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Found 3 papers, 1 papers with code
Dynamical phase transition in quantum neural networks with large depth
Via mapping the Hessian of the training dynamics to a Hamiltonian in the imaginary time, we reveal the nature of the phase transition to be second-order with the exponent $\nu=1$, where scale invariance and closing gap are observed at critical point.
Generative quantum machine learning via denoising diffusion probabilistic models
Inspired by the classical counterpart, we propose the quantum denoising diffusion probabilistic model (QuDDPM) to enable efficiently trainable generative learning of quantum data.
Energy-dependent barren plateau in bosonic variational quantum circuits
Bosonic continuous-variable Variational quantum circuits (VQCs) are crucial for information processing in cavity quantum electrodynamics and optical systems, widely applicable in quantum communication, sensing and error correction.
