with those obtained, with the same data, in the canonical adiabatic extension model of Lima. While these choices have some impact, overall we find that such violations are constrained to percent level, and that a single non-standard parameter suffices to describe them. We also show that the directly fitted slope of the temperature-redshift relation is compatible with (but slightly smaller than) the one inferred from FIRAS, and that standard cosmography lore, based on scale factor expansions, does not apply to this observable, e.g. Padé approximants have no meaningful advantage over plain Taylor series.