642 citations · 3k across the 51 of their papers we have counts for
53 papers
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…
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…
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…
Background Suppression in Quantum Sensing of Dark Matter via Collective Entangled-State Projection
Shion Chen, Hajime Fukuda, Yutaro Iiyama +5
We show that measuring dark matter signal by projecting quantum sensors in the collective excited state can highly suppress the non-collective noise background, hence improving the…
Fast numerical generation of Lie closure
Yutaro Iiyama
Finding the Lie-algebraic closure of a handful of matrices has important applications in quantum computing and quantum control. For most realistic cases, the closure cannot be dete…
Search for Dark Photon Dark Matter with a Mass around 36.1 μeV Using a Frequency-tunable Cavity Controlled through a Coupled Superconducting Qubit
Kan Nakazono, Shion Chen, Hajime Fukuda +10
We report the results of a search for dark photon dark matter using a cavity that employs a transmon qubit as a frequency tuner. The tuning mechanism utilizes the energy level shif…
The Linear Collider Facility (LCF) at CERN
H. Abramowicz, E. Adli, F. Alharthi +406
In this paper we outline a proposal for a Linear Collider Facility as the next flagship project for CERN. It offers the opportunity for a timely, cost-effective and staged construc…
A Linear Collider Vision for the Future of Particle Physics
H. Abramowicz, E. Adli, F. Alharthi +446
In this paper we review the physics opportunities at linear colliders with a special focus on high centre-of-mass energies and beam polarisation, take a fresh look at the…
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…
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…
Initial-State Dependent Optimization of Controlled Gate Operations with Quantum Computer
Wonho Jang, Koji Terashi, Masahiko Saito +5
There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivity, and coherence times, a quantum circuit optimization is essenti…
Measurement-Free Ultrafast Quantum Error Correction by Using Multi-Controlled Gates in Higher-Dimensional State Space
Toshiaki Inada, Wonho Jang, Yutaro Iiyama +4
Quantum error correction is a crucial step beyond the current noisy-intermediate-scale quantum device towards fault-tolerant quantum computing. However, most of the error correctio…
Event Classification with Multi-step Machine Learning
Masahiko Saito, Tomoe Kishimoto, Yuya Kaneta +6
The usefulness and value of Multi-step Machine Learning (ML), where a task is organized into connected sub-tasks with known intermediate inference goals, as opposed to a single lar…
Quantum Gate Pattern Recognition and Circuit Optimization for Scientific Applications
Wonho Jang, Koji Terashi, Masahiko Saito +7
There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivities, and coherence times, circuit optimization is essential to ma…
An Improvement of Object Detection Performance using Multi-step Machine Learnings
Tomoe Kishimoto, Masahiko Saito, Junichi Tanaka +3
Connecting multiple machine learning models into a pipeline is effective for handling complex problems. By breaking down the problem into steps, each tackled by a specific componen…
Fast convolutional neural networks on FPGAs with hls4ml
Thea Aarrestad, Vladimir Loncar, Nicolò Ghielmetti +17
We introduce an automated tool for deploying ultra low-latency, low-power deep neural networks with convolutional layers on FPGAs. By extending the hls4ml library, we demonstrate a…
Search for new physics in top quark production with additional leptons in proton-proton collisions at 13 TeV using effective field theory
CMS Collaboration
Events containing one or more top quarks produced with additional prompt leptons are used to search for new physics within the framework of an effective field theory (EFT). The dat…
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics
Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta +19
Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering…
Quantum state preparation with multiplicative amplitude transduction
Yutaro Iiyama
Quantum state preparation is an important class of quantum algorithms that is employed as a black-box subroutine in many algorithms, or used by itself to generate arbitrary probabi…
Fast convolutional neural networks for identifying long-lived particles in a high-granularity calorimeter
Juliette Alimena, Yutaro Iiyama, Jan Kieseler
We present a first proof of concept to directly use neural network based pattern recognition to trigger on distinct calorimeter signatures from displaced particles, such as those t…
Dynamo -- Handling Scientific Data Across Sites and Storage Media
Yutaro Iiyama, Benedikt Maier, Daniel Abercrombie +2
Dynamo is a full-stack software solution for scientific data management. Dynamo's architecture is modular, extensible, and customizable, making the software suitable for managing d…
Measurement of the cross section for electroweak production of a Z boson, a photon and two jets in proton-proton collisions at 13 TeV and constraints on anomalous quartic couplings
CMS Collaboration
A measurement is presented of the cross section for electroweak production of a Z boson and a photon in association with two jets (Zjj) in proton-proton collisions. The Z boson…
Search for direct top squark pair production in events with one lepton, jets, and missing transverse momentum at 13 TeV with the CMS experiment
CMS Collaboration
A search for direct top squark pair production is presented. The search is based on proton-proton collision data at a center-of-mass energy of 13 TeV recorded by the CMS experiment…
Measurement of the top quark pair production cross section in dilepton final states containing one lepton in pp collisions at 13 TeV
CMS Collaboration
The cross section of top quark pair production is measured in the final state, where ref…