Materials Science
Role of Resonant $\mathbf{k}$-Points in the Transient Optical Response of Pumped Germanium
Amir Eskandari-asl, Giacomo Inzani, Matteo Lucchini et al. (+1 more)
Pump-induced transient optical properties combine contributions from electronic states throughout the Brillouin zone, but the relative relevance of off-resonant and l-
photon resonant
crystal momenta has remained unexplored. We address this issue in pumped germanium by resolving the transient absorptive response into momentum-space classes defined by the presence or absence of 1-, 2-, and 3-
photon resonances with respect to the pump. Using the Dynamical Projective Operatorial Approach together with the related generalized linear response theory, we compute the differential imaginary part of the dielectric function and evaluate the contributions of each resonance class. Resonant regions account for nearly the entire optical response, whereas points outside the identified resonance sets contribute only negligibly. Nevertheless, the 2-
photon-resonant set, although containing more than 98% of the residual (post-pump) excitation population, does not reproduce the full transient spectrum. Conversely, resonance classes with very small residual populations generate non-negligible contributions to the transient optical properties. This mismatch shows that the transient optical weight is not determined solely by the real-charge dynamics (which results in post-pulse residual excitation population) and is consistent with substantial virtual pump-induced contributions, whose dominant optical weight nevertheless arises from the resonant regions of momentum space. The class-resolved phase of the dominant 2$\omega_{\mathrm{pu}}$ oscillations further shows that, whenever a class contributes appreciably, the phase of its oscillatory component follows that of the corresponding full signal. The resulting decomposition provides a momentum-resolved connection among multi-
photon resonances and transient optical observables in a realistic material.
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All authors Amir Eskandari-asl, Giacomo Inzani, Matteo Lucchini, Adolfo Avella
Quantum Physics
Entanglement dynamics through electromagnetic interactions in single-electron traps
Pablo Guillermo Carmona Rufo, Anupam Mazumdar and Carlos Sabín
We study the dynamics of
quantum entanglement between two harmonically trapped electrons interacting via the electromagnetic force. Starting from two-mode Gaussian states at thermal
equilibrium, we make use of the covariance
matrix formalism in order to compute the logarithmic negativity of the evolved state as a quantitative measure of
entanglement. We analyze two initial configurations: thermal single-mode and two-mode squeezed states, and describe the time
evolution of
entanglement in the system for different values of squeezing and temperature, while identifying the parameter regimes accessible to current and near-future single-electron trap experiments.
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Computational Physics
Dynamical and Optimization Trade-offs of Levi–Civita Coordinates for Learned Close-Encounter Dynamics
Abhishek Shankar
Classical regularization removes the binary-collision singularity from the Kepler problem, but its value as a representation for learned
Hamiltonian dynamics has not been systematically isolated. We compare Cartesian and planar Levi–Civita formulations of a perturbed Kepler system with a smooth quadrupole potential. With the perturbation supplied analytically, a Levi–Civita
Hamiltonian splitting holds the maximum relative energy error near $2.1\times10^{-5}$ through eccentricity $e=0.99$, while the Cartesian splitting becomes unstable. This advantage persists at matched physical horizon and force-evaluation budget, where the regularized baseline is $3\times10^{-5}$, about $4.7$–$8.3$ orders of magnitude below the Cartesian arm depending on eccentricity. In held-out high-eccentricity tests with matched sampling, regularized models produce finite rollouts in $40/40$ runs versus $0/40$ for Cartesian. However, the fixed-shell construction supplies the regularized model with the exact initial orbit energy, and survival still carries $\mathcal{O}(1)$ energy error. Four neural residual objectives fail to approach the analytic result. Exact-feature controls show that the regularized residual is a four-monomial degree-6
polynomial that a direct least-squares solve fits to the baseline. The remaining exact-feature gap is due to severe raw-basis ill-conditioning: orthogonalization restores baseline fitting for L-BFGS in two iterations. Small MLPs remain at $\mathcal{O}(1)$ rollout error even after gauge symmetrization. Levi–Civita coordinates therefore improve dynamical conditioning while worsening raw-basis optimization conditioning; accurate neural residual learning remains unresolved. This is a controlled falsification-plus-trade-off study, not a solution to learned close-encounter dynamics.
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Quantum Physics
Coupling phase interference effects in a multimode cavity magnonics system
M. Avicena, G. Bourcin, V. Vlaminck et al. (+2 more)
Coupling phases play a decisive yet often overlooked role in cavity magnonics, particularly in complex multimode systems. Here, we investigate phase-mediated interference effects in a cavity magnonics system comprising a four-post re-entrant microwave cavity coupled to Yttrium Iron Garnet (YIG) spheres. Using an input-output model that explicitly accounts for both internal and external coupling phases, we achieve agreement with experimental microwave transmission measurements. Our results unravel the emergence of a positionally-dependent uncoupled mode due to interference of cavity
photon-
magnon (internal) coupling phases. Further, we experimentally observed large nonreciprocity at the antiresonance frequencies and show that this feature arises due to the far-detuned modes' odd parity cavity
photon-probe (external) coupling phase interfering with the internal coupling phases. Bridging theory, simulation and experiment, these results establish coupling-phase engineering as a key principle for accurately modeling and designing multimode cavity magnonics devices.
