Quantum computing at the quantum advantage threshold: a down-to-business review
AK Fedorov, N Gisin, SM Beloussov… - arXiv preprint arXiv …, 2022 - arxiv.org
It is expected that quantum computers would enable solving various problems that are
beyond the capabilities of the most powerful current supercomputers, which are based on …
beyond the capabilities of the most powerful current supercomputers, which are based on …
Efficiency optimization in quantum computing: balancing thermodynamics and computational performance
We investigate the computational efficiency and thermodynamic cost of the D-Wave
quantum annealer under reverse-annealing with and without pausing. Our demonstration on …
quantum annealer under reverse-annealing with and without pausing. Our demonstration on …
Non-Unitary Quantum Machine Learning
We introduce several novel probabilistic quantum algorithms that overcome the normal
unitary restrictions in quantum machine learning by leveraging the Linear Combination of …
unitary restrictions in quantum machine learning by leveraging the Linear Combination of …
Stochastic optimization algorithms for quantum applications
Hybrid classical quantum optimization methods have become an important tool for efficiently
solving problems in the current generation of noisy intermediate-scale quantum computers …
solving problems in the current generation of noisy intermediate-scale quantum computers …
Quantum-inspired optimization for wavelength assignment
AS Boev, SR Usmanov, AM Semenov… - Frontiers in …, 2023 - frontiersin.org
Problems related to wavelength assignment (WA) in optical communications networks
involve allocating transmission wavelengths for known transmission paths between nodes …
involve allocating transmission wavelengths for known transmission paths between nodes …
Quantum Monte Carlo simulations for financial risk analytics: scenario generation for equity, rate, and credit risk factors
T Matsakos, S Nield - Quantum, 2024 - quantum-journal.org
Monte Carlo (MC) simulations are widely used in financial risk management, from estimating
value-at-risk (VaR) to pricing over-the-counter derivatives. However, they come at a …
value-at-risk (VaR) to pricing over-the-counter derivatives. However, they come at a …
Optimized QUBO formulation methods for quantum computing
D De Santis, S Tirone, S Marmi… - arXiv preprint arXiv …, 2024 - arxiv.org
Several combinatorial optimization problems can be solved with NISQ devices once that a
corresponding quadratic unconstrained binary optimization (QUBO) form is derived. The aim …
corresponding quadratic unconstrained binary optimization (QUBO) form is derived. The aim …
Faster Quantum Algorithms with" Fractional''-Truncated Series
Y Wang, Q Zhao - arXiv preprint arXiv:2402.05595, 2024 - arxiv.org
Quantum algorithms frequently rely on truncated series approximations, necessitating a high
truncation order to achieve even moderate accuracy and consequently resulting in intensive …
truncation order to achieve even moderate accuracy and consequently resulting in intensive …
Artificial Intelligence and Quantum Computing
BW Wirtz - Digital Business and Electronic Commerce: Strategy …, 2024 - Springer
In the eighth chapter, the basics, services, and applications of artificial intelligence are
presented and explained using the AI framework. The opportunities and risks of artificial …
presented and explained using the AI framework. The opportunities and risks of artificial …
Balancing Thermodynamics and Computational Performance
T Smierzchalsk, Z Mzaouali, S Deffner - UMBC Faculty Collection - mdsoar.org
We investigate the computational efficiency and thermodynamic cost of the D-Wave
quantum annealer under reverse-annealing with and without pausing. Our experimental …
quantum annealer under reverse-annealing with and without pausing. Our experimental …