Hazem Daoud

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements Uniform Manifold Approximation and Projection (UMAP) for non-linear dimensionality reduction to reveal correlations in highly dimensional data. We also discuss potential extensions to deep autoencoders for feature learning, and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric's robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT's capabilities, we analyze photo double ionization data measured using the COLTRIMS method for 3-body dissociation of the D2O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software's modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Bimolecular reactions are ubiquitous in chemistry, but it is exceptionally difficult to resolve the motion of atoms for such processes on the ultrafast timescales that the breaking and creation of chemical bonds occur. Detecting small changes in atom positions requires high temporal and spatial resolution and reliable signal-to-noise characteristics. Here, we have exploited solid-state alignment to track a photoinduced bimolecular disproportionation reaction that transforms two pairs of adjacent triiodide anions into the metastable tetraiodide molecule and the diiodide fragment. We use ultrafast electron diffraction and dynamic structure refinement, where the atomic displacements are directly reconstructed from the diffraction data with plausible restraints on the atomic trajectories starting from the known ground-state structure. The excited-state structures are supported by theoretical calculations in the solid state and the reaction courses show clear site dependence on the ultrafast timescale. Our results provide a close-up view of the atomic motions involved in this classic reaction in real time, from bond elongation to breaking at the parent ion, to collision and subsequent bond formation of the liberated I atom with the neighbouring triiodide, all within a picosecond.