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All authors M. Avicena, G. Bourcin, V. Vlaminck, J. Bourhill, V. Castel
High Energy Astrophysical Phenomena
Identifying Kilonovae in the Presence of Optical Afterglow for the Wide Field Survey Telescope
Huan Yang, Zhengyan Liu, Liang-Duan Liu et al. (+2 more)
Identifying kilonovae associated with binary
neutron star mergers is often complicated by the presence of a dominant synchrotron afterglow. In this work, we evaluate the performance of the Wide Field Survey
Telescope (WFST) in identifying kilonova signals in composite afterglow-kilonova transients. Using a numerical framework based on the Fisher information
matrix, we simulate $10,000$ realizations for each of two scenarios: an AT2017gfo-based template model and a physically sampled population that accounts for kilonova diversity. Our results indicate that kilonova identification is primarily limited by source distance. In both scenarios, the identification efficiency is largely insensitive to variations in afterglow microphysical parameters and exceeds $80\%$ at distances within approximately $600~\rm Mpc$ for AT2017gfo-like events. Under our adopted assumptions and a short gamma-ray burst (sGRB)-triggered target-of-opportunity (ToO) observational strategy, we estimate that the WFST could identify $0.1-1.2$ kilonovae per year in the optimistic scenario. Furthermore, we find that the discriminating power of color-based filters rapidly saturates, reaching a stable plateau by the second night after the merger. We therefore propose a staged observing strategy that prioritizes high-cadence $g$ and $r$-band monitoring during the first night and incorporates the $z$ band from the second night onward. This strategy improves the identification precision by exploiting the increasingly prominent red excess produced by the kilonova. Our results provide a physical basis for optimizing WFST observing resources to efficiently detect and characterize kilonovae in the multimessenger era.
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All authors Huan Yang, Zhengyan Liu, Liang-Duan Liu, Wen Zhao, Zigao Dai
Quantum Physics
Lattice quantum electrodynamics of a molecular emitter in a topological gap
Clarisse Fournier, Johannes Düreth, Elena Fanella et al. (+12 more)
Engineering the photonic environment using
lattices of coupled resonators, which we refer to as
lattice quantum electrodynamics (QED), provides a route to control both the spontaneous emission of individual
quantum emitters and the
photon-mediated interactions between them. Here we introduce an optical
lattice QED platform based on individual dibenzoterrylene (DBT) molecules embedded in anthracene
crystals and coupled to
lattices of open optical microcavities. This hybrid architecture benefits from narrow-linewidth molecular emitters, site-resolved optical access, engineered coupled-resonator bands, and compatibility with established molecular frequency-tuning techniques. As a proof-of-principle demonstration, we observe emitter-
photon bound states formed when the optical transition of a single molecule is tuned to the band gap of a Su-Schrieffer-Heeger (SSH) cavity
lattice. These in-gap states display directional localization and
photon emission on a single sublattice, inherited from the vacancy-induced topological edge modes of the underlying SSH
lattice. Our results establish open-cavity
lattices coupled to DBT molecules as a versatile architecture for engineering many-emitter
quantum optical systems with controllable
photon-mediated interactions.
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All authors Clarisse Fournier, Johannes Düreth, Elena Fanella, Hugo Levy-Falk, Maja Colautti, Anna Beauvironnet, Gauthier Dekyndt, Clément Hainaut, Tomáš Neuman, Simon Betzold, Sven Höfling, Sebastian Klembt, Alejandro González-Tudela, Costanza Toninelli, Alberto Amo
Biological Physics
Static and Dynamic Estimation of Flexural Rigidity of Soybean
Akihito Kiyama, Haruka Tomobe, Jisoo Yuk et al. (+2 more)
This paper evaluates a cantilever system as a simple method for measuring the mechanical
rigidity (bending
rigidity EI or Young's modulus E) of plants. Using soybeans as a test sample – whose E values have rarely been reported – we conducted static and dynamic experimental measurements alongside numerical modal analysis. Results showed good agreement in EI values between the static and dynamic tests when branches and leaves were removed, provided the stem responded uniformly. However, the added mass of attached foliage causes complex dynamic interactions, which we analyze through both experimental and numerical approaches. Ultimately, our findings suggest that cantilever force-deflection measurements provide a practical, on-site approach, contributing to the development of an affordable and reliable standard for estimating plant mechanical properties.
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All authors Akihito Kiyama, Haruka Tomobe, Jisoo Yuk, Sharon Wang, Sunghwan Jung
Quantum Physics
DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems
Seongmin Kim, Abhinav Rijal, Yuri Alexeev et al. (+5 more)
While combinatorial optimization problems are central to many scientific and engineering applications, their solution remains challenging due to exponentially large search spaces. Variational
quantum algorithms offer a promising route for tackling such problems, yet their practical performance is limited by repeated
quantum circuit evaluations and classical parameter updates. In this work, we introduce DQAOA-GPT, a hybrid framework that integrates the distributed
quantum approximate optimization
algorithm (DQAOA), which decomposes a large optimization problem into smaller sub-problems, with GPT-based
quantum circuit generation for solving those sub-problems. Rather than relying on iterative variational optimization, the proposed approach uses a trained generative model to directly generate high-quality
quantum circuits for the decomposed sub-problems. As a
benchmark, we evaluate DQAOA-GPT against conventional DQAOA on dense HUBO optimization problems with up to 100 decision variables. The results demonstrate that DQAOA-GPT significantly reduces computational cost while maintaining competitive solution quality, with larger acceleration observed for larger sub-problem sizes. Although this work focuses on
benchmark-scale validation, the framework provides a promising foundation for larger-scale combinatorial optimization in hybrid HPC-QC environments through increased GPU resources and parallel computing capability.
