Papers
Live trends in quantum computing research, updated daily from arXiv.
Total Papers
26,835
This Month
452
Today
0
Research Volume
12,429 papers in 12 months (-19% vs prior quarter)
Research Focus Areas
Papers by research theme (12 months). Hover for details.
Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Sample-based training of quantum generative models
Maria Demidik, Cenk Tüysüz, Michele Grossi +1 more·Nov 14, 2025
Quantum computers can efficiently sample from probability distributions that are believed to be classically intractable, providing a foundation for quantum generative modeling. However, practical training of such models remains challenging, as gradie...
Physics-Informed Neural Networks for Gate Design using Quantum Optimal Control
Sofiia Lauten, Matthew Otten·Nov 12, 2025
Implementing quantum gates on quantum computers can require the application of carefully shaped pulses for high-fidelity operations. We explore the use of physics-informed neural networks (PINNs) for quantum optimal control to assess their usefulness...
QIBONN: A Quantum-Inspired Bilevel Optimizer for Neural Networks on Tabular Classification
Pedro Chumpitaz-Flores, My Duong, Ying Mao +1 more·Nov 12, 2025
Hyperparameter optimization (HPO) for neural networks on tabular data is critical to a wide range of applications, yet it remains challenging due to large, non-convex search spaces and the cost of exhaustive tuning. We introduce the Quantum-Inspired ...
A Classical-Quantum Hybrid Architecture for Physics-Informed Neural Networks
Said Lantigua, Gilson Giraldi, Renato Portugal·Nov 10, 2025
In this work, we introduce the Quantum-Classical Hybrid Physics-Informed Neural Network with Multiplicative and Additive Couplings (QPINN-MAC): a novel hybrid architecture that integrates the framework of Physics-Informed Neural Networks (PINNs) with...
Exploring Replica Symmetry Breaking and Topological Collapse in Spin Glasses with Quantum Annealing
Kumar Ghosh·Nov 9, 2025
Replica symmetry breaking (RSB) underlies the complex organization of disordered systems, yet quantitative validation beyond $N \sim 100$ spins has remained computationally challenging. We use quantum annealing to access ground states of the Sherring...
Metabolic quantum limit to the information capacity of magnetoencephalography
E. Gkoudinakis, S. Li, I. K. Kominis·Nov 9, 2025
Magnetoencephalography, the noninvasive measurement of magnetic fields produced by brain activity, utilizes quantum sensors such as superconducting quantum interference devices and atomic magnetometers. Combining the energy resolution limit of magnet...
Quantum optical neural networks using atom-cavity interactions to provide all-optical nonlinearity
Chuanzhou Zhu, Tianyu Wang, Peter L. McMahon +1 more·Nov 9, 2025
Optical neural networks (ONNs) have been developed to enhance processing speed and energy efficiency in machine learning by leveraging optical devices for nonlinear activation and establishing connections among neurons. In this work, we propose a qua...
Representational power of selected neural network quantum states in second quantization
Zhendong Li, Tong Zhao, Bohan Zhang·Nov 7, 2025
Neural network quantum states emerge as a promising tool for solving quantum many-body problems. However, its successes and limitations are still not well-understood in particular for Fermions with complex sign structures. Based on our recent work [J...
QuPCG: Quantum Convolutional Neural Network for Detecting Abnormal Patterns in PCG Signals
Yasaman Torabi, Shahram Shirani, James P. Reilly·Nov 4, 2025
Early identification of abnormal physiological patterns is essential for the timely detection of cardiac disease. This work introduces a hybrid quantum-classical convolutional neural network (QCNN) designed to classify S3 and murmur abnormalities in ...
Towards Continuous-variable Quantum Neural Networks for Biomedical Imaging
Daniel Alejandro Lopez, Oscar Montiel, Oscar Castillo +1 more·Nov 3, 2025
Continuous-variable (CV) quantum computing offers a promising framework for scalable quantum machine learning, leveraging optical systems with infinite-dimensional Hilbert spaces. While discrete-variable (DV) quantum neural networks have shown remark...
HyperNQ: A Hypergraph Neural Network Decoder for Quantum LDPC Codes
Ameya S. Bhave, Navnil Choudhury, Kanad Basu·Nov 3, 2025
Quantum computing requires effective error correction strategies to mitigate noise and decoherence. Quantum Low-Density Parity-Check (QLDPC) codes have emerged as a promising solution for scalable Quantum Error Correction (QEC) applications by suppor...
A Stochastic Quantum Neural Network Model for Ai
Gautier-Edouard Filardo, Thibaut Heckmann·Nov 3, 2025
Artificial intelligence (AI) has drawn significant inspiration from neuroscience to develop artificial neural network (ANN) models. However, these models remain constrained by the Von Neumann architecture and struggle to capture the complexity of the...
Correspondence Between Ising Machines and Neural Networks
Andrew G. Moore·Nov 2, 2025
Computation with the Ising model is central to future computing technologies like quantum annealing, adiabatic quantum computing, and thermodynamic classical computing. Traditionally, computed values have been equated with ground states. This paper g...
QiNN-QJ: A Quantum-inspired Neural Network with Quantum Jump for Multimodal Sentiment Analysis
Yiwei Chen, Kehuan Yan, Yu Pan +1 more·Oct 31, 2025
Quantum theory provides non-classical principles, such as superposition and entanglement, that inspires promising paradigms in machine learning. However, most existing quantum-inspired fusion models rely solely on unitary or unitary-like transformati...
Enabling Fast and Accurate Neutral Atom Readout through Image Denoising
Chaithanya Naik Mude, Linipun Phuttitarn, Satvik Maurya +3 more·Oct 29, 2025
Neutral atom quantum computers hold promise for scaling up to hundreds of thousands or more qubits, but their progress is constrained by slow qubit readout. Parallel measurement of qubit arrays currently takes milliseconds, much longer than the under...
Hybrid Quantum-Classical Recurrent Neural Networks
Wenduan Xu·Oct 29, 2025
We present a hybrid quantum-classical recurrent neural network (QRNN) architecture in which the recurrent core is realized as a parametrized quantum circuit (PQC) controlled by a classical feedforward network. The hidden state is the quantum state of...
Scalable Neural Decoders for Practical Real-Time Quantum Error Correction
Changwon Lee, Tak Hur, Daniel K. Park·Oct 26, 2025
Real-time, scalable, and accurate decoding is a critical component for realizing a fault-tolerant quantum computer. While Transformer-based neural decoders such as \textit{AlphaQubit} have demonstrated high accuracy, the computational complexity of t...
An Analytic Theory of Quantum Imaginary Time Evolution
Min Chen, Bingzhi Zhang, Quntao Zhuang +1 more·Oct 26, 2025
Quantum imaginary time evolution (QITE) algorithm is one of the most promising variational quantum algorithms (VQAs), bridging the current era of Noisy Intermediate-Scale Quantum devices and the future of fully fault-tolerant quantum computing. Altho...
SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
Reda Marzouk, Shahaf Bassan, Guy Katz·Oct 24, 2025
Although Shapley additive explanations (SHAP) can be computed in polynomial time for simple models like decision trees, they unfortunately become NP-hard to compute for more expressive black-box models like neural networks - where generating explanat...
Quantum Neural Network Architectures for Multivariate Time-Series Forecasting
Sandra Ranilla-Cortina, Diego A. Aranda, Jorge Ballesteros +4 more·Oct 24, 2025
In this paper, we address the challenge of multivariate time-series forecasting using quantum machine learning techniques. We introduce adaptation strategies that extend variational quantum circuit models, traditionally limited to univariate data, to...