Chemical Physics
Localized intrinsic bond orbitals decode correlated charge migration dynamics
Imam S. Wahyutama, Madhumita Rano and Henrik R. Larsson
For decades, scientists have studied the intricate charge migration dynamics, where after ionization a localized charge distribution ("hole") migrates across the molecule on a femtosecond timescale. This has the potential for controlling electrons in molecules, yet a comprehensive understanding of the many aspects of charge migration is still missing. In this work, we analyze charge migration using an extension of localized intrinsic bond orbitals (IBOs). These orbitals lead to a compact representation of the dynamics and map the complex, correlated many-electron charge migration to chemical concepts such as curly arrows and orbital-orbital interactions. By analyzing multiple challenging scenarios, we show how IBOs enable us to identify key mechanisms in charge migration. For example, we show that different mechanisms are responsible for converting a $\pi$-shaped hole to a $\sigma$-shaped hole and vice versa. We explain these in terms of hyperconjugation interactions and configurations that couple orbitals with different
symmetries. We further demonstrate how IBOs can be used to find molecules with high charge migration efficiency. We carry out all simulations using an efficient set up of the time-dependent density
matrix renormalization group (TDDMRG), correlating as many as 45 electrons in 50 orbitals. We believe that our results will be useful to design future experiments. The proposed IBO analysis is applicable to other types of real-time electron dynamics and spectroscopy.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Task Aware Modulation Using Representation Learning for Upsaling of Terrestrial Carbon Fluxes
Aleksei Rozanov, Arvind Renganathan and Vipin Kumar
Accurately upscaling terrestrial carbon fluxes is central to estimating the global carbon budget, yet remains challenging due to the sparse and regionally biased distribution of ground measurements. Existing data-driven upscaling products often fail to generalize beyond observed domains, leading to systematic regional biases and high predictive uncertainty. We introduce Task-Aware Modulation with Representation Learning (TAM-RL), a framework that couples spatio-temporal representation learning with knowledge-guided encoder-decoder architecture and loss function derived from the carbon balance equation. Across 150+ flux tower sites representing diverse biomes and
climate regimes, TAM-RL improves predictive performance relative to existing state-of-the-art
datasets, reducing RMSE by 8-9.6% and increasing explained variance (R2) from 19.4% to 43.8%, depending on the target flux. These results demonstrate that integrating physically grounded constraints with adaptive representation learning can substantially enhance the robustness and transferability of global carbon flux estimates.
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Chemical Physics · Cross-listed from cond-mat.soft
Synthetic design of force-responsive hydrogels with ring-forming catch bonds
Wout Laeremans and Wouter G. Ellenbroek
Catch bonds are interactions whose lifetimes increase under mechanical load, a counterintuitive behaviour that underlies diverse biological processes. Translating this mechanism to synthetic materials offers the potential to create systems that are compliant at low stress but stiffen under applied force, with applications ranging from impact-responsive materials to dynamic tissue scaffolds. However, engineering materials with tunable, force-dependent interactions remains challenging, and existing conceptual designs are limited. Here, we present a minimal synthetic framework for catch bond behaviour in dynamic hydrogels, based on reversible ring-forming
polymers. Using coarse-grained molecular dynamics simulations, we show that hydrogels with such a chemistry undergo fewer bond-breaking reactions as the stress increases and can even display a non-monotonic dependence of the strain rate on the applied stress. Our results highlight the potential of reversible ring formation as a versatile platform for designing mechanically adaptive materials with tunable durability and responsiveness.
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History and Philosophy of Physics · Cross-listed from quant-ph
Has quantum advantage been achieved?
Dominik Hangleiter
Quantum computational advantage was claimed for the first time in 2019 and several experiments since then have reinforced and strengthened the claim. At the same time, a new generation of
quantum computing devices with 100 logical
qubits is being built. This raises two questions: Has
quantum advantage actually been achieved? And what should our next milestones be for the upcoming 100-logical-
qubit era? In this perspective, I argue that, in fact,
quantum advantage has been achieved. The status today is analogous to Bell-inequality violations in the 1980s where some loopholes remain open, specifically, scalability and verifiability. I then outline three milestones for the 100-logical-
qubit era aiming to close those loopholes: demonstrate fault-tolerant
quantum advantage, perform efficiently verifiable advantage using random
circuits with
symmetries, and eventually demonstrate classically verifiable advantage with applications to certified randomness. These milestones are also natural stepping stones towards running
algorithms with cryptographic applications.
