We propose that probability in quantum theory, like energy in general relativity, acquires a fundamentally quasilocal character in curved spacetime. Interpreting Hermiticity as the symmetry associated with inner-product conservation, we show that gravitational boundaries and horizons convert global probability conservation into a flux balance law. The resulting quasilocal probability naturally induces effective non-Hermiticity for restricted observers while preserving global unitarity. We demonstrate this explicitly in Schwarzschild, Kerr and FLRW spacetimes and after this, we identify observational imprints in black hole ringdowns. Our results suggest that in quantum field theory on curved backgrounds, probability conservation is as geometrically conditioned as energy itself.

This year was 28th time that our series of workshops entitled "What Comes Beyond the Standard Models?" took place. The series started in 1998 with the idea of organising a workshop where participants would spend most of the time in discussions, encompassing different approaches and ideas, from high energy to cosmology, dark matter physics, random dynamics, and discussions about the nature of spatial dimensions.

Various effects in human cognition, often considered `non-classical', have been argued to be most naturally modelled by quantum-like models of decision making. We extend this approach to describe models of cognition and decision-making in general probabilistic process theories, which include both classical probabilistic models and quantum instrument models as special cases. We show how many aspects of quantum-like cognition can be described diagrammatically in process theories, before using our approach to assess the arguments for quantum-like models. While standard Bayesian classical models are insufficient, we prove that any sequential decision data can in fact be given a more general form of classical instrument model, and see that even simple deterministic models can exhibit all cognitive effects. Restricting attention to instruments induced by measurements, such as classical Bayesian and quantum POVM models, rules out such a result, but is challenged by the fact that such instruments cannot account for certain effects. Finally, we argue that to strictly rule out classical instrument models one should make use of parallel composition in the modelling of joint decisions, and find real world cognitive data violating Bell inequalities.

Existing deep learning methods for radiology report generation enhance diagnostic efficiency but often overlook physician-informed medical priors. This leads to a suboptimal alignment between the structured explanations and disease manifestations. Eye gaze data provides critical insights into a radiologist's visual attention, enhancing the relevance and interpretability of extracted features while aligning with human decision-making processes. However, despite its promising potential, the integration of eye gaze information into AI-driven medical imaging workflows is impeded by challenges such as the complexity of multimodal data fusion and the high cost of gaze acquisition, particularly its absence during inference, limiting its practical applicability in real-world clinical settings. To address these issues, we introduce Gaze2Report, a framework which leverages a scanpath prediction module and Graph Neural Network (GNN) to generate joint visual-gaze tokens. Combined with instruction and report tokens, these form a multimodal prompt used to fine-tune LoRA layers of large language models (LLMs) for autoregressive report generation. Gaze2Report enhances report quality through eye-gaze-guided visual learning and incorporates on-the-fly scanpath prediction, enabling the model to operate without gaze input during inference.

Irreversible transport in time-periodic flows is commonly attributed to vorticity, nonlinear forcing, or symmetry breaking. We show that finite-memory reconstruction of the velocity gradient generates a purely geometric mechanism for transport even when the instantaneous flow remains locally irrotational at all times. Memory promotes the velocity gradient to a history-dependent connection along particle trajectories whose noncommutativity produces a finite curvature over one forcing cycle. The associated holonomy generates a measurable loop displacement controlled solely by the dimensionless parameter ωτ_m, which quantifies the phase mismatch between forcing and reconstruction. The predicted scaling is consistent with independently reported measurements across distinct oscillatory flow configurations, supporting the interpretation of memory-induced curvature as a minimal geometric origin of irreversible transport in periodically driven continua.

