106 citations · 149 across the 11 of their papers we have counts for
8 papers · 1 filter
Quantum Computing Solution of the Bethe-Salpeter Equation for Relativistic Scalar Bound States via Tensor-Network VQE
Gerhard Hellstern
We present a gate-based quantum computing solution of the homogeneous Bethe-Salpeter equation (hBSE) for the bound state of two massive relativistic scalar particles interacting vi…
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…
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 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…
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…
Quantum computer based Feature Selection in Machine Learning
Gerhard Hellstern, Vanessa Dehn, Martin Zaefferer
The problem of selecting an appropriate number of features in supervised learning problems is investigated in this paper. Starting with common methods in machine learning, we treat…
Heart Disease Detection using Quantum Computing and Partitioned Random Forest Methods
Hanif Heidari, Gerhard Hellstern, Murugappan Murugappan
Heart disease morbidity and mortality rates are increasing, which has a negative impact on public health and the global economy. Early detection of heart disease reduces the incide…
Benchmarking the performance of portfolio optimization with QAOA
Sebastian Brandhofer, Daniel Braun, Vanessa Dehn +6
We present a detailed study of portfolio optimization using different versions of the quantum approximate optimization algorithm (QAOA). For a given list of assets, the portfolio o…