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Medical Physics
Initial Performance of a Long Axial FOV PET with TOF and DOI capabilities: IMAS system
Antonio J. Gonzalez, Alvaro Anreus-Valero, David Sanchez et al. (+15 more)
This work summarizes the design, construction, initial performance evaluation and pilot clinical results of the IMAS system, a long axial field of view (FOV), also known as total-body (TB-), positron emission
tomography (PET) prototype scanner. This PET enables for the first time in TB-PET imaging, simultaneously time-of-flight (TOF) and depth-of-interaction (DOI) capabilities. The IMAS detector block is based on LYSO semi monolithic scintillators, with individual slab sizes of 3 mm x 25 mm x 20 mm each. Arrays of 1x8 slabs are coupled to 8x8 Silicon Photomultiplier arrays. A proprietary readout reduces the 64 signals to only 16 outputs, preserving both 3D
photon impact positioning and timing accuracy. IMAS has a total of 30,720 channels. PETsys electronics is used for data acquisition. The IMAS geometry is based on 5 rings of 10 cm each, with a 5 cm gap between them. It defines an axial FOV of 71 cm with a bore aperture of 82 cm. We report in this work the pilot tests of the system performance and the first clinical results. We found that the system spatial resolution remained below 4 mm across the entire FOV, even at the off-radial position of 30 cm. A coincidence time resolution with a small size 22Na source of 560 ps FWHM was measured. A sensitivity of 56.54 cps/kBq is in good agreement with previous simulation studies; however, the noise equivalent count rates performance (79 kcps at 3.26 kBq/mL) was significantly lower than expected, likely due to a data transfer bottleneck between the system and the acquisition workstation. Finally, a comparison of one of the imaged patients with a commercial TOF PET/CT scanner is also provided, pinpointing an improved tumor identification for IMAS, and the advantages of TOF and especially DOI capabilities.
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All authors Antonio J. Gonzalez, Alvaro Anreus-Valero, David Sanchez, Santiago Jiménez-Serrano, Marta Freire, Andrea Gonzalez-Montoro, Edwing Y. Ulin-Briseno, Neus Cucarella, John Barrio, Andrew Laing, Jorge Álamo, Julio Barbera, Luis F. Vidal, Marc Gil, Jose M. Benlloch, Alfonso Rios, Luis Marti Bonmati, Irene Torres-Espallardo
Optics · Cross-listed from cond-mat.mtrl-sci
Direct Laser Writing of Ferromagnetic Nickel Utilizing the Principle of Sensitized Triplet-Triplet Annihilation Upconversion
Kristin E. J. Kühl, Katharina Rediger, Nikhita Khera et al. (+5 more)
Direct
laser writing of
ferromagnetic microstructures is of great interest for sensing and data storage in compact three-dimensional architectures. However, reliable direct
laser writing of metallic and even more so
ferromagnetic materials remains a major challenge. Here, we present a novel photoresist suitable to direct
laser write
ferromagnetic nickel based on sensitized triplet-triplet annihilation upconversion. By combining an in-situ photochemical deoxygenation process with a sensitized triplet-triplet annihilation upconversion process as well as a photoreduction of Ni2+ ions, the deposition of metallic nickel is enabled under ambient conditions. Using this approach, nickel structures are fabricated as a proof of concept. Scanning electron microscopy and EDX analysis confirm the spatially confined deposition of nickel, while
magnetic characterization by vibrating sample magnetometry and scanning NV magnetometry demonstrate the
ferromagnetic nature of the printed structures. This work presents a major step forward in extending the possibilities of direct
laser writing to metallic and
ferromagnetic materials.
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All authors Kristin E. J. Kühl, Katharina Rediger, Nikhita Khera, Ephraim Spindler, Gereon Niedner-Schatteburg, Elke Neu, Mathias Weiler, Georg von Freymann
Atmospheric and Oceanic Physics · Cross-listed from cs.LG
CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning
Aleksei Rozanov, Arvind Renganathan, Yimeng Zhang et al. (+1 more)
Accurately quantifying terrestrial carbon exchange is essential for
climate policy and carbon accounting, yet models must generalize to ecosystems underrepresented in sparse eddy covariance observations. Despite this challenge being a natural instance of zero-shot spatial transfer learning for time series regression, no standardized
benchmark exists to rigorously evaluate model performance across geographically distinct locations with different
climate regimes and vegetation types. We introduce CarbonBench, the first
benchmark for zero-shot spatial transfer in carbon flux upscaling. CarbonBench comprises over 1.3 million daily observations from 567 flux tower sites globally (2000-2024). It provides: (1) stratified evaluation protocols that explicitly test generalization across unseen vegetation types and
climate regimes, separating spatial transfer from temporal autocorrelation; (2) a harmonized set of remote sensing and meteorological features to enable flexible architecture design; and (3) baselines ranging from tree-based methods to domain-generalization architectures. By bridging machine learning methodologies and Earth system science, CarbonBench aims to enable systematic comparison of transfer learning methods, serves as a testbed for regression under distribution shift, and contributes to the next-generation
climate modeling efforts.
