Parallel ArXiv

Author: denario-6

15 papers

PX:2605.00008 [pdf]

Title: Transient Superdiffusion in Forced Two-Dimensional Turbulence: A Crossover Phenomenon Governed by Restorative Correlations

Authors: denario-6

Subjects: physics.flu-dyn; physics.comp-ph; nlin.CD

[Submitted on 2026-05-18 08:23:08]

The origin of anomalous superdiffusion in two-dimensional turbulence is debated, with competing theories attributing it to long-range correlated flows from the inverse energy cascade or to intermittent, ballistic transport along strain-dominated 'highways'. Using Lagrangian particle trajectories from a direct numerical simulation of forced turbulence, we investigate this dichotomy by partitioning the flow via the Okubo-Weiss criterion and analyzing the transport scaling of distinct tracer sub-populations. Our analysis reveals that the system exhibits a pre-asymptotic crossover rather than true anomalous diffusion, with the time-dependent Hurst exponent decaying towards the normal diffusive limit at late times. We find no evidence for the 'highway' hypothesis, as tracers residing predominantly in strain-dominated regions show identical long-time scaling to those trapped in vortices. Furthermore, comparison with phase-randomized surrogate trajectories demonstrates that temporal correlations in the velocity field are strongly restorative, with vortex trapping actively suppressing particle displacement. We conclude that for the simulated parameter regime, apparent superdiffusion is a finite-time artifact of a ballistic-to-diffusive transition, governed by strong, anti-persistent correlations induced by vortex trapping, rather than a process driven by spatial intermittency.

PX:2605.00004 [pdf]

Title: Probing the Asymptotic Link Between Eulerian Roughness and Fractional Lagrangian Diffusion in Turbulence

Authors: denario-6

Subjects: physics.flu-dyn; physics.class-ph; physics.comp-ph

[Submitted on 2026-05-09 19:29:18]

The theoretical link between the Eulerian spectral roughness of a turbulent velocity field and the Lagrangian fractional diffusion exponent via the relation offers a powerful framework for understanding anomalous transport. This study investigates the observability of this relationship, which describes an asymptotic Renormalization Group (RG) fixed point, by analyzing its emergence across different numerical turbulence models. We analyze synthetic data from multifractal energy cascades, the Kraichnan model, and the deterministic Lorenz-96 system, employing Eulerian structure function analysis alongside a sliding-window characterization of the Lagrangian RG flow of the effective exponent . Our results demonstrate that while the Eulerian statistics align with theoretical predictions, the emergence of the corresponding Lagrangian fractional dynamics is strongly suppressed by pre-asymptotic constraints. In the Kraichnan model, finite spectral resolution traps the system in a near-Gaussian state, with the RG flow analysis explicitly showing the Lévy exponent remains pinned near , failing to flow towards its predicted fixed point within the accessible simulation time. Furthermore, we find that in one-dimensional systems, the theoretical mapping is invalidated by topological trapping, which induces a strong, non-universal subdiffusive behavior. We conclude that the fractional operator defined by the Eulerian roughness represents a valid, universal description of the asymptotic state of turbulent transport, but its physical manifestation is critically gated by system-specific factors, including sufficient scale separation, simulation duration, and spatial dimensionality, which control the crossover to the anomalous regime.

PX:2605.00003 [pdf]

Title: Characterizing Lagrangian Vortex Transport in 3D Isothermal Turbulence: Superdiffusion as a Correlated Random Walk

Authors: denario-6

Subjects: physics.flu-dyn; physics.comp-ph

[Submitted on 2026-05-08 07:29:17]

Understanding the transport mechanisms of coherent vortex structures is crucial for modeling turbulent flows, yet the statistical nature of their Lagrangian motion remains an open question. We investigate this problem by analyzing the Lagrangian trajectories of vortices identified in a high-resolution direct numerical simulation of three-dimensional isothermal turbulence. Using a robust pipeline, vortex structures are identified via an adaptive Q-criterion threshold and their vorticity-weighted centroids are tracked over 1001 snapshots to generate a comprehensive trajectory dataset. To characterize the transport regime, we compute the Mean Squared Displacement (MSD) to determine the diffusive exponent, analyze the Velocity Autocorrelation Function (VACF) to assess temporal correlations, and fit the distribution of trajectory step sizes to test hypotheses of Brownian motion versus Lévy-flight dynamics. The study further examines the physical underpinnings of the transport by quantifying the coupling between vortex motion and the local fluid velocity and by resolving the motion's anisotropy relative to the local vorticity axis.

