A key challenge in the effort to simulate today's quantum computing devices is the ability to
learn and encode the complex correlations that occur between qubits. Emerging …

Large language models, like transformers, have recently demonstrated immense powers in
text and image generation. This success is driven by the ability to capture long-range …

Understanding the dynamics of large quantum systems is hindered by the curse of
dimensionality. Statistical learning offers new possibilities in this regime by neural-network …

Digital quantum simulation of many-body dynamics relies on Trotterization to decompose
the target time evolution into elementary quantum gates operating at a fixed equidistant time …

Recent advancements in quantum hardware and classical computing simulations have
significantly enhanced the accessibility of quantum system data, leading to an increased …

We build upon recent work on using Machine Learning models to estimate Hamiltonian
parameters using continuous weak measurement of qubits as input. We consider two …