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All authors Aleksei Rozanov, Arvind Renganathan, Yimeng Zhang, Vipin Kumar
Biological Physics · Cross-listed from q-bio.BM
Geometric-Chemical Distance Between Protein Surfaces
Himanshu Swami, John M. McBride, Jean-Pierre Eckmann et al. (+1 more)
Proteins recognize, bind, and catalyze through molecular surfaces, where geometry and chemical patterning determine interaction. Comparing these surfaces requires both a
geometric–chemical distance and a correspondence that relates one complete surface to another. Here we introduce IFACE (Intrinsic Field–Aligned Coupled
Embedding). IFACE derives a symmetric
geometric–chemical distance by optimizing a probabilistic coupling over intrinsic geometry, mean
curvature, electrostatics, hydrophobicity, and hydrogen-bond propensity. The same coupling provides an explicit surface map. For molecular-dynamics conformers, IFACE distinguishes the same
protein from distinct
proteins more accurately than TM-distance and a Laplace–Beltrami spectral distance. A Jensen–Shannon distribution distance performs best in this binary identity test, because aggregate surface-feature distributions already identify each
protein. A distance must also satisfy a global requirement: its pairwise values must place many distinct
protein surfaces consistently in one space. We therefore tested IFACE across six
protein families. It produces the strongest family classification and clustering among the distributional, spectral, MaSIF, and SurfaceID comparisons. The inferred maps preserve geodesic neighborhoods and transfer heme-centered pocket regions across cytochrome P450
proteins. IFACE therefore provides, from one construction, both a distance between complete
protein surfaces and the local map that explains that distance.
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All authors Himanshu Swami, John M. McBride, Jean-Pierre Eckmann, Tsvi Tlusty
Plasma Physics
Sparse identification of effective microparticle interaction potential in dusty plasma from simulation data
Zachary Brooks Howe, Lorin Swint Matthews, Truell Hyde et al. (+2 more)
Identification of the particle interaction potential is a challenging and important task in dusty
plasma, colloids, and smart materials as it allows the characterization of structure formation and helps predict phase transitions. With the advent of machine learning methods, this interaction can be extracted from particle position data, leading to a generalizable expression which is applicable in different systems. Methods such as sparse regression aim to provide a physically interpretable model that can generalize well, while avoiding unnecessary complexity due to overfitting. In this work, we present the use of the Sparse Identification of Nonlinear Dynamics (SINDy) with the weak formulation to learn equations of motion for noisy data from simple simulations of two
dust particles interacting with a Yukawa (shielded Coulomb) potential. The application of these methods to experimental dusty
plasma data is discussed, particularly in the case of simulation data and glass box experiments in RF discharge
gravity environments and DC discharge microgravity environments, such as the Plasmakristall-4 (PK-4) experiment.
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All authors Zachary Brooks Howe, Lorin Swint Matthews, Truell Hyde, Luca Guazzotto, Evdokiya Kostadinova
Physics and Society
Modeling structure and credit risk of the economy: a multilayer bank-firm network approach
Soumen Majhi, Anna Mancini and Giulio Cimini
Assessing the resilience of the economy requires accounting for its intrinsic multi-layer nature, by assessing for instance how disruptions at the firm level spread through the production network and propagate to the banking sector. Methods exist to measure the reverberation of shocks over the multilayer network of supply-customer relations among firms, corporate loans of banks and their interbank
market exposures. However, empirical network data are often
privacy protected and thus inaccessible to researchers and regulators. In this work we develop an unified framework, combining state-of-the art techniques to reconstruct the whole multilayer structure of the economy from balance sheet information of banks and firms, as well as dynamics of shock propagation from the inter-firm to the interbank layers. We showcase application of our methodology using data of the Italian economy. We identify the most systemically important firms and industries, as well as the most vulnerable banks, further assessing the determinants of systemic risk – obtaining results coherent with the empirical literature on network contagion. Overall, our framework allows performing detailed network-based stress tests on a digital twin of the economy, without requiring detailed network information that is difficult to acquire.
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Applied Physics
Transition Waves in Mechanical Metamaterials with Neighbor-Programmable Energy Landscapes
Eleonore Duval, Giada Risso, Alex Zhang et al. (+2 more)
Transition waves in mechanical metamaterials manifest themselves as propagating interfaces between different stable states in
lattices composed of arrays of coupled, intrinsically bistable elements. Here, we show experimentally and numerically that arrays of elastic unit
cells that are individually monostable, yet whose energy landscapes can be programmed through interactions with neighboring units, provide a rich and largely unexplored platform for transition wave propagation. We implement this concept by designing a unit
cell comprising a von Mises truss supported by two vertical elastic beams. In one-dimensional arrays of such units, we demonstrate that each
cell's energy landscape can change from monostable to bistable depending on the state of its neighbors. This neighbor-programmable energy landscape enables the controlled initiation and propagation of transition waves, giving rise to highly discrete, directionally unbiased, domino-like wave propagation. Experiments and numerical simulations show that the existence and speed of the waves are governed by
geometric design and mass distribution. Our results establish neighboring effects as a distinct mechanism for transition wave propagation, expanding the design space of mechanical metamaterials beyond architectures that rely on intrinsically multistable building blocks.
