1 citations · 2 across the 8 of their papers we have counts for
10 papers
Reducing QUBO Complexity in Drone Delivery Through Classical Feasibility Preprocessing
Silvie Illésová, Vojtěch Novák, Martin Beseda
Drone-delivery planning combines routing decisions with operational constraints such as payload capacity and limited onboard energy, resulting in combinatorial optimization problem…
Optimization Geometry of QAOA and Variational Quantum Algorithms
Vojtěch Novák, Ivan Zelinka, Silvie Illésová +2
Variational quantum algorithms turn choices of Hamiltonian, ansatz, and parameterization into a classical nonconvex optimization problem. We study how this objective function can b…
Adaptive Differential Evolution and Multistart Search for Noisy QAOA Optimization
Vojtěch Novák, Ivan Zelinka, Swagatam Das +1
We benchmark classical optimization of a fixed low-depth Quantum Approximate Optimization Algorithm (QAOA) ansatz across four cost-Hamiltonian families at , , and .…
Optimization Landscape Geometry in VQE for Frustrated Quantum Spin Models
Vojtěch Novák, Ivan Zelinka, Swagatam Das +1
We benchmark eight classical optimizers for exact-statevector VQE calculations on a controlled hierarchy of frustrated spin models, ranging from a diagonal Ising glass to transvers…
Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors
Vojtěch Novák, Ivan Zelinka, Lenka Přibylová +3
This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analyzing clinical data with 14\%…
A Longitudinal Analysis of the CEC Single-Objective Competitions (2010-2024) and Implications for Variational Quantum Optimization
Vojtěch Novák, Tomáš Bezděk, Ivan Zelinka +2
This paper provides a historical analysis of the IEEE CEC Single Objective Optimization competition results (2010-2024). We analyze how benchmark functions shaped winning algorithm…
A Kernel-Based Approach for Accurate Steady-State Detection in Performance Time Series
Martin Beseda, Vittorio Cortellessa, Daniele Di Pompeo +2
This paper addresses the challenge of accurately detecting the transition from the warmup phase to the steady state in performance metric time series, which is a critical step for…
Benchmarking gate-based quantum devices via certification of qubit von Neumann measurements
Paulina Lewandowska, Martin Beseda
We present an updated version of PyQBench, an open-source Python library designed for benchmarking gate-based quantum computers, with a focus on certifying qubit von Neumann measur…
Numerical Optimization Strategies for the Variational Hamiltonian Ansatz in Noisy Quantum Environments
S. Illésová, V. Novák, T. Bezděk +2
The prevalence of variational methods in near-term quantum computing makes optimizer choice critical, yet selection is frequently intuition-based. We therefore present a systematic…
A Preliminary Investigation on the Usage of Quantum Approximate Optimization Algorithms for Test Case Selection
Antonio Trovato, Martin Beseda, Dario Di Nucci
Regression testing is key in verifying that software works correctly after changes. However, running the entire regression test suite can be impractical and expensive, especially f…