Papers

PER has consistently demonstrated the effectiveness of small-group tutorials in helping students develop conceptual understanding and fluency, but instructor uptake is limited by resource constraints. To test the effectiveness of out-of-class tutorials using computer-generated feedback as an instructor-friendly alternative, we conducted think-aloud interviews with students in a quantum computing course who were randomly assigned to either a traditional validated small-group, pencil-and-paper tutorial on tensor products, or a solo computerized adaptation thereof. We found that while the computer-generated feedback was broadly considered useful by students, student engagement patterns were markedly different in the solo setting, with students demonstrating reluctance to use the interface's built-in help features and tending to internalize failure in unproductive ways counter to our intention of a formative learning environment. We discuss implications for curriculum design and directions for future research that may help to answer the longstanding question in PER of why tutorials work so well.

We present a quantum-classical algorithm for electronic structure calculations that dramatically reduces the quantum measurement cost of variational quantum eigensolver (VQE) approaches. While conventional VQE methods require measurements scaling as O(M^4) with system size M, the proposed occupation-number VQE (ON-VQE) reduces this cost to O(M/2) by avoiding reduced density matrix (RDM) measurements and relying exclusively on ONs. The method exploits only the diagonal elements of the one-particle RDM in the natural orbital representation, where occupations are obtained directly from computational-basis measurement outcomes. By restricting the variational ansatz to double excitations within orbital subspaces associated with electron pairs, the required measurements can be grouped into a small number of qubit-wise commuting observables, yielding an efficient and scalable measurement strategy. The approach is validated through simulations and executions on quantum hardware for the cubic H$_8$ cluster, demonstrating the feasibility of extracting accurate ONs from quantum measurements and evaluating electronic energies within the natural orbital functional (NOF) framework. Across representative molecular systems, the extracted ONs enable accurate energy evaluation with state-of-the-art NOFs while maintaining a dramatically reduced measurement cost. These results establish a scalable route toward quantum simulation of strongly correlated electronic systems, demonstrating that accurate electronic energies can be obtained from quantum measurements of ONs alone.

The birth of a new phase is usually described thermodynamically, but in the gas phase it begins as chemistry. Here, we show that gas-phase nucleation can be described as a termolecular reaction network controlled primarily by long-range intermolecular forces. In single-component mixtures, dimer formation emerges as a direct termolecular process, whereas in binary mixtures a chaperon mechanism can enhance nucleation, with the second component acting as a catalyst for cluster formation. By incorporating cluster evaporation, the same framework can be extended beyond the collision limit, providing a molecular route to nucleation in regimes where larger critical clusters become relevant. We test the theory against unary and binary nucleation of water, toluene, and butane, obtaining agreement in absolute rates within one order of magnitude across the explored temperature and density ranges. These results identify long-range intermolecular forces as molecular drivers of gas-phase nucleation and establish elementary termolecular chemistry as a predictive route to cluster formation.

The impact of astigmatism on randomly scattered light, here speckles which are generated from a ground glass (GG) plate, is investigated by studying the change in the shape of the intensity correlation function (ICF) of the speckles for different amount of astigmatism introduced to it by rotating a lens at different angles. It is observed that the shape of the ICF, which reflects the average shape of the speckles, changes from circular to elliptical with the change of the tilt angle of the lens (theta), and the variation of length of two axes of the ICF with theta is completely different in nature. It is shown that these different natures are observed due to a contest between the diverging k-vectors of the speckles and the astigmatism introduced by the tilted lens system. It is also found that the diverging k-vectors resist the effect of astigmatism on the speckles, and after a certain theta, the impact of astigmatism becomes prominent. The contest between the diverging k-vectors and astigmatism in an aberrated speckle pattern are confirmed by further experimental studies and are discussed in detail. This study will surely be helpful in designing different imaging systems, where scattered light plays an important role.