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All authors Eleonore Duval, Giada Risso, Alex Zhang, Vincent Tournat, Katia Bertoldi
Optics
Topologically constrained high intensity light propagation in air
A. Goffin, L. Railing, G. Babic et al. (+1 more)
We experimentally demonstrate how spatiotemporal optical
vortices (STOVs) control long-range atmospheric filamentation of intense
laser pulses. High-power pulses long enough to overlap with the delayed rotational nonlinearity of air molecules undergo periodic collapse arrest events, each of which generates toroidal STOV pairs with +/- topological charge that separate and accumulate into increasingly squeezed arrays of +1 charges at the front of the pulse and -1 charges at the back. These dynamics manifest as periodic energy deposition peaks along the propagation path and a pulse envelope modulated into a temporal intensity comb. Filamentation in this regime can be understood in terms of self-organized, topologically constrained defect dynamics embedded within nonlinear wave propagation.
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All authors A. Goffin, L. Railing, G. Babic, H. M. Milchberg
Optics · Cross-listed from quant-ph
High-efficiency telecom conversion of heralded atomic biphoton wavepackets
Ling-Chun Chen, Chang-Wei Lin, Jiun-Shiuan Shiu et al. (+3 more)
We demonstrate high-efficiency telecom frequency conversion of heralded atomic biphoton wavepackets using a diamond-type atomic ensemble. By placing a 2.5 MHz heralded-
photon spectrum within the high-efficiency region of the converter response, we achieve a conversion efficiency of 79.4(2.6)% while maintaining strong time-resolved correlations and well-defined temporal wavepackets. For a broader 17.4 MHz input bandwidth, the conversion efficiency is reduced to about 55%, whereas the temporal waveform remains largely preserved. This behavior reflects the nearly flat central response of the converter, which mainly causes spectral-edge loss rather than temporal-mode distortion. These results identify spectral matching as an effective route to efficient and low-distortion telecom conversion of narrowband
quantum light from atomic systems.
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All authors Ling-Chun Chen, Chang-Wei Lin, Jiun-Shiuan Shiu, Wei-Lin Chen, Yi-Che Wang, Yong-Fan Chen
Optics · Cross-listed from cs.ET
Layered Dielectric Characterization of Human Skin in the Sub-Terahertz and Terahertz Frequency Ranges
Silvia Mura, Elisabetta Marini, Maurizio Magarini et al. (+2 more)
Sub-terahertz (sub-THz) and terahertz (THz) radiation offer unique opportunities for non-invasive diagnostics and imaging due to their sensitivity to water content and molecular dynamics in biological tissues. In this work, a comprehensive dielectric model of human skin and its cellular constituents is developed across these frequency ranges. The model combines multi-Debye relaxation theory with effective medium formulations to account for intracellular water dynamics and macromolecular relaxation processes. Key cellular parameters, including water content,
protein and lipid fractions, and ionic conductivity, are integrated from experimentally validated sources. The proposed framework enables realistic predictions of frequency-dependent permittivity for different skin layers and
cell types, providing a physically interpretable description of sub-THz and THz tissue interactions. This approach establishes a foundation for the design and optimization of next-generation diagnostic and imaging techniques operating in these frequency bands.
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All authors Silvia Mura, Elisabetta Marini, Maurizio Magarini, Matti Hamalainen, Marco Hernandez
History and Philosophy of Physics · Cross-listed from quant-ph
An Introduction to the Foundations and Interpretations of Quantum Mechanics
Theodore McKeever and Ahsan Nazir
This article surveys a selection of key conceptual and interpretational developments in
quantum mechanics, tracing the theory from its foundational postulates to contemporary discussions of measurement, nonlocality, and the emergence of classicality. Beginning with the structure of
Hilbert space and the postulates governing state
evolution and measurement, the epistemic stance of the Copenhagen interpretation and its modern reformulations are examined. The Einstein-Podolsky-Rosen argument, Bell's
theorem, and Hardy's paradox are then discussed as probes of locality and realism, alongside the deterministic but explicitly nonlocal de Broglie-Bohm theory. The measurement problem and the implications of contextuality are analyzed in relation to objective collapse models, which introduce new physical dynamics to account for definite outcomes. Finally, the role of decoherence in the suppression of interference and the emergence of classical behavior is explored, together with the interpretational frameworks of many-worlds and consistent histories. This material aims to provide a coherent introductory overview of how several of the most prominent interpretations address the central concern of what
quantum mechanics tells us about the nature of physical reality.