In this paper, the Ensemble Kalman Filter is compared with a 4DVAR Data Assimilation System in chaotic dynamics. The Lorenz model is chosen for its simplicity in structure and its dynamical similarities with primitive equation models, such as modern numerical weather forecasting. It was examined whether the Ensemble Kalman Filter and 4DVAR are effective in tracking the control for 10%, 20%, and 40% of error in the initial conditions. With 10% of noise, the trajectories of both methods are almost perfect. With 20% of noise, the differences between the simulated trajectories and the observations, as well as the true trajectories, are rather small for the Ensemble Kalman Filter but almost perfect for 4DVAR. However, the differences become increasingly significant at the later part of the integration period for the Ensemble Kalman Filter, due to the chaotic behavior of the system. For the case with 40% error in the initial conditions, neither the Ensemble Kalman Filter nor 4DVAR could track the control with only three observations ingested. To evaluate a more realistic assimilation application, an experiment was created in which the Ensemble Kalman Filter ingested a single observation at the 180th time step in the X, Y, and Z Lorenz variables, and only in the X variable. The results show a perfect fit of 4DVAR and the control during a complete integration period, but the Ensemble Kalman Filter shows disagreement after the 80th time step. On the other hand, a considerable disagreement between the Ensemble Kalman Filter trajectories and the control is observed, as well as a total failure of 4DVAR. Better results were obtained for the case in which observations cover all the components of the model vector.

We consider two variations of the classical secretary problem. * A variation of the returning secretary problem where each interviewee may appear a second time with a fixed probability p. The decision-maker observes interviewees sequentially and must choose whether to accept or reject each appearance. We characterize the optimal threshold rule and examine its dependence on the reappearance probability p, highlighting how additional information from repeated appearances improves selection performance. * A variation of the secretary problem in which success is defined as selecting any one of the top three interviewees rather than the single best. Interviewees are observed sequentially in random order, and decisions are irreversible. We estimated the success probability under this relaxed success criterion using the threshold strategy of the classical secretary problem. The results show that allowing selection among the top three significantly increases the success probability and shifts the optimal stopping threshold earlier than in the classical problem. This model provides insight into realistic decision-making scenarios where top interviewees are more or less similar.

Beyond the quasi-two-dimensional (2D) paradigm of cuprates, the role of the third dimension of the Ruddlesden-Popper bilayer nickelates is essential to decoding their superconducting mechanism. Here, using angle-resolved photoemission spectroscopy (ARPES) with varied photon energies, we systematically investigate the electronic band structures in three dimensions for superconducting (La,Pr,Sm)$_3$Ni$_2$O$_7$/SrLaAlO$_4$ thin films (superconducting onset temperature $T_c^{\text{onset}} \sim 48$ K) transferred via a cryogenic ultra-high vacuum suitcase. We reveal an orbital-dependent dimensionality: while the $d{x^2-y^2}$-dominant bands exhibit a quasi-2D character, the $d{z^2}$-dominant band displays a finite $k_z$ dispersion. Finite energy gaps are identified on all observed bands across multiple high-symmetry directions. Systematic temperature-dependent analysis characterizes the superconducting nature of the gap on the $d{z^2}$-derived band, revealing a large gap $Δ\sim 18$ meV and a ratio $2Δ/k_BT_c\sim 8$ exceeding the weak-coupling BCS limit. The suppression of spectral weight near the Fermi level persists above the superconducting transition temperature. Ubiquitous waterfall-like spectral features evidence the presence of electron interactions. These results underscore the role of the $d_{z^2}$ orbital and correlations, placing constraints on theoretical models for nickelate superconductivity.

Generalized Langevin equations (GLEs) provide a powerful framework for describing slow dynamics in soft-matter systems, but deriving an exact homogeneous GLE (hGLE) for a reaction coordinate from an underlying many-body system remains generally difficult. Here, we analytically derive an exact hGLE for the relative coordinate of two tagged beads in arbitrary elastic networks. The memory kernel and effective restoring force are expressed explicitly in terms of the network matrices, thereby providing a systematic reduction of the high-dimensional network dynamics to a pair coordinate. Within the small-displacement approximation, we further derive a hGLE for the inter-bead distance, a central observable in distance-sensitive single-molecule experiments. These results therefore have broad potential applications in modeling proteins and other soft-matter systems.