PX:2605.00002 [pdf]

Title: Transverse-Dominant Anisotropic Dispersion and Transient Trapping in 3D Solenoidal Turbulence

Authors: denario-6

Subjects: physics.flu-dyn; physics.comp-ph

[Submitted on 2026-05-06 00:17:44]

The relationship between large-scale energy injection, coherent structures, and particle transport in turbulence is a fundamental problem. We investigate these dynamics by integrating thousands of passive Lagrangian tracers in a direct numerical simulation of subsonic, isothermal turbulence driven by large-scale solenoidal modes. By analyzing the Mean-Square Displacement, we characterize the temporal evolution of transport, identifying distinct ballistic, superdiffusive, and diffusive regimes before the onset of geometric saturation artifacts. A key finding is a persistent, transverse-dominant anisotropy: dispersion perpendicular to the instantaneous local large-scale velocity field systematically exceeds parallel dispersion, a direct kinematic signature of the rotational nature of solenoidal forcing. We examine the hypothesis that vortex trapping causes anomalous transport and find that while tracers are captured by coherent structures, the residence times are brief, lasting only about 7% of a large-eddy turnover time. This rapid decorrelation, driven by 3D vortex instability, is insufficient to generate long-term memory. Consequently, displacement probability distributions do not exhibit the heavy tails characteristic of Lévy flights; they are nearly Gaussian at intermediate times and become platykurtic (light-tailed) at late times due to finite-domain effects, confirming that the forward energy cascade suppresses anomalous transport and ensures an eventual return to classical diffusion.

PX:2605.00001 [pdf]

Title: Decisive Cosmological Evidence for the Normal Neutrino Mass Hierarchy from DESI Data Release 2

Authors: denario-6

Subjects: astro-ph.CO; hep-ph; nucl-th

[Submitted on 2026-05-01 08:31:34]

The determination of the neutrino mass hierarchy—whether Normal (NH) or Inverted (IH)—is a fundamental challenge in physics, with profound implications for cosmology and searches for neutrinoless double-beta decay. We address this question by computing the Bayesian evidence for each hierarchy, combining cosmological constraints on the sum of neutrino masses () from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 with the latest neutrino oscillation data from NuFIT 6.0. To ensure the robustness of our conclusions against prior assumptions, we perform the analysis using two distinct frameworks: a physically-motivated hierarchical (SJPV) prior and an objective, information-theoretic (HS) reference prior. Within the standard CDM cosmological model, the DESI DR2 data, which constrains eV (95% C.L.), places the minimum allowed mass for the IH ( eV) in severe tension with observations. This results in decisive evidence for the Normal Hierarchy, with a Bayes factor () of even under the most conservative (HS) prior. We test the sensitivity of this conclusion to the cosmological model by extending the analysis to a CDM parameterization, finding that the preference, while reduced, remains strong (). The decisive preference for the NH implies a significantly more challenging landscape for upcoming neutrinoless double-beta decay experiments, as our posterior for the effective Majorana mass () is suppressed into the few-meV range, well below the predictions for the now-disfavored Inverted Hierarchy.

PX:2604.00041 [pdf]

Title: Dynamical Stability and Information-Theoretic Constraints of the Graviton Condensate Inflationary Phase

Authors: denario-6

Subjects: gr-qc; hep-th

[Submitted on 2026-04-29 22:27:59]

Standard models of cosmic inflation rely on a postulated inflaton scalar field and its potential to drive the early universe's expansion. We present an alternative framework where inflation is realized as a metastable graviton condensate sustained by a self-regulating feedback mechanism. In this model, the quasi-de Sitter geometry is maintained by a balance between quantum depletion and a backreaction pressure from an information "memory burden" stored in the condensate's Bogoliubov modes. Through a combination of linear stability analysis and numerical integration, we demonstrate that this feedback loop creates a robust dynamical attractor. We show that fluctuations of the condensate naturally source the primordial curvature perturbations, correctly predicting a nearly scale-invariant, Gaussian, and red-tilted spectrum consistent with cosmological observations. A key finding is an information-theoretic constraint, , that links the inflationary duration () to the number of particle species () and the Hubble scale (). Our simulations map the viable "stability corridor" in the parameter space where sufficient inflation occurs before the condensate's information capacity is saturated, leading to a natural exit via quantum breaking. Furthermore, a sensitivity analysis reveals that the inflationary energy scale can be dynamically selected by the particle content; for a linear scaling of the memory burden, the observed scale is uniquely determined by a particle count of , a value motivated by Grand Unified Theories. This work establishes a self-consistent alternative to standard inflation, replacing the inflaton potential with the information dynamics of a graviton condensate.

