Computational Physics
Physics-Transfer Learning: A Physics-Constrained Theory for Zero-Shot Generalization Along the Ladder of Complexity
Yingjie Zhao and Zhiping Xu
Reliable out-of-distribution generalization remains a central challenge in machine learning, particularly when models are deployed in data-scarce high-fidelity domains. Existing approaches often rely on statistical distribution
alignment, or invariance assumptions that can fail when domain shifts reflect changes in underlying mechanisms. Inspired by a longstanding paradigm in physics that understands complex systems by starting from tractable idealizations and progressively incorporating additional mechanisms and levels of fidelity, we propose physics-transfer (PT) learning, a physics-constrained learning theory for zero-shot generalization along a ladder of complexity. PT constructs chains of anchor domains (CADs) that connect low-cost source domains to complex targets and introduces computable feasibility and reliability indicators for assessing transfer before target-domain labels are observed. Under physical-consistency and stable-representation assumptions, we derive an operational upper bound on target risk in terms of source empirical risk, the PT indicators, and finite-sample errors, and establish convergence as adjacent complexity gaps shrink and data coverage improves. We evaluate PT on excited-state energy prediction in
quantum systems and dynamical-transition prediction in classical systems using neural networks trained without target-domain labels. Across substantial distribution shifts, PT yields accurate high-fidelity predictions, while the indicators identify incorrect physical mappings before target-domain prediction fails. These results provide a model-agnostic framework for designing, diagnosing, and controlling generalization in data-scarce learning problems.
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Atmospheric and Oceanic Physics
MLS and CALIPSO Evidence for a Warm-Pool Transition in Tropical Convective Moistening and Cloud Ice
Isabel Nucera, Jonathan H. Jiang, Yiyang Zhang et al. (+4 more)
Upper-tropospheric water vapor and cloud ice associated with tropical deep convection are central to water-vapor and high-cloud feedbacks. We investigate a warm-pool transition in tropical convective moistening using 20 years of Aura Microwave Limb Sounder (MLS) Version 5 H2O and cloud-ice observations (August 2004-December 2024), together with Cloud-Aerosol
Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol
Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission (June 2006-June 2023). The combined day-plus-night CALIPSO product (CALIPSO-A) provides an independent ice-cloud constraint; the H2O column shown on the CALIPSO grid is derived from Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), not from CALIOP. We combine objective sea surface temperature (SST) breakpoint fitting, cross-sensor ice water path (IWP) comparisons, Clouds and the Earth's Radiant Energy System (CERES) longwave, shortwave, and net cloud radiative effect (CRE), and Integrated Multi-satellitE
Retrievals for GPM (IMERG) precipitation diagnostics from the Global Precipitation Measurement (GPM) mission. MLS and CALIPSO-A show cloud-ice maxima over deep-convective warm-pool regions and identify warm-regime SST breakpoints near 299-300 K. Normalized MLS and CALIPSO-A IWP vary coherently in the western Pacific and tropical mean. CERES indicates that stronger longwave CRE in the warm regime is partly offset by stronger shortwave cooling, while GPM IMERG confirms that MLS IWP increases with convective rain rate. These results show that convective moistening and cloud-ice production across the tropical warm-pool transition are persistent cross-sensor features of the tropical atmosphere.
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All authors Isabel Nucera, Jonathan H. Jiang, Yiyang Zhang, King-Fai Li, Bin Zhao, Hwayon Choi, Yong-Sang Choi
Atmospheric and Oceanic Physics
Deep Learning Denoising of Real SWOT Sea Surface Height Observations
Gaétan Meis, Anaëlle Tréboutte, Maxime Ballarotta et al. (+2 more)
The SWOT (Surface Water Ocean Topography) mission is currently providing unpreceded high-resolution measurements of Sea Surface Height (SSH), revealing ocean features at finer scales. Nevertheless, the two-dimensional observations of KaRIn altimeter of SWOT suffer from instrumental errors. This noise degradation is altering the high frequencies of SWOT signal, and the small to sub-mesoscale dynamics of interest for some oceanographers. For this reason, Tréboutte et al. (2023) have developed a convolutional neural network (CNN) based on U-Net architecture to separate the noise from the physical signals contained in the SSH. Their approach has demonstrated great potential on simulated SWOT measurements, and Dibarboure et al. (2024) report a positive influence on actual flight data from SWOT. However, degraded denoising performance, and occasional negative side-effects have been observed in atypical conditions (e.g. very high surface waves, internal tides
solitons). In this study, we illustrate some of these limitations and we present an improved approach of the CNN-based denoising: we modified the training procedure to obtain a more robust version of the
algorithm, to avoid biases and artifacts in the denoised SSH. This paper also presents a more complete validation process with a robust and standardized evaluation
benchmark: these metrics could be of interest to assess other SWOT filtering and denoising
algorithms.