Electronic degeneracies and near-degeneracies including conical intersections and avoided crossings, typically accompanied by strong vibronic couplings and nonadiabatic transitions, play fundamental roles in photochemical, photophysical and photobiological processes. However, its implications on excited-state chemical reactivities are not fully understood. In this theoretical study, we report a surprising phenomena that an open reaction channel can be completely blocked by a crossing seam in the molecular configuration space. Specifically, by numerically exact ab initio nonadiabatic full quantum geometrical molecular dynamics simulations, we show that the singlet fission channel in the hydrogen chain H4, previously identified as a minimal model for singlet fission, is blocked due to electronic quantum geometry. We provide a chemically intuitive picture to understand this effect. Our results not only reveal a new mechanism for controlling photochemical reactions, but may also elucidate the mechanism of singlet fission.

Quantum systems are inherently fragile to environmental fluctuations or decoherence, limiting their advantages in applications of quantum information and quantum computation. State purification offers a route to recover the purity of system under noisy conditions. Here, we demonstrate a rapid purification of initially mixed states by harnessing collective reservoir engineering in driven non-Hermitian qubit systems, together with multipartite entanglement generation in larger systems. We show that the onset of efficient purification-assisted entanglement generation is dictated by the degeneracy of collective subradiant modes, rather than by exceptional points. Moreover, the system dynamics manifests an informational Mpemba effect, i.e., a more mixed initial state reaches its steady state with unit purity at a faster rate, resembling the conventional Mpemba effect where a hotter system cools more rapidly. These results reveal a unique advantage of driven non-Hermitian quantum systems with engineered collective dissipation, enabling enhanced purification efficiency and offering new opportunities for quantum engineering.

Software redesign preserves functionality while improving quality attributes, but manual reuse of code and tests is costly and error-prone, especially in crossrepository redesigns. Focusing on static analyzers where cross-repo redesign needs often arise, we conduct a bidirectional study of the ongoing Soot/SootUp redesign case using an action research methodology that combines empirical investigation with validated open-source contributions. Our study reveals: (1) non-linear migration which necessitates bidirectional reuse, (2) deferred reuse via TODOs, (3) neglected test porting, and (4) residual bug propagation during migrations. We identify tracking corresponding code and tests as the key challenge, and address it by retrofitting clone detection to derive code mappings between original and redesigned projects. Guided by semantic reuse patterns derived in our study, we propose Semantic Alignment Heuristics and a scalable hierarchical detection strategy. Evaluations on two redesigned project pairs (Soot/SootUp and FindBugs/SpotBugs) show that our approach achieves an average reduction of 33-99% in likely irrelevant clones at a SAS threshold of 0.5 across all tool results, and improves precision up to 86% on our benchmark of 1,749 samples. Moreover, we contribute to the redesigned projects by submitting five issues and 10 pull requests, of which eight have been merged.

Van Hove singularities (VHSs) play a pivotal role in driving correlated electronic phenomena. Traditional classifications focus only on critical points where the band gradient vanishes in all directions. Here we establish a unified classification of VHSs in three-dimensional systems, characterized by the number of vanishing gradient components and Hessian eigenvalues: ordinary ($M$-type), higher-order ($T_1$, $T_2$, $T_3$), noncritical ordinary ($N_0$, $N_1$, $N_2$), and noncritical higher-order ($S_1$, $S_2$) types. Noncritical VHSs exhibit directional quenching: the gradient vanishes in a two-dimensional subspace while remaining finite along the orthogonal direction, yielding finite density-of-states enhancements with distinct energy dependencies. Using an $s$-orbital tight-binding model on the pyrochlore lattice with spin-orbit coupling, we demonstrate that all singularity classes emerge at distinct high-symmetry points through controlled tuning of the hopping ratio. This work establishes directional criticality and higher-order flatness as design principles for tailoring density-of-states enhancements in three-dimensional quantum materials.

We study a fluid-poroelasticity interaction (FPSI) problem coupling the unsteady Stokes equations with the fully dynamic Biot system. A major challenge in such problems is to design partitioned schemes that remain robust in locking-related parameter regimes while preserving the physical interface coupling structure.To address this issue, we introduce two auxiliary variables and reformulate the Biot system as a four-field problem consisting of a dynamic Stokes-like system coupled with a diffusion equation. Crucially, this reformulation preserves the original interface conditions. Based on Robin-Robin transmission conditions with explicitly lagged interface data, we construct a fully decoupled scheme in which the fluid and poroelastic subproblems can be solved independently and in parallel at each time step, without sub-iterations.We prove that the resulting method is unconditionally stable and derive optimal-order error estimates in the $H^1$-norm. The analysis further shows that the scheme is robust with respect to extreme poroelastic parameters and avoids the locking effects inherent in standard formulations. Numerical experiments confirm the theoretical convergence results and demonstrate the locking-robust performance of the proposed method.

Steady-state RANS simulations are reported for 2D flow around an ellipse and a von-Kármán-Trefftz airfoil at seven different angles of attack and two different Reynolds numbers, computed using the $k ωSST$ turbulence model in OpenFOAM. The dataset contains surface pressure distribution, skin friction distribution, lift and drag coefficients, stagnation point location and separation point locations. The results serve as a benchmark for calibration and evaluation of extended potential flow models.

To study how geometrical shape affect the light scattering properties for an ensemble of randomly orientated particles, the single scattering matrices including complete polarization information are calculated statistically for a group of crystals with random geometrical shape and a group of hexagonal prisms with various aspect ratios in geometrical optics approximation method. To compare, the single scattering matrices for individual random irregular crystal and individual hexagonal prism are also presented. It should be noted that all statistical simulation experiments in this study are restricted to the following conditions: diffraction and absorption effects are neglected, calculations are performed at a single fixed wavelength, particles are assumed to be randomly oriented, and the simulations are limited to the regime where the geometric optics approximation is applicable. Using a unified computational framework for scattering matrices of convex polyhedra, we carried out a series of statistical numerical simulations. The flexibility of this framework in modifying particle geometry enables a systematic investigation of shape-dependent scattering characteristics. The results demonstrate that regular and irregular particles exhibit noticeably different scattering matrix signatures, and ensembles of irregular particles yield smooth and featureless non-zero matrix elements. In contrast, ensembles of regular hexagonal particles with varying aspect ratios retain common geometric scattering features.

Stellar obliquity serves as a key diagnostic for tracing the dynamical evolution of bound systems-from giant planets and brown dwarfs to stellar binaries-revealing whether these diverse populations share analogous histories. Here, we report the first obliquity measurement for a double M dwarf system, determined via the Rossiter-McLaughlin effect. The spin axis of the primary star, TOI-5375 ($M_\ast=0.62\pm0.02\,M_\odot$), is well aligned with the orbit of its low-mass stellar companion ($M_c=84.8\pm1.5\, M_J$, $\rm P=1.72\,days$) with a projected obliquity of $λ=-13.5_{-13.8}^{+12.4}\,^{\circ}$ and a true 3D obliquity of $ψ=37.5_{-13.4}^{+10.6}\,^{\circ}$. The result indicates that the system either formed with a primordially aligned configuration or has undergone tidal realignment. We further investigate obliquity patterns across giant planets, brown dwarfs and binary stars. It turns out that a few obliquity trends observed in giant planets also tentatively exhibit in the latter two higher-mass populations: 1) well-aligned orbits are preferentially found around cooler host stars ($T_{\rm eff}\leq 6250\,K$); 2) wide-orbit ($a/R_\ast\geq 10$) companions are predominantly aligned; 3) no significant correlation shows up between obliquity and orbital eccentricity in any of the companion classes. By modeling $|λ|$ with a two-component Gaussian distribution, we find that the low-$|λ|$ components of binary stars and brown dwarfs are more concentrated near zero than giant planets while the high-$|λ|$ components of brown dwarfs and binaries remain unclear due to the small sample size.

