activity
20222026
most citedA Lie Algebraic Theory of Barren Plateaus for Deep Parameterized Quantum Circuits

149 citations · 282 across the 6 of their papers we have counts for

collaborators
Showing quant-phShow all

6 papers · 1 filter

quant-ph2026

On the Metastability of the Mean-Field Interchange Model for Local Dimension

Sergio Escobar, Lin Lin, Michael Ragone +1

Many quantum systems are believed to thermalize slowly at low temperatures due to the existence of metastable phases. However, there are cases where further cooling can restore pol…

quant-ph2026

Quantum Markov State Models for Metastable Dynamics

Hao-En Li, Lin Lin, Michael Ragone

Open quantum systems can rapidly lose most microscopic information, leaving only a few degrees of freedom to govern their long-time dynamics. Classical Markov state models (MSMs) d…

quant-ph2026

Spectral Gap of the Davies Generator for the Mean-Field Heisenberg Model

Joao Basso, Thiago Bergamaschi, Lin Lin +2

The mean-field Heisenberg ferromagnet is a quantum spin model on the complete graph with isotropic spin-1/2 interactions. This non-commuting Hamiltonian is permutation and $\mathsf…

quant-ph2023★ 149 cited

A Lie Algebraic Theory of Barren Plateaus for Deep Parameterized Quantum Circuits

Michael Ragone, Bojko N. Bakalov, Frédéric Sauvage +4

Variational quantum computing schemes train a loss function by sending an initial state through a parametrized quantum circuit, and measuring the expectation value of some operator…

quant-ph2022★ 99 cited

Theory for Equivariant Quantum Neural Networks

Quynh T. Nguyen, Louis Schatzki, Paolo Braccia +5

Quantum neural network architectures that have little-to-no inductive biases are known to face trainability and generalization issues. Inspired by a similar problem, recent breakth…

quant-ph2022★ 32 cited

Representation Theory for Geometric Quantum Machine Learning

Michael Ragone, Paolo Braccia, Quynh T. Nguyen +5

Recent advances in classical machine learning have shown that creating models with inductive biases encoding the symmetries of a problem can greatly improve performance. Importatio…