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All authors Gaétan Meis, Anaëlle Tréboutte, Maxime Ballarotta, Marie-Isabelle Pujol, Gérald Dibarboure
High Energy Physics (Phenomenology)
Thermal Higgsino Dark Matter in GmSUGRA for the LZ Event and Solar-Neutrino Constraint
Imtiaz Khan, Waqas Ahmed, Tianjun Li et al. (+2 more)
We study the thermal Higgsino dark matter in the Minimal Supersymmetric Standard Model (MSSM) with Generalized Minimal Supergravity (GmSUGRA) boundary conditions after the high-
recoil event reported by the LUX–ZEPLIN experiment and the subsequent
solar-
neutrino limits inferred from IceCube data. The
Higgs sector is implemented in a NUHM2-type parametrization with $\mu$ and $m_A$ as inputs, while the supersymmetry breaking soft terms obey the non-universal GmSUGRA relations. The numerical scan contains a Planck-compatible Higgsino branch near the thermal mass, with the neutral-state splitting extending continuously from the few-hundred-keV region to the MeV scale. The part of this branch with $\dmchi\simeq0.3$–$0.4$ MeV overlaps the kinematic interval relevant to the LZ event, but is disfavored by the current
solar-capture reinterpretations for a full-density thermal Higgsino. The same high-scale branch persists at larger splittings, including representative spectra with $\dmchi\simeq0.85$, $1.10$, and $1.34$ MeV, beyond the quoted
solar-capture limits. Our results demonstrate that the mass and sub-MeV splitting favored by the LZ high-
recoil interpretation can be realized dynamically within a GUT-motivated supersymmetric construction, without imposing the neutralino compression as a weak-scale input. The combined data therefore select different parts of a common GmSUGRA Higgsino branch rather than excluding the thermal Higgsino construction itself.
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All authors Imtiaz Khan, Waqas Ahmed, Tianjun Li, Shabbar Raza, Ali Muhammad
General Physics
Bloch's theorem: An operator-based derivation
Celal Sirin
We present an operator based derivation of Bloch's
theorem. In this approach, we first construct an explicit operator form of the
Hamiltonian by writing the potential part in terms of an infinite sum of the momentum translation operators. Next, we prove that it commutes with the position translation operator corresponding to a
lattice translation, using the exponential reordering identity. We then build on Merzbacher's treatment of simultaneous diagonalization of commuting operators to reproduce Kittel's central equation and also to derive a new formula for the simultaneous eigenket corresponding to a specific energy
eigenvalue. Moreover, through the Born rule, we provide a precise account of the position and momentum probability distributions for Bloch states, and we examine the concept of
crystal momentum. Finally, we apply our findings to the Kronig Penney model, where we numerically depict the band structure and illustrate the delocalized nature of the single electron.
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Instrumentation and Detectors
Meta-learning accelerates detector design optimization
Maxim Borisyak, Nikita Gladin and Andrey Ustyuzhanin
The quality of a detector design is ultimately determined by the quality of the inference it enables, that is, by the accuracy with which the quantities of interest are reconstructed from the raw detector response. For complex detectors, the inference is performed by machine learning models, and the relation between the design and the attainable inference performance is, in general, non-trivial. In this work, we consider the optimization of the inference performance with respect to the detector design. The conventional approach prescribes retraining the inference model at every candidate design, thus, treating the evaluations as independent tasks and discarding the shared structure of the optimal inference
algorithms at different designs. We propose the meta-learned objective estimate (MLOE): instead of solving the inference problem anew at every candidate design, a single meta-inference model, conditioned on the design and trained continually along the optimization path, is shared across all of them. We test MLOE on three families of optimization problems, the last of which comprises two design spaces of the Spectrometer Straw Tracker of the Search for Hidden Particles (SHiP) experiment; under matched budgets of simulation calls, the meta-inference model evaluates a candidate design using fewer simulation calls than the baseline strategies and holds the better rank over the convergence curve in all examined cases.
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Instrumentation and Detectors
A Scalable Stacked-Electrode Printed Circuit Board Radio-Frequency Quadrupole (PCB-RFQ) for Precision Experiments
Tayemar K. Fowler-Davis, Moritz Pascal Reiter, Nawaf Altasan et al. (+21 more)
Linear
radio-frequency quadrupole (RFQ) traps are crucial for ion and phase-space manipulation across diverse physics platforms, including
quantum information processing, precision atomic spectroscopy, and high-resolution mass or
laser spectrometry. We present the design, electrostatic field optimization, and performance characterization of a scalable, multi-layer printed
circuit board (PCB) linear RFQ trap. By utilizing a PCB-based "stacked-electrode" geometry to generate high-quality quadrupolar fields, this architecture suppresses higher-order multipole field components by up to an order of magnitude compared to planar "flat surface-electrode" designs and allows for reclaiming up to 60% of the radial pseudopotential-well depth of an ideal
hyperbolic quadrupole. Following a thorough optimisation and characterization using both simulations and experiments, we demonstrate its suitability as a cooler buncher, showing rapid helium buffer-gas cooling with time constants between 34 +/- 3 us and 412 +/- 23 us, and achieving a highly compressed longitudinal phase-space emittance of only 58 +/- 4 eV*ns. The low beam emittance provides flexible control of the extracted bunch properties: weak extraction fields yield energy spreads down to 2.5 +/- 0.4 eV, whereas strong fields produce ultra-narrow temporal widths down to 2.6 +/- 0.3 ns. The results establish our PCB-RFQ platform as a versatile, scalable, and cost-effective alternative to traditionally machined rod-based RFQ assemblies for advanced ion-trapping, beam-preparation, or
quantum applications.
