Multifractality of light in photonic arrays based on algebraic number theory

Anno: 2020

Autori: Sgrignuoli F., Gorsky S., Britton WA., Riboli F., Dal Negro L.

Affiliazione autori: Boston Univ, Dept Elect & Comp Engn, 8 St Marys St, Boston, MA 02215 USA; Boston Univ, Photon Ctr, 8 St Marys St, Boston, MA 02215 USA; Boston Univ, Div Mat Sci & Engn, 15 St Marys St, Brookline, MA 02446 USA; CNR, Inst Nazl Ott, Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy; European Lab Nonlinear Spect, Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy;‎ Boston Univ, Dept Phys, 590 Commonwealth Ave, Boston, MA 02215 USA

Abstract: Many natural patterns and shapes, such as meandering coastlines, clouds, or turbulent flows, exhibit a characteristic complexity that is mathematically described by fractal geometry. Here, we extend the reach of fractal concepts in photonics by experimentally demonstrating multifractality of light in arrays of dielectric nanoparticles that are based on fundamental structures of algebraic number theory. Specifically, we engineered novel deterministic photonic platforms based on the aperiodic distributions of primes and irreducible elements in complex quadratic and quaternions rings. Our findings stimulate fundamental questions on the nature of transport and localization of wave excitations in deterministic media with multi-scale fluctuations beyond what is possible in traditional fractal systems. Moreover, our approach establishes structure-property relationships that can readily be transferred to planar semiconductor electronics and to artificial atomic lattices, enabling the exploration of novel quantum phases and many-body effects.
Emergent multifractality is the object of both fundamental and technology-oriented research. Here, the authors demonstrate and characterize multifractality in the optical resonances of aperiodic arrays of nanoparticles designed from fundamental structures of algebraic number theory.


Volume: 3 (1)      Da Pagina: 106-1  A: 106-9

DOI: 10.1038/s42005-020-0374-7

Citazioni: 6
dati da “WEB OF SCIENCE” (of Thomson Reuters) aggiornati al: 2022-10-02
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