20 papers
Ambient unitaries don't enable shallow group designs
Maxwell West, M. Cerezo, Martin Larocca
Characterising the efficiency with which designs over various subsets of the unitary group may be constructed is an important goal of quantum information theory. While it is now kn…
Quantum machine learning models for graphs
Frédéric Sauvage, Pranav Kalidindi, Frederic Rapp +1
Geometric Machine Learning (GML) successes have been achieved through the thorough study and design of new equivariant neural networks. In comparison, geometric quantum machine lea…
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…
Classical shadows over symmetric spaces
Rebecca Chang, Maureen Krumtünger, Martin Larocca +1
Efficiently learning expectation values of unknown quantum states via classical shadows has become an important primitive in both theoretical and experimental aspects of quantum co…
Classical shadows with arbitrary group representations
Maxwell West, Frederic Sauvage, Aniruddha Sen +6
Classical shadows (CS) has recently emerged as an important framework to efficiently predict properties of an unknown quantum state. A common strategy in CS protocols is to paramet…
The commutant of fermionic Gaussian unitaries
Paolo Braccia, N. L. Diaz, Martin Larocca +2
In this work, we characterize the -th order commutants of fermionic Gaussian unitaries and of their particle-preserving subgroup acting on fermionic modes. These commutants…