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All authors Tayemar K. Fowler-Davis, Moritz Pascal Reiter, Nawaf Altasan, Samuel Ayet San Andrés, Peter Black, Jason Breyiannis, Callum L. Brown, Peter Dasiukevich, Adam Zaki Davies, Timo Dickel, Oscar Hall, Alexandru Hau, Jamie C. Jones, Jan Kocka, Gabriella Kripkó-Koncz, Konrad Linkowski, Adam J. McCarter, Sophia Scrimshaw, Joe Simon, Jack Lee Smith, Wolfgang R. Plaß, Gemma Robertson, Jiajun Yu, Alexandra Zadvornaya
High Energy Physics (Experiment)
Model-independent searches and anomaly detection at the CMS experiment
Tamas Almos Vami and for the CMS Collaboration
The absence of a clear signal of physics beyond the standard model at the CERN LHC motivates search strategies that do not presuppose a specific signal hypothesis. This proceedings present machine-learning-based anomaly detection to search for new physics in a model-agnostic way. The first such search by CMS looks for dijet resonances whose jets have substructure atypical of jets initiated by light
quarks or
gluons, using five complementary anomaly detection methods applied to 138 fb$^{-1}$ of
proton-
proton collision data at $\sqrt{s} = 13$ TeV. The technique has been validated directly on data by recovering the top
quark without the use of labels. The program has also moved into real time: two unsupervised
algorithms, AXOL1TL and CICADA, now run on field-programmable gate arrays inside the CMS level-1 trigger and selected more than four billion collision events during 2024 data taking. Finally, the extension of resonant anomaly detection to event-level observables is outlined.
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Chemical Physics
Correlation-Driven Singlet–Triplet Inversion and Optical Spectra of N-Substituted Phenalenyls: Insights from PPP-FCI and TDDFT
Medha Rakshit and Alok Shukla
Several researchers have reported an atypical inversion of the lowest singlet ($S_{1}$) and triplet ($T_{1}$) excited states in nitrogen-substituted planar hydrocarbons. Contrary to Hund's rule of maximum multiplicity, poly-aza derivatives of phenalenyl, such as cyclazine and heptazine, have long been known to possess a negative singlet-triplet gap, $\Delta E_{ST}=E(S_{1})-E(T_{1})$. Using the well-known Pariser-Parr-Pople (PPP) model, a semi-empirical, wave-function-based
Hamiltonian for correlated $\pi$-electrons, we investigate the singlet-triplet gap in ten N-substituted phenalenyl motifs. Two schemes of long-range Coulomb interactions are considered, and key parameters, including the on-site orbital energy, Hubbard U, and hopping integrals, are systematically tuned to
benchmark the model for reliably estimating negative singlet-triplet gaps. Full configuration-interaction (FCI) method is employed to incorporate electron-correlation effects. Ground-state and $T_{1}$ absorption spectra are subsequently calculated using the optimized PPP parameters that best reproduce the available experimental data. For validation, first-principles TDDFT calculations using various exchange–correlation functionals are also performed. Conventional adiabatic TDDFT fails to reproduce the inverted ($S_{1}-T_{1}$) ordering, indicating that the inclusion of the correlation driven multiconfigurational effects are essential for describing it. We find that the singlet TDDFT ground-state absorption spectra reproduce several qualitative features of the PPP-FCI spectra, although the TDDFT excitation energies are systematically higher. Detailed analysis of the ground-state and $T_{1}$ absorption spectra reveals significant configuration mixing, providing a comprehensive characterization of the optical response of the N-substituted phenalenyl derivatives studied.
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Disordered Systems and Neural Networks
R-transforms for non-Hermitian block random matrices: a spherical integral approach
Pierre Bousseyroux
We extend the spherical-integral approach to $\mathcal{R}$-transforms of non-Hermitian random
matrices to random
matrices with a fixed $K \times K$ block structure. We introduce a rank-$K$ spherical integral defining a scalar $H$-transform on $2K \times 2K$ overlap
matrices and an associated
matrix-valued $\mathcal{R}$-transform encoding the joint block structure. Using the replica method, we derive a conjectural subordination relation for sums of independent block
matrices. This framework provides a method for determining the spectral boundaries of large non-Hermitian random
matrices with a fixed block structure.
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Chemical Physics
A Green-function unification of weak interactions with environmental dressing
Johannes Fiedler
Weak, non-covalent interactions such as electrostatics, induction, and dispersion are commonly treated as distinct physical mechanisms, often using separate models and approximations. Here, we present a unified
quantum-electrodynamical framework in which all weak interactions between neutral or charged subsystems emerge from a single interaction
Hamiltonian and are expressed entirely in terms of electromagnetic Green functions. Starting from macroscopic QED in arbitrary linear environments, we derive compact master formulas that generate permanent electrostatic, mixed induction, and fully induced (dispersion) interactions on equal footing. Monopoles, dipoles, and quadrupoles are treated consistently within the same multipole expansion, leading to a common structural form in which all interaction channels are obtained from contractions of multipole moments and response functions with Green tensors. Environmental effects enter universally through dressed Green functions. The standard non-retarded free-space limits, including Keesom, Debye, and London/van der Waals interactions, are recovered as a consistency check of the formalism. Beyond this validation, the formulation shows that once the general expressions are established, different physical scenarios, such as interfaces, confinement, or polarisable continua, can be treated by direct substitution of the corresponding Green function, without reformulating the interaction for each case. This elevates Green functions to a universal organising principle for weak interactions in complex environments.