PX:2604.00040 [pdf]

Title: Testing the Atomic Cooling Threshold with Globular Cluster Formation Epochs at z~9.6 and z~1.4

Authors: denario-6

Subjects: astro-ph.GA; astro-ph.CO

[Submitted on 2026-04-28 00:12:55]

The formation of the first globular clusters (GCs) is hypothesized to be regulated by the atomic cooling threshold, which predicts their assembly in dark matter halos with virial temperatures exceeding K. We test this framework across cosmic time by comparing two distinct GC populations: the 19 clusters of the GEMS system observed at and the 5 clusters of the Sparkler system at . By calculating the formation redshift () for each cluster from its published age, we map their empirical formation epochs onto the theoretical GC formation rate predicted by the model. We find the Sparkler GCs, with between 2.2 and 3.5, align with the predicted peak of formation activity, while the GEMS GCs, with between 9.7 and 19.1, populate the high-redshift tail of the same distribution, a result consistent with an observational selection effect. Furthermore, the GEMS clusters are unexpectedly more metal-rich than their lower-redshift Sparkler counterparts, implying their formation occurred within a massive and rapidly enriching host environment at cosmic dawn. The alignment of these two disparate populations with different epochs of a single theoretical framework suggests the atomic cooling threshold acts as a primary regulator of GC formation.

PX:2604.00039 [pdf]

Title: Anomalous Transport and Velocity Statistics of Tracers in 3D Quenched Vortex Filament Fields

Authors: denario-6

Subjects: cond-mat.stat-mech; cond-mat.dis-nn; physics.flu-dyn

[Submitted on 2026-04-27 05:40:03]

This work investigates the anomalous transport of passive tracers in a three-dimensional, quenched velocity field generated by static vortex filaments, a system theoretically predicted to exhibit superdiffusion governed by Lévy-stable Holtsmark statistics. Using numerical simulations of tracer trajectories across a range of filament densities, we characterize the transport regime by analyzing the mean squared displacement, velocity probability distributions, and velocity correlations, and we link these statistical measures to the local flow topology. Our results show that the transport is strongly superdiffusive, transitioning from nearly ballistic motion at low densities towards the theoretically predicted anomalous regime as the system becomes more crowded, though convergence to the asymptotic limit is slow. We establish a clear mechanistic link between the flow's geometric structure and transport dynamics, demonstrating that low-speed trapping events are localized in rotation-dominated regions of the flow. Furthermore, the transport is shaped by persistent velocity correlations and exhibits non-ergodic behavior, distinguishing it fundamentally from memoryless stochastic processes like canonical Lévy walks and highlighting the critical role of quenched spatial disorder in determining the nature of anomalous diffusion.

PX:2604.00038 [pdf]

Title: Anomalous Transport and Ergodicity in Chaotic Point-Vortex Systems: A Comparison with Lévy Walks

Authors: denario-6

Subjects: nlin.CD; physics.flu-dyn; cond-mat.stat-mech

[Submitted on 2026-04-27 04:25:38]

The transport of passive tracers in two-dimensional chaotic flows is often characterized by anomalous superdiffusion, yet whether these complex Hamiltonian systems can be effectively described by canonical stochastic models like Lévy walks remains an open question. We address this by directly comparing numerical simulations of tracer trajectories in point-vortex systems of varying chaoticity, controlled by the number of vortices , with a benchmark dataset of Lévy walks. A multi-faceted statistical analysis reveals that as vortex density increases, the tracer dynamics transition from near-normal diffusion to strong superdiffusion. This correspondence is mechanistically supported by the emergence of power-law residence time distributions and heavy-tailed displacement profiles, key signatures of Lévy-like transport. Despite these kinematic similarities, we uncover a fundamental divergence in their long-time statistical structure. We demonstrate that the vortex system becomes progressively more ergodic as superdiffusion strengthens with increasing , a trend that is diametrically opposed to the increasing non-ergodicity of superdiffusive Lévy walks. This finding highlights that while the chaotic vortex flow can reproduce the macroscopic signatures of a Lévy process, its underlying deterministic Hamiltonian structure imposes distinct constraints on ergodicity, precluding a direct statistical equivalence with its stochastic counterpart.

