6 papers
Arbitrary-Distance Quantum Error Correction with Gauss's Law for Lattice Gauge Theory
Neel S. Modi, Lento Nagano, Masazumi Honda +2
It has previously been shown by Rajput, Roggero, and Wiebe that Gauss's law constraints can be used to build efficient quantum error-correcting codes (QECCs) that are…
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…
Ground state preparation in -dimensional pure lattice gauge theory via deterministic quantum imaginary time evolution
Minoru Sekiyama, Lento Nagano
In this paper, we apply the deterministic quantum imaginary time evolution (QITE) algorithm to obtain the ground state of a -dimensional pure lattice gauge theo…
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…