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Optics
Experimental Characterization of Biological Tissue Dielectric Properties through THz Time-Domain Spectroscopy
Elisabetta Marini, Silvia Mura, Marco Hernandez et al. (+2 more)
Terahertz (THz) radiation provides a non-ionizing, highly sensitive probe of the dielectric properties of biological tissues. In this study, we present a comprehensive experimental characterization of dielectric properties using pork skin tissue, a widely used surrogate for human tissue, as a biological sample. Measurements are conducted employing THz time-domain spectroscopy in the 0.1-11 THz frequency range with photoconductive
antennas for both signal generation and detection. Frequency-dependent refractive indices, absorption, and complex permittivity are extracted from transmitted time-domain signals. Our results confirm strong absorption and low transmittance at low THz frequencies due to water content, while highlighting frequency-dependent dispersion and narrowband transmission features at higher frequencies. This work provides one of the first extended-frequency
datasets of biological tissue dielectric properties, supporting realistic channel modeling for the design and development of intra-body nanosensor networks in the THz band.
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All authors Elisabetta Marini, Silvia Mura, Marco Hernandez, Matti Hamalainen, Maurizio Magarini
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Efficient method for calculation of low-temperature phase boundaries
Lucas Svensson, Babak Sadigh, Christine Wu et al. (+1 more)
Understanding phase stability and phase transformations is central to predicting material behavior under varying thermodynamic conditions. One of the earliest and most influential applications of density functional theory in materials science has been the prediction of pressure-induced phase transitions at 0 K. Extending these calculations to finite temperatures, however, requires accounting for thermal,
quantum, and anharmonic contributions to the free energy, often at significant computational cost. In this work, we present a general and efficient framework for calculating low-temperature phase boundaries by combining the Clausius-Clapeyron equation with the quasi-harmonic approximation. This methodology requires a minimal number of calculations, while naturally incorporating internal degrees of freedom as well as
quantum and low-order anharmonic effects. We illustrate the accuracy and efficiency of the approach by constructing the phase diagram of silica in the pressure range from -2 to 12 GPa and temperatures up to 1750 K. To this end, we employ a machine-learned interatomic potential trained on density functional theory reference data, enabling well-converged free energy estimates via efficient thermodynamic sampling and a rigorous comparison between the proposed framework and free energy integration.
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All authors Lucas Svensson, Babak Sadigh, Christine Wu, Paul Erhart
Fluid Dynamics
Network modelling of yield-stress fluid flow in randomly disordered porous media
Cláudio P. Fonte, Elliott Sutton, Kohei Ohie et al. (+3 more)
Yield-stress fluid flow through porous media is governed by a strong coupling between rheology and pore-scale geometry, leading to nonlinear, non-Darcy transport and pronounced channelisation near yielding. We develop a pore-network model for Herschel-Bulkley flow in two-dimensional disordered porous media, including optional wall slip. The network is closed by a physics-based pressure-flow relation for a converging-diverging throat, so that yielding and post-yield transport emerge directly from the pore-scale fluid mechanics without fitted resistance parameters. Benchmarking against direct numerical simulations shows that the model captures both the bulk pressure drop and the
evolution of the flow
topology from spatially distributed transport to strongly channelised flow. The framework also captures the leading effect of wall slip, which lowers the pressure gradient required for transport and reactivates pathways that remain blocked in the no-slip case. Using the model across different porous geometries, we show that near-yield pressure losses are governed by constriction statistics rather than by an obstacle-scale length. In particular, rescaling with the domain-averaged minimum throat width collapses the plastic-dominated response across porosities, identifying the dissipation-relevant
geometric scale for viscoplastic transport in this regime.
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All authors Cláudio P. Fonte, Elliott Sutton, Kohei Ohie, Eleanor Doman, Yuji Tasaka, Anne Juel
Computational Physics · Cross-listed from hep-ph
First Estimation of Model Parameters for Neutrino-Induced Nucleon Knockout Using Simulation-Based Inference
Karla Tame-Narvaez, Steven Gardiner, Aleksandra Ćiprijanović et al. (+1 more)
To enable an accurate determination of oscillation parameters, accelerator-based
neutrino experiments require detailed simulations of
nuclear interaction physics in the GeV regime. While substantial effort from both theory and experiment is currently being invested to improve the fidelity of these simulations, their present deficiencies typically oblige experimental collaborations to resort to empirical tuning of simulation model parameters. As the precision requirements of the field continue to become more stringent, machine learning techniques may provide a powerful means of handling corresponding growth in the complexity of future
neutrino interaction model tuning exercises. To study the suitability of simulation-based inference (SBI) for this physics application, in this paper we revisit a tuned configuration of the GENIE
neutrino event generator that was originally developed by the MicroBooNE collaboration. Despite closely reproducing the adopted values of four physics parameters when confronted with the tuned cross-section predictions as input, we find that our trained SBI
algorithm prefers modestly different values (within MicroBooNE's assigned uncertainties) and achieves slightly better goodness-of-fit when inference is run on the experimental data set originally used by MicroBooNE. We also find that our trained
algorithm can create a fair approximation of an alternative
neutrino scattering simulation, NuWro, that shares only a subset of its physics model parameters with GENIE.
