no code implementations • 20 Nov 2023 • Akira Sone, Akira Tanji, Naoki Yamamoto
Motivated by the great success of classical generative models in machine learning, enthusiastic exploration of their quantum version has recently started.
no code implementations • 20 Jun 2022 • C. Huerta Alderete, Max Hunter Gordon, Frederic Sauvage, Akira Sone, Andrew T. Sornborger, Patrick J. Coles, M. Cerezo
We show that, for a general class of unitary families of encoding, $\mathcal{R}(\theta)$ can be fully characterized by only measuring the system response at $2n+1$ parameters.
no code implementations • 6 Oct 2020 • Akira Sone, M. Cerezo, Jacob L. Beckey, Patrick J. Coles
In this work, we present a lower bound on the quantum Fisher information (QFI) which is efficiently computable on near-term quantum devices.
Quantum Physics Mathematical Physics Mathematical Physics Data Analysis, Statistics and Probability
no code implementations • 28 Jul 2020 • Samson Wang, Enrico Fontana, M. Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, Patrick J. Coles
Specifically, for the local Pauli noise considered, we prove that the gradient vanishes exponentially in the number of qubits $n$ if the depth of the ansatz grows linearly with $n$.
no code implementations • 2 Jan 2020 • M. Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, Patrick J. Coles
Variational quantum algorithms (VQAs) optimize the parameters $\vec{\theta}$ of a parametrized quantum circuit $V(\vec{\theta})$ to minimize a cost function $C$.