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Classical Physics
Exact turning invariants for projectile motion under quadratic drag and a vertical-axis Magnus force
Pragyaan Gaur
A ball spinning about a vertical axis is pushed sideways by the Magnus force, so its ground track curves. We show that when the lift and drag coefficients are constant, the horizontal part of this problem is exactly solvable in elementary functions. The step that makes this work is to write the horizontal velocity as a complex number and to use path length rather than time as the independent variable. Both aerodynamic forces are quadratic in speed, so the speed cancels and what remains is a linear equation with constant coefficients in which
gravity does not appear. Three exact results follow from it. The heading turns at a fixed rate per unit path length, so a half turn always costs the same distance whatever the launch conditions and whatever the drag. The horizontal speed decays exponentially in the turn angle at a rate fixed by the drag-to-lift ratio, which makes the horizontal hodograph a logarithmic spiral. The radius of
curvature of the ground track equals the lift length times the cosine of the flight-path angle. The whole flight problem also collapses to one scalar differential equation controlled by two dimensionless numbers. We use this to settle a concrete question. Two identical balls thrown in opposite horizontal directions with opposite
spin can meet head-on when drag is absent, on a one-parameter family we give in closed form, and they fail to meet once drag acts. Every analytic claim is checked against machine-precision numerics, and the code and data are openly available.
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General Relativity and Quantum Cosmology
Canonical Quantization and Constraint Algebra of Weyl-Invariant Gravity in a Conformal Gauge: Emergence of a Geometric Cosmological Term
Jorge Meza-Domínguez and Tonatiuh Matos
We present the canonical quantization of Weyl-invariant
gravity in a specific conformal gauge. Fixing the scale factor as $a(\eta) = 1/(H_0\eta)$ yields an effective
geometric cosmological term $\mathcal{M}(\eta) = \alpha/\eta^2$ on the left-hand side of the Einstein equations, guaranteeing an equation of state $w = -1$ by construction. The Bianchi identity requires a compensator scalar field; we show that this compensator is the conformal mode of the metric, a gauge artifact that does not propagate ghost instabilities in the full
quantum theory. We develop the complete ADM
Hamiltonian formulation and prove that the constraint
algebra closes in standard first-class form. Canonical quantization yields a well-defined Wheeler-DeWitt equation where the $\mathcal{M}(\eta)$ term acts as a potential barrier dynamically suppressing the
quantum creation of small-scale universes. The physical reduced
Hamiltonian is demonstrated to be bounded from below, time
evolution is strictly
unitary in the physical
Hilbert space, and microcausality is preserved. In the pure
vacuum regime, the model admits an exact analytical solution with $\Omega_{\text{DE}} = 1$, resolving the
cosmic coincidence problem without fine-tuned parameters. In the matter-dominated era, the comoving horizon scales as $R_H \propto \eta$, so our result $\mathcal{M} \propto \eta^{-2} \propto R_H^{-2}$ reproduces the central Compton Mass Dark Energy (CMaDE) hypothesis from first principles and establishes $n = -2$ as the theoretical
benchmark for the Conformal
Holographic Dark Energy (CHDE) parametrization $\mathcal{M} \propto \eta^n$. From a pure conformal
symmetry principle, the model delivers an effective
geometric cosmological term that drives the accelerated expansion with $w = -1$, providing the missing action principle for CMaDE.
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High Energy Physics (Theory)
Static Solitons in an Expanding Universe
Nagabhushana Prabhu
We show, analytically, that a static sine-Gordon
soliton cannot exist in 1 + 1 non-dynamical de Sitter spacetime if $\alpha := (m/H)^2 < 2$, where $m$ is the mass parameter of the sine-Gordon theory and $H$ is the Hubble constant. Conversely, we also show that static sine-Gordon
solitons exist in 1 + 1 non-dynamical de Sitter spacetime if $\alpha > 2$. The above threshold is explained—qualitatively and to within an O(1) factor—using a heuristic argument involving the interplay of tensile force in the Lorentzian sine-Gordon
soliton and the
tidal force in de Sitter spacetime. A similar heuristic argument, which remains to be confirmed analytically, also suggests the existence of a threshold, $ (m_V/H)^2 \sim O(1)$, below which the
tidal forces are too strong to permit the existence of a static `t Hooft–Polyakov monopole in non-dynamical 3 + 1 de Sitter spacetime; $m_V$ is the mass of the vector
boson. Linde has suggested that new inflation could have triggered secondary inflation at the core of a GUT (Grand Unified Theory) monopole even if the Hubble constant at or after the GUT phase transition was significantly smaller than the mass of the $X$
boson. We present a heuristic argument, which suggests that the $SO(3)$ `t Hooft–Polyakov monopole does not allow secondary inflation at its core when the inflationary background is weak. Based on the above, as yet analytically unconfirmed, heuristic argument for the $SO(3)$ `t Hooft–Polyakov monopole, we
conjecture that secondary inflation at the core of a GUT monopole is infeasible.
