  In recent years, there has been an emerging trend of combining two
innovations in computer science and physics to achieve better computation
capability. Exploring the potential of quantum computation to achieve highly
efficient performance in various tasks is a vital development in engineering
and a valuable question in sciences, as it has a significant potential to
provide exponential speedups for technologically complex problems that are
specifically advantageous to quantum computers. However, one key issue in
unleashing this potential is constructing an efficient approach to load
classical data into quantum states that can be executed by quantum computers or
quantum simulators on classical hardware. Therefore, the split-step quantum
walks (SSQW) algorithm was proposed to address this limitation. We facilitate
SSQW to design parameterized quantum circuits (PQC) that can generate
probability distributions and optimize the parameters to achieve the desired
distribution using a variational solver. A practical example of implementing
SSQW using Qiskit has been released as open-source software. Showing its
potential as a promising method for generating desired probability amplitude
distributions highlights the potential application of SSQW in option pricing
through quantum simulation.

Quantum Physics;Pricing of Securities