106 citations · 149 across the 11 of their papers we have counts for
11 papers
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…
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…
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…
Introducing Quantum Information and Computation to a Broader Audience with MOOCs at OpenHPI
Gerhard Hellstern, Jörg Hettel, Bettina Just
Quantum computing is an exciting field with high disruptive potential, but very difficult to access. For this reason, many approaches to teaching quantum computing are being develo…
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…
From Portfolio Optimization to Quantum Blockchain and Security: A Systematic Review of Quantum Computing in Finance
Abha Naik, Esra Yeniaras, Gerhard Hellstern +2
In this paper, we provide an overview of the recent work in the quantum finance realm from various perspectives. The applications in consideration are Portfolio Optimization, Fraud…
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…