[HTML][HTML] The variational quantum eigensolver: a review of methods and best practices
The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …
received significant attention from the research community in recent years. It uses the …
Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
Quantum multiagent actor–critic neural networks for internet-connected multirobot coordination in smart factory management
As one of the latest fields of interest in both academia and industry, quantum computing has
garnered significant attention. Among various topics in quantum computing, variational …
garnered significant attention. Among various topics in quantum computing, variational …
[HTML][HTML] Quantum computing optimization technique for iot platform using modified deep residual approach
Abstract The Internet of Things (IoT) is a global network of millions of devices connected in
wireless that exchange data. Multiple data are aiming to be observed through a single …
wireless that exchange data. Multiple data are aiming to be observed through a single …
Complex quantum networks: a topical review
These are exciting times for quantum physics as new quantum technologies are expected to
soon transform computing at an unprecedented level. Simultaneously network science is …
soon transform computing at an unprecedented level. Simultaneously network science is …
Quantum multi-agent reinforcement learning via variational quantum circuit design
In recent years, quantum computing (QC) has been getting a lot of attention from industry
and academia. Especially, among various QC research topics, variational quantum circuit …
and academia. Especially, among various QC research topics, variational quantum circuit …
Introduction to quantum reinforcement learning: Theory and pennylane-based implementation
The emergence of quantum computing enables for researchers to apply quantum circuit on
many existing studies. Utilizing quantum circuit and quantum differential programming, many …
many existing studies. Utilizing quantum circuit and quantum differential programming, many …
Analysis of quantum machine learning algorithms in noisy channels for classification tasks in the iot extreme environment
SK Satpathy, V Vibhu, BK Behera… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
By 2050, there will be a 50% rise in energy demand, and existing natural and renewable
resources will be under extreme scrutiny. Optimizing current power generation and …
resources will be under extreme scrutiny. Optimizing current power generation and …
A survey on quantum machine learning: Current trends, challenges, opportunities, and the road ahead
K Zaman, A Marchisio, MA Hanif… - arXiv preprint arXiv …, 2023 - arxiv.org
Quantum Computing (QC) claims to improve the efficiency of solving complex problems,
compared to classical computing. When QC is applied to Machine Learning (ML) …
compared to classical computing. When QC is applied to Machine Learning (ML) …
Ecg classification using an optimal temporal convolutional network for remote health monitoring
Increased life expectancy in most countries is a result of continuous improvements at all
levels, starting from medicine and public health services, environmental and personal …
levels, starting from medicine and public health services, environmental and personal …