5 papers · 1 filter
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…
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…
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…
Quantum convolutional neural networks for jet images classification
Hala Elhag, Tobias Hartung, Karl Jansen +3
Recently, interest in quantum computing has significantly increased, driven by its potential advantages over classical techniques. Quantum machine learning (QML) exemplifies one of…
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…