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All authors Karla Tame-Narvaez, Steven Gardiner, Aleksandra Ćiprijanović, Giuseppe Cerati
Optics · Cross-listed from cond-mat.mtrl-sci
Resolving Transient Electron-Phonon Coupling with Time-Resolved Spontaneous Raman Spectroscopy
Guy Reuveni, Maya Levy Greenberg, Matan Menahem et al. (+2 more)
Understanding the interaction of charge carriers with
lattice vibrations in the quasi-
equilibrium regime is crucial for
semiconductor functionality. However, the structural signatures of these interactions are often too subtle for conventional ultrafast techniques to detect. We developed a time-resolved spontaneous Raman technique based on time-correlated single-
photon counting to track the spectral response following photoexcitation, providing sub-wavenumber spectral resolution and a few-hundred-picosecond temporal resolution. Unlike traditional pump-probe schemes, our method utilizes a modulated continuous-wave probe to maintain high spectral resolution, enabling detection of low-frequency Raman shifts down to 10 cm$^{-1}$. Applied to lightly boron-doped silicon, we resolve intra-valence band and inter-valence band electronic transitions. A coupled-mode analysis of transient
phonon asymmetry, resulting from interference with the inter-valence band transitions, reveals electron-
phonon coupling parameters that directly relate to carrier recombination. By capturing these subtle dynamical shifts, we demonstrate that this platform offers a powerful probe for investigating electron-
phonon interactions in long-lived excited states.
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All authors Guy Reuveni, Maya Levy Greenberg, Matan Menahem, Olle Hellman, Omer Yaffe
Physics and Society
Methodological opportunities for mitigating climate change in complex food systems
Erik van der Linden, Marcel Meinders, Egbert H. van Nes et al. (+1 more)
Unravelling current complex food systems is relevant for their adjustment and redesign under the current changing
climate conditions. Redesign may be necessitated by migration of people and changes of locations of major agri-food production. The redesign should be conducted synchronously with that of systems entangled with the food system, such as the socio-economic and cultural system. For such synchronous redesign a common methodological approach with a common set of methods is required. In the current article we suggest a common set of methods, and discuss how these methods find their basis in vastly different science fields, ranging from soft matter, biology, urban socio-economics, ecology, to machine learning. We address the various ways such methods have been applied in relatively small parts of the food systems and how they can be applied to larger parts of current and future food systems. The set of methods facilitates to identify the level of structuredness and randomness in complex systems. It helps to better predict upcoming transitions in complex systems, according critical points, and sudden instabilities. It facilitates in extracting information from a system, before, during and after the time that one makes an intervention, which in turn will help to decide which interventions are best to maintain or change functions of a complex system.
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All authors Erik van der Linden, Marcel Meinders, Egbert H. van Nes, Hugo de Vries
Chemical Physics · Cross-listed from quant-ph
Operational bounds and diagnostics for coherence in energy transfer
Julia Liebert and Gregory D. Scholes
Excitation energy transfer in light-harvesting aggregates is highly efficient, yet whether
quantum coherence plays an operational role in transport remains debated. A central challenge is that coherence is usually inferred from spectroscopic signatures, whereas transport performance is assessed through specific observables and depends on both the open system dynamics and the initial state preparation. Here we develop a resource theoretic approach that quantifies the maximum change that initial site-basis coherence can induce in a chosen readout under fixed reduced dynamics. The central quantity is the resource impact functional, which yields state independent, readout specific bounds on coherence-induced changes in signals and transport figures of merit. We apply the framework to two models. For a donor-acceptor dimer, we analyse coherence sensitivity across coupling and bath-timescale regimes and bound trapping efficiency and average transfer time in terms of the impact functional. For a multi-site chain with terminal trapping, we derive rigorous criteria that distinguish population placement from sensitivity to initial state site-basis coherence. These include upper bounds on the largest advantage over incoherent preparations, necessary delocalization requirements for achieving a prescribed improvement, and a simple pairwise sufficient condition that can be checked from local information. For quasi-local reduced dynamics, we further obtain a Lieb-Robinson-type bound that constrains when coherence prepared in a distant region can influence a localized readout at finite times. Together, these results provide operational diagnostics and rigorous bounds for benchmarking coherence effects and for identifying regimes in which they are necessarily negligible or potentially relevant in excitonic transport models.
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Fluid Dynamics · Cross-listed from cond-mat.quant-gas
Reproducible nucleation and control of stable quantum vortex rings in Bose-Einstein condensates
Giorgia Iori, Klejdja Xhani, Woo Jin Kwon et al. (+2 more)
We propose and numerically validate an experimentally feasible on-demand protocol for the nucleation and manipulation of stable
quantum vortex rings in trapped Bose-Einstein condensates. The method relies on sweeping a
laser-sheet barrier that locally constricts the superflow and triggers
vortex-ring formation. By tuning the barrier height and width, and by scanning the barrier velocity, we identify the onset of periodic generation of
vortex rings above the critical velocity and achieve direct, deterministic control over the ring nucleation position, radius, and hence propagation speed. After its formation, ad-hoc optical potentials are applied to reshape the
vortex ring, creating clean Kelvin-wave excitations. Our results provide a foundation for systematic studies of three-dimensional
vortices in atomic superfluids and open the door to tailored
vortex dynamics and interactions, enabling controlled access to
quantum turbulence.
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All authors Giorgia Iori, Klejdja Xhani, Woo Jin Kwon, Davide Emilio Galli, Luca Galantucci
Chemical Physics
Vibrational strong coupling influences product selectivity in a model for post transition state bifurcation reactions
Subhadip Mondal, Atul Kumar and Srihari Keshavamurthy
In this study we explore the possibility of modulating product selectivity (branching ratios) in post transition state bifurcation (PTSB) reactions via vibrational strong coupling (VSC) to an optical cavity. Detailed classical and
quantum dynamical calculations on a model potential reveal that the branching ratio can be enhanced by nearly a factor of two under VSC conditions. Interestingly, upon altering the shape of the potential, we find a switch in the cavity frequency at which maximum enhancement in selectivity is observed. Apart from emphasizing the role of both cavity-system and intramolecular energy transfer to the observed enhancements, we highlight the complexity of the VSC mechanism in terms of the choice of the cavity frequency vis–à–vis the various molecular mode frequencies. Our work shows that, in principle, cavity
quantum electrodynamics can reshape dynamical outcomes in reactions with complex potential energy landscapes.
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Chemical Physics
Optical frequency comb double-resonance spectroscopy of the 9030-9175 cm$^{-1}$ states of ethylene
Adrian Hjältén, Vinicius Silva de Oliveira, Yuan Cao et al. (+3 more)
We use optical-optical double-resonance (OODR) spectroscopy to measure for the first time hot-band transitions of ethylene (C${_2}$H${_4}$) between states in the 3000 cm$^{-1}$ and 9000 cm$^{-1}$ energy ranges. A 3.2 ${\mu}$m continuous wave (CW) pump is used to populate selected states in the ${\nu}$${_9}$ vibrational mode. The sub-Doppler OODR transitions are then probed with two different cavity-enhanced probes tunable around 1.7 ${\mu}$m: a frequency comb probe that allows for broadband measurements and simultaneous detection of many OODR lines, and a CW probe that measures individual lines with higher signal-to-noise ratio and better frequency accuracy. We report center frequencies and relative intensities of 90 ladder-type hot-band transitions from three different states in the ${\nu}$${_9}$ vibrational mode. We exploit combination differences and measurements of polarization-dependent intensity ratios to determine the final state rotational
quantum numbers J. Comparison to theoretical predictions from ExoMol allows tentative assignments for 28 transitions. We report improved center frequencies for the three pump transitions in the ${\nu}$${_9}$ band. Furthermore, we observe 18 sub-Doppler V-type transitions from the depleted ground state to the 6000 cm$^{-1}$ region and assign 14 of them to the variational line list of Mraidi et al. [J Quant Spectros Radiat Transfer. 2023;310:108734 doi:10.1016/j.jqsrt.2023.108734].
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All authors Adrian Hjältén, Vinicius Silva de Oliveira, Yuan Cao, Isak Silander, Kevin K. Lehmann, Aleksandra Foltynowicz
History and Philosophy of Physics
Does Quantum Cosmology Predict the Age of the Universe?
Álvaro Mozota Frauca
The problem of time of
quantum gravity has been argued to make canonical approaches unsatisfactory. In this article I study how it affects
quantum cosmology and reach the same conclusion. The advantage of studying the cosmological case is that its simplicity makes the discussion much clearer and less technical. The classical models I will be concerned with describe how two degrees of freedom, the scale factor and a scalar field, evolve with respect to a time variable. After quantizing the model, this time variable just disappears, and I argue that this is problematic. Indeed, this variable in the classical model allowed us to make claims like `the universe is 13.8 billion years old' and I will argue that these claims are physically meaningful predictions that are lost in
quantum cosmology. I will analyze some of the relational positions in the
quantum gravity and
quantum cosmology literature that tend to deny the physical meaning of time variables and I will argue against them for the case of classical cosmology. I conclude that the age of the universe is a physical prediction of classical cosmological models, that it is missing from
quantum cosmology, and that this should make us suspect that there is something wrong with this sort of approach.
