Related papers: Spin parameter optimization for spin-polarized ext…
NV-diamonds have attracted keen interest for nanoscale sensing and spin manipulation. In particular, the non-equilibrium electron spin polarization after optical excitation of single NV centers has successfully been transferred to nuclear…
We present a joint experimental and theoretical study of spin coherence properties of 39K, 85Rb, 87Rb, and 133Cs atoms trapped in a solid parahydrogen matrix. We use optical pumping to prepare the spin states of the implanted atoms and…
The performance of two recent {\em ab initio} computational thermochemistry schemes, W1 and W2 theory [J.M.L. Martin and G. de Oliveira, J. Chem. Phys. 111, 1843 (1999}], is assessed for an enlarged sample of thermochemical data consisting…
We predict that exploiting spin-orbit coupling in a harmonically trapped spinor quantum gas can lead to scaling of the optimal measurement precision beyond the Heisenberg scaling. We show that quadratic scaling with the number of atoms can…
Optically addressable spins are a promising platform for quantum information science due to their combination of a long-lived qubit with a spin-optical interface for external qubit control and read out. The ability to chemically synthesize…
We present a method for total energy minimizations and molecular dynamics simulations based either on tight-binding or on Kohn-Sham hamiltonians. The method leads to an algorithm whose computational cost scales linearly with the system…
We investigate the transferability of machine learning interatomic potentials across concentration variations in chemically similar systems, using aqueous potassium hydroxide solutions as a case study. Despite containing identical chemical…
This work investigates the optimal control of the variable-exponent subdiffusion, which extends the work [Gunzburger and Wang, {\it SIAM J. Control Optim.} 2019] to the variable-exponent case to account for the multiscale and crossover…
The accuracy of classical force fields (FFs) has been shown to be limited for the simulation of cation-protein systems despite their importance in understanding the processes of life. Improvements can result from optimizing the parameters…
Many crucial scientific problems involve designing novel molecules with desired properties, which can be formulated as a black-box optimization problem over the discrete chemical space. In practice, multiple conflicting objectives and…
Quantifying uncertainty in predictive simulations for real-world problems is of paramount importance - and far from trivial, mainly due to the large number of stochastic parameters and significant computational requirements. Adaptive sparse…
An efficient technique to generate ensembles of spins that are highly polarized by external magnetic fields is the Holy Grail in Nuclear Magnetic Resonance (NMR) spectroscopy. Since spin-half nuclei have steady-state polarization biases…
We study the sensitivity of a collisional single-atom probe for ultracold gases. Inelastic spin-exchange collisions map information about the gas temperature T or external magnetic field B onto the quantum spin-population of single-atom…
We study Transformers through the perspective of optimal control theory, using tools from continuous-time formulations to derive actionable insights into training and architecture design. This framework improves the performance of existing…
This paper presents new lower and upper bounds for the optimal compression of binary prefix codes in terms of the most probable input symbol, where compression efficiency is determined by the nonlinear codeword length objective of…
High degree of electron spin polarization is of crucial importance in operation of spintronic devices. We study the propagation of spin-polarized electrons through a boundary between two n-type semiconductor regions with different doping…
A new unimodal distribution family indexed by the mode and three other parameters is derived from a mixture of a Gumbel distribution for the maximum and a Gumbel distribution for the minimum. Properties of the proposed distribution are…
Owing to the trade-off between the accuracy and efficiency, machine-learning-potentials (MLPs) have been widely applied in the battery materials science, enabling atomic-level dynamics description for various critical processes. However,…
We report on the fabrication and transport characterization of atomically-precise single molecule devices consisting of a magnetic porphyrin covalently wired by graphene nanoribbon electrodes. The tip of a scanning tunneling microscope was…
A theoretical study of spin dynamics in non-relativistic particle beams with interacting angular momenta traversing static, spatially varying magnetic fields is presented. The computational framework evaluates sinusoidal magnetic field…