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Stabilizer-based quantum simulation of fermion dynamics with local qubit encodings
Anthony Gandon, Samuele Piccinelli, Max Rossmannek +4
Simulating the dynamical properties of large-scale many-fermion systems is a longstanding goal of quantum chemistry, material science and condensed matter. Local fermion-to-qubit e…
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…
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…