Quantum computing (QC) is an emerging paradigm with the potential to offer significant
computational advantage over conventional classical computing by exploiting quantum …

Despite its undeniable success, classical machine learning remains a resource-intensive
process. Practical computational efforts for training state-of-the-art models can now only be …

Implementing a gate-based quantum algorithm on an noisy intermediate scale quantum
(NISQ) device has several challenges that arise from the fact that such devices are noisy …

Deep learning achieves unprecedented success involves many fields, whereas the high
requirement of memory and time efficiency tolerance have been the intractable challenges …

As quantum computers are based on the laws of quantum mechanics, they are capable of
solving certain problems faster than their classical counterparts. However, quantum …

This chapter discusses that the development of quantum applications typically incorporates
the development of quantum programs, classical programs, and workflows to orchestrate …

Quantum computers have the potential to solve certain problems faster than classical
computers. However, loading data into a quantum computer is not trivial. To load the data, it …

Quantum computers are expected to surpass the computational capabilities of classical
computers during this decade, and achieve disruptive impact on numerous industry sectors …

Abstract The Harrow-Hassidim-Lloyd (HHL) algorithm is a method to solve the quantum
linear system of equations that may be found at the core of various scientific applications …

A crucial subroutine in quantum computing is to load the classical data of N complex
numbers into the amplitude of a superposed n=⌈ log 2 N⌉-qubit state. It has been proven …