1 citations · 1 across the 3 of their papers we have counts for
5 papers
All-valid-state HOBO encoding for constrained combinatorial optimization on NISQ devices
Juncheng Wang, Takumi Kanezashi, Daisuke Tsukayama +5
Continued advancements in quantum computing have stimulated growing interest in translating quantum technologies into real-world applications. Consequently, the investigation of pr…
Efficient time-series prediction on NISQ devices via time-delayed quantum extreme learning machine
Mio Kawanabe, Saud Cindrak, Kathy Ludge +3
We proposed a time-delayed quantum extreme learning machine (TD-QELM) for efficient time-series prediction on noisy intermediate-scale quantum (NISQ) devices. By encoding multiple…
Utility of NISQ devices: optimizing experimental parameters for the fabrication of Au atomic junction using gate-based quantum computers
Takumi Kanezashi, Daisuke Tsukayama, Jun-ichi Shirakashi +2
Feedback-controlled electromigration (FCE) enables precise regulation of atomic migration by carefully optimizing multiple experimental parameters. However, manually fine-tuning th…
LLM-Guided Ansätze Design for Quantum Circuit Born Machines in Financial Generative Modeling
Yaswitha Gujju, Romain Harang, Tetsuo Shibuya
Quantum generative modeling using quantum circuit Born machines (QCBMs) shows promising potential for practical quantum advantage. However, discovering ansätze that are both expre…
QuProFS: An Evolutionary Training-free Approach to Efficient Quantum Feature Map Search
Yaswitha Gujju, Romain Harang, Chao Li +2
The quest for effective quantum feature maps for data encoding presents significant challenges, particularly due to the flat training landscapes and lengthy training processes asso…