2017
DOI: 10.1063/1.4977537
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Extending geometrical optics: A Lagrangian theory for vector waves

Abstract: Even when neglecting diffraction effects, the well-known equations of geometrical optics (GO) are not entirely accurate. Traditional GO treats wave rays as classical particles, which are completely described by their coordinates and momenta, but vector-wave rays have another degree of freedom, namely, their polarization. The polarization degree of freedom manifests itself as an effective (classical) "wave spin" that can be assigned to rays and can affect the wave dynamics accordingly. A well-known manifestatio… Show more

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Cited by 27 publications
(34 citation statements)
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“…This can be identified as a manifestation of polarization ("spin") effects that were recently discussed for both classical and quantum waves in Refs. [21,22].…”
Section: B Strong Pumpmentioning
confidence: 99%
“…This can be identified as a manifestation of polarization ("spin") effects that were recently discussed for both classical and quantum waves in Refs. [21,22].…”
Section: B Strong Pumpmentioning
confidence: 99%
“…If D H2 is neglected, the envelope equation (119) becomes a Dirac-type equation similar to those considered in the context of XGO [24][25][26][27][28] and also, for instance, in Refs. [58,59].…”
Section: A Hilbert Space For Vector Wavesmentioning
confidence: 90%
“…I), except here it is generalized to an arbitrary metric. This term causes polarization-driven bending of the ray trajectories, which is missed in traditional GO; also, it causes mode conversion, if more than one active mode is present [24][25][26][27][28]. These effects are is discussed in further detail in Sec.…”
Section: Equation For the Active Modesmentioning
confidence: 99%
“…This implies that conservation laws are also generally preserved, so a model inherits key features of the original system notwithstanding the reduction [1]. One of the areas that particularly benefit from this fact is wave theory [2,3], where even crude approximations to an action functional often yield insightful reduced models [4][5][6][7][8][9][10][11].…”
Section: A Motivationmentioning
confidence: 99%