quant-ph · 2026-07-26 · No. 65

Quantum Physics, 2026-07-26.

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

01 — The papers

3 entries
  1. 01

    Cautious optimism for deep parameterized quantum circuits

    Marie Kempkes, Elies Gil-Fuster, Carlos Bravo-Prieto, Aroosa Ijaz, Alissa Wilms, Jens Eisert, Evert van Nieuwenburg,...

    quant-ph · cs.LG · stat.ML

    A central challenge in quantum machine learning is understanding the scaling behavior of parameterized quantum circuits (PQCs). In particular, it remains unclear how their performance on unseen data changes as the number of trainable parameters increases. Prior works have derived formal generalization guarantees for quantum models, but it is well-known that many such results do not fully characterize generalization behavior in practice. In...

    arxiv.org/abs/2607.21409 · PDF

  2. 02

    Approximate Quantum State Preparation Through Proximal Policy Optimization

    Marco Mordacci, Michele Amoretti

    quant-ph · cs.ET · cs.LG

    In this work, a quantum architecture search framework for approximate quantum state preparation (QSP) is proposed. QSP is a challenging task, since the search space grows exponentially with the number of qubits, making the identification of the optimal circuit non-trivial. To address this problem, deep reinforcement learning is employed through an agent based on proximal policy optimization. The objective of the agent is to identify the best...

    arxiv.org/abs/2607.21121 · PDF

  3. 03

    An Analytically Trained Variational Surrogate for Quantum Phase Estimation on NISQ Hardware

    Mousumi Kundu, Ashish Kumar Patra, Anurag K. S. V., Ruchika Bhat, Sai Shankar P., Alok Shukla, Jaiganesh G

    quant-ph · cs.ET · cs.LG · physics.chem-ph

    Quantum Phase Estimation (QPE) is a foundational algorithm for molecular ground-state energy estimation, but its deep circuit requirements make direct hardware execution impractical on Noisy Intermediate-Scale Quantum (NISQ) devices. We present an analytically grounded variational surrogate framework in which a shallow Variational Quantum Circuit (VQC) is trained to reproduce the QPE measurement distribution without any quantum circuit...

    arxiv.org/abs/2607.20943 · PDF

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