6 papers
Constrained Quantum Optimization via Iterative Warm-Start XY-Mixers
David Bucher, Maximilian Janetschek, Michael Poppel +3
The Quantum Approximate Optimization Algorithm (QAOA) is a leading hybrid heuristic for combinatorial optimization, but efficiently handling hard constraints remains a significant…
Architecture Shape Governs QNN Trainability: Jacobian Null Space Growth and Parameter Efficiency
Michael Poppel, David Bucher, Maximilian Zorn +5
Variational quantum circuits with angle encoding implement truncated Fourier series, and architectures arranging qubits with encoding layers each -- sharing encoding budget…
Mitigating Exponential Mixed Frequency Growth through Frequency Selection
Michael Poppel, David Bucher, Maximilian Zorn +4
Angle encoding has emerged as a popular feature map for embedding classical data into quantum models, naturally generating truncated Fourier series with universal function approxim…
Efficient QAOA Architecture for Solving Multi-Constrained Optimization Problems
David Bucher, Daniel Porawski, Maximilian Janetschek +4
This paper proposes a novel combination of constraint encoding methods for the Quantum Approximate Optimization Ansatz (QAOA). Real-world optimization problems typically consist of…
IF-QAOA: A Penalty-Free Approach to Accelerating Constrained Quantum Optimization
David Bucher, Jonas Stein, Sebastian Feld +1
Traditional methods for handling (inequality) constraints in the Quantum Approximate Optimization Ansatz (QAOA) typically rely on penalty terms and slack variables, which increase…
CUAOA: A Novel CUDA-Accelerated Simulation Framework for the QAOA
Jonas Stein, Jonas Blenninger, David Bucher +4
The Quantum Approximate Optimization Algorithm (QAOA) is a prominent quantum algorithm designed to find approximate solutions to combinatorial optimization problems, which are chal…