Controlling Synchronization in Large Laser Networks

Nixon, Micha; Fridman, Moti; Ronen, Eitan; Friesem, Asher A.; Davidson, Nir; Kanter, Ido

doi:10.1103/physrevlett.108.214101

Cited by 86 publications

(61 citation statements)

References 25 publications

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“…For GCD>1, e.g. τ d /τ c =4/3 resulting in two loops of 8and 6thus GCD=2, the optical phase synchronization is close to zero as expected [13].…”

supporting

confidence: 76%

“…The later setup was already well examined in the literature [11,13], however, without a systematic examination of the quantitative level of phase locking as a function of heterogeneity. Next we quantitatively show how the optical phase and chaotic intensity synchronization depend on the tenable global quantity -network homogeneity.…”

mentioning

confidence: 99%

“…In similar fashion, delayed self feedback is introduced by mirror R 2 (in green) and a focusing lens f 2 that are posited along the other arm of the 50/50 beam splitter. With the angular orientation of R 2 aligned appropriately, self feedback to only one of the lasers is achieved with a delay time of τ d =4f 2 /c [13]. The self and mutual coupling delay times were selected to be a few ns and were much longer than the coherence time of 10 ps for each individual laser, so the coupling signal arrives long after the phase memory is lost.…”

mentioning

confidence: 99%

“…For homogeneous laser networks, where all coupling delay times are identical, the interplay between network topology and mode of synchronization is identical for phase and chaotic intensity [7,11,13]. Based on the theory of stochastic matrices, one can show that the mixing of information by the optical feedback leads to a number of synchronized clusters governed by the greatest common divisor (GCD) of the delay loops composing the network [14].…”

mentioning

confidence: 99%

“…Hence, most of our knowledge of large network synchronization of chaotic lasers is based on simulations. Optical phase synchronization on the other hand, was recently experimentally demonstrated for a homogeneous time delayed coupled network having up to 16 lasers as well as for heterogeneous laser networks [13].…”

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confidence: 99%

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Coupled lasers: phase versus chaos synchronization

et al. 2013

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“…For GCD>1, e.g. τ d /τ c =4/3 resulting in two loops of 8and 6thus GCD=2, the optical phase synchronization is close to zero as expected [13].…”

supporting

confidence: 76%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Coupled lasers: phase versus chaos synchronization

et al. 2013

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Coherent Combining for High‐Power Kerr Combs

Kim

Okawachi

Jang

et al. 2023

Laser & Photonics Reviews

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Kerr frequency combs enable the miniaturization of comb sources for applications such as data communications and spectroscopy. However, due to the high field confinement and effective nonlinearity, Kerr combs typically operate with low output comb powers. While nonsolitonic Kerr combs operating in the normal group velocity dispersion (GVD) regime can access high pump‐to‐comb conversion efficiencies and relatively flat spectral profiles, many frequency comb applications require even higher comb‐line powers that are otherwise fundamentally unattainable without the use of optical amplifiers. A high efficient coherent beam combining of Kerr combs is demonstrated via on‐chip synchronization to greatly enhanced comb‐line powers. Two normal GVD Kerr combs are coherently combined for a 2.9 dB increase in comb power compared to a single comb while maintaining a high total pump‐to‐comb conversion efficiency of 26%. Lastly, it is shown that via spectral engineering of two normal GVD combs, it should be possible to significantly increase the spectral flatness of a combined comb. This platform enables fully integrated systems with powers that can readily exceed that of an individual comb system by more than an order of magnitude.

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Dynamics of Complex Autonomous Boolean Networks

Rosin

2015

Springer Theses

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Network science provides a powerful framework for analyzing complex systems found in physics, biology, and social sciences. One way of studying the dynamics of networks is to engineer and measure them in the laboratory, which is particularly difficult with established approaches. In this thesis, I approach this problem using a hardware device with time-delay elements executing Boolean functions that can be connected to autonomous Boolean networks with chaotic, periodic, or excitable dynamics. I am able to make scientific discoveries for networks with each of these three different node dynamics, driven by the large flexibility and the non-ideal effects of the experiment complemented by analytical and numerical investigations.Using network realizations with periodic Boolean oscillators, I study socalled chimera states and find that they can disappear and reappear-the resurgence of chimera states. I measure the transient times of chimera states and find a power-law relationship between the average transient time and the phase space volume with an exponent of κ = −0.28 ± 0.10.I also study cluster synchronization in networks of coupled excitable systems. In these artificial neural networks, I find a breakdown of an established theoretical tool when the heterogeneity of the link time delays is greater than the neural refractory period. This phenomenon is used to derive a control scheme for spiking patterns generated by neural networks.Experimental implementations of these systems take advantage of the fast timescale of electronic logic gates, large scalability, and low price. These properties make the system attractive for technological applications, as I demonstrate by realizing a physical random number generator that has an ultra-high bitrate of 12.8 Gbit/s and a silicon neuron that is a thousand times faster than the fastest preceding silicon neuron. For the study of coupled oscillator networks, I develop a phase-locked loop allowing for multiple drivers that may be advantageous for clock synchronization. Instead of the common topologies with one driver per oscillator, it allows for heavily connected clock networks to increase robustness against failure.iii Z U S A M M E N FA S S U N G • D. P. Rosin, D. Rontani, and D. J. Gauthier. Ultrafast physical generation of random numbers using hybrid Boolean networks. Phys. Rev. E 87, 040902(R) (2013).• D. P. Rosin, D. Rontani, D. J. Gauthier, and E. Schöll. Excitability in autonomous Boolean networks. Europhys. Lett. 100, 30003 (2012).• D. P. Rosin, D. Rontani, D. J. Gauthier, and E. Schöll. Experiments on autonomous Boolean networks. Chaos 23, 025102 (2013).• D. P. Rosin, D. Rontani, and D. J. Gauthier. Synchronization of coupled Boolean phase oscillators. Phys. Rev. E 89, 042907 (2014).• D. P. Rosin, D. Rontani, E. Schöll, and D. J. Gauthier. Transient scaling and resurgence of chimera states in coupled Boolean phase oscillators.

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Controlling Synchronization in Large Laser Networks

Cited by 86 publications

References 25 publications

Coupled lasers: phase versus chaos synchronization

Coupled lasers: phase versus chaos synchronization

Coherent Combining for High‐Power Kerr Combs

Dynamics of Complex Autonomous Boolean Networks

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