arXiv subjects

Luca Morelli

Publications and source records attributed to Luca Morelli.

8 recordsLinked to original sources

arXiv2026

The $H_0$ World Cup. I. Summary of the baseline group stage results

The Hubble tension has reached a nominal significance above $7\sigma$, while new high-precision measurements of the cosmic microwave background (CMB) and baryon acoustic oscillations (BAO) sharpen the test of proposed solutions. Using a common framework, we compare fourteen representative alternatives to the standard $\Lambda$ Cold Dark Matter ($\Lambda$CDM) model in light of up-to-date CMB, BAO and supernovae data to gauge their ability to resolve the tension. The models span late-time modifications, modified recombination, and exotic pre-recombination expansion histories driven by additional radiation or a localized dark energy injection. We evaluate each proposal with complementary frequentist and Bayesian measures of the residual calibration tension and of the improvement in the joint fit. Both approaches identify the same broad hierarchy. Early dark energy and early modified gravity models perform best, shifting the $H_0$ inference without local measurement priors toward $70\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$ and reducing the residual discrepancy with SH0ES to approximately $2.5-3.6\sigma$, depending on the model and statistic, while receiving strong support over $\Lambda$CDM in the combined fit. Varying the electron mass at recombination yields an intermediate improvement, whereas the enhanced-radiation and late-time scenarios do not improve over $\Lambda$CDM. This Letter summarizes the group stage of the competition; in a companion paper (Paper II) we present the results of an exhaustive set of analyses and assess their robustness to variations in modeling assumptions and datasets.

astro-ph.CO↗

arXiv2026

The $H_0$ world cup. II. A comprehensive competition between proposed Hubble tension solutions

Cosmology stands at a crossroads. The Hubble tension has reached a nominal significance above $7\sigma$, while analyses combining DESI BAO and Type Ia supernova data show emerging hints of departures from $\Lambda$CDM. Meanwhile, high-precision CMB measurements from ACT and SPT enable a timely and more stringent reassessment of proposed solutions to the tension. In this paper, we revisit the $H_0$ Olympics, a systematic contest comparing proposed alternatives to $\Lambda$CDM using common datasets, likelihoods, and statistical criteria. In this updated edition, the $H_0$ World Cup, we subject fourteen representative solutions to a common analysis of current CMB, BAO, and SN data. The contenders span four broad mechanisms: late-time modifications of the expansion history, modified recombination, additional pre-recombination radiation, and early non-radiative energy injection. Relative to the original analysis, the present competition includes models and mechanisms proposed in the intervening years and evaluates all contenders using both Bayesian and Frequentist tests of tension and model performance, letting the neutrino mass sum vary. We further test if late-time extensions through curvature or the Chevallier-Polarski-Linder (CPL) dark energy parametrization can aid the success of the models. Finally, we subject the leading contenders to dedicated robustness tests involving alternative CMB likelihoods and multipole cuts, supernova samples, large-scale-structure information, and big-bang nucleosynthesis constraints. This framework assesses both the ability of each mechanism to ease the Hubble tension and the robustness of our conclusions to datasets and analysis choices.

astro-ph.CO↗

arXiv2025

A-TDOM: Active TDOM via On-the-Fly 3DGS

True Digital Orthophoto Map (TDOM), a 2D objective representation of the Earth's surface, is an essential geospatial product widely used in urban management, city planning, land surveying, and related applications. However, traditional TDOM generation typically relies on a complex offline photogrammetric pipeline, leading to substantial latency and making it unsuitable for time-critical or real-time scenarios. Moreover, the quality of TDOM may deteriorate due to inaccurate camera poses, imperfect Digital Surface Model (DSM), and incorrect occlusions detection. To address these challenges, this work introduces A-TDOM, a near real-time TDOM generation method built upon On-the-Fly 3DGS (3D Gaussian Splatting) optimization. As each incoming image arrives, its pose and sparse point cloud are computed via On-the-Fly SfM. Newly observed regions are then incrementally reconstructed as additional 3D Gaussians are inserted using a Delaunay triangulated Gaussian sampling and integration and are further optimized via adaptive training iterations and learning rate, especially in previously unseen or coarsely modeled areas. With orthogonal splatting integrated into the rendering pipeline, A-TDOM can actively produce updated TDOM outputs immediately after each 3DGS update. Code is now available at https://github.com/xywjohn/A-TDOM.

