A5062827051- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Blockchain Technology Applications and Security
- Advanced Queuing Theory Analysis
- Cloud Computing and Resource Management
- Quantum many-body systems
- Advancements in Semiconductor Devices and Circuit Design
- Matrix Theory and Algorithms
- Quantum and electron transport phenomena
- Neural Networks and Applications
- Caching and Content Delivery
- Machine Learning and ELM
The University of Tokyo
2024
Osaka University
2021-2024
Nara Institute of Science and Technology
2017-2018
To explore the possibilities of a near-term intermediate-scale quantum algorithm and long-term fault-tolerant computing, fast versatile circuit simulator is needed. Here, we introduce Qulacs, for circuits intended research purpose. We show main concepts explain how to use its features via examples, describe numerical techniques speed-up simulation, demonstrate performance with benchmarks.
<p style='text-indent:20px;'>In Bitcoin system, a transaction is given priority value according to its attributes such as the remittance amount and fee, transactions with high priorities are likely be confirmed faster than those low priorities. In this paper, we analyze transaction-confirmation time for system. We model process queueing system batch service, M/<inline-formula><tex-math id="M1">\begin{document}$ \mbox{G}^B $\end{document}</tex-math></inline-formula>/1. consider joint...
Simulating quantum many-body dynamics is important both for fundamental understanding of physics and practical applications information processing. Therefore, classical simulation methods have been developed so far. Specifically, the Trotter-Suzuki decomposition can analyze a highly complex dynamics, if number qubits sufficiently small that main memory store state vector. However, via requires huge steps, each which accesses vector, hence time becomes impractically long. To settle this...
In Bitcoin, it is well known that the confirmation of a transaction issued by user takes longer time than mean block-generation 10 minutes. order to understand stochastic behavior transaction-confirmation process, we consider queueing model with batch service and general input. our model, assume interarrival times are independent identically distributed (i.i.d.), follow distribution, transactions waiting in queue served manner. We define number just before arrival as system state, deriving...
t-stochastic neighbor embedding (t-SNE) is a nonparametric data visualization method in classical machine learning. It maps the from high-dimensional space into low-dimensional space, especially two-dimensional plane, while maintaining relationship or similarities between surrounding points. In t-SNE, initial position of randomly determined, and achieved by moving to minimize cost function. Its variant called parametric t-SNE uses neural networks for this mapping. paper, we propose use...
Abstract Quantum neural networks are expected to be a promising application in near-term quantum computing, but face challenges such as vanishing gradients during optimization and limited expressibility by number of qubits shallow circuits. To mitigate these challenges, an approach using distributed has been proposed make prediction approximating outputs large circuit multiple small However, the approximation requires exponential evaluations. Here, we instead propose distribute partitioned...
Data visualization is important in understanding the characteristics of data that are difficult to see directly. It used visualize loss landscapes and optimization trajectories analyze performance. Popular analysis performed by visualizing a landscape around reached local or global minimum using principal component analysis. However, this depends on variational parameters quantum circuit rather than states, which makes it understand mechanism process through property states. Here, we propose...
Quantum neural networks are expected to be a promising application in near-term quantum computing, but face challenges such as vanishing gradients during optimization and limited expressibility by number of qubits shallow circuits. To mitigate these challenges, an approach using distributed has been proposed make prediction approximating outputs large circuit multiple small However, the approximation requires exponential evaluations. Here, we instead propose distribute partitioned features...