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All authors Seongmin Kim, Abhinav Rijal, Yuri Alexeev, Nora Bauer, Martin Roetteler, Mina Yoon, George Siopsis, In-Saeng Suh
Fluid Dynamics
Bayesian finite element regression for vascular flow reconstruction with quantified uncertainty
Cem Gormezano and Shawn Shadden
Reconstructing accurate velocity and pressure fields from under-resolved noisy measurements of blood flow is an ill-posed inverse problem due to unknown inlet and outlet boundary conditions. We present a
Bayesian finite element regression framework that reconstructs steady three-dimensional velocity and pressure fields, with quantified uncertainty, from noisy velocity observations without offline training data. We represent velocity and pressure fields in Taylor-Hood finite element basis functions, and construct physics-informed priors on the nodal degrees of freedom from maximum-
entropy principles. Combined with a likelihood specified by a noise-model, this yields a posterior whose maximum-a-posteriori estimate (MAP) gives velocity and pressure reconstructions. The MAP estimate is computed by solving a large-scale sparse nonlinear least-squares problem where pressure is eliminated analytically, no-slip walls are enforced exactly, and gradient is computed without forward/adjoint solves or automatic differentiation. A Laplace approximation of the posterior quantifies the uncertainties in our reconstructions and propagates them to clinically relevant quantities of interest including, pressure drop, flow rates, and wall shear stress. On patient-specific cerebral aneurysm, aortic aneurysm, and aortic coarctation geometries, the method reconstructs velocity and pressure more accurately than tricubic interpolation and comparably to a PINN, while recovering region-of-interest wall shear stress more accurately than both.
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Soft Condensed Matter
A Theoretical Framework for the Coupling of Macroscale-Nanoscale Mechanochemical Phenomena in Condensed Matter
Brenden W Hamilton
The field of covalent mechanochemistry has transitioned from fundamental science to engineering applications, yet it lacks a robust theoretical framework for predicting reaction kinetics in condensed matter. Existing analytical models fail under realistic conditions where macroscopic strains drive molecular-scale deformations that are highly non-linear. We develop a non-perturbative theoretical framework that captures activation barrier changes in highly strained molecules undergoing complex, non-linear deformations, describing the macroscale-nanoscale coupling of phenomena. The framework yields general expressions, parameterizable from atomistic simulations, enabling multiscale prediction of mechanochemical behavior. By presenting the expressions in terms of general observables, this work enables predictions of mechanochemical effects from simple structure optimization calculations, enabling the use of high level
quantum chemical methods. We demonstrate this approach on the mechanochromic
polymer spiropyran, showing how non-linear strain fields govern mechanophore activation.
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High Energy Astrophysical Phenomena
Shock acceleration in vortex driven magnetic fields of black holes
Zaza N. Osmanov
The aim of this work is to investigate particle acceleration by shock waves in the magnetospheres of supermassive black holes, where the
magnetic field is
vortex-driven. For this purpose, we investigated the first-order
Fermi acceleration process at relativistic shocks in the magnetospheres of supermassive black holes. In our analysis, we considered synchrotron radiation and inverse Compton scattering as the principal energy-loss mechanisms limiting the maximum attainable particle energy. We investigated the acceleration of both
protons and electrons and demonstrated that, for a typical supermassive black hole with a mass of $10^8$
solar masses,
protons can be accelerated to energies of several hundred PeV, whereas electrons can attain energies of up to approximately 120 GeV.
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Chemical Physics
A Comprehensive Experimental and Theoretical Spectroscopic Study of Proteinogenic Amino Acids
Ann S. Y. Lu, Prajna Bhatt, Nathalie K. Fernando et al. (+2 more)
Amino acids are essential building blocks of life, yet our understanding of their chemistry and electronic structure in the solid state remains limited. This is particularly important because amino acids in the solid state are relevant to biological and pharmaceutical processes. X-ray photoelectron spectroscopy provides a powerful experimental probe of chemical states and occupied electronic structure; however, most spectroscopy studies of amino acids focus on gas-phase species or surface adsorbates, while crystalline amino acids remain underexplored, largely because of experimental challenges associated with radiation damage. Additionally, the spectra are often complex and difficult to interpret, motivating a combined experimental-theoretical approach. This study combines X-ray photoelectron spectroscopy and density functional theory calculations to systematically investigate the core, semi-core, and valence states of 20 proteinogenic amino acids as well as selenomethionine which can be incorporated during
protein synthesis and deliver the essential nutrient, Se, required by humans. Calculated relative core binding energies show excellent agreement with experiment and enable reliable assignments. Projections of the density of states provide insight into the influence of local coordination and extended
crystal structure, yielding a systematic understanding of the electronic structure and bonding in solid-state AAs. The insights gained from this study enhance the understanding of crystalline amino acids and validate the robustness of an integrated experiment–theory framework.
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All authors Ann S. Y. Lu, Prajna Bhatt, Nathalie K. Fernando, Laura E. Ratcliff, Anna Regoutz
Fluid Dynamics
A formal log(Re)-cost framework for the engineering turbulence problem
Jiaqi Li, Robert F. Kunz, George Huang et al. (+1 more)
In fluid engineering, the
turbulence problem is the longstanding challenge of obtaining accurate predictions of engineering quantities at affordable computational cost. Viewed through computational complexity, a practical
algorithm requires cost growth no worse than $O(N)$, where $N$ denotes problem size. For turbulent flows, the problem size may be approximated by the number of dynamically relevant scales and hence by the Reynolds number $Re$. We propose a multi-fidelity, physics-constrained, data-driven framework designed to meet this criterion under stated assumptions. We augment the Spalart–Allmaras model through field inversion and machine learning using a constrained formulation that preserves the law of the wall. The model is trained at a low Reynolds number, where high-fidelity data are affordable, and deployed at higher Reynolds numbers. For a mean-flow-aligned grid in a wall-bounded flow, fixed spanwise resolution, and steady-solver cost linear in grid-point count, the low-fidelity RANS prediction scales as $O(\log(Re))$. The high-fidelity calculation and learning stage each contribute $O(Re^0)$ relative to the target Reynolds number, giving an overall formal cost of $O(\log(Re))$. In plane channel flow, a model trained at $Re_\tau=1000$ corrects the wake-layer error of the baseline model and retains the improvement at $Re_\tau=5200$. In the periodic hill, a model trained at $Re_b=5600$ is tested at $Re_b=10595$, $19000$, and $37000$. The constrained formulation preserves separation and recovery behavior as Reynolds number increases, yields the lowest root-mean-square error across all tests, and exhibits nearly Reynolds-number-independent error, indicating robust extrapolation.