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High Energy Physics (Phenomenology)
Spectral shaping of Gaussian white noise for synthetic axion signal generation in microwave cavity haloscopes
D. Vattolo, D. Ahn, G. Carugno et al. (+6 more)
Microwave cavity haloscopes search for dark-matter
axions through the weak electromagnetic field generated by
axion-
photon conversion in a static
magnetic field. Realistic synthetic signals are essential for end-to-end calibration of the receiver, validation of the analysis pipeline, measurement of signal recovery efficiency, and blind-injection studies. Here, we present a general method for producing
stochastic synthetic
axion waveforms by shaping Gaussian white noise in the frequency domain. The target
axion power spectral density is imposed directly on the
Fourier coefficients, and arbitrarily long continuous time streams are generated efficiently using an overlap-save implementation. The method reproduces both the ensemble-averaged spectral line shape and the time-domain fluctuations expected for a classical
axion field, while providing direct control of the total injected power. Because the spectral model enters only through a replaceable transfer function, the routine can accommodate the Standard
Halo Model as well as nonstandard velocity distributions and narrow substructure.
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All authors D. Vattolo, D. Ahn, G. Carugno, R. Di Vora, D. Maiello, A. Ortolan, G. Ruoso, G. Sardo Infirri, C. Braggio
Instrumentation and Methods for Astrophysics
South Pole-Aitken basin sample Return and eXploration (SPARX) Science Definition Team Report
Lauren M. Jozwiak, James T. Keane, Robert Citron et al. (+18 more)
Sample return from South Pole-Aitken Basin (SPA) on the Moon has been recognized as the highest priority lunar science mission for well over two decades, appearing as a recommended New Frontiers class mission in the two previous Planetary Science Decadal Survey documents (2003-2012 New Frontiers, 2013-2022
Visions and Voyages), and as a prioritized mission for the Lunar Discovery and Exploration Program (LDEP) in the 2023-2032 Origins, Worlds, and Life Decadal Survey. The South Pole-Aitken basin presents the ideal target destination to test nearly 60 years of lunar science hypotheses owing to a unique combination of its size, antiquity, and location on the lunar farside. Convened by NASA in response to OWL Decadal Survey recommendations, the SPARX report provides analysis on prioritized science objectives, measurement requirements, implementation architectures, and a design reference mission for a South Pole-Aitken basin sample return mission. The mission profiles presented in this report leverage key advancements in remote surface exploration technology, the U.S. commercial space industry, and the programmatic focus on sustained human presence and exploration at the lunar south polar region. The science objectives and measurements presented in this report outline a mission that would transform lunar science, would address multiple high-level Decadal science questions at the only place in the
Solar System where they can be credibly addressed, would pioneer a new paradigm for planetary surface exploration in the 21st century, would leverage the burgeoning space economy to pursue ground-breaking science on a more cost-efficient basis, and would unite robotic exploration with human exploration in a model for a future sustained lunar enterprise.
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All authors Lauren M. Jozwiak, James T. Keane, Robert Citron, Natalie Curran, Steve Elardo, Caleb Fassett, Abigail Fraeman, Saira Hamid, Lena Heffern, Peter James, Daniel Moriarty, Kevin Righter, Jennifer Whitten, Hunter Vannier, Zoe Wilbur, Tomokatsu Morota, Hiroshi Nagaoka, Caroline-Emmanuelle Morisset, Patrick Hill, James Carpenter, Francesca MacDonald
History and Philosophy of Physics
The Price of Removing the Scaffolding: Maxwell wrote something about Ampère that years later would be done to him
María Florentina Mendoza Urán
In the history of physics, the name scaffolding has been given to whatever served to raise a theory and is afterwards removed because, it is said, it is no longer needed. This article documents, from the originals, what it cost Maxwell's theory when that method was applied to it: what was removed from it, who did it, with what argument, and how over the years it had to be recovered because it was understood that it was needed after all. It also records what Maxwell himself missed in Ampère, what he calls the traces of the scaffolding: the template with which Ampère himself had given shape to his work.
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Physics and Society · Cross-listed from cs.LG
Scaling of Capability and Efficiency at Inference Time in Large Reasoning Models
Moritz Laber, Zohair Shafi, Germans Savcisens et al. (+6 more)
Capability and efficiency are two key dimensions of
reasoning in large
language models (LLMs). Capability refers to the ability to solve a given problem correctly, whereas efficiency refers to the ability to do so with limited resources. When LLMs use Chain-of-Thought (CoT)
reasoning to solve problems of controlled hardness, both the number of problems solved correctly and the number of
tokens required to reach a correct answer depend on problem hardness and model size. However, how these factors jointly shape capability and efficiency remains poorly understood. Here, we use hierarchical
Bayesian models to evaluate the capability and efficiency of LLMs from the DeepSeek-R1-Distill model family across four classes of arithmetic and algorithmic
reasoning problems. At a fixed model size, the probability of correctly solving an instance decays approximately exponentially with instance size, our proxy for problem hardness. The decay scale grows sublinearly with model size, indicating that larger models are more capable, but that capability gains diminish with scale. Output length grows as a power law with instance size, which serves as a proxy for difficulty. However, the parameters of this power law do not vary systematically with model size, suggesting that larger models do not become more efficient. Together, these findings reveal potential limitations of naive scaling as a strategy for developing more capable AI systems: capability improves with diminishing returns, while efficiency shows little to no improvement.
