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Researchers used a Bose-Einstein condensate as a mini universe to experimentally demonstrate that time can emerge from entropy exchange, supporting the theory of relational or emergent time in quantum physics.
Proposes Quantum Flow Matching (QFM), a generative model that uses spin Wigner functions and functional flow matching to learn and generate multi-qubit quantum distributions, accurately capturing physical properties like purity and entanglement entropy.
CARVE-Q introduces a quantum-AI search layer for certified interactive driving repair, using quantum minimum finding on repair lattices while keeping safety authority classical. It provides structured certificates for vetoed maneuvers, achieving 100% right-of-way respect and blame consistency on INTERACTION replay scenarios.
Researchers at ETH Zurich have demonstrated a method for generating 'perfect randomness' using entangled superconducting qubits, a breakthrough with implications for cryptography and secure communications.
This paper introduces Quiver, a paradigm that enriches classical machine learning models with quantum-inspired features derived from the quantum Fisher information matrix, demonstrating improvements on molecule property prediction and jet flavor classification benchmarks.
The article explores the concept of quantum jamming, a process that could break quantum cryptographic protocols, and discusses efforts to understand causality at a deeper level to ensure security even beyond quantum mechanics.
A survey on quantum adversarial machine learning, covering attacks, defenses, and theoretical underpinnings.