Papers
Live trends in quantum computing research, updated daily from arXiv.
Total Papers
26,974
This Month
563
Today
0
Research Volume
12,533 papers in 12 months (-16% vs prior quarter)
Research Focus Areas
Papers by research theme (12 months). Hover for details.
Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
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...
Morphological computational capacity of Physarum polycephalum
Suyash Bajpai, Aviva Lucas-DeMott, Nirosha J Murugan +2 more·Oct 22, 2025
While computational capacity limits of the universe and carbon-based life have been estimated, a stricter bound for aneural organisms has not been established. Physarum polycephalum, a unicellular, multinucleated amoeba, is capable of complex problem...
An integrated neural wavefunction solver for spinful Fermi systems
Alexander Avdoshkin, Max Geier, Liang Fu·Oct 21, 2025
We present an approach to solving the ground state of Fermi systems that contain spin or other discrete degrees of freedom in addition to continuous coordinates. The approach combines a Markov chain Monte Carlo sampling for energy estimation that we ...
QINNs: Quantum-Informed Neural Networks
Aritra Bal, Markus Klute, Benedikt Maier +3 more·Oct 20, 2025
Classical deep neural networks can learn rich multi-particle correlations in collider data, but their inductive biases are rarely anchored in physics structure. We propose quantum-informed neural networks (QINNs), a general framework that brings quan...
A Variance-Based Convergence Criterion in Neural Variational Monte Carlo for Quantum Systems
Huan-Chen Shi, Er-Liang Cui, Dan Zhou·Oct 20, 2025
The optimization of neural wave functions in variational Monte Carlo crucially relies on a robust convergence criterion. While the energy variance is theoretically a definitive measure, its practical application as a primary convergence criterion has...
Near-Equilibrium Propagation training in nonlinear wave systems
Karol Sajnok, Michał Matuszewski·Oct 17, 2025
Backpropagation learning algorithm, the workhorse of modern artificial intelligence, is notoriously difficult to implement in physical neural networks. Equilibrium Propagation (EP) is an alternative with comparable efficiency and strong potential for...
IQNN-CS: Interpretable Quantum Neural Network for Credit Scoring
Abdul Samad Khan, Nouhaila Innan, Aeysha Khalique +1 more·Oct 16, 2025
Credit scoring is a high-stakes task in financial services, where model decisions directly impact individuals' access to credit and are subject to strict regulatory scrutiny. While Quantum Machine Learning (QML) offers new computational capabilities,...
Adiabatic transport of neural network quantum states
Matija Medvidović, Alev Orfi, Juan Carrasquilla +1 more·Oct 16, 2025
Variational methods have offered controllable and powerful tools for capturing many-body quantum physics for decades. The recent introduction of expressive neural network quantum states has enabled the accurate representation of a broad class of comp...
Quantum machine learning and quantum-inspired methods applied to computational fluid dynamics: a short review
Cesar A. Amaral, Vinícius L. Oliveira, Juan P. L. C. Salazar +1 more·Oct 15, 2025
Computational Fluid Dynamics (CFD) is central to science and engineering, but faces severe scalability challenges, especially in high-dimensional, multiscale, and turbulent regimes. Traditional numerical methods often become prohibitively expensive u...
Hybrid Boson Sampling-Neural Network Architecture for Enhanced Classification
Mohammad Sharifian, Abolfazl Bayat·Oct 15, 2025
Demonstration of quantum advantage for classical machine learning tasks remains a central goal for quantum technologies and artificial intelligence. Two major bottlenecks to this goal are the high dimensionality of practical datasets and limited perf...
Bayes or Heisenberg: Who(se) Rules?
Volker Tresp, Hang Li, Federico Harjes +1 more·Oct 14, 2025
Although quantum systems are generally described by quantum state vectors, we show that in certain cases their measurement processes can be reformulated as probabilistic equations expressed in terms of probabilistic state vectors. These probabilistic...
Neural Guided Sampling for Quantum Circuit Optimization
Bodo Rosenhahn, Tobias J. Osborne, Christoph Hirche·Oct 14, 2025
Translating a general quantum circuit on a specific hardware topology with a reduced set of available gates, also known as transpilation, comes with a substantial increase in the length of the equivalent circuit. Due to decoherence, the quality of th...
Snapshot renormalization group for quantum matter
Laurin Brunner, Tobias Wiener, Tiago Mendes-Santos +2 more·Oct 14, 2025
Recent advances in quantum simulator experiments enable unprecedented access to quantum many-body states through snapshot measurements of individual many-body configurations. Here, we introduce an exact renormalization group (RG) transformation that ...
Hybrid Vision Transformer and Quantum Convolutional Neural Network for Image Classification
Mingzhu Wang, Yun Shang·Oct 14, 2025
Quantum machine learning (QML) holds promise for computational advantage, yet progress on real-world tasks is hindered by classical preprocessing and noisy devices. We introduce ViT-QCNN-FT, a hybrid framework that integrates a fine-tuned Vision Tran...