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All authors Jiaqi Li, Robert F. Kunz, George Huang, Xiang I. A. Yang
Quantum Physics
Observable Geometry for Effective Quantum Circuits
Huan-Hsin Tseng, Hsin-Yi Lin, Samuel Yen-Chi Chen et al. (+3 more)
We study redundancy and effectiveness of Variational
Quantum Circuits via algebraic and
geometric views of Lie groups. Considering
unitary transformations acting on Hermitian observables, a stabilizer group decomposition is given. Subsequently, we identify the Hermitian orbit with a quotient space of a symmetric space. Through this connection, we characterize the effective
circuit degrees of freedom. Our approach of spectral decompositions and homogeneous spaces yields tractable calculation criteria, which are verified by numerical experiments.
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All authors Huan-Hsin Tseng, Hsin-Yi Lin, Samuel Yen-Chi Chen, Yan Mong Chan, Tzu-Chieh Wei, Shinjae Yoo
Quantum Physics
Mesoscopic mechanical superpositions by gluing individual quantum systems
Thiago Guerreiro
We propose a protocol for preparing mechanical Schrödinger kittens – mesoscopic
quantum superpositions of coherent motional states of an optically levitated nanoparticle – by adhering single electron time-bin states to its surface. Over short protocol timescales, coherence of the mesoscopic superposition survives the dominant decoherence mechanisms afflicting levitated systems, and can be observed by varying the phase of the time-bin electrons. Interference fringes can be detected with real-time, near-Heisenberg limited interferometry of
photons scattered from the particle. This approach eliminates the need for coherent state expansion, dark potentials, and particle release-and-recapture mechanisms, providing a new route to test
quantum mechanics in unprecedented scales.
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Fluid Dynamics
Parameter mapping and physical reconstruction of Akhmediev breathers at the interface of two fluid half-spaces
Olga Avramenko and Volodymyr Naradovyi
A methodology combining parameter mapping and physical reconstruction of Akhmediev breathers at the interface between two fluid half-spaces is developed on the basis of the Nayfeh model. Parameter maps are constructed to characterize the breather modulation period, the modulational instability growth rate, and the relative contribution of the bound second harmonic to the reconstructed interfacial profile. Their combined analysis provides a physically meaningful classification of breather regimes beyond the conventional focusing condition of the nonlinear Schrödinger equation. Reconstruction of the physical interfacial profile establishes a quantitative relation between nonlinear wave deformation and the contribution of the bound second harmonic, making it possible to identify the range of applicability of the weakly nonlinear approximation. Representative regimes from different modulational instability regions are analyzed to demonstrate the influence of resonance and focusing boundaries on breather characteristics and interfacial wave profiles. The proposed approach provides a direct link between the mathematical description of Akhmediev breathers and their physical interpretation and can be extended to other localized solutions of the nonlinear Schrödinger equation and to a broad class of stratified hydrodynamic systems.
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Instrumentation and Methods for Astrophysics
Asgard/NOTT: Cryogenic characterization of the mid-infrared chip
G. Garreau, D. Defrère, R. Laugier et al. (+25 more)
NOTT is part of the new visitor instrument suite Asgard for the Very Large
Telescope Interferometer (VLTI), and the first long-baseline nulling interferometer that will be operational in the southern hemisphere. It is an L'-band (3.5-4$\,\mu$m) instrument optimized for imaging hot exozodiacal
dust and young
giant planets orbiting around the snowline of nearby main-sequence
stars. For
planet imaging, the L' band has the advantage of relaxing the requirements on the
star-
planet contrast to $\sim 10^{-5}$ while limiting the level of background noise compared with longer wavelengths. Nulling interferometry in the L'-band was made possible by the development of mid-infrared integrated optics with high throughput. NOTT uses a photonic beam combiner made of Gallium Lanthanum Sulfide (GLS), manufactured at Macquarie University and characterized at ambient temperatures at Universität zu Köln. This first characterization showed that the chip could achieve the broadband contrast requirement for
exoplanet imaging. Using the test bench of the NOTT instrument assembled at KU Leuven, and its test cryostat, we successfully cooled the chip down to $\sim 138\,$K and performed its first characterization at cryogenic temperatures. The results show a raw broadband contrast of $\sim1\,\%$, similar to the previous measurements done at ambient temperatures. The splitting ratios of the different couplers are also shown to remain stable at cryogenic temperatures, with less than $\sim 2\,\%$ uncertainty compared to ambient measurements. These results thus show that the beam-combining properties and splitting ratios are behaving as expected at 138$\,$K. The current maximum throughput of the chip is estimated at $\sim37\,\%$. Future work will investigate an anti-reflection coating to reduce its Fresnel losses and increase its throughput to $\sim50\,\%$.
