3 citations · 7 across the 18 of their papers we have counts for
11 papers · 2 filters
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…
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…
Large-scale implementation of quantum subspace expansion with classical shadows
Laurin E. Fischer, Daniel Bultrini, Ivano Tavernelli +1
Quantum subspace expansion (QSE) offers promising avenues to perform spectral calculations on quantum processors but comes with a large measurement overhead. Informationally comple…
Neutrino thermalization via randomization on a quantum processor
Oriel Kiss, Ivano Tavernelli, Francesco Tacchino +2
The dynamical evolution of neutrino flavor in supernovae can be modeled by an all-to-all spin Hamiltonian with random couplings. Simulating such two-local Hamiltonian dynamics rema…
Hardware-efficient formulation of molecular cavity-QED Hamiltonians
Francesco Troisi, Simone Latini, Heiko Appel +3
Light-matter coupled Hamiltonians are central to cavity materials engineering and polaritonic chemistry, but are challenging to simulate with classical hardware due to the scaling…
Quantum chemistry with provable convergence via randomized sample-based Krylov quantum diagonalization
Samuele Piccinelli, Alberto Baiardi, Stefano Barison +12
Quantum algorithms based on classical processing of individual samples have recently emerged as the most effective and robust methods to approximate ground-state wave functions of…