We introduce a simple method for generating droplets at the surface of a liquid bath by rapidly stretching a liquid ligament with a spring-loaded cylindrical probe. By varying the probe radius $a$ and retraction length $L$, we identify three regimes. Overstretching a thin ligament produces multiple drops, while insufficient stretching of a thick ligament yields none. The optimal regime for single-drop generation lies in between. In the single-drop regime, the drop radius scales as $R \sim a^{2/3} L^{1/3}$, consistent with volume conservation of the stretched ligament. This method enables repeatable generation of single droplets (with <5% variation in $R$) on both still and vibrating baths and of ordered droplet lattices for pilot-wave hydrodynamics experiments.

We present induction-heated resonant reactors, a new concept in electrified thermochemistry in which the reactor itself serves as a volumetric electromagnetic resonator heated through resonant wireless power transfer. We use the Swiss roll resonator as a model system and show that it can be designed to support uniform volumetric heating profiles and enhanced heat transfer characteristics, creating opportunities for process intensification in scaled systems. Compared to conventional (i.e., non-resonant) induction heating systems, resonant reactors can achieve exceptionally high system efficiencies through the combination of near-unity power-to-heat efficiencies and low thermal losses, both enabled by the utilization of resonant energy transfer. These concepts demonstrate how the integration of electromagnetic power transduction with thermochemical reaction engineering enables new opportunities for utilizing green electricity in sustainable chemical conversion.

Resolving multiscale fluid flows or boundary layers effectively requires the use of nonuniform meshes with local grid clustering. The standard lattice Boltzmann method (LBM), a kinetic theory-based approach for computational fluid dynamics, however, is restricted to the use of uniform Cartesian grids. We present new and improved formulations of the LBM that accommodate continuously varying spatial grids via coordinate transformations to simulate the Navier-Stokes equations (NSE) in the general orthogonal coordinates (GOC). They are constructed using a Chapman-Enskog analysis to specify the equilibrium moments of the distribution functions and the geometric force terms used in the collision step to be dependent on the local metric factors and their spatial derivatives, along with the density, momentum and their fluxes, and some correction terms related to the normal velocity gradients so as to accurately represent the NSE in the GOC. The resulting GOC-LBM importantly maintains the simplicity of the collide-and-stream approach and is Galilean invariant that is free of the cubic velocity artifacts. Our GOC-LBM is general and modular in that it can be used with any collision model with appropriate modifications to the equilibria and forcing terms. We present its implementation details for a variety of collision models while the central moments-based model using multiple relaxation times was found to be the most robust in practical implementations. We validate the GOC-LBM through numerical simulations for various benchmark flow problems. Moreover, we demonstrate significant computational advantages of our approach for a case study on simulating boundary layer flows efficiently that involves coupling the GOC-LBM for the NSE with a new GOC-LB scheme for solving the magnetic induction equation for magnetohydrodynamics (MHD), and for another case study involving orthogonal curvilinear grids.

We demonstrate an asymptotic gate complexity improvement in first-quantized ground-state energy estimation of electronic structure Hamiltonians in a plane wave basis by employing the sum-of-squares spectral gap amplification protocol. The improvement relies on identifying a sum-of-squares representation of the Hamiltonian which provides a lower bound certificate and low cost block encoding that leads to a provably lower quantum phase estimation gate cost. This is achieved by using a sum-of-squares operator generated by the total charge density operator resulting in a block encoding normalization improvement of $\lambda = \mathcal{O}\left(\eta\Delta^{-1.5}+\eta^{1.5}\Delta^{-1} \right)$ compared to prior work $\lambda = \mathcal{O}(\eta\Delta^{-2}+\eta^2\Delta^{-1})$ where $\eta$ is the number of electrons and $\Delta$ is the simulation grid spacing. The asymptotic reduction in block encoding normalization and similar block encoding costs to prior work is demonstrated to reduce resource estimates for materials and chemical systems by a factor of $2 - 44\times$ corresponding to the lowest cost estimates for ab initio materials simulation.

We introduce a geometric framework that organizes the second-order statistics of the Elasser fields into polarization states on generalized Poincaré spheres. In this representation, energy, cross-helicity, residual energy, and the phase lag between counter-propagating wave packets emerge as complementary polarization parameters. We derive a Bloch-analogue equation governing the evolution of polarization states and show that distinct polarization geometries are associated with different cascade dynamics. The framework predicts that transitions in the turbulent spectral scaling coincide with changes in the polarization state of the interacting modes.

Numerical breakdown at high Weissenberg number is often attributed to loss of symmetric positive definiteness (SPD) of the conformation tensor. That conclusion follows from Maxwell-type models without solvent viscosity. With solvent fraction $\beta>0$, the initial-value problem is locally well posed for arbitrary symmetric stress. We derive the missing quantitative theory for indefinite states and test its computational consequences. Frozen-coefficient analysis gives a growth rate uniformly bounded in wavenumber and the direction-resolved instability threshold $\lambda_{\min}(A)<-\beta/(1-\beta)$; stress diffusion supplies a closed-form cutoff, while the classical $\sigma\propto k$ catastrophe is recovered as solvent viscosity vanishes. A determinant identity shows that violations self-heal on the timescale $\lambda/2$, so persistent violations measure the truncation error that recreates them. Spectral and lattice Boltzmann tests reproduce the threshold, solvent-fraction reversal, and resolution independence. In four-roll-mill interventions, enforcing SPD delays blow-up by 15 convective times but reduces the stagnation-point Weissenberg number by 30%. Across five coupling schemes, a local second-moment stress source remains stable through the full budget at $\mathrm{Wi}=50$ while carrying $\det A\approx-8.5\times10^5$; the divergence-coupled variant fails at $t^*=47$. The surviving scheme matches published benchmarks within 0.05% and 0.18% at $\mathrm{Wi}=10$ and 20. Thus loss of positive definiteness is neither necessary nor sufficient for breakdown: the discrete coupling route decides, and the violation is a resolution gauge for which we provide run-time monitors.

The Bethe-Feynman formula has proven useful for estimating the explosive yields of simple fission weapons. However, derivations of the Bethe-Feynman formula found in the open literature utilize approximations whose validity is not obvious, and which contain an apparent contradiction. Here we show that the Bethe-Feynman formula can be extracted in a straightforward manner from the results of an earlier approach for estimating yield by Arthur H. Compton, as presented in the 1941 National Academy of Sciences Uranium Committee report. Compton's detailed derivation provides a more intuitive understanding of the physical basis for the Bethe-Feynman formula.

Coenen et al.\ (J. Fluid Mech., vol.~921, 2021, p.~R2) developed a reduced-order model of peristaltic pumping in non-axisymmetric annular conduits with rigid walls, in the context of periarterial space (PAS) flows. In vivo studies show that the PAS's outer wall undergoes significant displacement due to flow within and that the penetrating PASs form a porous pathway. To account for these biomechanical aspects, we revisit the problem of flow in an eccentric annular conduit and incorporate porous drag and two-way-coupled fluid–structure interaction between the compliant outer wall and the cerebrospinal fluid flow within. A Darcy–Brinkman term in the axial momentum equation accounts for drag due to the porous medium. We account for changes in hydraulic resistance due to peristalsis and compliant-wall displacements perturbatively, thereby reducing the problem to a single nonlinear partial differential equation for the axial pressure. This reduced-order model allows us to build a mechanistic understanding of flow through a porous penetrating PAS and enables parametric studies. For small-amplitude peristaltic waves, analytical solutions are possible.

The undamped Duffing oscillator is a nonlinear dynamical system with broad applications in physics, engineering and biological system. We present a comprehensive analysis of this system using the Lindstedt Poincare method (LPM) and its modifications and make comparison with numerical solution obtained using higher order Runge-Kutta. It is also shown the method suggested in this article converges better than the standard LPM and Lindstedt Poincare method with Burton's modification.

We demonstrate a method to measure energy shifts of the top level in a four-level ladder setup induced by atom interactions in thermal vapors. It utilizes the observation of two transmission minima corresponding to a split electromagnetically induced absorption (EIA) effect. We apply this method to measure mean Rydberg atom interactions in a hot vapor. We believe this approach could provide a valuable tool for accurately modeling mean-field Rydberg atom interactions, as well as sensing the occurrence of strong interactions.

Stochastic binary networks are widely used to describe collective dynamics in complex systems and to perform neuromorphic computation, yet realistic networks often contain both asymmetric interactions and finite signal propagation times that fall outside conventional theories. Here we study stochastic binary networks with asymmetric and time-delayed interactions motivated by experimental observations in coupled superparamagnetic tunnel junctions. We find that time delay fundamentally reshapes the dynamics induced by anti-symmetric couplings, producing strong oscillatory temporal correlations consistent with experiment. At the same time, sufficiently long delays drive the steady-state probabilities toward equal state occupations even in strongly coupled systems. These apparently featureless probability distributions coexist with pronounced temporal correlations, distinguishing them from equilibrium high-temperature behavior. We further show analytically that delay-induced uniform distributions emerge in a broad class of stochastic networks, while symmetry-breaking bias fields restore interaction-dependent steady states with qualitatively modified behavior. Simulations of networks with five coupled spins demonstrate that these effects persist beyond minimal systems with only two spins. Our results establish a unified framework for stochastic binary networks in the intermediate regime between symmetric instantaneous interactions and asymmetric or time-delayed interactions, and suggest that asymmetry and delay can be exploited as functional resources in neuromorphic hardware and complex network dynamics.

The paper considers the effect of degenerate higher-order mode (HOM) interaction, which may lead to the formation of trapped modes with high shunt impedance. Methods for eliminating these modes are discussed.

Volatile outgassing from planetary interiors controls the composition of rocky exoplanets' secondary atmospheres. However, observations indicate that disequilibrium processes, such as photochemistry and vertical transport, can strongly alter the chemical structure of Hot Jupiters. Which process dominates under different types of rocky planets, and how outgassing and photochemistry jointly determine the atmospheric composition, remain open questions. Sulfur species are promising tracers of interior-atmosphere coupling because their atmospheric abundances are sensitive to both mantle redox state and stellar irradiation. The PROTEUS planetary interior-atmosphere evolution modelling framework is coupled to two chemical models, FastChem and VULCAN, for post-processed chemistry calculations. We run a grid of planetary evolution simulations spanning diverse mantle redox states, instellation fluxes, and Solar versus M-star host-star spectra. For each case, we compare atmospheric compositions under thermochemical equilibrium, only vertical transport, and vertical transport plus photochemistry. The bulk atmospheric composition remains controlled by the redox state of the mantle and outgassing history, even when disequilibrium chemistry is included. Reduced mantles produce atmospheres rich in H2, and oxidised mantles are dominated by CO2. Photochemistry affects the upper atmosphere, strongly depleting neutral volatiles and enhancing radicals, especially for highly irradiated cases. SO2 is strongly enhanced at intermediate-to-oxidised redox states. Synthetic emission spectra show that photochemical SO2 can generate absorption features at 4 um and at 7.3 / 8.7 um, reaching ~60 ppm and ~100 ppm, before sequentially returning to the outgassed signatures of ~30 ppm and ~50 ppm for the oxidised mantle redox state. These signatures are detectable with JWST, motivating targeted observational campaigns.

