7 papers
Combining non-parametric quantum states and MERA tensor networks for ground-state optimization
Julian Schuhmacher, Alberto Baiardi, Francesco Tacchino +1
Hybrid tensor networks offer a promising route to enhance the expressivity of classical tensor network methods by incorporating quantum states prepared on a quantum computer. Exist…
Optimizing two-dimensional isometric tensor networks with quantum computers
Sebastian Leontica, Alberto Baiardi, Julian Schuhmacher +2
We propose a hybrid quantum-classical algorithm for approximating the ground state of two-dimensional quantum systems using an isometric tensor network ansatz, which maps naturally…
Observation of hadron scattering in a lattice gauge theory on a quantum computer
Julian Schuhmacher, Guo-Xian Su, Jesse J. Osborne +3
Scattering experiments are at the heart of high-energy physics (HEP), breaking matter down to its fundamental constituents, probing its formation, and providing deep insight into t…
Hybrid Tree Tensor Networks for quantum simulation
Julian Schuhmacher, Marco Ballarin, Alberto Baiardi +4
Hybrid Tensor Networks (hTN) offer a promising solution for encoding variational quantum states beyond the capabilities of efficient classical methods or noisy quantum computers al…
Symmetry-invariant quantum machine learning force fields
Isabel Nha Minh Le, Oriel Kiss, Julian Schuhmacher +2
Machine learning techniques are essential tools to compute efficient, yet accurate, force fields for atomistic simulations. This approach has recently been extended to incorporate…
Quantum Computing for High-Energy Physics: State of the Art and Challenges. Summary of the QC4HEP Working Group
Alberto Di Meglio, Karl Jansen, Ivano Tavernelli +43
Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage…