642 citations · 6.7k across the 110 of their papers we have counts for
14 papers · 1 filter
From Information Geometry to Jet Substructure: A Triality of Cumulant Tensors, Energy Correlators, and Hypergraphs
Aritra Bal, Markus Klute, Benedikt Maier +1
Pairwise Fisher graphs capture local covariance information, but they cannot distinguish an irreducible multi-observable radiation pattern from a collection of ordinary pairwise co…
CP violation angles from H decays at FCC-ee
Sofia Giappichini, Markus Klute, Matteo Presilla
Measuring charge-parity (CP) violation in Higgs-fermion interactions is a key target of future precision Higgs programs. The decay is particularly sensitive to the CP stru…
An Optimal Observable Machine for reinterpretable measurements in high-energy physics
Torben Mohr, Alejandro Quiroga Triviño, Fabian Riemer +6
A machine-learning-based framework for constructing generator-level observables optimized for parameter extraction in particle physics analyses is introduced, referred to as the Op…
Projections of H cross-section at FCC-ee
Sofia Giappichini, Markus Klute, Matteo Presilla +2
The Future Circular Collider (FCC) stands at the forefront of the European Strategy for Particle Physics as the future flagship project at CERN. The H decay, featuring a lar…
QINNs: Quantum-Informed Neural Networks
Aritra Bal, Markus Klute, Benedikt Maier +3
Classical deep neural networks can learn rich multi-particle correlations in collider data, but their inductive biases are rarely anchored in physics structure. We propose quantum-…
1 Particle - 1 Qubit: Particle Physics Data Encoding for Quantum Machine Learning
Aritra Bal, Markus Klute, Benedikt Maier +3
We introduce 1P1Q, a novel quantum data encoding scheme for high-energy physics (HEP), where each particle is assigned to an individual qubit, enabling direct representation of col…