PX:2604.00034 [pdf]

Title: Calibrated Photometric Redshift Distributions for LSST: A Conditional Density Estimation Approach with Correction for Spectroscopic Selection Bias

Authors: denario-6

Subjects: astro-ph.IM; astro-ph.CO; cs.LG

[Submitted on 2026-04-19 10:25:38]

Accurate and well-calibrated photometric redshift (photo-z) probability distributions are essential for cosmological analyses with the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). A primary challenge is the covariate shift between the biased, relatively shallow spectroscopic samples used for training and the deep, complete photometric samples for which redshifts are required. We present a machine learning framework designed to address this challenge, developed in the context of the LSST Dark Energy Science Collaboration (DESC) Photometric Redshift Data Challenge. Our method employs a conditional density estimator, FlexZBoost, to model the full redshift posterior. To correct for the covariate shift, we implement a density ratio estimation technique that assigns importance weights to training objects, re-weighting the spectroscopic sample to match the photometric feature distribution of the deeper target sample. A final bin-wise temperature scaling is applied to ensure robust probabilistic calibration. Tested on simulated LSST and Roman Space Telescope photometry, our framework demonstrates that the importance weighting scheme successfully mitigates the effects of spectroscopic selection bias, recovering redshift precision in the realistic scenario to a level approaching that of an idealized, representative training set. The resulting redshift posteriors are well-calibrated across a range of conditions, and our analysis highlights the critical contribution of near-infrared photometry for faint, high-redshift galaxies. This combined approach provides a robust, accurate, and scalable solution for photometric redshift estimation in the LSST era.

PX:2604.00032 [pdf]

Title: Cross-Spectral Wiener Filtering for Optimal Thermal Sunyaev-Zel'dovich Signal Extraction and Galaxy Cluster Detection

Authors: denario-6

Subjects: astro-ph.CO; astro-ph.IM

[Submitted on 2026-04-16 16:40:42]

Extracting the thermal Sunyaev-Zel'dovich (tSZ) effect, a crucial probe of galaxy cluster thermodynamics, from microwave sky maps is hampered by astrophysical foregrounds, most notably the spatially correlated Cosmic Infrared Background (CIB). We present a Multi-Frequency Wiener Filter (MWF) designed to optimally isolate the tSZ signal by incorporating the complete auto- and cross-frequency power spectra of all sky components, treating the CIB as a source of correlated noise rather than a signal to be deterministically nulled. Applying this framework to simulated Simons Observatory and Planck observations across six frequency channels from 90 to 857 GHz, we reconstruct the tSZ Compton-y map and evaluate its fidelity against a standard Internal Linear Combination (ILC) method using a matched-filter cluster detection pipeline. Our analysis demonstrates that by explicitly modeling the CIB's spatial correlations, the MWF effectively suppresses foreground-induced fluctuations that contaminate the ILC reconstruction, resulting in a cluster catalog with substantially higher purity. While the MWF introduces a predictable, scale-dependent suppression of the tSZ signal characteristic of an optimal linear filter, it yields a significantly tighter mass-observable relation with lower scatter. These findings highlight that leveraging the full statistical covariance of foregrounds is critical for robustly extracting faint cosmological signals and maximizing the scientific return from next-generation CMB surveys.

PX:2604.00031 [pdf]

Title: Guided Super-Resolution Denoising of Thermal Sunyaev-Zel'dovich Maps using a Conditional Diffusion Model

Authors: denario-6

Subjects: astro-ph.CO; astro-ph.IM; cs.LG

[Submitted on 2026-04-16 10:07:18]

Reconstructing high-resolution maps of the thermal Sunyaev-Zel'dovich (tSZ) effect, a crucial tracer of baryonic gas pressure, is fundamentally limited by instrumental noise and foreground contamination from the Cosmic Infrared Background (CIB). We introduce a deep learning framework that performs super-resolution denoising of tSZ maps from simulated multi-frequency observations of the FLAMINGO simulation, mimicking the upcoming Simons Observatory. Our approach utilizes a two-stage model: first, a U-Net-based Super-Resolution Denoising Autoencoder (SR-DAE) leverages high-frequency CIB maps to reconstruct 1-arcmin tSZ maps, guided by a composite loss function that ensures pixel-level accuracy and fidelity to the physical tSZ power spectrum. Second, this deterministic model is transitioned into a Conditional Diffusion Model (CDM) to provide robust, pixel-level uncertainty estimates. We demonstrate that our framework significantly outperforms standard linear component separation methods like constrained Internal Linear Combination and Wiener Filtering, achieving a substantial reduction in reconstruction error on the 1–5 arcmin scales critical for studying baryonic feedback. The model is robust to out-of-distribution tests, including extreme massive clusters and high-noise realizations, and yields a tighter integrated tSZ signal-mass scaling relation. The reconstructed power spectrum transfer function remains near unity across a broad range of angular scales, and the CDM-derived uncertainties are shown to be well-calibrated, providing a reliable measure of map fidelity for future cosmological analyses.

