We study the dynamics of quantum skyrmions under a magnetic field gradient using neural
network quantum states. First, we obtain a quantum skyrmion lattice ground state using …

The flow of electric current through a two-dimensional material in a magnetic field gives rise
to the family of Hall effects. The quantum versions of these effects accommodate robust …

We propose a variational wave function to represent quantum skyrmions as bosonic
operators. The operator faithfully reproduces two fundamental features of quantum …

Recently, large degeneracy based on product eigenstates has been found in spin ladders,
kagome-like lattices, and motif magnetism, connected to spin liquids, anyonic phases, and …

Skyrmions are topological magnetic textures, mostly treated classically, studied extensively
due to their potential spintronics applications due to their topological stability. However, it …

In recent years, machine learning leveraging neural networks has emerged as a potent tool
across various domains, including natural language processing, image recognition, game …

We develop an approach for characterizing non-local quantum correlations in spin systems
with exactly or nearly degenerate ground states. Starting with linearly independent …

Capturing the correlation emerging between constituents of many-body systems accurately
is one of the key challenges for the appropriate description of various systems whose …

Solid materials where quantum mechanical effects dominate the behavior can contribute to
faster and more energy-efficient computers. The road to technological application starts with …

Capturing the correlation emerging between constituents of many-body systems is one of
the key challenges to describe various quantum systems accurately. This thesis discusses …