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quant-ph2026

Symmetries and overparametrization properties of Hamiltonian variational ansatzes for the d lattice gauge theory

Kanta Yamanaka, Takanori Daiza, Katsumi Imaizumi +4

We perform detailed studies of five Hamiltonian variational ansatzes (HVA) based on the Hamiltonian of the d lattice gauge theory. The ansatzes are designed t…

quant-ph2026

Double Descent in Quantum Kernel Ridge Regression

Kensuke Kamisoyama, Lento Nagano, Koji Terashi

Various classical machine learning models, including linear regression, kernel methods, and deep neural networks, exhibit double descent, in which the test risk peaks near the inte…

quant-ph2026

Comprehensive Numerical Studies of Barren Plateau and Overparametrization in Variational Quantum Algorithm

Himuro Hashimoto, Akio Nakabayashi, Lento Nagano +4

The variational quantum algorithm (VQA) with a parametrized quantum circuit is widely applicable to near-term quantum computing, but its fundamental issues that limit optimization…

quant-ph2025

Quantum decision trees with information entropy

Zhelun Li, Koji Terashi

We present a classification algorithm for quantum states, inspired by decision-tree methods. To adapt the decision-tree framework to the probabilistic nature of quantum measurement…

quant-ph2024

Enforcing exact permutation and rotational symmetries in the application of quantum neural network on point cloud datasets

Zhelun Li, Lento Nagano, Koji Terashi

Recent developments in the field of quantum machine learning have promoted the idea of incorporating physical symmetries in the structure of quantum circuits. A crucial milestone i…

quant-ph2024

Qudit-Generalization of the Qubit Echo and Its Application to a Qutrit-Based Toffoli Gate

Yutaro Iiyama, Wonho Jang, Naoki Kanazawa +3

The fidelity of certain gates on noisy quantum computers may be improved when they are implemented using more than two levels of the involved transmons. The main impediments to ach…