Quantum science and technology are poised to revolutionize industries worldwide, and nations across the globe are investing heavily in advancing quantum computing. Leading this charge is IBM Quantum, which has made significant strides in transforming quantum computation from theoretical constructs to practical realities by building the world's first quantum computers. Through cloud access, IBM has democratized quantum computing, enabling anyone with an internet connection to explore this cutting-edge technology. This perspective paper offers a global perspective on the potential applications of quantum computing across various domains. From healthcare and life sciences to chemistry, materials science, and agriculture, IBM, in collaboration with its Academic and Industrial partners, is conducting groundbreaking research to harness the power of quantum computing for solving complex problems. This article also provides an overview of the learning opportunities IBM offers to users at all levels, as well as efforts to develop middleware solutions that ensure a seamless user experience on quantum platforms. By shedding light on the current state of art in quantum computing and its potential impact, this paper aims to inspire researchers worldwide to contribute to this transformative field, accelerating the global momentum towards a quantum-powered future.

Line spectra is an important phenomenon in many signal processing application including radar, sonar, communications, and spectroscopy. The estimation of a frequency component in a noisy sinusoidal signal for source localization and Doppler estimation is often required for practical systems such as cooperative communication, and vehicular communications. Here, we propose a quantum framework for the line spectrum estimation in the presence of observation noise and quantum error. We propose quantum algorithm, namely quantum line spectrum estimation (QLSE) to estimate the frequency of a sinusoidal signal from a quantum measurement probability histogram. Considering complex sinusoidal waveform, we show how to estimate single tone and multiple tone signals from the quantum circuit. We demonstrate a fully quantum computational model implemented on an IBM quantum machine and discuss quantum complexity advantage and error performance of the proposed algorithm in comparison with classical method. The experimental study shows promising result for super-resolution frequency estimation application with the proposed QLSE algorithm. The numerical results are given to support the proposition in the quantum regime. This manuscript is submitted to a journal with adequate modifications. The copyright may be transferred without notice, and this preprint may not be available after publication. 

This work is peer-reviewed and published in IEEE Transactions on Quantum Engineering. The readers are requested to go through the latest version and cite the work to this: https://ieeexplore.ieee.org/abstract/document/10304328

This work is peer-reviewed and published in Nature Scientific report. The readers are requested to go through the latest version and cite the work to this link: https://www.nature.com/articles/s41598-024-59851-5