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Swarm Learning: A Survey of Concepts, Applications, and Trends
Elham Shammar, Xiaohui Cui, Mohammed A. A. Al-qaness
https://arxiv.org/abs/2405.00556 https:…

Swarm Learning: A Survey of Concepts, Applications, and Trends
Deep learning models have raised privacy and security concerns due to their reliance on large datasets on central servers. As the number of Internet of Things (IoT) devices increases, artificial intelligence (AI) will be crucial for resource management, data processing, and knowledge acquisition. To address those issues, federated learning (FL) has introduced a novel approach to building a versatile, large-scale machine learning framework that operates in a decentralized and hardware-agnostic m…

Swarm Learning: A Survey of Concepts, Applications, and Trends
Elham Shammar, Xiaohui Cui, Mohammed A. A. Al-qaness
https://arxiv.org/abs/2405.00556 https:…

Swarm Learning: A Survey of Concepts, Applications, and Trends
Deep learning models have raised privacy and security concerns due to their reliance on large datasets on central servers. As the number of Internet of Things (IoT) devices increases, artificial intelligence (AI) will be crucial for resource management, data processing, and knowledge acquisition. To address those issues, federated learning (FL) has introduced a novel approach to building a versatile, large-scale machine learning framework that operates in a decentralized and hardware-agnostic m…

This https://arxiv.org/abs/2311.00695 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Predicting Arbitrary State Properties from Single Hamiltonian Quench Dynamics
Analog quantum simulation is an essential routine for quantum computing and plays a crucial role in studying quantum many-body physics. Typically, the quantum evolution of an analog simulator is largely determined by its physical characteristics, lacking the precise control or versatility of quantum gates. This limitation poses challenges in extracting physical properties on analog quantum simulators, an essential step of quantum simulations. To address this issue, we introduce the Hamiltonian …

This https://arxiv.org/abs/2307.06503 has been replaced.
initial toot: https://mastoxiv.page/@ar…

A quantum Monte Carlo algorithm for arbitrary spin-1/2 Hamiltonians
We present a universal parameter-free quantum Monte Carlo (QMC) algorithm designed to simulate arbitrary spin-$1/2$ Hamiltonians. To ensure the convergence of the Markov chain to equilibrium for every conceivable case, we devise a clear and simple automated protocol that produces QMC updates that are provably ergodic and satisfy detailed balance. We demonstrate the applicability and versatility of our method by considering several illustrative examples, including the simulation of the XY model …