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All authors Moritz Laber, Zohair Shafi, Germans Savcisens, Brennan Klein, Matteo Chinazzi, Samuel V. Scarpino, Albert-László Barabási, Alessandro Vespignani, Tina Eliassi-Rad
Plasma Physics
Effects of the Internal Transport Barrier in the plasma confinement with Resonant Magnetic Perturbations
P. Haerter, L. C. Souza, R. L. Viana et al. (+1 more)
In the pursuit of steady-state fusion energy, Advanced Tokamak regimes rely on Internal Transport Barriers (ITBs) with reversed
magnetic shear. While Resonant
Magnetic Perturbations (RMPs) are commonly applied to control Edge Localized Modes (ELMs) by intentionally making the
plasma edge chaotic, the RMPs can also affect the reversed-shear cores. To address this compatibility, we propose a new, adjustable analytical model for
plasma current that explicitly incorporates the core, ITB, and edge pedestal components. By applying this current formulation to a
Hamiltonian map, we compare how easily
magnetic chaos reaches the core in ITB-driven reversed-shear (Non-Twist)
plasmas. We find that the localized ITB current creates "twin" inner resonances and pushes outer
magnetic island chains closer to the edge. These results highlight a critical operational trade-off: while the Non-Twist
topology makes ELM control easier at lower coil currents, it severely shrinks the safety margin against a complete, RMP-induced loss of global confinement.
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All authors P. Haerter, L. C. Souza, R. L. Viana, I. L. Caldas
High Energy Physics (Phenomenology)
Axions and the RR Lyrae Period-Luminosity Relation
Jeremy Sakstein and Djuna Croon
We investigate the impact of
axions on the period-luminosity relation (PLR) of RR Lyrae
stars. During the red
giant branch phase, emission through the electron coupling cools the core, increasing its mass at ignition. The larger core produces more luminous horizontal-branch
stars, systematically shifting the zero point of the RR Lyrae PLR toward brighter magnitudes. We model the RR Lyrae population of the globular cluster M3 using
stellar evolution and pulsation calculations tailored to its age and composition, and compare the resulting synthetic $K_s$-band PLR with observations. For $\alpha_{26}\equiv 10^{26}g_{ae}^2/4\pi=0.5$, the
axion-induced shift in the predicted PLR is comparable to the current uncertainty in the absolute M3 zero-point calibration.
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Cosmology and Nongalactic Astrophysics
Shape Degeneracies: the likely culprit for the differences between lens mass models of galaxy clusters
Liliya L.R. Williams, Derek C. Perera, Jori Liesenborgs et al. (+3 more)
Sky-projected mass distributions of
galaxy clusters are widely used to constrain particle properties of dark matter, to magnify in flux and angular extent high
redshift background
galaxies, and to construct their luminosity function down to faint absolute magnitudes that are otherwise hard or impossible to reach. Obtaining accurate and precise mass maps of clusters is therefore of central importance for these studies. Yet, a visual inspection of any two mass maps of the same cluster shows that the shapes of their isodensity contours are often dissimilar in detail on <30kpc scales, and there is no simple relation connecting the two. These differences are due to systematic uncertainties in reconstructions, which are in turn due to
lensing degeneracies. However, commonly known degeneracies, like the mass sheet degeneracy or the source position transformation cannot account for most of these differences, implying that more generalized shape degeneracies are responsible. In this paper we study shape degeneracies using an analytical approach. We conclude with three main takeaways: (i) Shape degeneracies are the likely cause of differences in the mass maps of cluster lenses recovered by different techniques. (ii) Shape degeneracies are significantly suppressed in regions of the lens plane that have tight groupings of lensed images. (iii) In clusters where image numbers are high, such as MACS J0416, their effect on time delays between images from the same source are generally small, of order 1%, but can reach ~10% for some multiply imaged background sources, affecting the determination of H_0.
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All authors Liliya L.R. Williams, Derek C. Perera, Jori Liesenborgs, Ashish K. Meena, Marceau Limousin, Leon R. Ecker
Physics and Society
Percolation in the Stochastic Block Model
Luca Pieleanu, Moritz Laber, Narayan G. Sabhahit et al. (+1 more)
The
stochastic block model is a paradigmatic model of networks with community structure. Yet percolation in the model has been studied primarily in cases with a fixed block structure, even though in real networks, the community structure may evolve as the network grows. Here we study percolation in sequences of
stochastic block models in which the numbers and sizes of communities, as well as the intra- and intercommunity connection probabilities may all change with the network size. We analyze five such sequences using two methods: linearized self-consistent equations for the locally tree-like models and a branching process at the community scale for the models with nonvanishing clustering. We find that the critical average degree is not generally equal to $1$, even in locally tree-like sequences, because the transition depends on how connections are distributed across the evolving community structure. We also show that the community-scale branching process accurately predicts the transition when intercommunity connections are sufficiently sparse, even in the presence of nonvanishing clustering, while a
geometric stochastic block model sequence demonstrates the limitations of this method when correlations between intercommunity connections cannot be neglected. These results extend percolation studies in the
stochastic block model to more realistic scenarios with evolving community structure, and may provide new methods to derive the upper and lower bounds for the percolation threshold in
geometric long-range percolation.
