5 papers
Variational Quantum Conditional Boltzmann Machines for Time-Series Forecasting: Architectures, Symmetric Hyperparameter Evaluation, and a Nonlinear Benchmark
Gerhard Hellstern, Danyal Maheshwari, Martin Zaefferer +2
In this study, we developed and evaluated four conditional energy-based forecasting architectures: a classical Gaussian-Bernoulli CRBM, a hybrid quantum-classical QCRBM, a full-reg…
Extrapolation method to optimize linear-ramp QAOA parameters: Evaluation of QAOA runtime scaling
Vanessa Dehn, Martin Zaefferer, Gerhard Hellstern +3
The Quantum Approximate Optimization Algorithm (QAOA) has been suggested as a promising candidate for the solution of combinatorial optimization problems. Yet, whether - or under w…
Learning Temporal Patterns in Financial Time Series: A Comparative Study of Quantum LSTM and Quantum Reservoir Computing
Danyal Maheshwari, Gerhard Hellstern, Martin Zaefferer +2
This study explores quantum and classical hybrid architectures for financial time-series fore casting, focusing on Quantum Long Short-Term Memory (QLSTM) networks and Quantum Reser…
Quantum Workshop for IT-Professionals
Bettina Just, Jörg Hettel, Gerhard Hellstern
Quantum computing is gaining strategic relevance beyond research-driven industries. However, many companies lack the expertise to evaluate its potential for real-world applications…
Quantum Leap in Finance: Economic Advantages, Security, and Post-Quantum Readiness
Gerhard Hellstern, Esra Yeniaras
This paper provides an in-depth review of the evolving role of quantum computing in the financial sector, emphasizing both its computational potential and cybersecurity implication…