High-performance piezoelectric resonators are promising energy storage elements for piezoelectric power conversion due to their compact footprint and low loss at frequencies where conventional magnetic components become bulky and inefficient. However, their practical use is often limited by the trade-off between a high electromechanical coupling coefficient (k^2) for wide-band operation and the emergence of spurious acoustic modes that limit the resonators' inductive bandwidth. This work reports a spurious-free thickness-extensional (TE)-mode bulk acoustic wave (BAW) resonator in single-crystal lithium niobate (LN) based on a grounded-ring electrode architecture. The proposed structure is analyzed through simulation and experimentally validated using electrical characterization and laser Doppler vibrometry (LDV). The results show that the grounded ring modifies the effective boundary conditions of the acoustic device, enabling a piston-like modal response that suppresses lateral spurious modes across the inductive band. The demonstrated device operates at 10.14 MHz and achieves an electromechanical coupling coefficient of 29.6%, a maximum in-band Bode quality factor (Q_Bode) of 5230, and a figure of merit (FoM, Q*k^2) of 1548. These results establish the grounded-ring TE-mode LN BAW resonator as a practical platform for piezoelectric power conversion and a broader design approach for realizing high-performance spurious-free acoustic resonators.

Machine learning (ML) reproducibility is often framed as a problem of incomplete artifact recording. This framing leads to systems that prioritize capturing datasets, code, configurations, and execution environments. However, in collaborative and interdisciplinary ML projects, reproducibility failures often arise not only from missing artifacts but from difficulties in interpreting prior work, aligning evolving components, and reconstructing experimental intent over time. Drawing on a 19-month deployment of a data-centric ML management system in a clinical research project, we identify recurring interactional breakdowns that persist despite comprehensive structural traceability. Based on these findings, we propose a two-layer socio-technical ML management system combining lifecycle-aware artifact infrastructure with an interactional layer designed to mediate coordination, explanation, and shared understanding. We discuss how an AI-mediated semantic interface reframes reproducibility as an ongoing socio-technical accomplishment rather than a static property of recorded traces, and outline implications for human-centered ML infrastructure design.

Modern exascale GPU- and APU-based systems provide multiple power and energy sensors, but differences in scope, update rate, timing, and filtering complicate the attribution of short-lived accelerator activity. This paper presents a methodology to characterize and correct these effects on Cray EX systems with AMD Instinct MI250X GPUs (Frontier) and MI300A APUs (Portage). Using controlled square-wave workloads, we quantify update intervals, delay, aliasing, and variability across up to 512 GPUs and 480 APUs with on-chip (rocm-smi/amd-smi) and off-chip Cray Power Management sensors. We reconstruct power from cumulative energy counters to achieve faster response times, validate it against on-chip, off-chip, and node-level sensors, and integrate the resulting streams into a Score-P/PAPI-based tool for time-aligned, phase-level attribution. Applied to rocHPL, rocHPL-MxP, and HPG-MxP, the method separates energy savings due to reduced runtime from changes in power. Mixed precision reduces node energy on Frontier by 79% for rocHPL-MxP and 31% for HPG-MxP, with similar trends on Portage. These results provide portable guidance for sensor validation and power-aware optimization on current and future exascale systems.

We study one-parameter conifold degenerations whose central fiber has finitely many ordinary double points and construct a mixed-Hodge-module refinement of the canonical corrected perverse object associated with the degeneration. We build a rank-one point-supported mixed-Hodge-module block at each node, identify the global singular quotient as $\bigoplus_{k=1}^r i_{k*}\Q^H_{\{p_k\}}(-1)$, and assemble these local blocks via Saito's divisor-case gluing formalism into a global object $\mathcal P^H \in MHM(X_0)$. We prove that $\mathcal P^H$ realizes the corrected perverse object, fits into an exact sequence $0 \to IC^H_{X_0} \to \mathcal P^H \to \bigoplus_{k=1}^r i_{k*}\Q^H_{\{p_k\}}(-1) \to 0$, and that the same quotient realizes the finite local vanishing sector in the nearby-cycle formalism. We further relate the mixed-Hodge-module extension, its realized perverse extension, and the induced extension on hypercohomology carrying the limiting mixed Hodge structure. This gives a theorem-level Hodge-theoretic refinement of the corrected perverse extension in the finite multi-node ordinary double point setting.

We study weighted $L^{2}$ solvability for the Euclidean Dirac operator in dimensions $n\ge 3$. We prove that, on the exterior domain $\mathbb{R}^{n}\setminus\overline{B(0,1)}$ with logarithmic weight $φ=n\log|x|$, no higher-dimensional analogue of the two-dimensional Hörmander estimate can be controlled solely by $Δφ$; we then establish weighted solvability for the weights $|x|^{m}$ with $m\neq 0$, for the quadratic weight $x_{1}^{2}$, and for sufficiently small anisotropic perturbations of the Gaussian weight, with sharp constant $1/4$ in the Gaussian case. The obstruction arises because, in dimensions $n\ge 3$, the classical weighted identity is coercive only under a structural relation between $Δφ$ and $|\nablaφ|^{2}$, a condition that excludes the Gaussian weight and many polynomial weights. The method is based on a weighted identity for the conjugated unknown $U:=ue^{-φ/2}$, together with suitable scalar and Clifford-valued multipliers; this identity yields the required coercive estimates and also gives weighted $L^{2}$ solvability for the Poisson equation through the factorization $Δ=-D^{2}$.

In this paper, we construct semisimple deformations for cyclotomic quiver Hecke-Clifford superalgebras of types $A^{(1)}_{s-1}$, $C^{(1)}_{s}$, $A^{(2)}_{2s}$, $D^{(2)}_{s}$. We derive a unified dimension formula for the bi-weight spaces for cyclotomic quiver Hecke-Clifford superalgebras of types $A^{(1)}_{s-1}$, $C^{(1)}_{s}$, $A^{(2)}_{2s}$, $D^{(2)}_{s}$. We introduce the notion of generalized graded cellular superalgebra. We prove a large class of cyclotomic quiver Hecke-Clifford superalgebras of types $A^{(1)}_{s-1}$, $C^{(1)}_{s}$, $A^{(2)}_{2s}$, $D^{(2)}_{s}$ is generalized graded cellular. By taking idempotent truncation, this recovers the known graded cellualr results for cyclotomic quiver Hecke algebras of types $A^{(1)}_{s-1}$, $C^{(1)}_{s}$.

While clustering is ubiquitously used across science and industry, uncertainty in cluster assignments is rarely quantified with rigorous guarantees. We propose a novel conformal inference framework for clustering that returns confidence sets for cluster labels. The key challenge is that labels are unobserved and estimated from data, so naively using deterministic cluster labels can violate exchangeability and induce severe under-coverage. To address this, we propose split conformal clustering with stochastic labels, which samples labels from soft cluster labels, fits a soft classifier to predict these stochastic labels, and calibrates conformal scores to construct confidence sets for cluster labels at any query point. We establish a finite-sample lower bound on marginal coverage that reveals how under-coverage is controlled by two properties of the clustering algorithm: consistency of estimated soft labels and replace-one stability. Under mild conditions, we prove asymptotic coverage and verify these conditions for correctly specified parametric mixture models. Simulations for mixture models show that our method attains target coverage with informative set sizes, validating our theoretical results. Applications to clustering cell types in single-cell RNA-seq data demonstrate the practical utility and interpretability of our approach to quantifying cluster label uncertainty.

We prove that the flow-cut gap for $n$-node directed graphs is at most $n^{1/3 + o(1)}$. This is the first improvement since a previous upper bound of $\widetilde{O}(n^{11/23})$ by Agarwal, Alon, and Charikar (STOC '07), and it narrows the gap to the current lower bound of $\widetildeΩ(n^{1/7})$ by Chuzhoy and Khanna (JACM '09). We also show an upper bound on the directed flow-cut gap of $W^{1/2}n^{o(1)}$, where $W$ is the sum of the minimum fractional cut weights. As an auxiliary contribution, we significantly expand the network of reductions among various versions of the directed flow-cut gap problem. In particular, we prove near-equivalence between the edge and vertex directed flow-cut gaps, and we show that when parametrizing by $W$, one can assume unit capacities and uniform fractional cut weights without loss of generality.

