36 citations · 107 across the 12 of their papers we have counts for
13 papers
Effectiveness of Hybrid Optimization Method for Quantum Annealing Machines
Shuta Kikuchi, Nozomu Togawa, Shu Tanaka
To enhance the performance of quantum annealing machines, several methods have been proposed to reduce the number of spins by fixing spin values through preprocessing. We proposed…
Compressed space quantum approximate optimization algorithm for constrained combinatorial optimization
Tatsuhiko Shirai, Nozomu Togawa
Combinatorial optimization is a promising area for achieving quantum speedup. Quantum approximate optimization algorithm (QAOA) is designed to search for low-energy states of the I…
Toward Practical Benchmarks of Ising Machines: A Case Study on the Quadratic Knapsack Problem
Kentaro Ohno, Tatsuhiko Shirai, Nozomu Togawa
Combinatorial optimization has wide applications from industry to natural science. Ising machines bring an emerging computing paradigm for efficiently solving a combinatorial optim…
Post-processing variationally scheduled quantum algorithm for constrained combinatorial optimization problems
Tatsuhiko Shirai, Nozomu Togawa
We propose a post-processing variationally scheduled quantum algorithm (pVSQA) for solving constrained combinatorial optimization problems (COPs). COPs are typically transformed in…
Linearizing Binary Optimization Problems Using Variable Posets for Ising Machines
Kentaro Ohno, Nozomu Togawa
Ising machines are next-generation computers expected to efficiently sample near-optimal solutions of combinatorial optimization problems. Combinatorial optimization problems are m…
Hybrid Optimization Method Using Simulated-Annealing-Based Ising Machine and Quantum Annealer
Shuta Kikuchi, Nozomu Togawa, Shu Tanaka
Ising machines have the potential to realize fast and highly accurate solvers for combinatorial optimization problems. They are classified based on their internal algorithms. Examp…
Dynamical process of a bit-width reduced Ising model with simulated annealing
Shuta Kikuchi, Nozomu Togawa, Shu Tanaka
Ising machines have attracted attention as efficient solvers for combinatorial optimization problems, which are formulated as ground-state (lowest-energy) search problems of the Is…
Fast Hyperparameter Tuning for Ising Machines
Matthieu Parizy, Norihiro Kakuko, Nozomu Togawa
In this paper, we propose a novel technique to accelerate Ising machines hyperparameter tuning. Firstly, we define Ising machine performance and explain the goal of hyperparameter…
Towards optimization of photonic-crystal surface-emitting lasers via quantum annealing
Takuya Inoue, Yuya Seki, Shu Tanaka +3
Photonic-crystal surface-emitting lasers (PCSELs), which utilize a two-dimensional (2D) optical resonance inside a photonic crystal for lasing, feature various outstanding function…
QuDASH: Quantum-inspired rate adaptation approach for DASH video streaming
Bo Wei, Hang Song, Makoto Nakamura +3
Internet traffic is dramatically increasing with the development of network technologies and video streaming traffic accounts for large amount within the total traffic, which revea…
R-HTDetector: Robust Hardware-Trojan Detection Based on Adversarial Training
Kento Hasegawa, Seira Hidano, Kohei Nozawa +2
Hardware Trojans (HTs) have become a serious problem, and extermination of them is strongly required for enhancing the security and safety of integrated circuits. An effective solu…
Node-wise Hardware Trojan Detection Based on Graph Learning
Kento Hasegawa, Kazuki Yamashita, Seira Hidano +3
In the fourth industrial revolution, securing the protection of the supply chain has become an ever-growing concern. One such cyber threat is a hardware Trojan (HT), a malicious mo…
Guiding Principle for Minor-Embedding in Simulated-Annealing-Based Ising Machines
Tatsuhiko Shirai, Shu Tanaka, Nozomu Togawa
We propose a novel type of minor-embedding (ME) in simulated-annealing-based Ising machines. The Ising machines can solve combinatorial optimization problems. Many combinatorial op…