4 citations · 4 across the 5 of their papers we have counts for
7 papers · 1 filter
Equivalence between exponential concentration in quantum machine learning kernels and barren plateaus in variational algorithms
Pranav Kairon, Jonas Jäger, Jonas Jäger +1
We formalize a rigorous connection between barren plateaus (BP) in variational quantum algorithms and exponential concentration of quantum kernels for machine learning. Our results…
Advantage of discrete variable representation in variational quantum eigensolvers for vibrational energy calculations
K. Asnaashari, D. Bondarenko, R. V. Krems
While quantum computing algorithms have been widely applied for electronic structure calculations, applications to molecular dynamics remain scarce. Complex and varied landscapes o…
Echoes in a parametrically perturbed Kerr-nonlinear oscillator
Yun-Wen Mao, Ilia Tutunnikov, Roman V. Krems +1
We study classical and quantum echoes in a Kerr oscillator driven by a frequency-controlling pulsed perturbation. We consider dynamical response to the perturbation for a single co…
Modern applications of machine learning in quantum sciences
Anna Dawid, Julian Arnold, Borja Requena +26
In this book, we provide a comprehensive introduction to the most recent advances in the application of machine learning methods in quantum sciences. We cover the use of deep learn…
Molecular representations of quantum circuits for quantum machine learning
Elham Torabian, Roman V. Krems
We establish an isomorphism between quantum circuits and a subspace of polyatomic molecules, which suggests that molecules can be used as descriptors of quantum circuits for quantu…
Lattice stitching by eigenvector continuation for Holstein polaron
Elham Torabian, Roman V. Krems
Simulations of lattice particle - phonon systems are fundamentally restricted by the exponential growth of the number of quantum states with the lattice size. Here, we demonstrate…