We present a theory of a flow of salt solutions in long axisymmetric channels induced by concentration and pressure drops between their ends. The consideration is restricted to thin, compared to the local radius, electrostatic diffuse layers, but remains valid even when the concentration drop is quite large. We show that the magnitude of the diffusio-osmotic fluid flow rate $Q_{DO}$ in the cylinder is the same as in the slit of equal to its diameter thickness, but channels of variable cross-sections could either retard or enhance it, depending on their geometry. The application of the pressure drop $\Delta p \neq 0$ results in an extra contribution $Q_{P}$ to the total flow rate of fluid $Q$, but does not affect $Q_{DO}$. We calculate the curves $\Delta p (Q)$ for several axisymmetric channels and conclude that they are nearly linear, with the sensitive to the shape slopes. This leads to the possibility of introducing a simple, but rather accurate, cylinder approximation, where the radius of the imaginary cylinder is related to a hydrodynamic resistivity of the real channel and can be easily determined, if its geometry is known. We also derive an equation relating the ionic flux with the total flow rate of fluid and demonstrate that both the sign and magnitude of ionic flux could be tuned by using the appropriate channel shape. Our analysis provides a framework for interpreting experimental and numerical data, as well as may guide the design of micro- and nanofluidic devices.

The volume of clear-air turbulence (CAT) in the atmosphere at flight cruising altitudes is increasing rapidly, posing a growing problem for civil aviation and resulting in reduced confidence in aviation safety. There are limited remote detection capabilities for CAT, since clear air produces no measurable radar return. Lidar has been proposed as a viable detection methodology, and several systems have been demonstrated. However, these systems have to date demonstrated limited detection ranges of less than 15 km. In this work, we propose a novel lidar-based CAT detection methodology that uses Rayleigh scattering and relies on a differential detector measurement to quantify beam spread and thereby estimate the eddy dissipation rate (EDR), which is the international aircraft-independent metric for quantifying aviation turbulence strength. Additionally, we present experimental results demonstrating the validity of the optical efficiency model used in the detection simulations. We show that, under modest assumptions, a size, weight, and power (SWAP) constrained system that implements this method can detect moderate CAT at ranges in excess of 30 km, equating to two minutes of flight time for typical commercial aviation cruising speeds, which represents a substantial range improvement over prior approaches. This is an important advance because-for the first time-it potentially allows the cabin to be secured before the turbulence is encountered, reducing the injury risk to passengers and flight attendants.

We calculate radiative-recoil contribution of order $Z^2\alpha(Z\alpha)^5(m/M)^2m$ to the Lamb shift in muonium. This correction is due to insertion of radiative photons in the heavy line in the two-photon exchange diagrams. Our calculations are inspired by a new round of precise $1S-2S$ and $2S-2P$ experiments currently in progress.

Photonic integrated circuits (PICs) generate, route, and process light with high efficiency, scalability, and functional density on a single chip. Yet the tightly confined on-chip modes can not easily access or effectively interact with atomic vapors, fluids, gain media, and biological samples. Existing approaches require bringing the medium onto the chip or into a weak, tightly confined evanescent field, which restricts the interaction volume and the range of accessible media. Here, we demonstrate a re-entrant chip-free-space interface in which a thin-film lithium niobate circuit frequency-doubles telecom light, emits the 780~nm field through a Rubidium vapor cell, and recollects the reflected probe on the same chip. This emit-interact-recollect loop resolves the saturated absorption spectrum and stabilizes the telecom laser to within $\pm 280$~kHz over 2 hours. Our study paves an route to embed external media into PICs through the re-entrant photonic interface.

