Quantum Machine Learning: Scope for real-world problems

A Jadhav, A Rasool, M Gyanchandani - Procedia Computer Science, 2023 - Elsevier
Quantum computing with its inherent parallelism provides a quantum advantage over
classical computing. Its potential to offer breakthrough advances in various areas of science …

Quantum algorithms for scientific computing

R Au-Yeung, B Camino, O Rathore… - Reports on Progress in …, 2024 - iopscience.iop.org
Quantum computing promises to provide the next step up in computational power for diverse
application areas. In this review, we examine the science behind the quantum hype, and the …

Quantum algorithms for scientific applications

R Au-Yeung, B Camino, O Rathore… - arxiv preprint arxiv …, 2023 - arxiv.org
Quantum computing promises to provide the next step up in computational power for diverse
application areas. In this review, we examine the science behind the quantum hype and …

Quantum pixel representations and compression for N-dimensional images

MG Amankwah, D Camps, EW Bethel… - Scientific reports, 2022 - nature.com
We introduce a novel and uniform framework for quantum pixel representations that
overarches many of the most popular representations proposed in the recent literature, such …

An efficient quantum partial differential equation solver with chebyshev points

F Oz, O San, K Kara - Scientific Reports, 2023 - nature.com
Differential equations are the foundation of mathematical models representing the universe's
physics. Hence, it is significant to solve partial and ordinary differential equations, such as …

Quantum simulation of nuclear inelastic scattering

W Du, JP Vary, X Zhao, W Zuo - Physical Review A, 2021 - APS
We present a time-dependent quantum algorithm for nuclear inelastic scattering in the time-
dependent basis function on qubits approach. This algorithm aims to quantum simulate a …

Enhanced machine learning using quantum computing

A Jhanwar, MJ Nene - 2021 Second international conference …, 2021 - ieeexplore.ieee.org
In recent times, increasing amount of the data have enriched the decision making using
machine learning. Despite of the growth in the domain of machine learning, the proximity to …

Signal Analysis-Synthesis using the quantum Fourier Transform

A Sharma, G Uehara… - ICASSP 2023-2023 …, 2023 - ieeexplore.ieee.org
This paper presents the development of Quantum Fourier transform (QFT) education tools in
the object-oriented Java-DSP (J-DSP) simulation environment. More specifically, QFT and …

Exploiting OFDM method for quantum communication

AMA Sabaawi, MR Almasaoodi, S Imre - Quantum Information Processing, 2024 - Springer
Orthogonal frequency-division multiplexing (OFDM) is a crucial modulation method used in
contemporary digital communication systems for its significant spectral efficiency, low …

[HTML][HTML] A brief review on mathematical tools applicable to quantum computing for modelling and optimization problems in engineering

Y Mahmoudi, N Zioui, H Belbachir, M Tad**e… - Emerging Science …, 2022 - ijournalse.org
Since its emergence, quantum computing has enabled a wide spectrum of new possibilities
and advantages, including its efficiency in accelerating computational processes …