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quant-ph2026

Imaginarity as a necessary resource for trainability in QAOA

Syed Muhammad Ali Hassan, Kostas Blekos, Stefan Kühn +2

The quantum approximate optimization algorithm (QAOA) tackles combinatorial problems by tuning a quantum circuit in a classical loop, often guided by gradients. We show that the gr…

quant-ph2025

Warm Start of Variational Quantum Algorithms for Quadratic Unconstrained Binary Optimization Problems

Yahui Chai, Karl Jansen, Stefan Kühn +2

Variational Quantum Eigensolver (VQE) is widely used in near-term hardware. However, their performances remain limited by the poor trainability and are dependent on random paramete…

quant-ph2025

Quantum computing inspired paintings: reinterpreting classical masterpieces

Arianna Crippa, Yahui Chai, Omar Costa Hamido +2

We aim to apply a quantum computing technique to compose artworks. The main idea is to revisit three paintings of different styles and historical periods: ''Narciso'', painted circ…

quant-ph2025

Fermionic wave packet scattering: a quantum computing approach

Yahui Chai, Arianna Crippa, Karl Jansen +4

Quantum computing provides a novel avenue towards simulating dynamical phenomena, and, in particular, scattering processes relevant for exploring the structure of matter. However,…

quant-ph2024

Gaussian boson sampling for binary optimization

Jean Cazalis, Tirth Shah, Yahui Chai +2

Binary optimization is a fundamental area in computational science, with wide-ranging applications from logistics to cryptography, where the tasks are often formulated as Quadratic…

quant-ph2024

Benchmarking Variational Quantum Algorithms for Combinatorial Optimization in Practice

Tim Schwägerl, Yahui Chai, Tobias Hartung +2

Variational quantum algorithms and, in particular, variants of the varational quantum eigensolver have been proposed to address combinatorial optimization (CO) problems. Using only…