ترغب بنشر مسار تعليمي؟ اضغط هنا

Dynamically Emerging Topological Phase Transitions in Nonlinear Interacting Soliton Lattices

236   0   0.0 ( 0 )
 نشر من قبل Hrvoje Buljan
 تاريخ النشر 2021
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

We demonstrate dynamical topological phase transitions in evolving Su-Schrieffer-Heeger (SSH) lattices made of interacting soliton arrays, which are entirely driven by nonlinearity and thereby exemplify emergent nonlinear topological phenomena. The phase transitions occur from topologically trivial-to-nontrivial phase in periodic succession with crossovers from topologically nontrivial-to-trivial regime. The signature of phase transition is gap-closing and re-opening point, where two extended states are pulled from the bands into the gap to become localized topological edge states. Crossovers occur via decoupling of the edge states from the bulk of the lattice.



قيم البحث

اقرأ أيضاً

We investigate numerically and experimentally the influence of coupling disorder on the self-trapping dynamics in nonlinear one-dimensional optical waveguide arrays. The existence of a lower and upper bound of the effective average propagation consta nt allows for a generalized definition of the threshold power for the onset of soliton localization. When compared to perfectly ordered systems, this threshold is found to decrease in the presence of coupling disorder.
We study - experimentally, theoretically, and numerically - nonlinear excitations in lattices of magnets with long-range interactions. We examine breather solutions, which are spatially localized and periodic in time, in a chain with algebraically-de caying interactions. It was established two decades ago [S. Flach, Phys. Rev. E 58, R4116 (1998)] that lattices with long-range interactions can have breather solutions in which the spatial decay of the tails has a crossover from exponential to algebraic decay. In this Letter, we revisit this problem in the setting of a chain of repelling magnets with a mass defect and verify, both numerically and experimentally, the existence of breathers with such a crossover.
180 - A. Tikan , C. Billet , G. El 2017
We present experimental evidence of the universal emergence of the Peregrine soliton predicted in the semi-classical (zero-dispersion) limit of the focusing nonlinear Schr{o}dinger equation [Comm. Pure Appl. Math. {bf 66}, 678 (2012)]. Experiments st udying higher-order soliton propagation in optical fiber use an optical sampling oscilloscope and frequency-resolved optical gating to characterise intensity and phase around the first point of soliton compression and the results show that the properties of the compressed pulse and background pedestal can be interpreted in terms of the Peregrine soliton. Experimental and numerical results reveal that the universal mechanism under study is highly robust and can be observed over a broad range of parameters, and experiments are in very good agreement with numerical simulations.
We present a formal demonstration that light can simultaneously exhibit a superfluid behavior and spatial long-range order when propagating in a photonic crystal with self-focussing nonlinearity. In this way, light presents the distinguishing feature s of matter in a supersolid phase. We show that this supersolid phase provides the stability conditions for nonlinear Bloch waves and, at the same time, permits the existence of topological solitons or defects for the envelope of these waves. We use a condensed matter analysis instead of a standard nonlinear optics approach and provide numerical evidence of these theoretical findings.
We study phase transitions in a lattice of square-arranged driven-dissipative polariton condensates with nearest-neighbour coupling. Simulating the polarization (spin) dynamics of the polariton lattice, we observe regions of qualitatively different s teady-state behaviour which can be identified in time-integrated measurements. The transition between these regions resemble phase transitions ubiquitous in statistical physics, but have inherently non-equilibrium nature and cannot be classified in the conventional way. To overcome this challenge, we use machine learning methods to determine the boundaries separating the regions. We use unsupervised data mining techniques to sketch the regions of phase transition. We then apply learning by confusion, a neural network-based method for learning labels in the dataset, and extract the polaritonic phase diagram. Our work takes a step towards AI-enabled studies of polaritonic systems.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا