Optics
Parallel Spatial Photonic Programming of Optoelectronic IGZO RRAM with a compact $\mu$LED Array
Andrew Adair, Joshua Robertson, Andreas Tsiamis et al. (+6 more)
Optoelectronic resistive random-access
memory elements (ORRAM) are critical emerging devices that leverage photonic technologies to bring the advantages of optical programming to traditionally electronic memristive platforms for neuromorphic computing and artificial intelligence. In this work, a free-space optic micro-LED ($\mu$LED) array is combined with a 2-terminal
oxide semiconductor ORRAM (based on IGZO\textsubscript{Rich}/IGZO active layers), to realise parallel spatial programming of form-free memristive arrays. We report the optical and electrical programming of resistive states with potentiation/depression analysis of various stimuli parameters (pulse frequency, pulse width, pulse amplitude). Further, we demonstrate the simultaneous photonic-electronic programming of the ORRAM with optical SET (blue 450\,nm) and electrical RESET functionality. Persistent photocurrent is also observed and exploited as a pathway to fading
memory or synaptic plasticity for temporal bit encoding. Finally, parallel optical $\mu$LED to ORRAM channels are demonstrated to achieve the simultaneous photonic programming of multiple devices and the writing of spatial patterns across a chip of memristive IGZO devices. This work highlights the light-enabled scalability of the optoelectronic platform and the feasibility of ORRAM to interface with spatially-multiplexed optical sources to bring neuromorphic technologies directly into applications that process and sense in the optical domain.
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All authors Andrew Adair, Joshua Robertson, Andreas Tsiamis, Mohamed Awadein, Spyros Stathopoulos, Johannes Herrnsdorf, Martin D. Dawson, Themis Prodromakis, Antonio Hurtado
Computational Physics · Cross-listed from nucl-th
Nuclear Drip Line and the Composition of Supernova Matter
S. Maity and S. Mallik
The
nuclear drip line plays a crucial role in determining the composition of matter under extreme astrophysical conditions. In core-collapse
supernovae and
neutron-
star crusts, matter is driven far from saturation density and
nuclear stability;
nuclei coexist with a sea of free
neutrons, an effect that is present even at zero temperature in
neutron-
star crusts and becomes more pronounced in the hotter,
neutron-rich
supernova environment. This makes a careful treatment of drip-line physics essential for a realistic description of the equation of state and composition. In this work, the influence of the
nuclear drip line on the baryonic composition of
supernova matter is investigated within the framework of
nuclear statistical
equilibrium (NSE). The composition is evaluated in terms of free nucleons, light clusters, and heavy
nuclei at finite temperature and global sub-saturation densities. The results indicate that, at low
proton fractions and higher densities, the inclusion of
nuclei beyond the drip line enhances the formation of extremely
neutron-rich light clusters, leading to a significant reduction in the free-
neutron density and the charge fraction of heavy
nuclei. These findings demonstrate that drip-line physics has a significant impact on the composition of
supernova matter and should be carefully incorporated in
supernova modeling and nucleosynthesis studies.
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Physics and Society
Spectral Fingerprints of Street-Network Morphology: A Size-Adjusted Graph-Laplacian Descriptor of Urban Fabric
Piotr C. Kaminski
Decades of space-syntax research have established that the
topology of the street network conditions movement, co-presence and urban activity. The standard vocabulary for this – integration, choice and connectivity – summarises each street's position as a scalar centrality, yet two streets with identical centrality can sit in radically different morphological fabric. We introduce a compact, comparable, machine-learning-ready encoding of that local fabric: the spectral fingerprint, a fixed-dimensional kernel-density representation of the graph-
Laplacian eigenvalue distribution of each node's k-hop ego subgraph, computed on the COINS dual graph of the street network. From it we derive two interpretable scalar readouts: the Mesh Index (MI), a normalised spectral
entropy, and the Connectivity Resilience Index (CRI), the algebraic connectivity (Fiedler value). Both are corrected for an ego-subgraph-size confound that dominates raw spectral statistics. Applied to the full street network of Poznan, Poland (1,908 continuity-based strokes), the descriptor is robust to its encoding hyperparameters (spectral resolution and kernel bandwidth; Spearman rho >= 0.98) while remaining scale-dependent in its neighbourhood radius. The size adjustment leaves the Mesh Index near-orthogonal to integration (r = 0.06), carrying information classical centrality does not. The fingerprint separates morphological tissue types without supervision, and the Mesh Index is associated with the functional diversity of street-adjacent activity at the neighbourhood scale (r ~ 0.19, on open OpenStreetMap data). We delineate the method's scope honestly: it characterises what kind of activity a street's position affords, not the price that activity commands. It offers an information-theoretic morphological descriptor that complements space syntax and is directly consumable by modern graph-learning pipelines.
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Fluid Dynamics
A diffuse-interface method for compressible two-phase flows with seven- and six-equation models
Luis H. Hatashita and Suhas S. Jain
In this work, a novel phase-field method is proposed for the six- and seven-equation non-
equilibrium models for simulating compressible two-phase flows. Such formulations allow for monotonic mixture speed of sound, minimizing artificial wave delay during transmission across an interface. The proposed phase field formulation is constructed from the baseline seven-equation model, and interface-regularization terms are added in divergence form, while maintaining consistency between the partial differential equations without introducing spurious source terms. It admits conservative phasic and mixture
entropy transport equations, thus facilitating the construction of discrete conservative schemes. The six-equation formulation is obtained under instantaneous velocity
equilibrium. To avoid eigenvector degeneracy of the system of PDEs, the volumetric interface regularization flux is modified to account for a finite amount of conjugate phase, which improves on how phasic density is captured implicitly. Stability of compressible two-phase flow rely on the preservation of the interface-
equilibrium conditions, and the preservation of discrete kinetic energy and
entropy. A detailed analysis of IEC demonstrates additional requirements on the consistency of flux splittings between the convective and interface-regularization terms for all quantities, as well as the effects on the phasic internal energy flux splittings. A KEEP discretization is proposed and evaluated over a suite of high-density ratio test cases, including interface advection, acoustic wave-induced bubble oscillation, oblique acoustic wave reflection and transmission, and two-phase Taylor-Green
vortex flow. Results demonstrate accuracy, stability and robustness for very long time integrations, a desired feature for simulation of turbulent flows and acoustics, since the framework does not rely on the addition of numerical dissipation.
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Space Physics
In-situ measurements of space plasma: recent progress and future challenges
Daniel Verscharen
Space
plasmas like the
solar wind or the Earth's space environment offer unique opportunities to observe fundamental
plasma processes and their impact in situ. With modern space instrumentation, we measure the velocity distribution function of the
plasma particles as well as the electromagnetic fields at high resolution and with minimal perturbation of the observed
plasma systems.
Plasma measurements like this are often not possible in laboratory settings on Earth. This review article focuses on modern diagnostic methods for the in-situ detection of
plasma particles in space. It presents the detection principle of top-hat electrostatic analysers and highlights recent examples of scientific discoveries based on data from the heliospheric space missions Parker
Solar Probe and
Solar Orbiter. These examples demonstrate the capabilities of modern space
plasma instrumentation. The article then discusses future directions in space
plasma physics as well as the involved challenges in terms of the required
plasma diagnostics. These new developments include, for example, upcoming and proposed space missions such as the operational space-weather mission Vigil, the multi-spacecraft mission HelioSwarm, the Mars mission M-MATISSE, and the electron-astrophysics mission Debye.
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Fluid Dynamics
A source-term interpretation of turbulent rough wall-pressure spectra
J. M. O. Massey, A. J. Smits and B. J. McKeon
Wall-pressure fluctuations beneath a turbulent boundary layer drive the flow-induced noise and structural loading of rough surfaces. On a smooth wall their variance grows with the logarithm of the Reynolds number, a growth carried, in a source-term reading, by the nonlinear
turbulence–
turbulence part of the pressure source acting across the logarithmic layer. We ask what sets the same growth once the wall is fully rough. Standard rough-wall phenomenology answers it: above the roughness the mean flow keeps its smooth-wall logarithmic form, so the active source range is cut off at the roughness height rather than the viscous length, and the variance grows on the logarithmic span between the roughness height and the layer thickness in place of the Reynolds number. Splitting the pressure source into its two physical parts then distinguishes separate contributions to the energy: a roughness-local one from the mean-shear source, fixed at high frequency on the roughness scale, and an energetic one from the nonlinear source at the outer scale, which alone carries the growth. Calibrated against rough-wall cases, the model collapses the spectral shape onto this energetic peak and holds it Reynolds-independent at fixed geometry. The canopy contribution decays with distance from the wall and contributes a finite offset. The growth coefficient is predicted to be the smooth-wall one. The present range is too narrow to discriminate that rate from twice or half it, so the contribution is a parameter-free prediction and the identification of a suitable roughness-size sweep that would test it.
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Instrumentation and Detectors
The ASD2 Chip for the Upgrade of the ATLAS MDT Chamber Readout at HL-LHC
S. Abovyan, A. Baschirotto, V. Danielyan et al. (+8 more)
Upgrading the ATLAS detector for operation at the High-Luminosity LHC requires a new, more se-lective trigger scheme to control the readout of MDT drift-tube chambers by incorporating RPC trigger information. This necessitates replacing the MDT readout electronics, including the front-end boards that house the ASD amplifiers and the custom-designed TDC. The latter buffers timing measurements for transmission to a chamber-mounted data concentrator (CSM), which, in turn, communicates with the MDT Data Processor, where MDT tracking data are combined with RPC timing information, to specifically identify high-energy
muon tracks. In this article, we report on the new ASD2 preamplifier, discussing its architecture, design details, functionality and measured performance. We also present test results for chips from MPW runs, the engineering run and the volume production of 80,000 chips. Unlike the ASD1 preamplifier, currently used for MDT readout, which relies on 500 nm chip tech-nology, the ASD2 is manufactured using the more advanced 130 nm technology. This offers a range of technical improvements that enhance critical performance parameters such as signal rise time, noise levels, and the reproducibility of threshold settings across a chip's channels. Comparative measurements are presented to verify this improved performance. Finally, we discuss the robust-ness of ASD2 against environmental conditions like radiation exposure and potential high-voltage discharges within the MDT drift tubes.
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All authors S. Abovyan, A. Baschirotto, V. Danielyan, M. Fras, O. Kortner, S. Kortner, H. Kroha, M. de Matteis, F. Resta, R. Richter, Y. Zhao
Applied Physics
Impact of Nonlinear Absorption on Energy Distribution During FLASH-Like Deposition
Bo-Rong Lin
FLASH radiotherapy for tumors has proven highly effective in preserving normal tissue; however, the physical origin of its biological selectivity has yet to be elucidated. This study developed a minimal
diffusion-absorption model to examine the effects of nonlinear energy absorption on the spatial distribution of energy during FLASH-like deposition. Simulations revealed that nonlinear absorption alters the transfer of energy through the system while reducing the amount of energy absorbed in surrounding, unexposed regions. This behavior qualitatively resembles the tissue-sparing effect observed in FLASH radiotherapy. Parameter-space analysis revealed that the effect of incident pulse intensity depends on the absorption properties of the material, including its saturation behavior and energy threshold. These results suggest that energy-deposition conditions should be matched to the absorption characteristics of the target material.
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Fluid Dynamics
Intermittent turbulence in inclined gravity currents
Lianzheng Cui, Graham O. Hughes and Maarten van Reeuwijk
Inclined
gravity currents on shallow slopes can exhibit pronounced
turbulence intermittency. Using direct numerical simulations, we investigate this behaviour for a temporal
gravity current over a range of initial Reynolds numbers $Re_0$. For $Re_0=2500$ and a slope angle of $0.5^\circ$, the outer layer of the current exhibits large excursions in
turbulence intensity and repeated transitions between turbulent and weakly turbulent states. Analysis of the flow energetics reveals that the intermittency is associated with a finite delay between shear production and dissipation of turbulent kinetic energy. During transitional phases, this delay permits a transient amplification of
turbulence, which significantly weakens the mean shear by extracting kinetic energy from the mean flow and promoting entrainment-driven layer growth, ultimately leading to relaminarisation. Increasing $Re_0$ reduces the delay and progressively suppresses intermittency, steering the flow towards a more sustained turbulent state. Motivated by these observations, we develop an autonomous delay-differential model based on the coupled
evolution of the mean and turbulent kinetic energies. The model reproduces the observed transition from intermittent to sustained
turbulence as the delay is reduced and predicts an increased tendency towards intermittency at larger flux Richardson numbers. The results support an interpretation of intermittent
turbulence in inclined
gravity currents as a delay-induced oscillation arising from the finite adjustment time of
turbulence to changes in the mean flow.
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Atomic Physics
Sensitivity Scaling and Limits of Cavity Enhancement in Miniaturized Optically Pumped Magnetometers
Christopher H. Kiehl, María Hernández Ruiz, Cristina Sastre Jachimska et al. (+1 more)
The sensitivity of miniaturized optically pumped magnetometers (OPMs) is limited by weak atom-light coupling, which an optical cavity can enhance. In this work, we model the
photon-shot-noise-limited sensitivity of cavity-enhanced OPMs in the regime of strongly collisionally broadened optical transitions, characteristic of buffer-gas-filled miniaturized vapor
cells. The cavity enhancement is benchmarked against a single-pass free-induction-decay OPM employing Faraday-rotation readout, with the probe power and detuning jointly optimized using the Cramér-Rao lower bound as a figure of merit. For a Fabry-Pérot cavity, we compare side-of-fringe, homodyne, Pound-Drever-
Hall, and Faraday-rotation readout. All four yield an optimal sensitivity enhancement scaling as $\alpha\sqrt{2\mathcal{F}/\pi}$, where $\mathcal{F}$ is the cavity finesse and $0.5\leq \alpha \leq 1$ is a readout-dependent prefactor. The enhancement is maximized at critical coupling, and we quantify its degradation away from this point. We further show that, despite
spin-dependent absorption associated with the ensemble's vector polarizability, near-critical coupling can be maintained throughout
spin precession at arbitrary finesse by exceeding a derived probe-power threshold and increasing the atomic detuning with finesse. We also establish a limit to the maximum cavity enhancement set by vector light-shift noise.
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All authors Christopher H. Kiehl, María Hernández Ruiz, Cristina Sastre Jachimska, Morgan W. Mitchell
Plasma Physics · Cross-listed from astro-ph.HE
Collisionless Shock Driven by a Supersonic Velocity Shear
Kazuki Kamiido and Yutaka Ohira
The long-term
evolution of a relativistic collisionless velocity shear in an unmagnetized electron-positron
plasma is investigated using a first-principle particle-in-
cell simulation. The Alves instability converts the shear kinetic energy into thermal and
magnetic field energy. The resulting pressures push the
plasma, leading to the formation of collisionless shocks. The generated collisionless shocks would accelerate high energy particles, which is a possible solution to the injection problem of shear acceleration. In addition, the collisionless shocks generate a
magnetic field
turbulence that is required for the shear acceleration to work.
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Plasma Physics
New Formalism for Modelling Flowing Plasmas in a Magnetic Field
Subhasish Bag, Ashish Ganguli, Vikrant Saxena et al. (+2 more)
A new formalism for modelling a flowing
plasma in a
magnetic field, having potential for application in
plasma thrusters, materials processing, space
plasmas, etc., is developed. In this framework, the
plasma expands downstream from the source region into an expansion chamber along an axisymmetric
magnetic field. For
plasma flowing along a
magnetic field, the ion velocity parallel to the
magnetic field lines is much greater than the perpendicular velocity. This characteristic permits a unique ordering of the relevant flow variables when the flow equations are transformed into a
magnetic coordinate system (MCS), in which the coordinate axes are parallel and perpendicular to the field lines. The ordering of the flow variables in the MCS further simplifies the flow equations by allowing them to be split into sets of reduced equations. As a specific implementation, the proposed formalism was validated by using data (for boundary conditions) from a small volume
plasma system experiment (Ganguli et al 2016
Plasma Sources Sci. Technol. 25 025026). The model shows favourable agreement with the experiments and is used to predict various physical quantities relevant for applications. The corresponding physical implications are discussed in detail.
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All authors Subhasish Bag, Ashish Ganguli, Vikrant Saxena, Ramesh Narayanan, Debaprasad Sahu
Optics
Sublime Transfer Printing of Three-Dimensional Nanostructure Ensembles
Lei Chen, Hao Wang, Wang Zhang et al. (+11 more)
High-resolution three-dimensional (3D) nanostructures for visible-light
photon manipulation provide unique and bespoke capabilities in optics and photonics. However subwavelength nanofabrication and reliable ensemble manipulation of the 3D prints onto arbitrary substrates remain challenging. Here, we introduce sublime transfer strategy tailored for transfer printing ensembles of delicate 3D printed nanostructures. This strategy enables conformal, damage-free integration of arrays of 3D structures on diverse substrates. Naphthalene acts as a transient stamp to encapsulate the structures during transfer and placement. We rely on the low sublimation temperature of naphthalene to release the structures reliably with nearly zero stress, preventing mechanical damage and positional misalignment. This approach is broadly applicable to integrate diverse nanostructures and photonic devices onto various substrates, and enabling inorganic architectures through ensemble uniform post-processing, including 2.5D photonic
crystals on flexible PDMS, diffractive optical elements on curved lenses, spiral phase plates on CMOS chips, multilayer achromatic metalens on optical fiber facet, as well as 3D glass photonic
crystals and optical topological resonators on anti-stiction quartz.
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All authors Lei Chen, Hao Wang, Wang Zhang, Fu Fan, Peng Liu, Xiaoxue Bi, John You En Chan, Cheng-Feng Pan, Bochang Wu, Zhengchao Liu, Rou Yun Teo, Hongtao Wang, Huigao Duan, Joel K.W. Yang
Physics and Society
Declining Modularity of Intellectual Bases During the Emergence of Research Areas
Kazuki Nakajima, Yuya Sasaki and Masaki Aida
Understanding how research areas emerge can help identify nascent areas early and inform research strategy, yet how the intellectual base of a field restructures as an area takes shape remains unclear. We hypothesize that the emergence of a research area is accompanied by the integration of largely separate knowledge communities, observable as a decline in the modularity of its co-citation network, which represents its intellectual base. We propose a framework that tracks this modularity over time, evaluates the statistical robustness of its changes, and identifies the papers highly associated with the decline. We applied it to three areas with different modes of growth: higher-order network science, superstring theory, and graph representation learning. In all three, modularity declined in correspondence with each area's emergence or transformation, and in superstring theory, the decline aligns with an independently documented transition. Further analysis of higher-order network science shows that its decline reflects a cross-disciplinary integration. In graph representation learning, the gradual decline is followed by a rise, which we interpret as a re-differentiation after the emergence period. Our results suggest that a decline in the modularity of a co-citation network can serve as a structural signature that retrospectively characterizes this integrative mode of emergence.
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Optics
Engineering Polarization Switching in VCSELs with Custom Aperture Shapes
Zifeng Yuan, Dewen Zhang, Hong-Lin Lin et al. (+1 more)
We experimentally fabricate and measure vertical-cavity surface-emitting
lasers (VCSELs) with custom aperture shapes, demonstrating predictable polarization control and switching, supporting their use in photonic computation schemes like Ising machines with polarization-based information encoding.
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All authors Zifeng Yuan, Dewen Zhang, Hong-Lin Lin, Aaron Danner
Atomic and Molecular Clusters · Cross-listed from quant-ph
Evidence for cavity-induced metallic phase from entropic electron correlation effects
Jacob Horak and Dominik Sidler
Experiments have revealed that collective strong coupling in optical cavities can drastically alter the conductivity and dielectric properties of molecular ensembles, or even trigger abrupt phase transitions (in Rayleigh scattering or dispersion force driven conformational
equilibrium). Until now, the underlying physical mechanism has remained unknown. A recently proposed theory attributes these collective effects to cavity-induced electron correlations that share properties of the known spherical Sherrington-Kirkpatrick model of a
spin glass. As a consequence, entropic effects can trigger a phase transition in the inter-molecular electron correlations that could potentially explain the above experiments. In the following work, we derive analytic expressions for the correlation (free-)energy-induced polarizability changes, which reveal that under certain conditions collective strong coupling can even render our molecular ensemble metallic by entropically ionizing collectively degenerate molecular orbitals. Our results are a first major step towards a holistic theory of cavity-mediated electron correlation effects.
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Chemical Physics
Through the Looking-Glass: Efficient Parity-Complete Learning via Local $O(2)$ Frames
Zemin Xu and Wenbo Xie
Making all
symmetry-allowed tensor representations computationally accessible remains a central challenge in equivariant atomistic learning. Clebsch–Gordan tensor products (CGTPs) are computationally demanding, whereas efficient $SO(2)$-based alternatives lack a unified treatment of natural- and unnatural-parity representations. We first introduce a generalized Wigner-$6j$ convolution that exactly recouples interactions involving additional node representations, replacing the first edge-level tensor-product intermediate with reusable node features. This reduces edge computation and storage but leaves the $\mathcal O(L^5)$ angular scaling of the sparse CGTPs unchanged. To address this remaining bottleneck, we develop a local $O(2)$ framework whose convolutions scale as $\mathcal O(L^3)$. The framework explicitly accounts for both rotations and reflections. Its linear maps, tensor products, and gated nonlinearities, combined with frame transformations, ensure global $O(3)$ equivariance for both spatial parities. Incorporating time-reversal labels extends this construction to $O(3)\times\mathbb Z_2^{\mathcal T}$. We apply the framework to
magnetic TACE (mTACE), using distinct interactions for systems with and without
spin–orbit coupling. On collinear CrN and noncollinear Fe
benchmarks, mTACE achieves substantial reductions in atomic- and
magnetic-force errors. We also provide EquivariantX, a library for global and local $O(2)$-equivariant computation.
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Computational Physics
Differential-Embedding Reconstruction of Dynamical Systems from Scalar Time Series
Ameir Shaa and Claude Guet
We study the reconstruction of an unknown dynamical system from a single noisy scalar time series. The goal is to recover the underlying dynamics for
forecasting. We introduce a method that uses differential
embedding coordinates to identify a rational closure of the
embedding dynamics directly from data. The closure is identified through a weak-form regression pipeline, which avoids unstable pointwise differentiation of noisy data. When applied to noise-free Lorenz and Rössler systems, the method recovers closures that support long forecasts across a broad ensemble of realizations ($18.1$ and $7.1$ Lyapunov times respectively). Under $15$–$30\%$ additive Gaussian noise, performance becomes system-dependent. For the Lorenz system, forecast horizons remain short even in the best cases, whereas the Rössler system generally performs better in absolute terms, though not once normalized by the Lyapunov time. Our proposed method recovers directly interpretable closure coefficients which we compared against the known analytic closures of the Lorenz and Rössler systems.
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Optics
Physics-Aligned Deep Learning Enables SERS Resolving and Sequencing of Dynamic Single-Molecule DNA Oligomers in Plasmonic Nanocavity
Kuo Zhan, Peilin Xin, Yingqi Zhao et al. (+7 more)
Single-molecule surface-enhanced Raman spectroscopy (SM-SERS) captures dynamic molecular behavior with ultrahigh sensitivity, but its biopolymer analysis is hindered by strong spectral heterogeneity, transient hotspot sampling, and background interference. Here, we develop a physics-aligned deep learning framework integrating contrastive
attention-based multiple-instance learning (CAMIL), a tri-channel multi-kernel CNN classifier, and trajectory-level transition-guided sequence reconstruction to decode single-molecule DNA oligomer dynamics in a plasmonic nanocavity. In this work, CAMIL mines informative spectra enriched with chain-embedded nucleotide and dinucleotide signatures from contrastive positive and negative DNA trajectory bags, generating a single-molecule DNA-segment spectral-states library. This library trains a 12-class CNN to assign query time-resolved DNA SM-SERS frames to high-confidence DNA-segment states, enabling trajectory-level analysis of state composition, dwell length,
entropy, switching frequency, and transition
matrix. The transition
matrix is further converted into state-transition-edge evidence for candidate sequence scoring, enabling asymmetric DNA sequences inference from confined
stochastic sampling dynamics. This framework transforms SM-SERS heterogeneity into quantitative analytical information, advancing dynamic single-molecule decoding.
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All authors Kuo Zhan, Peilin Xin, Yingqi Zhao, Han Gu, Enock Adjei Agyekum, Zhou Chen, Shuai Li, Jian Ye, Lu Cheng, Jian-an Huang
Biological Physics · Cross-listed from quant-ph
Scientific applications of quantum computing: challenges and opportunities
Bruno Camino, C. Richard A. Catlow, John Buckeridge et al. (+13 more)
The predictive simulation of molecules and materials has had a broad and significant impact. It nevertheless remains constrained by the cost of accurately treating electronic correlation, excited states, and complex energy landscapes.
Quantum computing offers a fundamentally different computational paradigm in which
quantum states are encoded and manipulated directly rather than approximated on classical hardware. Here we discuss where this approach may provide a genuine scientific advantage in chemistry, materials science, and biochemistry. Promising directions include the high-accuracy treatment of correlated active spaces, improved excited-state simulations, and accelerated exploration of combinatorial structure spaces. The central challenge is therefore not
qubit scaling alone, but demonstrably chemically meaningful gains in predictive reliability. We argue that near-term value is most likely to come from disciplined workflow integration rather than wholesale replacement of classical methods. Noisy physical devices, error-mitigated utility experiments, early fault-tolerant devices, and fully fault-tolerant
quantum computers offer different scientific prospects, and claims of usefulness must be tied to the specific regime being discussed.
Quantum computing will become scientifically valuable when it demonstrably reduces uncertainty in computed energies, rates, spectra, or materials stability after the full costs of state preparation, measurement, error handling, and coupling to classical simulation are included.
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All authors Bruno Camino, C. Richard A. Catlow, John Buckeridge, Alin M. Elena, Vladimir V. Gusev, Sarah Harris, Thomas W. Keal, Glenn Jones, Vivien Kendon, Syma Khalid, Phalgun Lolur, Jamal A. Nasir, Matthew J. Rosseinsky, Chris-Kriton Skylaris, Paul A. Warburton, Scott M. Woodley
Optics · Cross-listed from quant-ph
Imaginary Barrier, Real Transfer: Non-Hermitian Dynamical Tunnelling
Eva-Maria Graefe
We identify a non-Hermitian counterpart of dynamical tunnelling induced by a localised absorbing region in a symmetric confining potential. The absorbing region, described by an imaginary potential barrier, induces an effective double-well structure with a pair of long-lived states that have little population in the barrier. In contrast to the periodic tunnel oscillations through a real barrier, the system slowly evolves towards equal population of the two sides, while the absorbing region remains only weakly populated. We demonstrate this generic mechanism in two continuous potentials, and capture its essence analytically in a minimal $3\times 3$
matrix model. We propose a realistic optical waveguide setup for the experimental observation of the effect.
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Fluid Dynamics
Collision efficiency of rapidly settling particle pairs in a turbulent flow
Pijush Patra, Donald L. Koch and Anubhab Roy
We investigate the collision dynamics of hydrodynamically interacting inertialess spherical particle pairs sedimenting in a homogeneous isotropic turbulent flow. The analysis focuses on the rapid-settling limit, in which the particle settling time across a Kolmogorov eddy is much shorter than the Kolmogorov time scale. We also consider continuum breakdown during lubrication interactions, which is important when the separation the particles is comparable to the $O(100)$ nm mean-free path of a gaseous media. Owing to the sub-Kolmogorov particle sizes considered here, we approximate the local flow field in the vicinity of a particle pair as a
stochastic linear flow induced by the background
turbulence. In the rapid-settling regime, the cumulative effect of turbulent strain fluctuations is weak, and the relative particle motion may therefore be described as a diffusive process. In addition, hydrodynamic interactions generate a net relative drift between the particle pairs. We obtain the hydrodynamic diffusivity and relative drift velocity from the Lagrangian autocorrelation function of the fluid velocity gradient evaluated along the settling trajectory. The rapid-settling assumption further enables us to relate the autocorrelation function to the
turbulence energy spectrum. Using these results, we solve the advection-
diffusion equation for the pair probability density function to determine the collision rate. We show that the ideal collision rate increases monotonically with increasing relative strength of
gravity to
turbulence, whereas the collision efficiency decreases monotonically over the same range.
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Plasma Physics
Data-Driven Reconstruction of Spatially Resolved Electron and Ion Energy Distributions from Macroscopic Plasma Quantities with Deep Neural Networks
Libin Varghese, Kaushik Prajapati and Bhaskar Chaudhury
Spatially resolved EEDFs/IEDFs provide essential kinetic information about low-temperature
plasmas (LTPs) and play a central role in determining transport, chemical reaction rates, and
plasma surface interactions. While kinetic simulations directly resolve these distributions, experimental measurements remain challenging and are often invasive, spatially limited, or require assumptions regarding the distribution shape such as a Maxwellian. However, several macroscopic
plasma observables can be measured non-invasively using advanced diagnostic techniques, providing spatially resolved information about the
plasma state. An important inverse problem is therefore whether readily measurable macroscopic
plasma quantities contain sufficient information to reconstruct the underlying kinetic state. In this work, we investigate this problem by learning a nonlinear mapping from spatially resolved macroscopic
plasma observables to the corresponding spatially resolved EEDFs/IEDFs using a deep learning framework. Paired
datasets comprising 2D macroscopic observables and spatially resolved EDFs are generated using 2D-3V PIC-MCC simulations. Three representative learning paradigms, a U-Net, a FNO, and a MeshGraphNet, are employed in this study to learn this inverse mapping. The predicted EDFs reproduce both bulk
plasma and sheath characteristics with good agreement to the PIC-MCC reference data, with the FNO providing the best overall performance. Beyond conventional metrics, physics-based validation demonstrates that the reconstructed EDFs accurately recover the corresponding density and temperature, and rate coefficients. These results demonstrate that macroscopic
plasma observables encode sufficient information to infer important kinetic properties in LTPs, providing a potential foundation for surrogate kinetic modeling and next-generation
plasma diagnostics.
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Chemical Physics
Unravelling carbene moiety role in the N-heterocyclic carbene-phosphinidenes coordination chemistry: bonding and reactivity in gold chemistry
Guillaume Thiam, Leonardo Belpassi and Paola Belanzoni
The coordination properties of the emerging class of N-heterocyclic carbene-phosphinidene (NHCP) ligands have been reported to be strongly affected by the carbene (NHC) moiety, but a clear understanding remains strikingly limited. In this work the bonding features and reactivity of 13 NHCP gold hydride complexes, [NHCPAuH], bearing different classes of NHCs have been systematically explored and compared to carbene analogues, using an unbiased computational protocol. The analyses reveal that, although the $\pi$-acceptor ability trend of NHCPs qualitatively parallels that of NHCs, the $\sigma$-donor ability trend reverses, with more $\sigma$-donating NHC moieties generating less $\sigma$-donating NHCP ligands. Concurrently, the nature of the NHC moiety impacts the coordination geometry at the P center, with the CNHC-P-Au bond angle appearing as a structural descriptor to monitor and/or design NHCP ligands with desired $\sigma$-donor properties. The NHCPs stronger $\sigma$-donor and weaker $\pi$-acceptor abilities compared to NHCs and their unique structural flexibility and electronic adaptability have been showcased to be directly controlled by the carbene moiety via modulation of the HOMO lone pair energy and its atomic phosphorous 3p character. The reactivity of [NHCPAuH] complexes with CO2, taken as a probe for potential NHCP applications in small molecule activation processes, demonstrates qualitatively similar mechanisms, with remarkably different activation barriers, which directly correlate with the NHCPs $\sigma$-donor ability, thus reflecting the high tunability of their bonding properties. This work provides insights and perspectives on the design principle of NHCP ligands, with a spotlight on the pivotal role of NHC moiety in modulating their electronic and steric properties, offering opportunities for burgeoning applications across diverse fields.
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Plasma Physics
Microcoulomb-level electron beam and multi-Joule hard X-rays driven by a high-efficiency laser-plasma accelerator
B. Mahieu, L. Ribotte, W. Cayzac et al. (+38 more)
We report on the production of ultrahigh-charge relativistic electron beams and the development of a
laser-wakefield acceleration platform at the LMJ facility. Making use of the kilojoule-class, sub-picosecond PETAL
laser pulse focused onto a supersonic helium gas jet, electron beams carrying a total charge beyond 1 $\mu$C were generated, with energies up to $\sim$500 MeV. Given the ps-scale
laser pulse duration, an on-target intensity approaching $10^{19}~\mathrm{W/cm^2}$, and a
plasma density reaching 2% of the critical density, electron energisation arises from a combination of self-modulated
laser wakefield acceleration (SMLWFA) and direct
laser acceleration (DLA). The resulting electron spectrum exhibits a Maxwellian-like distribution, characteristic of this mixed SMLWFA/DLA regime. The total energy carried by the electron beam is estimated to be up to 17 J, within a sub-ps duration. A broadband Joule-level
photon beam was also produced by Bremsstrahlung, demonstrating the potential for future applications. Experimental results are supported by start-to-end numerical simulations, including 3-D particle-in-
cell and Monte-Carlo particle transport calculations. These findings pave the way for applications requiring high-charge electron beams, including the generation of high-power secondary radiation or particle sources. The use of these beams to probe matter in high-energy density states driven by the nanosecond-duration LMJ beams represents another promising avenue.
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All authors B. Mahieu, L. Ribotte, W. Cayzac, G. Boutoux, R. Parreault, J. Gastineau, E. Lamoine, F. Audo, R. Babjak, D. Batani, N. Blanchot, J. L. Bourgade, M. Brochier, T. Caillaud, P. Canel, S. Cavaro, C. Chappuis, S. Debesset, R. Diaz, E. D Humieres, W. Duchastenier, R. du Jeu, A. Duval, B. Etchessahar, M. Ferri, M. Garandeau, L. Gremillet, V. Henot, E. Journot, J. C. Kieffer, I. Lantuejoul, L. Le Deroff, N. Lemos, C. Rousseaux, F. Scol, K. Ta Phuoc, W. Vaillant, B. Vauzour, M. Vranic, X. Davoine, F. Albert
Computational Physics · Cross-listed from hep-lat
Alexander Rothkopf
We construct the natural generalization of
stochastic quantization (in the Markovian sense) by considering jump-
diffusion processes. This class of
stochastic processes exhibits non-continuous paths, so-called Lévy flights. In the presence of jumps, action landscapes with barriers can be efficiently explored, improving and even restoring ergodicity where traditional
diffusion approaches become inefficient. We explore different strategies for constructing efficient jump updates, which we deploy to address the
benchmark problem of topological freezing in 2d U(1) gauge theory.