Optical thermodynamics is a newly developed framework that applies principles from statistical mechanics to describe the intricate behavior of weakly nonlinear, multimode photonic systems. Utilizing this theory, the collective dynamics of complex optical arrangements can be systematically uncovered and understood. The purpose of this work is to examine fundamental aspects of optical thermodynamics, including optical pressure, and provide a unified framework that can be applied to effectively any optical setting within the domain of validity of optical thermodynamics. We find that in addition to the conservation laws, the remaining extensive and intensive parameters of the system are naturally provided by the parameters of the propagation constants. At this point, several thermodynamic approaches exist for analyzing optical forces in multimode settings. Here, we develop a new theoretical methodology that unifies these perspectives in a variety of different configurations, irrespective of whether they are discrete or continuous. We apply our theory in four different settings. By studying Su-Schrieffer-Heeger lattices, we elucidate the thermodynamics of polyatomic chains and show that intercell and intracell bonds can display different optical forces. In addition, we provide a thermodynamic formalism to predict and understand the optical pressure at equilibrium arising in arrangements characterized by a continuous index variation and apply our results to graded-index fibers.

The dynamics of premixed flames propagating in two-dimensional and cylindrical channels are investigated using direct numerical simulations of the fully compressible reactive Navier-Stokes equations coupled with conductive heat transfer within the channel walls. The simulations employ a high-order numerical method, detailed chemical kinetics and transport models for a stoichiometric hydrogen-air combustion. The influence of heat losses during the early stages of flame propagation is examined for channels of different aspect ratios, with particular focus on tulip flame formation and its subsequent transition to distorted tulip structures. Heat losses are modelled considering convective heat transfer from the hot combustion products to the inner wall surface, thermal conduction heat transfer through the wall, and convective and radiative heat losses from the outer wall surface to the surroundings. The obtained results are compared with corresponding simulations under adiabatic wall boundary conditions. The simulations reproduce the principal features of flame dynamics observed experimentally, highlighting the combined influence of wall heat losses and geometric confinement on flame dynamics in confined channels.

We report on the ground and numerous excited electronic states. In the ground state the C4n rings are closed-shell systems possessing polyynic structures and can be classified as double anti-aromatic molecules. In their energetically lowest lying triplet state the rings exhibit aromatic cumulenic structures. The overall change in the electronic structures is rather dramatic upon the found moderate geometric changes from polyynic to cumulenic structure. Among others, Hund's rule is violated in both C8 and C12 in their cumulenic structures. We mention that until now, graphene is the only carbon allotrope reported to violate Hund's rule. The reasons for the violation are analyzed. Much effort has been invested to understand the relaxation pathways of the low-lying states leading the C8 from polyynic to cumulenic geometry and vice versa. On its minimum energy path, the first singlet excited state changes from open-shell character in the polyynic structure to a closed-shell state in the cumulenic structure. The cumulenic state lowest in energy is an open-shell singlet which relaxes to the closed-shell polyynic ground state.

A method is presented for the translation of acoustic field data from a source to a target region. Field data are represented as spherical harmonic expansions on spheres surrounding the source and target regions respectively and expansions are translated using a “point and shoot” method using the Kirchhoff–Helmholtz integral to carry out an axial translation from one sphere to the other. The principal motivation for the method is its use in a time-domain Fast Multipole Method, and test cases reflective of this application are presented. The method converges to six digits for appropriate values of parameters and for the values of $N$ considered here computational effort scales approximately as $N^{2}$ where $N$ is the order of spherical harmonic expansion for the field data. The method is causal and thus avoids artifacts generated in methods which are not based on intrinsically causal formulations.

Hysterons provide a minimal description of memory in driven matter: bistable elements with distinct switching thresholds whose interactions generate hysteresis, avalanches, and return point memory or its violation. Experimental realizations have so far been dominated by solid state mechanical systems, where bistability is usually encoded structurally through buckling, snap through, or geometric incompatibility. Here we realize hysteron physics through a hydrodynamic route. A single elastic fiber anchored in a microfluidic channel becomes bistable through nonlinear elastohydrodynamic feedback: viscous loading deforms the fiber, deformation reshapes hydraulic resistance, and flow redistribution modifies the loading. This feedback produces a fluidic hysteron whose onset is organized by a cusp catastrophe in geometric control parameters. A parallel bypass channel acts as a geometric load line that reshapes, and can even eliminate, bistability while simultaneously mediating long ranged hydraulic interactions between fibers. In arrays, varying a single geometric parameter drives a transition from a non interacting Preisach regime with return point memory to an interacting regime with avalanche like switching and return point memory violation. These results establish a passive hydrodynamic route to hysteron networks, in which memory emerges from flow structure feedback and global hydraulic constraints rather than solid state multistability or external control.

