From the 1 of 8 linked papers with an AI index.
8 papers
Neural quantum states for non-Abelian lattice gauge theories with dynamical fermions
Gabriel Rouxinol, Julian Bender, Michele Grossi +2
The paper introduces a neural-network based variational Monte Carlo method to study the ground state of continuous SU(2) lattice gauge theory with dynamical staggered fermions, pro…
Physics inspired quantum algorithm for QCD splitting functions
Gabriel Rouxinol, Yacine Haddad, Cenk Tüysüz +2
We introduce a modular quantum circuit primitive to model entanglement dynamics in QCD parton splitting and use it as a composable building block for data-driven, physics-consisten…
Coherent Quantum Evaluation of Collider Amplitudes for Effective Field Theory Constraints
Yacine Haddad, Kaidi Xu, Vincent Croft +2
Precision measurements at electron-positron colliders provide stringent tests of the Standard Model and powerful probes of possible higher-dimensional interactions. We present a hy…
Learning Reduced Representations for Quantum Classifiers
Patrick Odagiu, Vasilis Belis, Lennart Schulze +6
Data sets that are specified by a large number of features are currently outside the area of applicability for quantum machine learning algorithms. An immediate solution to this im…
Quantum Information meets High-Energy Physics: Input to the update of the European Strategy for Particle Physics
Yoav Afik, Federica Fabbri, Matthew Low +68
Some of the most astonishing and prominent properties of Quantum Mechanics, such as entanglement and Bell nonlocality, have only been studied extensively in dedicated low-energy la…
Guided Graph Compression for Quantum Graph Neural Networks
Mikel Casals, Vasilis Belis, Elias F. Combarro +3
Graph Neural Networks (GNNs) are effective for processing graph-structured data but face challenges with large graphs due to high memory requirements and inefficient sparse matrix…