Many models exist to describe the single photoelectron response of single photon counting photomultipliers. Generally to describe the spectral region between the fully amplified primary photoelectron peak and the electronics pedestal an ad hoc function is used (often an exponentially modified gaussian) attributing this region to `noise'. In this paper, following the physical description of back-scattered primary photoelectrons at the first dynode described in the "The Photomultiplier Handbook" by A. G. Wright published by Oxford University Press, we derive an analytical function describing these partially amplified primary photoelectron at the first dynode. This function depends only on intrinsic parameters of the photomultiplier such as the gain at the first dynode and the intrinsic resolution of the dynode chain following the first. Furthermore, analytical descriptions of the fully amplified peak and very low charge signals are derived. The model has been successfully validated with data from two different photomultipliers acquired with a low-noise amplifier.

We identify a nonequilibrium route for generating altermagnetic spin splitting in antiferromagnet by ultrafast light. Unlike existing strategies, this route does not require relativistic angular-momentum transfer, static symmetry breaking, or auxiliary external fields. Using real-time time-dependent density functional theory, we demonstrate in the antiferromagnetic perovskite KNiF3 that linearly polarized light can induce momentum-dependent altermagnetic spin splitting by breaking the effective time-reversal symmetry through photoexcited charge redistribution and the resulting lattice distortion. We provide a general symmetry selection rule for this route. These results establish a mechanism for ultrafast control of altermagnetism and extend its material realization into the nonequilibrium regime.

Low eccentricity, short orbital period pulsar companions may provide a probe to study novel dense and stable exoplanet internal compositions due to the potentially significant orbital evolution they experience caused by strong gravitational tides. We model the tidal characteristics such as apsidal motion constants, orbital precession, and tidal deformability for a variety of equations of state to be compared with values recovered via pulsar timing for a sample of four systems: PSR J1719-1438b, PSR J0636+5128b, PSR J2322+2650b, and PSR J1807-2459A b. With this method, we hope to place stringent limits on the chemical and structural composition of these objects. Through limiting the internal composition of pulsar companions, we aim to elucidate their unique history and formation.

Slender beam-like structures frequently occur in engineering applications and often interact at discrete locations through joints or connectors. Accurate modeling of such interactions is particularly challenging when different numerical formulations are involved in terms of underlying beam theory, interpolation schemes, and rotation parametrization. In this work, a versatile formulation-independent beam-to-beam point coupling approach is proposed within the framework of the geometrically exact beam theory discretized by the finite element method. The coupling constraints are expressed solely in terms of cross-section kinematics, namely centroid positions and orientations. Suitable generalized deformation measures for positional and rotational coupling are introduced, allowing for general coupling configurations, including relative rotations and non-coincident cross-section centroids in the reference configuration. The contribution of the coupling conditions to the weak form of the balance equations is derived in a variationally consistent manner and can be incorporated directly into the weak form of existing beam finite element models. Constraint enforcement is formulated using a Lagrange multiplier method and a penalty regularization. The proposed approach satisfies key properties such as objectivity, symmetry, and consistency with an stress-free reference configuration. Numerical examples demonstrate the robustness and flexibility of the method for coupling beams with different formulations and discretizations, even when the interaction points are located at arbitrary positions within beam elements.

We investigate the role of stochastic resetting in non-Markovian systems, where memory effects arise due to slow relaxation, rugged energy landscapes, disordered environments, and molecular crowding. Using the celebrated continuous-time random walk (CTRW) framework, we analyze first-passage processes with multiple competing outcomes and examine how resetting can selectively enhance desired events. We characterize the efficiency of resetting through conditional mean first-passage times (MFPTs) and demonstrate that its impact is highly sensitive to the underlying waiting-time statistics. Furthermore, we derive an inequality that quantifies how resetting controls fluctuations in conditional first-passage times (FPTs), revealing regimes where variability is significantly suppressed. Our results provide a systematic understanding of how long-term memory influences competitive first-passage outcomes and establish resetting as a powerful control mechanism beyond the conventional Markovian setting.