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All authors G. Garreau, D. Defrère, R. Laugier, P. Chingaipe, M-A. Martinod, T. Mattheussen, K. Missiaen, J. Morren, G. Raskin, M. Salman, W. Verstraeten, A. Bigioli, S. Ertel, S. Gross, X. Haubois, M. Ireland, A. P. Joó, S. Kraus, L. Labadie, S. Madden, F. Martinache, A. Mazzoli, G. Medgyesi, A. Sanny, N. Schuhler, J. P. Scott, T. A. Stuber, B. Vandenbussche
Instrumentation and Methods for Astrophysics
ESO-VLT BlueMUSE instrument - Conceptual Design for Phase A
Florence Laurent, Johan Richard, Rémi Giroud et al. (+23 more)
BlueMUSE is a blue-optimised, medium spectral resolution, panoramic integral field spectrograph under development for the ESO's Very Large
Telescope (VLT). The project is now entering preliminary design phase. With an optimised transmission down to 350 nm, spectral resolution of R $\sim$ 3500 on average across the wavelength range, and a large FoV (1 arcmin2), BlueMUSE will open up a new range of
galactic and extragalactic science cases facilitated by its specific capabilities. BlueMUSE consists of several subsystems arranged along the light path. A calibration unit reproduces the VLT's optical conditions, while the fore optics reshape the
telescope's focal image. The splitting and relay optics divide the field of view into 16 channels, each feeding an integral field unit that contains an image slicer, a spectrograph, and a detector vessel. The image slicer converts the 2D sub-field into a 1D pseudo-slit, which the spectrograph disperses into spectra recorded by a 4k x 4k CCD in each detector vessel. A
vacuum and cryogenic system cools the detectors, and the data reduction software processes the raw data into data cubes which are subsequently processed by a data analysis software system. All subsystems are supported by the instrument main structure and enclosed in a thermal housing for stability. The whole instrument is managed by an integrated control system combining electronics and software. This paper summarizes the baseline architecture, interfaces, and functional descriptions of the BlueMUSE instrument at the start of Design Phase. This architecture is derived from the top-level requirements and the experience acquired from MUSE. It presents the global concepts along with their preliminary performance estimates.
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All authors Florence Laurent, Johan Richard, Rémi Giroud, Davor Krajnović, Alexandre Jeanneau, Manuel Abreu, Angela Adamo, Théo Battrel, Didier Boudon, Zhemin Cai, Diane Chapuis-Kerouanton, Christopher Coote, Malak Galal, Joss Guy, Robert J. Harris, Andreas Kelz, Audrey Lanotte, Jon Lawrence, Rémy Le Breton, Helen McGregor, Gloria Mellinand, Jonathan Moller, Manuel Monteiro, Guiliano Parma, Arlette Pécontal, Peter M. Weilbacher
Fluid Dynamics
Information Transport and Observability in Compressible Aerodynamics
Bo Zhang
Pressure measurements provide sparse but direct observations of compressible aerodynamic flows, yet how information about hidden aerodynamic parameters is transported through the flow and encoded in these observations remains poorly understood. Here, we investigate information transport and observability in compressible aerodynamics using a differentiable shock-capturing immersed-boundary solver. By propagating gradients through the full unsteady flow solution, an automatic-differentiation-based observability metric is introduced to quantify the sensitivity of sparse pressure measurements to unknown aerodynamic parameters and identify informative sensing locations for inverse learning. The results reveal that aerodynamic information is transported non-uniformly through the flow field, producing localized regions of high observability. Inverse-learning experiments further demonstrate that observability and learnability are related but distinct concepts: although highly observable probes generally facilitate accurate parameter recovery, the highest-observability probe is not consistently the most effective for parameter inference. Furthermore, both the flow regime and the airfoil geometry substantially influence the distribution of observability and the convergence behavior of inverse learning. These findings establish a quantitative framework for understanding how aerodynamic information is encoded in sparse measurements and demonstrate the potential of automatic differentiation for observability analysis, informative sensor selection, and aerodynamic inverse analysis.
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Fluid Dynamics
Guarantees by Construction for Learned Finite Volume Schemes on Steady Supersonic Flow
Denis Gueyffier
A second order finite volume scheme rests on two local quantities: a gradient reconstructed in each
cell, and a limiter which scales it down where the reconstruction would overshoot. Both are set by fixed formulas, and on coarse unstructured meshes a small network can supply better values. But a network is free to output anything, and the usual safeguard is a penalty in the training loss, which discourages inadmissible states without preventing them. We replace the penalty by a hard constraint. The network still sets both quantities, and every value it can produce lies inside safe bounds: its stencil weights cannot cancel a neighbour, and its limiter is capped by the local flow. The flux, the wall treatment and the time step are not learned and carry their own guarantees. Admissibility therefore holds for every value of the weights rather than as an outcome of training, and no negative density or pressure occurred in any computation reported here. Because the scheme is safe whatever the network does, we could ask what the network contributes. We test it on supersonic channel flow over an obstacle, including the forward facing step of Woodward and Colella. Learning lowers the error by 38% on an unseen geometry and 29% on an unseen obstacle
topology, measured against the same scheme with the network switched off. The method aims at the accuracy of a fine mesh for the cost of a coarse one, and refining once improves the error fourfold while multiplying the run time by eight. Learning secures half of this improvement for a sixth of this time. All of this comes from one of the two quantities the network sets. The gradient reconstruction reproduces the full effect on its own, and the limiter accounts for about a tenth as much. This also explains why the gain fades beyond the Mach numbers the weights were trained on.
