Papers
Live trends in quantum computing research, updated daily from arXiv.
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12,932 papers in 12 months (-5% vs prior quarter)
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
QNN-QRL: Quantum Neural Network Integrated with Quantum Reinforcement Learning for Quantum Key Distribution
B. Behera, S. Al-kuwari, Ahmed Farouk·Jan 30, 2025
Quantum key distribution (QKD) has emerged as a critical component of secure communication in the quantum era, ensuring information-theoretic security. Despite its potential, there are issues in optimizing key generation rates, enhancing security, an...
Hybrid Quantum Neural Networks with Amplitude Encoding: Advancing Recovery Rate Predictions
Ying Chen, Paul Griffin, Paolo Recchia +2 more·Jan 27, 2025
Recovery rate prediction plays a pivotal role in bond investment strategies by enhancing risk assessment, optimizing portfolio allocation, improving pricing accuracy, and supporting effective credit risk management. However, accurate forecasting rema...
Neural Quantum Embedding via Deterministic Quantum Computation with One Qubit.
Hong-fang Liu, Tak Hur, Shitao Zhang +12 more·Jan 26, 2025
Quantum computing is expected to provide an exponential speedup in machine learning. However, optimizing the data loading process, commonly referred to as "quantum data embedding," to maximize classification performance remains a critical challenge. ...
Tensor-Based Binary Graph Encoding for Variational Quantum Classifiers
Shiwen An, Konstantinos Slavakis·Jan 24, 2025
Quantum computing has been a prominent research area for decades, inspiring transformative fields such as quantum simulation, quantum teleportation, and quantum machine learning (QML), which are undergoing rapid development. Within QML, hybrid classi...
End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml
G. D. Guglielmo, Botao Du, Javier Campos +10 more·Jan 24, 2025
In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, wh...
QuFeX: Quantum feature extraction module for hybrid quantum-classical deep neural networks
Naman Jain, Amir Kalev·Jan 22, 2025
We introduce Quantum Feature Extraction (QuFeX), a novel quantum machine learning module. The proposed module enables feature extraction in a reduced-dimensional space, significantly decreasing the number of parallel evaluations required in typical q...
Improving thermal state preparation of Sachdev–Ye–Kitaev model with reinforcement learning on quantum hardware
Akash Kundu·Jan 20, 2025
The Sachdev–Ye–Kitaev (SYK) model, known for its strong quantum correlations and chaotic behavior, serves as a key platform for quantum gravity studies. However, variationally preparing thermal states on near-term quantum processors for large systems...
Hybrid-Quantum Neural Architecture Search for The Proximal Policy Optimization Algorithm
Moustafa Zada·Jan 18, 2025
Recent studies in quantum machine learning advocated the use of hybrid models to assist with the limitations of the currently existing Noisy Intermediate Scale Quantum (NISQ) devices, but what was missing from most of them was the explanations and in...
Comprehensive Survey of QML: From Data Analysis to Algorithmic Advancements
Sahil Tomar, Rajeshwar Tripathi, Sandeep Kumar·Jan 16, 2025
Quantum Machine Learning represents a paradigm shift at the intersection of Quantum Computing and Machine Learning, leveraging quantum phenomena such as superposition, entanglement, and quantum parallelism to address the limitations of classical appr...
Robust Hybrid Classical-Quantum Transfer Learning Model for Text Classification Using GPT-Neo 125M with LoRA & SMOTE Enhancement
Santanam Wishal·Jan 12, 2025
This research introduces a hybrid classical-quantum framework for text classification, integrating GPT-Neo 125M with Low-Rank Adaptation (LoRA) and Synthetic Minority Over-sampling Technique (SMOTE) using quantum computing backends. While the GPT-Neo...
Q-MAML: Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms
Junyong Lee, Jeihee Cho, Shiho Kim·Jan 10, 2025
In the Noisy Intermediate-Scale Quantum (NISQ) era, using variational quantum algorithms (VQAs) to solve optimization problems has become a key application. However, these algorithms face significant challenges, such as choosing an effective initial ...
Physics-inspired Machine Learning for Quantum Error Mitigation
Xiao-Yue Xu, Xin Xue, Tianyu Chen +5 more·Jan 8, 2025
Noise is a major obstacle in current quantum computing, and Machine Learning for Quantum Error Mitigation (ML-QEM) promises to address this challenge, enhancing computational accuracy while reducing the sampling overheads of standard QEM methods. Yet...
Quantum neural compressive sensing for ghost imaging
Xinliang Zhai, Tailong Xiao, Jingzheng Huang +2 more·Jan 7, 2025
Demonstrating the utility of quantum algorithms is a long-standing challenge, where quantum machine learning becomes one of the most promising candidate that can be resorted to. In this study, we investigate a quantum neural compressive sensing algor...
A Distributed Hybrid Quantum Convolutional Neural Network for Medical Image Classification
Yangyang Li, Zhengya Qi, Yuelin Li +3 more·Jan 7, 2025
Medical images are characterized by intricate and complex features, requiring interpretation by physicians with medical knowledge and experience. Classical neural networks can reduce the workload of physicians, but can only handle these complex featu...
Noise-Mitigated Variational Quantum Eigensolver with Pre-training and Zero-Noise Extrapolation
Wanqi Sun, Jungang Xu, Chenghua Duan·Jan 3, 2025
As a hybrid quantum-classical algorithm, the variational quantum eigensolver is widely applied in quantum chemistry simulations, especially in computing the electronic structure of complex molecular systems. However, on existing noisy intermediate-sc...
Comparative Performance Analysis of Quantum Machine Learning Architectures for Credit Card Fraud Detection
Mansour El Alami, Nouhaila Innan, Muhammad Shafique +1 more·Dec 27, 2024
As financial fraud becomes increasingly complex, effective detection methods are essential. Quantum Machine Learning (QML) introduces certain capabilities that may enhance both accuracy and efficiency in this area. This study examines how different q...
Quantum-Inspired Weight-Constrained Neural Network: Reducing Variable Numbers by 100x Compared to Standard Neural Networks
Shaozhi Li, M Sabbir Salek, Mashrur Chowdhury +1 more·Dec 26, 2024
Although quantum machine learning has shown great promise, the practical application of quantum computers remains constrained in the noisy intermediate-scale quantum era. To take advantage of quantum machine learning, we investigate the underlying ma...
SentiQNF: A Novel Approach to Sentiment Analysis Using Quantum Algorithms and Neuro-Fuzzy Systems
Kshitij Dave, Nouhaila Innan, B. Behera +3 more·Dec 17, 2024
Sentiment analysis is an essential component of natural language processing, used to analyze sentiments, attitudes, and emotional tones in various contexts. It provides valuable insights into public opinion, customer feedback, and user experiences. R...
QNN-VRCS: A Quantum Neural Network for Vehicle Road Cooperation Systems
Nouhaila Innan, B. Behera, S. Al-kuwari +1 more·Dec 17, 2024
The escalating complexity of urban transportation systems, exacerbated by factors such as traffic congestion, diverse transportation modalities, and shifting commuter preferences, necessitates the development of more sophisticated analytical framewor...
Learning interactions between Rydberg atoms
Olivier Simard, Anna Dawid, Joseph Tindall +3 more·Dec 16, 2024
Quantum simulators have the potential to solve quantum many-body problems that are beyond the reach of classical computers, especially when they feature long-range entanglement. To fulfill their prospects, quantum simulators must be fully controllabl...