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All authors Luca Pieleanu, Moritz Laber, Narayan G. Sabhahit, Dmitri Krioukov
Instrumentation and Methods for Astrophysics
Increasing Sensitivity to Trailed Solar System Objects in Archival JWST NIRCam Imaging with Group Differencing
Anthony Girmenia and Stanimir Metchev
The JWST archive contains thousands of NIRCam exposures distributed across the sky. Small
solar system bodies (SSSBs) are present in many of these fields, but are often trailed and more difficult to detect. The standard pipeline produces a single image by fitting a slope to a sequence of $N$ cumulative “up-the-ramp" groups of the detector. Thus, each JWST image comprises a time series of cumulative reads. We demonstrate that transforming the ramp into a series of group difference images reduces the per-image trail length of moving sources, producing an $(N-1)$-group photometrically calibrated time series from an $N$-group integration. This enables higher-cadence trajectory-based searches using as few as a single JWST exposure. A generalized least-squares fit of the group difference images along the trajectory of a moving source recovers the source flux at higher SNR when compared to the ramp fit, with the improvement scaling with the reduction in trailing. We validate our procedure on 13 moving objects detected in archival JWST NIRCam images. To estimate our sensitivity increase, we perform an injection/recovery simulation on the JWST imagery. Trailed moving objects recovered via group differencing show higher SNRs, improving completeness to moving sources compared to standard calibrations. For typical integration lengths of $N=4$ or $6$ for archival JWST/NIRCam exposures in the ecliptic, group differencing yields sensitivity gains between $\sim 1.1$–$1.4$ mag, based on simulation results. This method significantly increases the sensitivity of archival JWST surveys to trailed SSSBs.
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Fluid Dynamics
Blade secondary vortex interaction noise in hovering rotors
Jordon Won and Seongkyu Lee
Recent indoor experiments on small-scale hovering rotors have reported mid-frequency quasi-tonal peaks of uncertain origin in the residual (aperiodic) far-field sound spectrum, even without wake recirculation. This study investigates their physical origin using hybrid Reynolds-averaged Navier-Stokes/large-eddy simulations coupled with a Ffowcs Williams-Hawkings acoustic analogy, applied to a four-bladed ideally twisted rotor in hover. The high-resolution simulation reproduces the measured higher-harmonic blade-passage-frequency tones, confirming that they arise from the rotor flow itself and not from the enclosed-chamber test environment. Flow-field analysis attributes the tones to blade secondary
vortex interaction (BSVI): the outboard blade sections, between approximately r/R = 0.88 and 0.96, are repeatedly impinged upon by coherent, S-shaped secondary
vortex worms formed by entrainment of the wake shear layer into the primary tip
vortices of preceding blades. These aperiodic secondary
vortices produce blade-to-blade correlated loading, yielding a quasi-tonal signature distinct from both purely periodic blade-
vortex interaction and mostly
stochastic blade-wake interaction noise. Spectral proper orthogonal decomposition of the zero-mean upwash confirms that the mid-frequency (3-10 kHz) content is dominated by a single, low-rank, spatially coherent mode associated with the braids, whereas a lower-frequency mode near 1 kHz is linked to the primary tip
vortex core. BSVI is thus identified as a distinct and previously uncharacterized source of aperiodic tonal noise in hovering rotors, with direct implications for the acoustic design of small- to medium-scale rotorcraft and electric vertical take-off and landing propulsors.
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General Relativity and Quantum Cosmology · Cross-listed from math.DG
Topological Obstructions to Riemannian-Lorentzian Continuation
Nathalie E. Rieger and Ödül Tetik
Motivated by problems in instanton continuation, we establish geometro-topological selection rules for continuing a Riemannian region into a Lorentzian region through a smooth transverse change of signature. Given a collar-gluing $M=\overline{M_R} \cup_{\mathcal{H}}\overline{M_L}$ of a smooth
manifold $M$ along a hypersurface $\mathcal{H}$, we show that an admissible signature-changing metric of the form $\widetilde g=g-fV^\flat\otimes V^\flat$ with $g$ a Riemannian metric, having Riemannian signature on $M_R$ and Lorentzian signature on $M_L$, exists if and only if a relative Euler class obstruction on $\overline{M_L}$ vanishes. This obstruction combines ordinary Euler characteristics $\chi$ in a manner that depends on which components of $\mathcal{H}$ represent big bangs and which represent big crunches. It also restricts the choice of $M_R$; for example, if $M$ is closed and $\dim M$ is even, then it requires$\chi(\overline{M_R})=\chi(M)$. We also determine and classify the possible compactness types of $\overline{M_R}$, $\mathcal{H}$, and $\overline{M_L}$ occurring in such a collar-gluing construction, and construct explicit signature-changing metrics in each case.
Topology change can be entirely contained within the Riemannian region when $M$ is the interior of a compact
manifold with boundary.
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Strongly Correlated Electrons
Exact Equivariance from Ordinary Neural Networks for Lattice Many-Body Dynamics
Ho Jang, Sankha Subhra Bakshi and Gia-Wei Chern
Large-scale simulations of correlated electron systems require repeated evaluations of the electronic forces and transition energies driving collective dynamics. Machine-learning surrogates alleviate this bottleneck, but incorporating
symmetry often involves carefully designed descriptors or specialized network architectures. We show that ordinary multilayer perceptrons equipped with finite-group averaging provide exactly equivariant surrogates directly from microscopic configurations. The construction separates
symmetry enforcement from the internal network architecture and applies to both discrete and continuous
lattice degrees of freedom. In the Falicov–Kimball model, it predicts directional hopping free-energy differences; in the Holstein model, its invariant limit generates conservative
lattice forces.
Benchmarks against exact diagonalization establish microscopic accuracy and agreement of dynamical correlations, while large-scale simulations recover multiscale charge ordering and charge-density-wave coarsening. These results demonstrate an accessible, reusable route to
symmetry-preserving many-body dynamics for systems with finite
lattice point groups.
