Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
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...
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...
An Advanced Hybrid Quantum Tabu Search Approach to Vehicle Routing Problems
James B. Holliday, Eneko Osaba, Khoa Luu·Jan 22, 2025
Quantum computing (QC) is expected to solve incredibly difficult problems, including finding optimal solutions to combinatorial optimization problems. However, to date, QC alone is still far to demonstrate this capability except on small-sized proble...
Solving Constrained Optimization Problems Using Hybrid Qubit-Qumode Quantum Devices
Rishab Dutta, Brandon Allen, Chuzhi Xu +8 more·Jan 20, 2025
Variational Quantum Algorithms (VQAs) provide a promising framework for tackling complex optimization problems on near-term quantum hardware. Here, we demonstrate that hybrid qubit--qumode quantum devices offer an efficient route to solving Quadratic...
Q-RESTORE: Quantum-Driven Framework for Resilient and Equitable Transportation Network Restoration
Daniel Udekwe, Ruimin Ke, J. Lu +1 more·Jan 20, 2025
Efficient and socially equitable restoration of transportation networks post disasters is crucial for community resilience and access to essential services. The ability to rapidly recover critical infrastructure can significantly mitigate the impacts...
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...
Investigating Parameter-Efficiency of Hybrid QuGANs Based on Geometric Properties of Generated Sea Route Graphs
Tobias Rohe, Florian Burger, Michael Kölle +3 more·Jan 15, 2025
The demand for artificially generated data for the development, training and testing of new algorithms is omnipresent. Quantum computing (QC), does offer the hope that its inherent probabilistic functionality can be utilised in this field of generati...
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...
Grid Cost Allocation in Peer-to-Peer Electricity Markets: Benchmarking Classical and Quantum Optimization Approaches
David Bucher, Daniel Porawski, Benedikt Wimmer +4 more·Jan 9, 2025
This paper presents a novel optimization approach for allocating grid operation costs in Peer-to-Peer (P2P) electricity markets using Quantum Computing (QC). We develop a Quadratic Unconstrained Binary Optimization (QUBO) model that matches logical p...
Quantum-Enhanced Conformal Methods for Multi-Output Uncertainty: A Holistic Exploration and Experimental Analysis
Emre Tasar·Jan 7, 2025
In this paper, we propose a unified approach to harness quantum conformal methods for multi-output distributions, with a particular emphasis on two experimental paradigms: (i) a standard 2-qubit circuit scenario producing a four-dimensional outcome d...
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...
Four-qubit variational algorithms in silicon photonics with integrated entangled photon sources
Alessio Baldazzi, M. Sanna, M. Borghi +2 more·Jan 2, 2025
Variational quantum algorithms are hybrid quantum-classical approaches extensively studied for their potential to leverage near-term quantum hardware for computational advantages. In this work, we successfully execute two variational quantum algorith...
Quantum Diffusion Model for Quark and Gluon Jet Generation
Mariia Baidachna, Rey Guadarrama, Gopal Ramesh Dahale +6 more·Dec 30, 2024
Diffusion models have demonstrated remarkable success in image generation, but they are computationally intensive and time-consuming to train. In this paper, we introduce a novel diffusion model that benefits from quantum computing techniques in orde...
Quantum annealing eigensolver as a NISQ era tool for probing strong correlation effects in quantum chemistry
A. Zade, K. Sugisaki, M. Werner +6 more·Dec 29, 2024
The quantum–classical hybrid variational quantum eigensolver (VQE) algorithm is arguably the most popular noisy intermediate-scale quantum (NISQ) era approach to quantum chemistry. We consider the underexplored quantum annealing eigensolver (QAE) alg...
Pilot-Quantum: A Middleware for Quantum-HPC Resource, Workload and Task Management
P. Mantha, Florian J. Kiwit, Nishant Saurabh +2 more·Dec 24, 2024
As quantum hardware advances, integrating quantum processing units (QPUs) into HPC environments and managing diverse infrastructure and software stacks becomes increasingly essential. Pilot-Quantum addresses these challenges as a middleware designed ...
Distribution-Adaptive Dynamic Shot Optimization for Variational Quantum Algorithms
Youngmin Kim, Enhyeok Jang, Hyungseok Kim +6 more·Dec 23, 2024
Variational quantum algorithms (VQAs) have attracted remarkable interest over the past few years because of their potential computational advantages on near-term quantum devices. They leverage a hybrid approach that integrates classical and quantum c...
Quantum Approximate Optimisation Applied to Graph Similarity
Nicholas J. Pritchard·Dec 23, 2024
Quantum computing promises solutions to classically difficult and new-found problems through controlling the subtleties of quantum computing. The Quantum Approximate Optimisation Algorithm (QAOA) is a recently proposed quantum algorithm designed to t...
A Quantum Dual Logarithmic Barrier Method for Linear Optimization
Zeguan Wu, Pouya Sampourmahani, Mohammadhossein Mohammadisiahroudi +1 more·Dec 20, 2024
Quantum computing has the potential to speed up some optimization methods. One can use quantum computers to solve linear systems via quantum linear system algorithms (QLSAs). QLSAs can be used as a subroutine for algorithms that require solving linea...