activity
20182026
most citedEfficient Learning for Deep Quantum Neural Networks

712 citations · 771 across the 19 of their papers we have counts for

collaborators

22 papers

quant-ph2026

Hypercontractivity and entropy decay for infinite-dimensional quantum Gibbs samplers

Simon Becker, Cambyse Rouzé, Robert Salzmann

We derive rates of exponential relative-entropy decay for a broad class of infinite-dimensional quantum Gibbs samplers. A key technical ingredient is a perturbative stability theor…

quant-ph2026

Discriminating Lindbladian Dynamics

Robert Salzmann, Ludovico Lami, Martin B. Plenio +1

The fundamental task of quantum hypothesis testing, which consists in discriminating quantum objects, has been extensively studied for quantum states and channels. Here, we investi…

quant-ph2026

Transmitting algebras through quantum channels

Robert Salzmann, Satvik Singh

We develop a theory of exact transmission of finite-dimensional -algebras through quantum channels. These algebras describe hybrid classical-quantum information, allowing the…

quant-ph2026

Computing the free energy of quantum Coulomb gases and molecules via quantum Gibbs sampling

Simon Becker, Cambyse Rouzé, Robert Salzmann

We develop a quantum Gibbs-sampling approach to free-energy estimation for trapped systems of distinguishable particles with Coulomb interactions in dimensions . The s…

quant-ph2026

Simulating Thermal Properties of Bose-Hubbard Models on a Quantum Computer

Simon Becker, Cambyse Rouzé, Robert Salzmann

While recent advances have established efficient quantum algorithms for preparing Gibbs states of finite-dimensional systems, comparable complexity results for bosonic and other in…

quant-ph2026

Quantum Gibbs Sampling in Infinite Dimensions: Generation, Mixing Times and Circuit Implementation

Simon Becker, Cambyse Rouzé, Robert Salzmann

We develop a rigorous and implementable framework for Gibbs sampling of infinite-dimensional quantum systems governed by unbounded Hamiltonians. Extending dissipative Gibbs sampler…