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Medical Physics
A simplified reconstruction of Positron Emission Tomography image using Time of Flight simulated data in Gate 10
Marcin Balcerzyk, Santiago Jimenez-Serrano, Óscar Pietrzyk et al. (+2 more)
Background: Ultrafast Time-of-Flight (TOF) information in Gate 10 simulations enables direct 3D PET reconstruction without scanner-specific modeling. Although such picosecond timing is not achievable in current detectors, simulated data allow exploration of idealized TOF regimes and rapid evaluation of prototype PET designs. Methods: The TOF-driven reconstruction assigns each coincidence to its annihilation position using sub-picosecond timestamps, producing voxelized 3D histograms with flexible voxel size and field-of-view selection. The approach operates directly on Gate-sorted coincidences, requires no corrections, and outputs MHD/DICOM images. Timestamp precision (~10^-13 s) enables localization on the millimeter scale. Results: Full 3D images of the simulated INSPIRE PET scanner are generated in under one second. The method resolves 0.25 mm features in point-source studies and 1.2 mm rods in the Derenzo phantom, reproduces ground-truth activity distributions in image-quality tests, and maintains quantitative stability across geometries. Performance reflects the theoretical benefits of ultrafast TOF rather than current detector capabilities. Significance: This fast, geometry-agnostic reconstruction tool supports early-stage PET prototyping, allowing rapid assessment of spatial resolution, sensitivity, and uniformity without implementing complex reconstruction software. It is broadly applicable to any simulated PET system with sorted coincidences and enables systematic exploration of ultrafast TOF performance in a controlled environment.
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All authors Marcin Balcerzyk, Santiago Jimenez-Serrano, Óscar Pietrzyk, Edwing Ulin-Briseño, Marta Freire
Quantum Physics · Cross-listed from q-fin.PR
Quantum Kernels and the Cross-Section of Stock Returns: Anatomy of a Vanishing Advantage
Junchi Shen
Do
quantum kernels improve cross-sectional stock return prediction? We run a controlled horse race on the Chinese A-share
market in which a
quantum fidelity kernel, a projected
quantum kernel, and a classical RBF control share identical training subsamples, solver, and tuning budgets, so that only the kernel is exchanged. On the main evaluation – a point-in-time universe and 170 walk-forward windows (2012-2025) – no
quantum advantage exists: the fidelity kernel is indistinguishable from its RBF control ($\Delta$IC $=+0.005$, $p=0.42$), and a $2\times2$ design crossing kernel type with training budget (a Nystrom extension to the full ~38,000-observation windows) shows
quantum kernels matching, but never beating, equal-budget linear models; after family-wise correction no pairwise difference among eleven models is significant, with point estimates favoring penalized linear regressions throughout. We then document how the opposite conclusion arises: a 60-window evaluation on a universe screened with full-sample information makes the same
quantum kernel appear dominant on stability criteria and significantly better than neural baselines. Interaction characteristics from the anomalies literature help nothing,
quantum or classical; a widened bandwidth grid reveals an interior optimum rather than the near-classical endpoint a coarse grid suggests; and the
geometric difference, while large throughout ($g \gg 1$), does not predict out-of-sample gains ($\rho=-0.20$). We propose protocol standards – kernel-swap controls, budget-equalized comparisons, point-in-time universes, and multiplicity-robust inference – for empirical claims of
quantum advantage in finance.
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Optics
Two Complementary Approaches to Determine the Effective Index of Dielectric Ring Resonators
Ergun Simsek
Open-source finite-element frameworks for modal analysis of dielectric ring resonators are presented based on two complementary approaches. The first computes resonant wavelengths for discrete azimuthal mode numbers and obtains the effective index at a target wavelength by interpolation; the second solves directly for the azimuthal mode number at a prescribed wavelength via a quadratic
eigenvalue formulation. Both approaches are validated against a commercial electromagnetic mode solver and yield nearly identical effective indices and dispersion curves. The fixed-mode-number approach requires slightly longer computation time but uses half as much
memory, making it the preferred choice for
memory-limited computers.
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Solar and Stellar Astrophysics
Relationship of ICME Composition Signatures with Solar Activity during 2009-2025
Diyorbek Pulatov, Zavkiddin Mirtoshev and Mirabbos Mirkamalov
Coronal Mass Ejections (CMEs) are among the most energetic
solar eruptions, expelling magnetized
plasma from the corona into interplanetary space. Their interplanetary counterparts, known as Interplanetary Coronal Mass Ejections (ICMEs), retain distinct compositional signatures that reflect the physical conditions of their
solar source regions. This study presents a statistical analysis of ICME composition dependence on
solar activity during 2009–2025, covering
Solar Cycle (SC) 24 and the ascending phase of SC~25 through its maximum, and compares the results with SC~23 studied by \citet{Song+etal+2021}. Using data from the
Solar Wind Ion Composition Spectrometer (SWICS) aboard the Advanced Composition Explorer (ACE), we examined the average iron charge state ($\langle Q_{\rm Fe}\rangle$), ionic ratios (C$^{6+}$/C$^{5+}$ and O$^{7+}$/O$^{6+}$), and the elemental abundance ratio (Fe/O) for 307 ICMEs listed in the Richardson and Cane ICME catalog. The results show strong positive correlations of $\langle Q_{\rm Fe}\rangle$ ($r$~=~0.86) and O$^{7+}$/O$^{6+}$ ($r$~=~0.85) with the annual sunspot number (SSN), whereas C$^{6+}$/C$^{5+}$ exhibits a weak correlation ($r$~=~0.17) primarily due to SWICS~2.0 upper-end saturation truncation that suppresses the
solar maximum signal, and Fe/O a moderate correlation ($r$~=~0.57). The Fe/O ratio, a proxy for the First Ionization Potential (FIP) effect, displayed elevated values during the maxima of both SC~24 and SC~25, suggesting enhanced elemental fractionation during periods of increased
magnetic activity. Comparing with SC~23, we find that the overall
solar cycle dependence of ICME composition persists across cycles, though with notable quantitative differences attributed to the different
magnetic activity levels between cycles. These findings confirm that ICME compositional signatures are strongly modulated by the
solar cycle.