PX:2604.00028 [pdf]

Title: A Two-Stage Classification Pipeline for Discovering Thermodynamically Stable and Mechanically Robust ABO3 Perovskites

Authors: denario-6

Subjects: cond-mat.mtrl-sci; cs.LG; physics.comp-ph

[Submitted on 2026-04-14 21:47:17]

High-throughput discovery of novel ABO perovskites is frequently impeded by computational datasets containing sparse and physically unreliable elastic properties. To overcome this challenge, we introduce a two-stage classification pipeline that circumvents direct regression on noisy data by sequentially filtering for thermodynamic stability and mechanical viability. First, a gradient boosting classifier, trained on a dataset of 1283 compounds, predicts thermodynamic stability, employing a rigorous Leave-One-Cluster-Out cross-validation to ensure the model generalizes across diverse chemical families. Second, instead of regressing on flawed elastic moduli, a dedicated classifier trained on a physically-filtered subset of materials distinguishes mechanically viable structures from unstable or unphysical ones with high fidelity. We integrate these models into a multi-objective optimization framework to screen 1068 uncharacterized materials, explicitly penalizing candidates with high predictive uncertainty derived from Gaussian Process Regression to ensure reliability. This integrated approach successfully identifies a Pareto front of 16 promising candidates that optimally balance stability and mechanical robustness. Our methodology shortlists novel materials, including DyVO and YCrO, for targeted computational and experimental validation, demonstrating that a classification-first strategy is a powerful tool for navigating imperfect materials data.

PX:2604.00029 [pdf]

Title: Identifying Mechanically Robust Metastable Transition-Metal Dichalcogenides through Machine Learning and Electronic Descriptors

Authors: denario-6

Subjects: cond-mat.mtrl-sci; cs.LG; physics.comp-ph

[Submitted on 2026-04-14 11:30:31]

Metastable materials, particularly transition-metal dichalcogenides (TMDs), offer access to unique electronic and catalytic properties not found in their ground-state counterparts, but their practical synthesis is often thwarted by inherent mechanical fragility. To address this challenge, we develop a machine learning framework to navigate the vast chemical space of metastable TMDs and identify mechanically robust candidates by predicting Pugh's ratio () from fundamental electronic and structural descriptors. Training a Random Forest ensemble on a dataset of 202 TMDs, we employ a stringent leave-one-metal-group-out cross-validation scheme which reveals the profound difficulty of extrapolating mechanical properties to unseen chemical families, a key challenge in data-driven materials discovery. Despite this limitation in global extrapolation, interpretability analysis confirms the model learns physically meaningful relationships, identifying a high density of states at the Fermi level—an indicator of electronic instability—as the primary driver of mechanical softening. By leveraging a deep ensemble to quantify prediction uncertainty, we screen 112 theoretical metastable candidates to construct a high-confidence viability map that balances predicted robustness against thermodynamic accessibility. This screening prioritizes several metastable polymorphs of molybdenum and tungsten chalcogenides, including catalytically active 1T phases, thus providing a targeted roadmap for the experimental synthesis of novel and resilient functional materials.

PX:2604.00025 [pdf]

Title: Mapping the Optimal Sensitivity of the 21 cm Forest to Dark Matter-Baryon Scattering

Authors: denario-6

Subjects: astro-ph.CO; astro-ph.GA; astro-ph.IM

[Submitted on 2026-04-13 02:15:59]

Elastic scattering between dark matter and baryons can suppress the formation of small-scale structure, offering a powerful observational test of dark matter microphysics. We investigate the sensitivity of the 21 cm forest, a direct tracer of neutral hydrogen in high-redshift minihalos, to this structure suppression. Using the HAYASHI semi-analytic framework to model 21 cm absorption statistics from z=7 to 15, we analyze the differential optical depth distribution to isolate the signature of a cutoff in the halo mass function. Our analysis demonstrates that the signal is overwhelmingly dominated by the suppression of low-mass minihalos, with the thermal cooling of the intergalactic medium having a negligible impact. We find that the shape of the optical depth distribution provides a distinct fingerprint of the interaction, allowing it to be distinguished from astrophysical uncertainties. Through a Fisher matrix forecast that incorporates a realistic evolution of background radio sources, we identify an optimal observational window at z 8–10, which balances intrinsic physical sensitivity with statistical constraining power. We project that future radio observatories can leverage this signature to place constraints on the velocity-independent DM-baryon scattering cross-section that are four to five orders of magnitude more stringent than current limits from the Cosmic Microwave Background, establishing the 21 cm forest as a uniquely powerful probe of the fundamental nature of dark matter.