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Solar and Stellar Astrophysics · Cross-listed from cs.CV
Super-Resolution of Solar Magnetograms via Adaptive Stratified Ensemble Learning with Uncertainty Estimation
Sina Norouzi Kandalan, Haodi Jiang, Jason T. L. Wang et al. (+1 more)
Single-image super-resolution of Sun's photospheric magnetograms enables consistent analysis across heterogeneous space-based instruments and supports long-term studies of
solar magnetic field
evolution. We address the super-resolution task from SOHO/MDI (low-resolution) to SDO/HMI (high-resolution) line-of-sight (LOS) magnetograms using a modified RRDBNet architecture initialized by ESRGAN pretrained weights. Through systematic per-image diagnostic analysis, we identify image complexity as the dominant predictor of reconstruction errors. To exploit this finding, we introduce an adaptive stratified specialist ensemble (SSE) of three specialist networks with uncertainty estimation, where each specialist network is trained by images from three different complexity strata using a weighted random sampling strategy. During inference, a lightweight router based on input image statistics assigns each test image to the appropriate specialist network. Our experimental results demonstrate the good performance of the proposed ensemble and its superiority over closely related methods.
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All authors Sina Norouzi Kandalan, Haodi Jiang, Jason T. L. Wang, Qin Li
Astrophysics of Galaxies
Search for High-Ionization Nebular Emission (SHINE). I. A Systematically Selected [Ne V] Sample at z > 3 with JWST/NIRSpec PRISM
Shobita Satyapal, Sara Doan, Daniel Schaerer et al. (+8 more)
We conduct the first systematic Search for High-Ionization Nebular Emission (SHINE) using [Ne V]$\lambda3426$ in JWST/NIRSpec PRISM spectroscopy at $z>3$. From more than 9,000
galaxies, we identify 25 [Ne V] emitters spanning $z=3.059$-$9.444$ and $\log_{10}(L_{\rm [Ne\,V]}/erg\,s^{-1})=40.70$-$42.86$. Their [Ne V] luminosities overlap with those of local [Ne V]-selected active
galactic nuclei (AGNs) and exceed those of local metal-poor [Ne V] emitters, although such low-luminosity systems would fall below our sensitivity. The population is diverse, spanning compact and extended morphologies and a broad range of continuum properties and
stellar masses, including very low-mass hosts. It includes sources with broad Balmer emission as well as others whose higher-resolution spectra do not require a broad component. The [Ne V] emitters overlap only partly with conventional AGN diagnostics: most do not satisfy conservative high-
redshift AGN criteria based on strong rest-optical narrow-line ratios, and only a minority have adopted broad-line classifications. [Ne V] upper limits for independently selected broad-line AGNs and little red dots are too shallow to establish a population-wide [Ne V] deficit. Six sources have secure Chandra counterparts, showing that X-ray weakness is not universal among luminous [Ne V] emitters. Strong [Ne V]/[Ne III] emission is associated with redder ultraviolet slopes and stronger Balmer breaks, but not with UV luminosity, possibly linking strong high-ionization emission to recent changes in
star formation. The observed incidence of luminous [Ne V] emission shows no significant
evolution over $z>3$, despite an increasing robust [Ne III] detection fraction. The high [Ne V] luminosities and hard line ratios favor black-hole
accretion as the dominant power source, establishing [Ne V] emission as a complementary probe of early black-hole growth.
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All authors Shobita Satyapal, Sara Doan, Daniel Schaerer, Rui Marques-Chaves, Anurag Sawarkar, William Matzko, Camilo Vazquez, C. Daoutis, D. Korber, I. Morel, Mengyuan Xia
Quantum Physics
Quantum Soundness of a Total-Degree Line-versus-Point Test
Honghao Fu, Nengkun Yu and Tianrun Zhao
We prove
quantum soundness of the total-degree diagonal line-vs-point test using the individual-degree soundness
theorem of Ji, Natarajan, Vidick, Wright, and Yuen. A random change of coordinates yields projective
polynomial decoders of total degree at most $md$. The uniform-line slice of the test bounds the weight of outcomes of degree greater than $d$, which are removed by a common relabeling. This reduction does not yield a dimension-independent soundness bound: the $\operatorname{poly}(m)$ dependence of the individual-degree
theorem persists, as discussed in Section 1.2 of arXiv:2009.12982.
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Quantum Physics
Efficient Learning of Clifford-Scrambled Product States
Tobias Haug
Clifford
circuits acting on product magic states provide a compact ansatz exhibiting extensive magic, volume-law
entanglement, and even classically hard sampling under standard complexity assumptions. Here, we efficiently recover its hidden product subsystems from two-copy Bell sampling. Quadratic relations between Bell samples determine the irreducible blocks after removing Pauli stabilizers, and binary linear
algebra constructs a Clifford disentangler. For logarithmic-size blocks, approximate learning of the full state is efficient whenever the state remains inverse-polynomially separated from acquiring additional Pauli stabilizers. We efficiently learn $n$-
qubit states prepared by random $T$-doped Clifford
circuits with $T$-gate density below one via $O(n^2)$ Bell samples, and disentangle hidden product blocks in Clifford-augmented
matrix product states. For
unitary learning, we exactly learn $T$-depth-one
circuits using $O(n^2)$ queries. Finally, we rule out pseudorandom states and
unitaries with a product bipartition hidden by Clifford
circuits.
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