We introduce a thermodynamic theory of voting and show that it provides a good description of distribution of party votes in EU elections. The theory traces parallels between system energies of coupled nonlinear oscillators and party vote fractions. Such a classical system evolution is characterized by the conservation of total energy and probability norm that leads to the Rayleigh-Jeans (RJ) thermalization and condensation at low energy states. A similar thermalization also describes the wealth inequality in society. This feature belongs to the phenomena of constraint driven condensation known in statistical mechanics. We show that the RJ theory well depicts the Lorenz and Pareto curves obtained from the EU vote results. The theory also recovers the dispersion of votes between candidates of first round presidential elections in France.

Optical frequency combs are key components of several photonics applications including spectroscopy, communications, and ultrafast photonics. A central challenge in frequency-comb photonics is to develop sources whose operating state can be precisely controlled and adapted to different application needs. We introduce frequency comb functionality to a THz metasurface vertical-external-cavity-surface-emitting laser (VECSEL), combining its characteristic high output power and excellent beam quality with a reconfigurable comb output. The source exhibits reversible switching between actively mode-locked 3.5 ps-long pulses and stable frequency-modulated quantum walk comb states. The flexible control of the intermodal phase relation is achieved through careful dispersion engineering via a Gires-Tournois interferometer (GTI) output-coupler combined with resonant RF bias modulation of the metasurface. These results pave the way for on-demand comb control in the THz range and provide a versatile strategy that could be extended to other semiconductor frequency-comb platforms and wavelength ranges.

The DFT-D3 dispersion correction is routinely added to machine learning force fields (MLFFs) trained on dispersion-deficient functionals such as PBE. Its environment-dependent pair coefficients, however, break the atom-centered separability that fast summation methods require, forcing practitioners either to truncate D3 or to accept a substantial slowdown. We introduce FourierD3, a method that uses a functional low-rank decomposition to restore this separability and enable particle-mesh evaluation in $O(N\log N)$ time without a real-space cutoff on the dispersion sum.

The kinetics of protein-ligand binding systems are increasingly recognized as a key determinant of drug efficacy, yet remain far harder to compute than binding affinities. Existing kinetics methods either bias the dynamics along a collective variable (CV), demanding careful system-specific CV design, or use path sampling, which keeps the dynamics unbiased but can struggle to converge rates out of deep free-energy wells and often relies on hand-engineered descriptors. By combining the `best of both worlds', we propose a method to compute accurate kinetics for general ligand-unbinding problems at modest computational expense and minimal fine tuning, building on the AI for Molecular Mechanism Discovery (AIMMD) path sampling framework. To avoid the need for feature engineering, we opt for modelling the committor with a single descriptor-free, equivariant graph neural network shared across all systems. We also partially flatten deep bound-state wells with a static, basin-restricted bias potential. This improves convergence by lifting the path sampling state boundary out of regions, where the committor is hard to learn, while leaving the reactive region strictly unbiased. Across host-guest and protein-ligand systems spanning roughly 17 orders of magnitude in residence time, the method robustly recovers rates in line with reference and experimental values. Simultaneously, and without further sampling, it also reconstructs the underlying unbinding mechanisms. We additionally find that accurate rates do not require globally accurate committor models, allowing for efficient kinetics estimation even in a low-data training regime. Requiring little system-specific setup, our approach offers an efficient and broadly generalizable route to binding kinetics, and its shared committor architecture lays crucial groundwork for probing structure-kinetics relationships across ligand series in drug discovery.