quant-ph · 2026-09-21 · No. 120

Quantum Physics, 2026-09-21.

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

    Guiding Agents of Quantum Games to Equilibrium using Matrix Exponential Fixed-Point Iteration

    Alireza Habibi, Luis F. Abanto Leon, Setareh Maghsudi

    quant-ph · cs.GT · cs.LG · cs.MA

    In recent years, quantum game theory has gained significant attention as a framework for studying decision-making in multi-agent systems using quantum principles. However, computing equilibrium strategies is challenging because the dimension of the joint Hilbert space grows as the product of the players' local dimensions. In this paper, we consider an extended Gutoski-Watrous (EGW) game in which each player's quantum strategy is represented...

    arxiv.org/abs/2609.21944 · PDF

  2. 02

    Weighted Quantum Signal Processing: Low-Depth Polynomial Approximation with Applications to Kolmogorov-Arnold Networks

    Rohit Sarma Sarkar, Rupayan Bhattacharjee, Elias F. Combarro, Michele Grossi, Lirandë Pira, Carmen G. Almudéver,...

    quant-ph · cs.CC · cs.LG

    Quantum Signal Processing is a powerful quantum framework for generating and approximating univariate polynomials. However, QSP is often limited by circuit-depth bottlenecks and parity constraints on the class of realizable polynomials. In this work, we introduce Weighted Quantum Signal Processing, an extension of QSP in which a weight function is assigned to the central rotation operator. This formulation provides a deeper understanding of...

    arxiv.org/abs/2609.21567 · PDF

  3. 03

    From Trainability Diagnostics to Optimization Claims: Boundaries and Controls in Variational Quantum Optimization

    Pilsung Kang

    quant-ph · cs.LG

    Barren plateau diagnostics characterize whether gradient signal remains available for training, but surviving signal need not translate into successful optimization. We study this trainability--optimization gap at the level of optimizer steps. Treating coefficient-weighted Hamiltonian-term gradients as task-like components, we introduce step-level diagnostics and derive an exact bridge between signed termwise organization, directional...

    arxiv.org/abs/2609.21243 · PDF

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