6 papers
Provable and scalable quantum Gaussian processes for quantum learning
Jonas Jäger, Paolo Braccia, Pablo Bermejo +3
Despite rapid recent advances in quantum machine learning, the field is in many ways stuck. Existing approaches can exhibit serious limitations, and we still lack learning framewor…
Quantum Convolutional Neural Networks are Effectively Classically Simulable
Pablo Bermejo, Paolo Braccia, Manuel S. Rudolph +3
Quantum Convolutional Neural Networks (QCNNs) are widely regarded as a promising model for Quantum Machine Learning (QML). In this work we tie their heuristic success to two facts.…
Analyzing the free states of one quantum resource theory as resource states of another
Andrew E. Deneris, Paolo Braccia, Pablo Bermejo +3
In the context of quantum resource theories (QRTs), free states are defined as those which can be obtained at no cost under a certain restricted set of conditions. However, when ta…
Exact spectral gaps of random one-dimensional quantum circuits
Andrew E. Deneris, Pablo Bermejo, Paolo Braccia +2
The spectral gap of local random quantum circuits is a fundamental property that determines how close the moments of the circuit's unitaries match those of a Haar random distributi…
A unified approach to quantum resource theories and a new class of free operations
N. L. Diaz, Antonio Anna Mele, Pablo Bermejo +4
In quantum resource theories (QRTs) certain quantum states and operations are deemed more valuable than others. While the determination of the ``free'' elements is usually guided b…
Characterizing quantum resourcefulness via group-Fourier decompositions
Pablo Bermejo, Paolo Braccia, Antonio Anna Mele +4
In this work we present a general framework for studying the resourcefulness in pure states for quantum resource theories (QRTs) whose free operations arise from the unitary repres…