activity
20202026
most citedQuantum Computing for High-Energy Physics: State of the Art and Challenges. Summary of the QC4HEP Working Group

211 citations · 309 across the 13 of their papers we have counts for

collaborators

15 papers

hep-lat2026

Trapped-ion quantum simulation of (1+1)D SU(2) lattice gauge theory via loop-string-hadron formulation

Toshiaki Kaji, Jesse R. Stryker, Yutaro Iiyama +4

We present a quantum simulation of the SU(2) lattice gauge theory in 1+1 dimensions with one flavor of fermions, performed using the trapped-ion Quantinuum System Model H2. This wo…

hep-lat2026

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…

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…

hep-lat2026

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…

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-ph2024

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…

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-ph2023★ 211 cited

Quantum Computing for High-Energy Physics: State of the Art and Challenges. Summary of the QC4HEP Working Group

Alberto Di Meglio, Karl Jansen, Ivano Tavernelli +43

Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage…

quant-ph2023★ 1 cited

Quantum data learning for quantum simulations in high-energy physics

Lento Nagano, Alexander Miessen, Tamiya Onodera +3

Quantum machine learning with parametrised quantum circuits has attracted significant attention over the past years as an early application for the era of noisy quantum processors.…

hep-ph2023★ 26 cited

Quench dynamics of the Schwinger model via variational quantum algorithms

Lento Nagano, Aniruddha Bapat, Christian W. Bauer

We investigate the real-time dynamics of the -dimensional U(1) gauge theory known as the Schwinger model via variational quantum algorithms. Specifically, we simulate quench…

quant-ph2022

Resolution enhancement of one-dimensional molecular wavefunctions in plane-wave basis via quantum machine learning

Rei Sakuma, Yutaro Iiyama, Lento Nagano +2

Super-resolution is a machine-learning technique in image processing which generates high-resolution images from low-resolution images. Inspired by this approach, we perform a nume…

hep-lat2021★ 52 cited

Classically emulated digital quantum simulation for screening and confinement in the Schwinger model with a topological term

Masazumi Honda, Etsuko Itou, Yuta Kikuchi +2

We perform digital quantum simulation, using a classical simulator, to study screening and confinement in a gauge theory with a topological term, focusing on ()-dimensional qu…

hep-th2021★ 10 cited

A Note on Commutation Relation in Conformal Field Theory

Lento Nagano, Seiji Terashima

In this note, we explicitly compute the vacuum expectation value of the commutator of scalar fields in a d-dimensional conformal field theory on the cylinder. We find from explicit…

hep-th2020★ 9 cited

Janus interface entropy and Calabi's diastasis in four-dimensional superconformal field theories

Kanato Goto, Lento Nagano, Tatsuma Nishioka +1

We study the entropy associated with the Janus interface in a 4 superconformal field theory. With the entropy defined as the interface contribution to an entangl…