activity
20202026
most citedFermionic Magic Resources of Quantum Many-Body Systems

8 citations · 8 across the 5 of their papers we have counts for

collaborators

14 papers

quant-ph2026

Mapping twist fields to local operators via tensor networks

Andrea Bulgarelli, Marco Panero, Paolo Stornati +1

Twist fields are a powerful formal tool to compute Rényi entropies in quantum many-body systems, but their conventional formulation in tensor network states involves operations act…

quant-ph2026

Exact stabilizer scars in two-dimensional lattice gauge theory

Sabhyata Gupta, Piotr Sierant, Luis Santos +1

The complexity of highly excited eigenstates is a central theme in nonequilibrium many-body physics, underpining questions of thermalization, classical simulability, and quantum in…

quant-ph2026

Limits of Clifford Disentangling in Tensor Network States

Sergi Masot-Llima, Piotr Sierant, Paolo Stornati +1

Tensor network methods leverage the limited entanglement of quantum states to efficiently simulate many-body systems. Alternatively, Clifford circuits provide a framework for handl…

quant-ph2026

Hardware-inspired Continuous Variables Quantum Optical Neural Networks

Todor Krasimirov-Ivanov, Alba Cervera-Lierta, Paolo Stornati +1

Continuous-variables (CV) quantum optics is a natural formalism for neural networks (NNs) due to its ability to reproduce the information processing of such trainable interconnecte…

quant-ph20258 cited

Fermionic Magic Resources of Quantum Many-Body Systems

Piotr Sierant, Paolo Stornati, Xhek Turkeshi

Understanding the computational complexity of quantum states is a central challenge in quantum many-body physics. In qubit systems, fermionic Gaussian states can be efficiently sim…

cs.LG2024

Physics-Informed Bayesian Optimization of Variational Quantum Circuits

Kim A. Nicoli, Christopher J. Anders, Lena Funcke +7

In this paper, we propose a novel and powerful method to harness Bayesian optimization for Variational Quantum Eigensolvers (VQEs) -- a hybrid quantum-classical protocol used to ap…