324 citations · 3k across the 77 of their papers we have counts for
8 papers · 1 filter
Learning crystal field parameters using convolutional neural networks
Noah F. Berthusen, Yuriy Sizyuk, Mathias S. Scheurer +1
We present a deep machine learning algorithm to extract crystal field (CF) Stevens parameters from thermodynamic data of rare-earth magnetic materials. The algorithm employs a two-…
Adaptive Variational Quantum Dynamics Simulations
Yong-Xin Yao, Niladri Gomes, Feng Zhang +4
We propose a general-purpose, self-adaptive approach to construct variational wavefunction ansätze for highly accurate quantum dynamics simulations based on McLachlan's variational…
Discovery of a weak topological insulating state and van Hove singularity in triclinic RhBi2
Kyungchan Lee, Gunnar F. Lange, Lin-Lin Wang +8
Time reversal symmetric (TRS) invariant topological insulators (TIs) fullfil a paradigmatic role in the field of topological materials, standing at the origin of its development. A…
Magnetic crystalline-symmetry-protected axion electrodynamics and field-tunable unpinned Dirac cones in EuIn2As2
S. X. M. Riberolles, T. V. Trevisan, B. Kuthanazhi +12
Knowledge of magnetic symmetry is vital for exploiting nontrivial surface states of magnetic topological materials. EuInAs is an excellent example, as it is predicted t…
Shallow-circuit variational quantum eigensolver based on symmetry-inspired Hilbert space partitioning for quantum chemical calculations
Feng Zhang, Niladri Gomes, Noah F. Berthusen +4
Development of resource-friendly quantum algorithms remains highly desirable for noisy intermediate-scale quantum computing. Based on the variational quantum eigensolver (VQE) with…
Efficient step-merged quantum imaginary time evolution algorithm for quantum chemistry
Niladri Gomes, Feng Zhang, Noah F. Berthusen +4
We develop a resource efficient step-merged quantum imaginary time evolution approach (smQITE) to solve for the ground state of a Hamiltonian on quantum computers. This heuristic m…