quant-ph · 2026-07-13 · No. 52

Quantum Physics, 2026-07-13.

6 new papers in quant-ph. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

6 entries
  1. 01

    Lean-QIT: Towards a Formal Infrastructure for Quantum Information Theory

    Chengkai Zhu, Ziao Tang, Guocheng Zhen, Yimeng Cao, Yusheng Zhao, Ranyiliu Chen, Xuanqiang Zhao, Lei Zhang, Xin Wang

    quant-ph · cs.AI

    Quantum information theory (QIT) characterizes the capabilities and fundamental limits of quantum information processing, underpinning quantum communication, computation, and error correction. Formalizing its coding theorems requires connecting finite-block protocols, analytic inequalities, and asymptotic limits within a unified machine-checked framework. Existing developments, however, lack a reusable operational layer that defines codes,...

    arxiv.org/abs/2607.09632 · PDF

  2. 02

    When Routes Run Out: Adversarial Co-Learning and Explainable Robustness in Quantum Repeater Networks

    Brennan Bell, Inti Gabriel Mendoza Estrada, Andreas Trügler, Paul Erker

    quant-ph · cs.AI · cs.CR

    We study an adversarial bandit problem for entanglement-based quantum-network routing over a modest graph corpus. Alice selects an end-to-end repeater route for an Ekert-91 protocol (E91) representing her move, while Eve selects an attack surface, either edge intercept--resend or repeater memory degradation. Payoffs are drawn from cached SeQUeNCe-simulated E91 transcripts, and Alice accepts a turn when the finite-sample statistic violates the...

    arxiv.org/abs/2607.09378 · PDF

  3. 03

    Hybrid Quantum and Classical Workload Management with Graph-based Scheduling

    Vanessa Sochat, Daniel Milroy

    quant-ph · cs.DC

    High Performance Computing (HPC) centers are expanding to encompass resources that extend beyond traditional computing. By extending resources to quantum computing, hybrid quantum-classical workflows tackle complex optimization problems that have never before been possible. However, integrating quantum processing units (QPUs) into cloud-native and scientific workload managers presents a unique orchestration challenge: remote quantum devices...

    arxiv.org/abs/2607.09151 · PDF

  4. 04

    Quantum-Enhanced Synthetic Data Generation Using Quantum Circuit Born Machines for Imbalanced Tabular Learning

    Tanapol Nuatho, Narisorn Sangnakara, Prapong Prechaprapranwong, Rajchawit Sarochawikasit

    quant-ph · cs.LG

    Data scarcity and class imbalance are persistent challenges in machine learning that degrade model generalization and introduce predictive bias. We present a hybrid quantum-classical framework for synthetic data generation using a Quantum Circuit Born Machine (QCBM) to address these limitations. The proposed approach exploits quantum mechanical properties -- superposition and entanglement -- within a parameterized variational quantum circuit...

    arxiv.org/abs/2607.09113 · PDF

  5. 05

    Quantum Logic as the Logic of Contexts

    Haruki Emori, Atsushi Iriki, Andrei Khrennikov, Kazunori Kondo

    quant-ph · cs.AI · math.LO · q-bio.NC

    Quantum logic is usually presented as a non-classical departure from ordinary reasoning forced on us by quantum mechanics, with classical logic kept as the secure starting point. We argue for the opposite order of explanation in a finite and fully computable setting. The free orthomodular lattice on two generators has ninety-six elements, the direct product of a six-element non-distributive factor and a sixteen-element Boolean factor. Reading...

    arxiv.org/abs/2607.09032 · PDF

  6. 06

    A Novel Parallel QCNN Architecture with Efficient Classical Simulability

    Lawrence Nguyen, Hiu Yung Wong

    quant-ph · cs.AI

    This work presents a study of an implementation of a novel Quantum Convolutional Neural Network (QCNN) for binary classification of images from the Modified National Institute of Standards and Technology (MNIST) dataset. Using a novel architecture inspired by previous QCNN and classical convolutional neural network (CNN) implementations, we use a hierarchical partitioning approach to implement a QCNN circuit that can be approximated and...

    arxiv.org/abs/2607.08928 · PDF

This edition is part of The Daily Abstract — quant-ph archive. Subscribe to receive these in your inbox each morning, automatically translated to Spanish, with reply-to-PDF: arxivdaily.ignorelist.com.

Colophon Set in Georgia, with system sans for interface chrome and a monospaced stack for code and paper identifiers. Sole accent: amber #D99C5E. Built and served on an always-free VM. The masthead is set 14% letterspaced because newspapers do that and it works.