FAU has received a U.S. Air Force T-1A Jayhawk Mixed Reality and 3D Motion flight simulator through an in-kind grant from the U.S. Air Force Office of Scientific Research. The motion-enabled, open-architecture system replicates real flight conditions for high-risk, cost-effective experimentation. It will support cross-disciplinary work in neuroscience, biomedical engineering, cybersecurity, robotics and systems engineering. The simulator provides hands-on training opportunities for students and faculty, fosters collaboration with industry and federal partners, and establishes FAU as a hub for experimentation in next-generation autonomous and AI-enabled systems.

This article investigates the classical limit of the Jarzynski equality in quantum systems, specifically using a nonlinear Jaynes-Cummings model representing a superconducting optical cavity with Kerr nonlinearity.

Key Findings:

Two Distinct Regimes: The study reveals a classical regime at high temperatures and low Kerr intensities where the Jarzynski equality holds, and a quantum regime at low temperatures and high Kerr intensities where it fails.

Quantum Resource Identification: The Kerr nonlinearity term creates quantum behavior that can be identified as a quantum resource for quantum computing advantages in non-zero temperature environments.

Work Operator Definition: The authors use a work operator in the interaction picture and apply Dyson expansion to evaluate the averaged exponentiated work.

Temperature-Nonlinearity Interplay: An intricate relationship between Kerr nonlinearity and temperature governs the quantum-to-classical transition and determines the validity domain of the Jarzynski equality.

Nonclassical Behavior: External work increases the state's nonclassicality, with deviations from Jarzynski equality serving as evidence of quantum behavior.

This article investigates Quantum Fisher Information (QFI) as a diagnostic tool for analyzing parameter sensitivity and entanglement in the Quantum Approximate Optimization Algorithm (QAOA).

Key Findings

Problem Analysis: The study examines Max-Cut problems on cyclic and complete graphs, plus random Ising model instances, comparing RX-only and hybrid RX-RY mixers up to depth p=9 .

QFI Insights: Complete-graph Max-Cut instances generate substantially larger QFI eigenvalues than cyclic ones, exceeding shot-noise scaling (4N) while remaining below the Heisenberg limit (4N2).

Entanglement Effects: The first entangling stage produces the dominant QFI increase, while additional stages yield diminishing returns. Entanglement primarily amplifies cross-parameter correlations rather than individual parameter sensitivity.

Practical Application: The authors propose QFI-Informed Mutation (QIm), a heuristic that adapts mutation probabilities using diagonal QFI entries. QIm outperforms uniform and random-restart baselines, especially for deeper circuits.

The work positions QFI as both a structural probe and practical optimization resource for NISQ-era quantum algorithms.