Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications

Y Gujju, A Matsuo, R Raymond - Physical Review Applied, 2024 - APS
The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …

[HTML][HTML] Efficient MPS representations and quantum circuits from the Fourier modes of classical image data

B Jobst, K Shen, CA Riofrío, E Shishenina… - Quantum, 2024 - quantum-journal.org
Abstract Machine learning tasks are an exciting application for quantum computers, as it has
been proven that they can learn certain problems more efficiently than classical ones …

Constant-depth preparation of matrix product states with adaptive quantum circuits

KC Smith, A Khan, BK Clark, SM Girvin… - ar** and Benchmarking Quantum-HPC Applications
N Saurabh, P Mantha, FJ Kiwit, S Jha… - Proceedings of the 2024 …, 2024 - dl.acm.org
With the increasing maturity and scale of quantum hardware and its integration into HPC
systems, there is a need to develop robust techniques for develo**, characterizing, and …

Quantum-Inspired Fluid Simulation of 2D Turbulence with GPU Acceleration

L Hölscher, P Rao, L Müller, J Klepsch… - arxiv preprint arxiv …, 2024 - arxiv.org
Tensor network algorithms can efficiently simulate complex quantum many-body systems by
utilizing knowledge of their structure and entanglement. These methodologies have been …

Quantum Computing for Automotive Applications: From Algorithms to Applications

BMWGQ Team, J Klepsch, JR Finžgar, F Kiwit… - arxiv preprint arxiv …, 2024 - arxiv.org
Quantum computing could impact various industries, with the automotive industry with many
computational challenges, from optimizing supply chains and manufacturing to vehicle …

Tensor Train Multiplication

AA Michailidis, C Fenton, M Kiffner - arxiv preprint arxiv:2410.19747, 2024 - arxiv.org
We present the Tensor Train Multiplication (TTM) algorithm for the elementwise
multiplication of two tensor trains with bond dimension $\chi $. The computational complexity …

The State Preparation of Multivariate Normal Distributions using Tree Tensor Network

H Manabe, Y Sano - arxiv preprint arxiv:2412.12067, 2024 - arxiv.org
The quantum state preparation of probability distributions is an important subroutine for
many quantum algorithms. When embedding $ D $-dimensional multivariate probability …

Representation of Classical Data on Quantum Computers

T Lang, A Heim, K Dremel, D Prjamkov… - arxiv preprint arxiv …, 2024 - arxiv.org
Quantum computing is currently gaining significant attention, not only from the academic
community but also from industry, due to its potential applications across several fields for …