Quantum Physics · Physics & Astronomy
Quantum Physics
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3,630 papers, from 4 September 2026 to 5 November 2026: 3,630 arXiv preprints.
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Long-horizon autoformalization of a core theorem underlying MIP* = RE
Landmark mathematical formalizations have taken specialist teams years to complete.Quantum Graph Convolutional Networks: Implementation and Trainability Analysis
Graph Neural Networks (GNNs) achieve state-of-the-art performance on graph-structured data, but training and inference on large graphs are often bottlenecked by memory constraints and sparse…Noise-Robust Quantum State Characterization for Remote State Preparation with Deep Learning
Quantum communication underpins secure information processing and scalable quantum networks.TetrisCNN for interpretable detection of phases of matter from experimental quantum simulator data
Detecting phases of matter in general relies on identifying the correct order parameter - a task that remains notoriously difficult for unknown transitions and traditionally is guided by physical…Do Quantum Models Scale Like LLMs?
In this work, we study the neural scaling laws of RydbergGPT, an autoregressive transformer model trained on qubit projective measurement data gathered from interacting Rydberg atom arrays.Fourier Analysis of Parametrized Interactive Quantum Classifiers
Interactive Quantum Classifiers (IQCs) constitute a family of quantum machine learning models inspired by open quantum systems, in which the interaction between a target qubit and an environment is…Variational Quantum Transformer Architecture for Synthetic Language Generation
We propose a compact NISQ-compatible quantum transformer architecture for synthetic QNLP sequence modelling.Learning to Program Adaptive Non-Local Observables for Machine Learning
Quantum neural networks (QNNs) are typically built from variational quantum circuits (VQCs), which are limited by local measurements.Query-Optimal and Gate-Efficient Lindbladian Simulation
We give a quantum algorithm for Lindbladian simulation given a block encoding of the Hamiltonian $H$ and a projected unitary encoding of the stacked jump operator $B=\sum_{k=1}^m \lvert…Securing quantum error correction against misleading advice from AI agents
Can an attacker turn influence over an artificial intelligence (AI) adviser into a harmful quantum error-correction update?Evaluating Verified Autonomy in Quantum Engineering
Reliable quantum engineering is essential for turning quantum phenomena into practical technologies.QiT: Quantum-Inspired Transformer for Visual Recognition Task
Quantum machine learning offers a compelling representational perspective: angle-encoded states inhabit Hilbert spaces in which periodic similarities and interactions can be expressed naturally.QEMScore: How Much Does the Measurement Add to Learned Quantum Error Mitigation?
How much does the noisy measurement add to learned quantum error mitigation?Structure-Preserving Quantum Circuit Architectures for Robot Kinematics
Structured spatial data require quantum encodings that preserve geometric relations, expose measurable observables, and remain implementable on finite-depth hardware.Towards Surrogate Based Dequantization of Quantum Reinforcement Learning
In recent years, the utility of parameterized quantum circuits as function approximators has been widely studied.Certification cost of quantum models: measurement correlation, not parameter count
Reporting the Fisher geometry of a trained variational quantum model is routine; quoting the shot budget that would establish it is not.Parameter-Efficient Quantum NLP for Paraphrase Detection: Performance, Robustness, and Entanglement
Rigorous empirical validation of quantum machine learning on natural language tasks remains scarce.Proving olympiad geometry theorems on a superconducting quantum processor
Automated theorem proving seeks to use computational systems to prove or disprove mathematical and logical statements [1, 2].When is global evolutionary search useful for variational quantum algorithms? A landscape-first study
Variational quantum algorithms recast state preparation as classical nonconvex optimization, but it is often unclear when multistart local search suffices and when population-based global search…GRPO-QM: Target Preserving Exploration for Quantum Tomography
Reward-based learning can alter the very posterior distribution that scientific inference aims to estimate.