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Extrapolation of polaron properties to low phonon frequencies by Bayesian machine learning
Pranav Kairon, John Sous, Mona Berciu +1
Feasibility of accurate quantum calculations is often restricted by the dimensionality of the truncated Hilbert space required for the numerical computations. The present work demo…
Efficient interpolation of molecular properties across chemical compound space with low-dimensional descriptors
Yun-Wen Mao, Roman V. Krems
We demonstrate accurate data-starved models of molecular properties for interpolation in chemical compound spaces with low-dimensional descriptors. Our starting point is based on t…
General classification of qubit encodings in ultracold diatomic molecules
K. Asnaashari, R. V. Krems, T. V. Tscherbul
Owing to their rich internal structure and significant long-range interactions, ultracold molecules have been widely explored as carriers of quantum information. Several different…
Neural network Gaussian processes as efficient models of potential energy surfaces for polyatomic molecules
Jun Dai, Roman V. Krems
Kernel models of potential energy surfaces (PES) for polyatomic molecules are often restricted by a specific choice of the kernel function. This can be avoided by optimizing the co…
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…