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Earth and Planetary Astrophysics
Dust and Gas Transport in Substructured Nonideal MHD Wind-Launching Disks with Embedded Planets
Chun-Yen Hsu, Zhi-Yun Li, Xiao Hu et al. (+2 more)
Radial
dust transport in protoplanetary disks is a key process shaping
planet formation and disk chemistry. We investigate how this transport, along with gas transport, is regulated in wind-launching disks with embedded
planets using three-dimensional nonideal MHD simulations. We find that disk substructures do not act as absolute barriers to transport. Low-mass
planets leave the disk structure dominated by the
magnetic wind, while a Jupiter-mass
planet opens a deep gap and drives spiral shocks. However, even in this regime, wind-driven
accretion persists; the
planet reshapes rather than replaces the magnetically driven flow, leaving the gap intrinsically time-dependent and partially permeable. Early-phase suppression of inward transport is followed by the development of localized, azimuthally intermittent inflow channels that enable continued cross-gap transport. This transport is strongly size-dependent: small grains remain coupled to the gas and readily penetrate the gap, whereas larger grains are efficiently trapped outside the
planet. Consequently, a
giant planet acts as an efficient but incomplete filter rather than a perfect barrier. These results support a "leaky gap" scenario, where radial transport is regulated rather than halted by substructures. Volatile-rich material can be delivered to the inner disk both before gap opening and via continued leakage, providing a natural explanation for the diverse inner disk compositions inferred from JWST. Similarly, pebble isolation during core growth should be viewed as a gradual filtering process rather than a binary transition. More generally, disk substructures are dynamically evolving features whose transport efficiency depends on their physical origin (
magnetic versus
planet-driven).
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All authors Chun-Yen Hsu, Zhi-Yun Li, Xiao Hu, Yisheng Tu, Min-Kai Lin
Instrumentation and Methods for Astrophysics
Achieving efficient broadband spatial filtering for LIFE: status and plan
G. Garreau, T. Birbacher, L. Desdoigts et al. (+8 more)
Nulling interferometry is one of the most promising techniques that is envisioned for the imaging and characterization of
exoplanets in the mid-infrared for ground-based and space-based observatories. On the ground, the upcoming Asgard/NOTT visitor instrument for the Very Large
Telescope Interferometer (VLTI) is expected to be the first nuller to observe young
giant exoplanets. The Large Interferometer For
Exoplanets (LIFE) project aims at implementing long-baseline nulling interferometry in space to image and characterize Earth-like
exoplanets. LIFE requires to reach deep ($<10^{-5}$) null depths over a large bandwidth in the mid-infrared (MIR: 4-18.5$\,\mu$m) with a high throughput ($>15\,\%$). These requirements are necessary to detect and characterize the thermal emission of Earth-like
exoplanets. To achieve deep null depths, a spatial filter is necessary to wash away the wavefront aberrations that would otherwise be a limiting factor for the contrast. However, efficient spatial filtering with high throughput ($>95\,\%$) is challenging to achieve over such a large bandwidth. In this study, we explore the possibility of broadband spatial filtering using two step-index fibers previously studied for the Darwin mission proposal: Te-As-Se chalcogenide (TAS) and silver halide (AgBr) fibers. Using $\partial$Lux, we also simulate the performance of phase-induced amplitude apodization (PIAA) with aspherical mirrors to achromatically apodize the pupil plane of a beam and improve its coupling efficiency in both fibers. The results show that a broadband
geometric coupling efficiency of $>95\,\%$ can be achieved, with a manufacturing precision of $<100\,$nm for the PIAA mirrors. An achromatic apodization of the beams for LIFE is therefore compatible with a number of spectral channels of $\geq2$, defined by the number of spatial filters used.
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All authors G. Garreau, T. Birbacher, L. Desdoigts, L. D. Feinberg, A. M. Glauser, J. T. Hansen, M. Ireland, J. Pino, E. Spalding, A. K. Taras, S. P. Quanz
Nuclear Experiment
Measurement of the $\gamma\gamma \to \tau \tau$ cross section and constraints on the anomalous magnetic moment of the $\tau$ lepton in ultraperipheral PbPb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV
CMS Collaboration
The production of $\tau$
lepton pairs via
photon-
photon fusion, $\gamma\gamma \to \tau \tau$, is studied in ultraperipheral lead-lead collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV. The
dataset, collected by the CMS experiment in 2018, corresponds to an integrated luminosity of 1.70 nb$^{-1}$. Four different $\tau^+\tau^-$ decay final states are analyzed. A simultaneous likelihood fit to the measured
lepton transverse momentum ($p_\mathrm{T}$) distributions, which incorporates information from both spectral shape and normalization, is used to constrain the anomalous
magnetic moment of the $\tau$
lepton, $a_\tau$, and to extract the cross section of the process. The measured 95% CL interval for $a_\tau$ is $-$0.039 $\lt$ $a_\tau$ $\lt$ 0.032. The fiducial cross section, $\sigma_{\gamma\gamma \to \tau \tau}^\text{fid}$ = 555$^{+60}_{-14}$ $\mu$b for tau
leptons with $p_\mathrm{T}^\tau$ $\gt$ 1 GeV and pseudorapidity $\lvert\eta^\tau\rvert$ $\lt$ 3, is the most precise measurement for this process at the LHC to date and is in agreement with next-to-leading-order
quantum electrodynamics predictions.
