Zobrazeno 1 - 10
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pro vyhledávání: '"A Lvovsky"'
Autor:
Filipovich, Matthew J., Lvovsky, A. I.
TorchOptics is an open-source Python library for differentiable Fourier optics simulations, developed using PyTorch to enable GPU-accelerated tensor computations and automatic differentiation. It provides a comprehensive framework for modeling, analy
Externí odkaz:
http://arxiv.org/abs/2411.18591
Autor:
Manannikov, K. S., Mironova, E. I., Poliakov, A. S., Mikhaylov, A., Ulanov, A. E., Lvovsky, A. I.
We exploit polarization self-rotation in atomic rubidium vapor to observe spontaneous symmetry breaking and bistability of polarization patterns. We pump the vapor cell with horizontally polarized light while the vertical polarization, which is initi
Externí odkaz:
http://arxiv.org/abs/2409.19065
The field of neural quantum states has recently experienced a tremendous progress, making them a competitive tool of computational quantum many-body physics. However, their largest achievements to date mostly concern interacting spin systems, while t
Externí odkaz:
http://arxiv.org/abs/2408.07625
A widely tested approach to overcoming the diffraction limit in microscopy without disturbing the sample relies on substituting widefield sample illumination with a structured light beam. This gives rise to confocal, image-scanning and structured-ill
Externí odkaz:
http://arxiv.org/abs/2405.20979
Robust reinforcement learning agents using high-dimensional observations must be able to identify relevant state features amidst many exogeneous distractors. A representation that captures controllability identifies these state elements by determinin
Externí odkaz:
http://arxiv.org/abs/2403.16369
Neural quantum states have established themselves as a powerful and versatile family of ansatzes for variational Monte Carlo simulations of quantum many-body systems. Of particular prominence are autoregressive neural quantum states (ANQS), which enj
Externí odkaz:
http://arxiv.org/abs/2310.04166
Diffractive optical neural networks (DONNs) have emerged as a promising optical hardware platform for ultra-fast and energy-efficient signal processing for machine learning tasks, particularly in computer vision. Previous experimental demonstrations
Externí odkaz:
http://arxiv.org/abs/2310.03679
Optics is an exciting route for the next generation of computing hardware for machine learning, promising several orders of magnitude enhancement in both computational speed and energy efficiency. However, to reach the full capacity of an optical neu
Externí odkaz:
http://arxiv.org/abs/2308.05226
Publikováno v:
Optica Vol. 10, Issue 9, pp. 1147-1152 (2023)
We investigate Hermite Gaussian Imaging (HGI) -- a novel passive super-resolution technique -- for complex 2D incoherent objects in the sub-Rayleigh regime. The method consists of measuring the field's spatial mode components in the image plane in th
Externí odkaz:
http://arxiv.org/abs/2304.09773
Quantum state tomography is an essential component of modern quantum technology. In application to continuous-variable harmonic-oscilator systems, such as the electromagnetic field, existing tomography methods typically reconstruct the state in discr
Externí odkaz:
http://arxiv.org/abs/2212.07406