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20242026
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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

Barren-plateau free variational quantum simulation of Z2 lattice gauge theories

Fariha Azad, Matteo Inajetovic, Stefan Kühn +1

In this work, we design a variational quantum eigensolver (VQE) suitable for investigating ground states and static string breaking in a lattice gauge theory (LGT).…

quant-ph2025

Resource-Efficient Simulations of Particle Scattering on a Digital Quantum Computer

Yahui Chai, Joe Gibbs, Vincent R. Pascuzzi +4

We develop and demonstrate methods for simulating the scattering of particle wave packets in the interacting Thirring model on digital quantum computers, with hardware implementati…

quant-ph2025

Flow-Based Sampling for Entanglement Entropy and the Machine Learning of Defects

Andrea Bulgarelli, Elia Cellini, Karl Jansen +5

We introduce a novel technique to numerically calculate Rényi entanglement entropies in lattice quantum field theory using generative models. We describe how flow-based approaches…

quant-ph2025

Adaptive Observation Cost Control for Variational Quantum Eigensolvers

Christopher J. Anders, Kim A. Nicoli, Bingting Wu +6

The objective to be minimized in the variational quantum eigensolver (VQE) has a restricted form, which allows a specialized sequential minimal optimization (SMO) that requires onl…