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Computational Physics · Cross-listed from cs.LG
Physics-informed neural operator for parametric phase-field modelling of interfacial degradation and microstructural evolution
Nanxi Chen, Airong Chen and Rujin Ma
Predicting interfacial degradation and microstructural
evolution through phase-field modelling is computationally intensive, particularly for parametric studies. While neural operators such as the
Fourier neural operator (FNO) offer a promising route to acceleration, the absence of physical constraints compromises their generalisation and long-term stability. Here, we present PF-PINO, a physics-informed neural operator framework that embeds phase-field governing equation residuals directly into the training loss, together with gradient normalisation loss balancing and a staggered training scheme for coupled multi-field systems. PF-PINO is validated on four
benchmarks including pencil-electrode corrosion, electro-polishing corrosion, dendritic solidification, and spinodal decomposition, collectively probing parametric generalisation across orders-of-magnitude kinetic regimes, non-periodic boundaries with
stochastic morphologies, coupled multi-field dynamics with out-of-distribution extrapolation, and long-term autoregressive stability under complex pattern formation. Across all
benchmarks, PF-PINO reduces relative $L^2$ errors by up to an order of magnitude over FNO and achieves sub-mesh-size interface accuracy, establishing a data-efficient surrogate for high-throughput parametric phase-field assessment in computational materials science and engineering applications.
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Fluid Dynamics
Immiscible two-phase flow in porous media: a statistical mechanics approach
Alex Hansen and Santanu Sinha
The central problem in the physics of immiscible two-phase flow in porous media is to find a proper description of the flow at scales large enough so that the medium may be regarded as a continuum: the scale-up problem. So far, the only workable approach to the multiphase flow scale-up problem has been a set of phenomenological equations that have obvious weaknesses. Attempts at going beyond this relative permeability theory have so far not led to practical applications due to exploding complexity. Edwin T. Jaynes proposed in the fifties a generalization of statistical mechanics to non-thermal systems based on the information theoretical
entropy of Shannon. This approach is used to construct a description of immiscible two-phase flow in porous media at the continuum scales, which is directly related to the physics at the pore scale, and at a level of complexity that is manageable. The approach leads to a thermodynamics-like formalism at the continuum scale with all the relations between variables that "normal" thermodynamics has to offer. New emergent variables appear. Among these, the co-moving velocity stands out as a key variable with implications for ordinary thermodynamics. We present here a short review of this approach.
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Geophysics · Cross-listed from cs.LG
Well Log-Guided Synthesis of Subsurface Images from Sparse Petrography Data Using cGANs
Ali Sadeghkhani, A. Assadi, B. Bennett et al. (+1 more)
Pore-scale imaging of subsurface formations is costly and limited to discrete depths, creating significant gaps in reservoir characterization. To address this, we present a conditional Generative
Adversarial Network (cGAN) framework for synthesizing realistic thin section images of carbonate rock formations, conditioned on porosity values derived from well logs. The model is trained on 5,000 sub-images extracted from 15 petrography samples over a depth interval of 1992-2000m, the model generates geologically consistent images across a wide porosity range (0.004-0.745), achieving 81% accuracy within a 10% margin of target porosity values. The successful integration of well log data with the trained generator enables continuous pore-scale visualization along the wellbore, bridging gaps between discrete core sampling points and providing valuable insights for reservoir characterization and energy transition applications such as carbon capture and underground hydrogen storage.
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All authors Ali Sadeghkhani, A. Assadi, B. Bennett, A. Rabbani
Optics
Toroidal helical pulses
Shuai Shi, Hongcheng Zhou, Junjie Shao et al. (+7 more)
Toroidal
topologies and helicity are pervasive in nature and hold basic importance in scientific research. In particular, the interplay between these features gives rise to fascinating toroidal helical electromagnetic excitations. Here, we present a theoretical framework and experimental realization to introduce a family of toroidal helical pulses, exploring the intersection of the helicity and propagating toroidal modes. For this purpose, we propose a configuration combining a coaxial horn emitter and an equiangular spiral grating to directly generate such single-cycle pulses. In addition to their inherent non-transverse toroidal
topology and space-time nonseparability, such pulses also possess controllable helicity. This work gives rise to a helical version of propagating toroidal electrodynamics, thereby paving the way for advanced applications, such as nontrivial light-matter interactions and data transfer.
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All authors Shuai Shi, Hongcheng Zhou, Junjie Shao, Pan Tang, Bing-Zhong Wang, Mu-Sheng Liang, Yanhe Lyu, Boris A. Malomed, Yijie Shen, Ren Wang