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Atmospheric and Oceanic Physics
Decadal wave reconstruction in the Mediterranean Sea with graph neural networks
Federica Benassi, Lorenzo Mentaschi, Salvatore Causio et al. (+3 more)
Accurate simulation and prediction of ocean waves are essential for coastal risk management and
climate studies. Deep learning has shown promising results for wave modeling, but most approaches still operate on regular grids and on
forecasting time scales, and do not generalize to unstructured discretization or to long time horizons. Here we present WaveGraph, a model based on Graph Neural Networks (GNNs) that emulates basin-scale wave dynamics directly on unstructured meshes with high resolution along the coasts (up to 2-3 km). Trained on bias-corrected simulation data over the Mediterranean Sea, WaveGraph uses a multiscale architecture combining the unstructured model mesh with a uniform graph, allowing simultaneous representation of local coastal interactions and large-scale wave dynamics. The model reconstructs the
evolution of significant wave height, mean period, and mean direction, and is applied autoregressively for a continuous 17-year period without reinitialization or drift. Validation against buoy and satellite observations shows skill comparable to the input data set, and ablation experiments indicate that wind forcing drives most of the long-term stability while wave history improves swell-driven and basin-scale dynamics. These results show that GNNs can provide stable and efficient emulators of spectral wave models on unstructured domains, enabling decadal wave reconstructions.
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All authors Federica Benassi, Lorenzo Mentaschi, Salvatore Causio, Daniel Holmberg, Ivan Federico, Nadia Pinardi
Optics · Cross-listed from cond-mat.mes-hall
Raman-detected quantum dot microscopy for nanoscale electrostatic potential imaging
Jiří Doležal, Amandeep Sagwal, Rodrigo Cezar de Campos Ferreira et al. (+1 more)
Quantification of electrostatic potentials at the nanoscale is crucial for understanding the principles governing properties of materials across multiple length scales. Currently, one of the most successful approaches relies on the charging response of a molecular
quantum dot, suspended on a tip of a scanning probe microscope and measured using dynamic force spectroscopy. We investigate the possibility of an optical detection, aiming to improve the speed and reduce the complexity of this measurement scheme. We show that the integrated tip-enhanced Raman scattering intensity strongly correlates with the charge state of the
quantum dot, and use it to map the electrostatic potential of a single atom. A quantitative equivalence with the established force spectroscopy method is found. We address the underlying photophysical principle of this new method by measuring the Raman spectra as a function of excitation wavelength and the molecular
quantum dot charge. We reveal that the observed Raman intensity variations are primarily driven by transitions between resonant and non-resonant Raman scattering regimes of the molecule.
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All authors Jiří Doležal, Amandeep Sagwal, Rodrigo Cezar de Campos Ferreira, Martin Švec
Plasma Physics
Proton Radiography with Isotrajectory Optics
Dmitry Varentsov, Maksym Miski-Oglu, Zs. Major et al. (+3 more)
We consider a compact isotrajectory-optics scheme for
proton radiography. The calculation uses a 30-60 MeV
proton interval as a reference example, typical of high-energy short-pulse
laser acceleration in the TNSA regime. The idea is to use synchronized time-dependent fields such that, for one selected energy-arrival-time branch, the
proton energy changes mainly the arrival time and not the transverse image position. The reference
lattice consists of four pulsed electric quadrupoles with horizontal sign pattern + - + -, magnification Mx = My = -3.0 at a detector plane of 2.57 m, a common
Fourier plane at zF = 0.962 m, and equal outer and equal inner lens lengths. The ideal closure residual is calculated from second central moments. Fourth central moments are kept separately as a diagnostic of non-Gaussian tails. The quoted residual widths are numerical closure tests of the ideal map, not experimental resolution predictions. Real electrode fields, waveform errors, scattering, detector blur, and space charge define the next level of the problem.
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All authors Dmitry Varentsov, Maksym Miski-Oglu, Zs. Major, Paul Neumayer, Martin Schanz, John Schmidt
Computational Physics · Cross-listed from cond-mat.mes-hall
Stability and optoelectronic properties of oligothiophene molecules confined in boron-nitride nanotubes : A many-body theoretical approach
Xavier Blase, Mauricio Rodriguez-Mayorga and Ivan Duchemin
We investigate the structural and optoelectronic properties of oligothiophene (nT) molecules encapsulated in boron-nitride (BN) nanotubes using density functional theory, many-body GW and Bethe-Salpeter equation approaches. We show that the binding energy is maximized for tube diameters of approximately 10 Å, decreasing gradually for larger diameters. The nT molecules can slide along the tube with a corrugation potential smaller than room temperature thermal energy, promoting their head-to-tail aggregation. Regarding the electronic properties, we find that hybridization with the tube electronic states has a much smaller effect than that of screening, which can close the nT photoemission gap by as much as an eV. A simple model for the polarization of the BN tube demonstrates how these polarization effects decrease with increasing nT molecule length and BN tube diameter. Compared to the gas phase optical properties, structural relaxation, hybridization, and screening can
redshift the absorption onset by up to 250 meV for isolated intercalated nTs. Additionally, the study of a head-to-tail sexithiophene dimer reveals an
exciton-
exciton interaction that splits the absorption onset into a lowest bright
exciton, separated by approximately 75 meV from a dark peak. This suggests possible collective effects upon the formation of nT chains inside BN tubes. Our results confirm and clarify experimental data, mitigating the conclusion that insulating BN tubes just act as a protecting environment for encapsulated molecules.
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