Superposition Of Spatial Modes Research Articles

Single-ended characterization of the coherent transfer matrix of coupled multimode transmission channels

Light propagation in random media is a subject of interest to the optics community at large, with applications ranging from imaging to communication and sensing. However, real-time characterization of wavefront distortion in random media remains a major challenge. Compounding the difficulties, for many applications such as imaging (e.g., endoscopy) and focusing through random media, we only have single-ended access. In this work, we propose to represent wavefronts as superpositions of spatial modes. Within this framework, random media can be represented as a coupled multimode transmission channel. Once the distributed coherent transfer matrix of the channel is characterized, wavefront distortions along the path can be obtained. Fortunately, backreflections almost always accompany mode coupling and wavefront distortions. Therefore, we further propose to utilize backreflections to perform single-ended characterization of the coherent transfer matrix. We first develop the general framework for single-ended characterization of the coherent transfer matrix of coupled multimode transmission channels. Then, we apply this framework to the case of a two-mode channel, a single-mode fiber, which supports two randomly coupled polarization modes, to provide a proof-of-concept demonstration. Furthermore, as one of the main applications of coherent channel estimation, a polarization imaging system through single-mode fibers is implemented. We envision that the proposed method can be applied to both guided and free-space channels with a multitude of applications.

Scattering of radiofrequency waves by randomly modulated density interfaces in the edge of fusion plasmas

In the scrape-off layer and the edge region of a tokamak, the plasma is strongly turbulent and scatters the radiofrequency (RF) electromagnetic waves that propagate through this region. It is important to know the spectral properties of these scattered RF waves, whether used for diagnostics or for heating and current drive. The spectral changes influence the interpretation of the obtained diagnostic data, and the current and heating profiles. A full-wave, three-dimensional (3-D) electromagnetic code ScaRF (see Papadopouloset al.,J. Plasma Phys., vol. 85, issue 3, 2019, 905850309) has been developed for studying the RF wave propagation through turbulent plasma. ScaRF is a finite-difference frequency-domain (FDFD) method used for solving Maxwell's equations. The magnetized plasma is defined through the cold plasma by the anisotropic permittivity tensor. As a result, ScaRF can be used to study the scattering of any cold plasma RF wave. It can also be used for the study of the scattering of electron cyclotron waves in ITER-type and medium-sized tokamaks such as TCV, ASDEX-U and DIII-D. For the case of medium-sized tokamaks, there is experimental evidence that drift waves and rippling modes are present in the edge region (see Ritzet al.,Phys. Fluids, vol. 27, issue 12, 1984, pp. 2956–2959). Hence, we have studied the scattering of RF waves by periodic density interfaces (plasma gratings) in the form of a superposition of spatial modes with varying periodicity and random amplitudes (see Papadopouloset al.,J. Plasma Phys., vol. 85, issue 3, 2019, 905850309). The power reflection coefficient (a random variable) is calculated for different realizations of the density interface. In this work, the uncertainty of the power reflection coefficient is rigorously quantified by use of the Polynomial Chaos Expansion (see Xiu & Karniadakis,SIAM J. Sci. Comput., vol. 24, issue 2, 2002, pp. 619–644) method in conjunction with the Smolyak sparse-grid integration (see Papadopouloset al.,Appl. Opt., vol. 57, issue 12, 2018, pp. 3106–3114), which is known as the PCE-SG method. The PCE-SG method is proven to be accurate and more efficient (roughly a2-orders of magnitude shorter execution time) compared with alternative methods such as the Monte Carlo (MC) approach.