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Quantum Physics
Biased-noise qubits: a guide to efficient fault-tolerance using the hierarchy of errors
Diego Ruiz, Jérémie Guillaud, Christophe Vuillot et al. (+1 more)
Qubits with strongly biased noise, in which phase-flip errors are orders of magnitude more frequent than bit-flips, arise both naturally, as in electron and
nuclear spins, and by engineering, as in stabilized cat
qubits. This noise structure holds the promise of reducing the daunting hardware overhead of fault-tolerant
quantum computing, but exploiting it requires physical operations that do not convert frequent phase-flips into rare bit-flips. In this review, we analyze the most prominent fault-tolerant protocols for biased-noise
qubits, organized according to the available set of such bias-preserving operations. When this set is restricted to the CZ gate together with preparation and measurement in the X basis, we show that the complexity of the required syndrome extraction gadgets essentially cancels the benefit of the noise bias: at experimentally relevant error rates, one may as well ignore the bias and rely on standard error correction designed for depolarizing noise. The situation changes drastically when a bias-preserving CX gate is available: the hierarchy of errors can then be reflected in the structure of the code, with frequent phase-flips corrected by a dedicated high-threshold code and rare bit-flips by concatenation with a high-rate code. The same hierarchy also enables hardware-efficient preparation of magic states. Finally, as a bias-preserving CX is forbidden in naturally biased platforms and challenging in engineered ones, we present a measurement-based architecture in which a high-fidelity
quantum non-demolition readout of multi-
qubit Pauli Z operators takes its place, extending these overhead reductions to a much broader range of physical platforms.
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All authors Diego Ruiz, Jérémie Guillaud, Christophe Vuillot, Mazyar Mirrahimi
Optics
Conjugate Gradient Unrolled Network with PSF Conditioning for Non-Diagonal Data Fidelity in CASSI Reconstruction
Xiang Li, Qiuyu Yue, Yang Zhang et al. (+1 more)
Deep unfolding methods achieve state-of-the-art performance in coded aperture snapshot spectral imaging (CASSI) reconstruction but typically rely on closed-form data-fidelity updates that assume an ideal optical system. In practical CASSI systems, the field-dependent and wavelength-dependent point spread function (PSF) introduces convolutional coupling that breaks the diagonal structure of the normal equation, rendering closed-form updates inapplicable. We propose a deep unfolding framework that addresses this fundamental algorithmic challenge through three contributions: (1)~a $K$-step conjugate gradient (CG) unrolling that explicitly solves the non-diagonal normal equation under PSF-inclusive forward operators; (2)~a learned gradient refinement module with wavelength-adaptive step sizes generated from a per-wavelength PSF
embedding; and (3)~a PSF-conditioned penalty
estimator that adapts the ADMM regularization strength to the optical degradation severity. A Monte Carlo PSF training strategy further improves robustness to manufacturing-induced PSF variations. Our method achieves 30.53~dB on the KAIST
dataset, +2.73~dB over the DPU baseline (1.27M) using a comparable number of parameters (1.42M), and +1.70~dB over a larger baseline (DPU-B+, 2.12M) using 33% fewer parameters.
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All authors Xiang Li, Qiuyu Yue, Yang Zhang, Zhenrong Zheng
Medical Physics
PRIME-SVR: Physics-infoRmed Implicit Multi-Echo Slice-to-Volume Reconstruction for Fetal T2 mapping
Busra Bulut, Maik Dannecker, Thomas Sanchez et al. (+14 more)
Slice-to-volume reconstruction (SVR) is the standard method for obtaining high-resolution (HR) 3D fetal
brain volumes from motion-corrupted 2D MRI slice stacks acquired in multiple orientations. Existing SVR methods are optimized and validated only for clinical-range echo times (TEs), limiting their use at non-clinical TEs and making them incompatible with quantitative T2 mapping, a protocol- and center-independent biomarker of fetal
brain maturation requiring HR reconstructions across multiple TEs. We present
PRIME-SVR, the first implicit neural representation (INR) framework for joint HR reconstruction from multi-echo MRI. A single fully connected network models a continuous function from spatial coordinates to signal intensities across TEs, while a second network estimates slice-specific acquisition degradations. Cross-TE coherence is enforced via a Bloch equation-derived regularization penalizing deviations from expected T2 decay, with adaptive weighting that strengthens coupling for degraded stacks. The method is fully self-supervised. We validate
PRIME-SVR on 39 in vivo fetal acquisitions (13 subjects x 3 TEs) from two centers, two vendors, and two field strengths (1.5 T and 0.55 T). Compared to state-of-the-art SVR,
PRIME-SVR improves reconstruction sharpness by 47%, anatomical accuracy by 30%, and cross-TE structural consistency by 14%. It enables reconstruction at late TEs previously inaccessible to SVR, yielding the first 0.8 mm isotropic T2 maps at 0.55 T and the first T2 maps derived from INR-based SVR.
PRIME-SVR also accelerates quantitative imaging by reducing the data needed for multi-TE reconstruction, cutting acquisition from 15 to 10 minutes while keeping T2 accuracy within 1.7% in white and deep gray matter, or to 5 minutes with a mean T2 error of 2.3% for high-quality acquisitions.
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All authors Busra Bulut, Maik Dannecker, Thomas Sanchez, Sara Neves Silva, Steven Jia, Jean-Baptiste Ledoux, Leo Pomar, Joanna Sichitiu, Yvan Gomez, Meriam Koob, Vincent Dunet, Maria Deprez, Guillaume Auzias, Francois Rousseau, Jana Hutter, Daniel Rueckert, Meritxell Bach Cuadra