Optical Spatial Shock Waves in Nonlocal Nonlinear Media

Dispersive shock waves are fascinating phenomena occurring when nonlinearity overwhelms linear effects, such as dispersion and diffraction. Many features of shock waves are still under investigation, as the interplay with noninstantaneity in temporal pulses transmission and nonlocality in spatial beams propagation. Despite the rich and vast literature on nonlinear waves in optical Kerr media, spatial dispersive shock waves in nonlocal materials deserve further attention for their unconventional properties. Indeed, they have been investigated in colloidal matter, chemical physics and biophotonics, for sensing and control of extreme phenomena.
Here we review the last developed theoretical models and recent optical experiments on spatial dispersive shock waves in nonlocal media. Moreover, we discuss observations in novel versatile materials relevant for soft matter and biology.

Giulia Marcucci et al. in arXiv:1907.02823

See also https://giuliasnonlinearworld.wordpress.com/2019/07/08/dswreview/

Super-Duper Ising Machine featured in Physics!

New hardware for solving NP-complete problems is of paramount importance in the modern theory of complexity and computation. In the new era of machine learning and quantum computing, many groups are working for realizing “annealing devices.” Ising machines are a special class that finds the minima of spin-glass Hamiltonians, as Sherrington-Kirkpatrick and Mattis models. Our recent work on a new simple and scalable Ising machine [Phys.Rev.Lett. 122, 213902(2019) and arXiv:1905.11548] has been featured in Physics.

Photonic Ising Machines Go Big: A new optical processor for solving hard optimization problems breaks previous size records and is based on a highly scalable technology”

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Super-Duper Ising Machine by a Single SLM

Quantum and classical physics can be used for mathematical computations that are hard to tackle by conventional electronics. Very recently, optical Ising machines have been demonstrated for computing the minima of spin Hamiltonians, paving the way to new ultra-fast hardware for machine learning. However, the proposed systems are either tricky to scale or involve a limited number of spins. We design and experimentally demonstrate a large-scale optical Ising machine based on a simple setup with a spatial light modulator. By encoding the spin variables in a binary phase modulation of the field, we show that light propagation can be tailored to minimize an Ising Hamiltonian with spin couplings set by input amplitude modulation and a feedback scheme. We realize configurations with thousands of spins that settle in the ground state in a low-temperature ferromagnetic-like phase with all-to-all and tunable pairwise interactions. Our results open the route to classical and quantum photonic Ising machines that exploit light spatial degrees of freedom for parallel processing of a vast number of spins with programmable couplings.

D. Pierangeli, G. Marcucci, C. Conti in ArXiv:1905.11548 and Phys. Rev. Lett. 122, 213902 (2019)

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Quantum Gates by TensorFlow and Reservoir Computing

Novel machine learning computational tools open new perspectives for quantum information systems. Here we adopt the open-source programming library TensorFlowTM to design multi-level quantum gates including a computing reservoir represented by a random unitary matrix. In optics, the reservoir is a disordered medium or a multimodal fiber. We show that trainable operators at the input and the readout enable to realize multi-level gates. We study single and qudit gates, including the
scaling properties of the algorithms with the size of the reservoir.

Quantum Reservoir Computing

G. Marcucci et al. in arXiv:1905.05264

See also