71 citations · 118 across the 9 of their papers we have counts for
7 papers · 2 filters
Portfolio Optimization with Digitized-Counterdiabatic Quantum Algorithms
N. N. Hegade, P. Chandarana, K. Paul +3
We consider digitized-counterdiabatic quantum computing as an advanced paradigm to approach quantum advantage for industrial applications in the NISQ era. We apply this concept to…
Quantum Stream Learning
Yongcheng Ding, Xi Chen, Rafael Magdalena-Benedicto +1
The exotic nature of quantum mechanics makes machine learning (ML) be different in the quantum realm compared to classical applications. ML can be used for knowledge discovery usin…
Active Learning for the Optimal Design of Multinomial Classification in Physics
Yongcheng Ding, José D. Martín-Guerrero, Yujing Song +2
Optimal design for model training is a critical topic in machine learning. Active Learning aims at obtaining improved models by querying samples with maximum uncertainty according…
Entangled Quantum Memristors
Shubham Kumar, Francisco A. Cárdenas-López, Narendra N. Hegade +4
We propose the interaction of two quantum memristors via capacitive and inductive coupling in feasible superconducting circuit architectures. In this composed system the input gets…
Digitized-counterdiabatic quantum approximate optimization algorithm
P. Chandarana, N. N. Hegade, K. Paul +4
The quantum approximate optimization algorithm (QAOA) has proved to be an effective classical-quantum algorithm serving multiple purposes, from solving combinatorial optimization p…
Digitized Adiabatic Quantum Factorization
Narendra N. Hegade, Koushik Paul, Francisco Albarrán-Arriagada +2
Quantum integer factorization is a potential quantum computing solution that may revolutionize cryptography. Nevertheless, a scalable and efficient quantum algorithm for noisy inte…