cs.CV↗

arXiv2024

Image Matching Filtering and Refinement by Planes and Beyond

This paper provides a consistent and extensive evaluation of state-of-the-art filtering and refinement methods on common image matching pipelines. Unlike previous comparisons, the designed benchmark also takes into account the more general, real, and practical cases where camera intrinsics are unavailable. Moreover, a novel and effective strategy combining non-deep traditional computer vision approaches based on planar constraints and cross correlation is presented. Experimental analysis provides several insights for current application design and future research directions. In particular, the choice of a proper evaluation protocol discloses the effective differences within the compared solutions which otherwise would tend to flatten. Moreover, the proposed classical algorithmic approach is competitive with recent deep methods. Besides providing robust baseline using traditional computer vision for the evaluation of deep-based methods, this knowledge is useful to improve and better understand the deep image matching architectures. On one hand, geometry-based filtering is effective in presence of outliers without degrading already robust deep pipelines; on the other hand cross-correlation refinement is valid in the case of corner-like keypoints and allows to not directly discard inaccurate matches by default in deep pipelines but to retain and refine them for achieving a better coverage of the scene.

cs.CV↗

arXiv2024

Exploring the potential of collaborative UAV 3D mapping in Kenyan savanna for wildlife research

UAV-based biodiversity conservation applications have exhibited many data acquisition advantages for researchers. UAV platforms with embedded data processing hardware can support conservation challenges through 3D habitat mapping, surveillance and monitoring solutions. High-quality real-time scene reconstruction as well as real-time UAV localization can optimize the exploration vs exploitation balance of single or collaborative mission. In this work, we explore the potential of two collaborative frameworks - Visual Simultaneous Localization and Mapping (V-SLAM) and Structure-from-Motion (SfM) for 3D mapping purposes and compare results with standard offline approaches.

cs.CV↗

arXiv2024

Deep Learning Meets Satellite Images -- An Evaluation on Handcrafted and Learning-based Features for Multi-date Satellite Stereo Images

A critical step in the digital surface models(DSM) generation is feature matching. Off-track (or multi-date) satellite stereo images, in particular, can challenge the performance of feature matching due to spectral distortions between images, long baseline, and wide intersection angles. Feature matching methods have evolved over the years from handcrafted methods (e.g., SIFT) to learning-based methods (e.g., SuperPoint and SuperGlue). In this paper, we compare the performance of different features, also known as feature extraction and matching methods, applied to satellite imagery. A wide range of stereo pairs(~500) covering two separate study sites are used. SIFT, as a widely used classic feature extraction and matching algorithm, is compared with seven deep-learning matching methods: SuperGlue, LightGlue, LoFTR, ASpanFormer, DKM, GIM-LightGlue, and GIM-DKM. Results demonstrate that traditional matching methods are still competitive in this age of deep learning, although for particular scenarios learning-based methods are very promising.

cs.CV↗

arXiv2024

SfM on-the-fly: Get better 3D from What You Capture

In the last twenty years, Structure from Motion (SfM) has been a constant research hotspot in the fields of photogrammetry, computer vision, robotics etc., whereas real-time performance is just a recent topic of growing interest. This work builds upon the original on-the-fly SfM (Zhan et al., 2024) and presents an updated version with three new advancements to get better 3D from what you capture: (i) real-time image matching is further boosted by employing the Hierarchical Navigable Small World (HNSW) graphs, thus more true positive overlapping image candidates are faster identified; (ii) a self-adaptive weighting strategy is proposed for robust hierarchical local bundle adjustment to improve the SfM results; (iii) multiple agents are included for supporting collaborative SfM and seamlessly merge multiple 3D reconstructions into a complete 3D scene when commonly registered images appear. Various comprehensive experiments demonstrate that the proposed SfM method (named on-the-fly SfMv2) can generate more complete and robust 3D reconstructions in a high time-efficient way. Code is available at http://yifeiyu225.github.io/on-the-flySfMv2.github.io/.

cs.CV↗

arXiv2013

Probing the statistical decay and alpha-clustering effects in 12c+12c and 14n+10b reactions

An experimental campaign has been undertaken at INFN Laboratori Nazionali di Legnaro, Italy, in order to progress in our understanding of the statistical properties of light nuclei at excitation energies above particle emission threshold, by measuring exclusive data from fusion-evaporation reactions. A first reaction 12C+12C at 7.9 AMeV beam energy has been measured, using the GARFIELD+Ring Counter experimental setup. Fusion-evaporation events have been exclusively selected. The comparison to a dedicated Hauser-Feshbach calculation allows us to give constraints on the nuclear level density at high excitation energy for light systems ranging from C up to Mg. Out-of-equilibrium emission has been evidenced and attributed both to entrance channel effects favoured by the cluster nature of reaction partners and, in more dissipative events, to the persistence of cluster correlations well above the 24Mg threshold for 6 alphas decay. The 24Mg compound nucleus has been studied with a new measurement 14N + 10B at 5.7 AMeV. The comparison between the two datasets would allow us to further constrain the level density of light nuclei. Deviations from a statistical behaviour can be analyzed to get information on nuclear clustering.

nucl-ex↗