The scientific progress is significantly transforming contemporary society with the introduction and widespread application of technologies like artificial intelligence and quantum computing. Despite their profound impact, these technologies necessitate en ...
This thesis uses femtosecond laser spectroscopy in studying strong correlation in condensed matters that are pertinent to future technology: a wide bandgap perovskite and a quantum material, with the employment of ultrafast time-resolved spectroscopy in th ...
Entanglement forging based variational algorithms leverage the bipartition of quantum systems for addressing ground-state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basis stat ...
Plasmonic photochemistry has a large potential to replace energy-intensive chemical processes with low-temperature, low-pressure light-driven chemical reactions. Plasmonic nanostructures have emerged as promising photocatalysts with exceptional and tunable ...
The multiflavor Mott insulators, whose local Hilbert space consists of multiple degrees of freedom, occur widely in both quantum materials and ultracold atom systems. This Comment recommends the review article by Chen and Wu that is, to the author's knowle ...
Topological Weyl semimetals represent a novel class of nontrivial materials, where band crossings with linear dispersions take place at generic momenta across reciprocal space. These crossings give rise to low -energy properties akin to those of Weyl fermi ...
Molecular junctions represent a fascinating frontier in the realm of nanotechnology and are one of the
smallest optoelectronic devices possible, consisting of individual molecules or a group of molecules
that serve as the active element sandwiched between ...
This thesis investigates the magnetic properties of single atoms and molecules adsorbed on thin magnesium oxide decoupling layers, grown on a silver single crystal. To address these systems experimentally, we use a low temperature scanning tunneling micros ...
Extensive machine-learning-assisted research has been dedicated to predicting band gaps for perovskites, driven by their immense potential in photovoltaics. Yet, the effectiveness is often hampered by the lack of high-quality band gap data sets, particular ...
We introduce a model-independent method for the efficient simulation of low-entropy systems, whose dynamics can be accurately described with a limited number of states. Our method leverages the time-dependent variational principle to efficiently integrate ...
Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we d ...
Quantum sensors and qubits are usually two-level systems (TLS), the quantum analogues of classical bits assuming binary values 0 or 1. They are useful to the extent to which superpositions of 0 and 1 persist despite a noisy environment. The standard prescr ...
