14 papers
Quantum Gaussian processes for prediction of channel observations
Jonas Jäger, Yaroslav Khmelnitskiy, Paolo Braccia +4
Given a set of input states, we consider the task of predicting the expectation value of a Pauli observable at the output of an unknown quantum evolution, using only a limited numb…
Particle-preserving fermionic shadows with mode-independent sample complexity
Maxwell West, M. Cerezo, Martin Larocca
We consider the problem of learning expectation values of particle-preserving operators with respect to an unknown -particle -mode fermionic state via classical shadows. Our…
Exponentially many initializations to avoid barren plateaus
Ankit Kulshrestha, Ricard Puig, Diego GarcÃa-MartÃn +4
Barren plateaus are stated as an average-case phenomenon: pick an ansatz, initialize it naively, and concentration follows. This has led to the common view that a potential cure fo…
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.…
Quantum Circuit Pre-Synthesis: Learning Local Edits to Reduce -count
Daniele Lizzio Bosco, Lukasz Cincio, Giuseppe Serra +1
Compiling quantum circuits into Clifford+ gates is a central task for fault-tolerant quantum computing using stabilizer codes. In the near term, gates will dominate the cost…