  The Kagome lattice, a captivating lattice structure composed of
interconnected triangles with frustrated magnetic properties, has garnered
considerable interest in condensed matter physics, quantum magnetism, and
quantum computing.The Ansatz optimization provided in this study along with
extensive research on optimisation technique results us with high accuracy.
This study focuses on using multiple ansatz models to create an effective
Variational Quantum Eigensolver (VQE) on the Kagome lattice. By comparing
various optimisation methods and optimising the VQE ansatz models, the main
goal is to estimate ground state attributes with high accuracy. This study
advances quantum computing and advances our knowledge of quantum materials with
complex lattice structures by taking advantage of the distinctive geometric
configuration and features of the Kagome lattice. Aiming to improve the
effectiveness and accuracy of VQE implementations, the study examines how
Ansatz Modelling, quantum effects, and optimization techniques interact in VQE
algorithm. The findings and understandings from this study provide useful
direction for upcoming improvements in quantum algorithms,quantum machine
learning and the investigation of quantum materials on the Kagome Lattice.
