29 citations · 53 across the 9 of their papers we have counts for
9 papers
Generative IQP Circuit Learning with Physics-Informed Latent Initialization
Chen-Yu Liu, Leonardo Placidi, Marco Ballarin +1
Quantum generative learning based on instantaneous quantum polynomial-time (IQP) circuits can benefit from efficient classical training strategies. A recent latent adaptation frame…
Exact log-depth preparation of highly entangled matrix product states
Keisuke Murota, Frédéric Sauvage, Marco Ballarin +2
Preparing matrix product states (MPS) on a quantum device is a key subroutine in many quantum algorithms. The most competitive methods, based on the renormalisation group, prepare…
Quantum algorithms for equational reasoning
Davide Rattacaso, Daniel Jaschke, Marco Ballarin +2
As a cornerstone of automated reasoning, equational reasoning finds equivalences between symbolic expressions and fuels advances across scientific disciplines. Yet, its potential r…
Benchmarking Quantum Red TEA on CPUs, GPUs, and TPUs
Daniel Jaschke, Marco Ballarin, Nora Reinić +2
We benchmark simulations of many-body quantum systems on heterogeneous hardware platforms using CPUs, GPUs, and TPUs. We compare different linear algebra backends, e.g., NumPy vers…
Quantum circuit compilation with quantum computers
Davide Rattacaso, Daniel Jaschke, Marco Ballarin +2
Compilation optimizes quantum algorithms performances on real-world quantum computers. To date, it is performed via classical optimization strategies. We introduce a class of quant…
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…
Optimal sampling of tensor networks targeting wave function's fast decaying tails
Marco Ballarin, Pietro Silvi, Simone Montangero +1
We introduce an optimal strategy to sample quantum outcomes of local measurement strings for isometric tensor network states. Our method generates samples based on an exact cumulat…
Digital quantum simulation of lattice fermion theories with local encoding
Marco Ballarin, Giovanni Cataldi, Giuseppe Magnifico +5
We numerically analyze the feasibility of a platform-neutral, general strategy to perform quantum simulations of fermionic lattice field theories under open boundary conditions. Th…
Entanglement entropy production in Quantum Neural Networks
Marco Ballarin, Stefano Mangini, Simone Montangero +2
Quantum Neural Networks (QNN) are considered a candidate for achieving quantum advantage in the Noisy Intermediate Scale Quantum computer (NISQ) era. Several QNN architectures have…