An analytical approximation to measure the extinction cross-section using: Localized Waves

We present a general expression for the optical theorem in terms of Localized Waves. This representation is well-known and commonly used to generate Frozen waves, Xwaves, and other propagation invariant beams. We analyze several examples using different input beam sources on a circular detector to measure the extinction cross-section.

An adaptive approach to machine learning for compact particle accelerators

Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However, for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no longer accurately represented by the data with which the ML models were trained. For complex systems, re-training is only possible if the changes are slow relative to the rate at which large numbers of new input-output training data can be non-invasively recorded. In this work, we present an approach to deep learning for time-varying systems that does not require re-training, but uses instead an adaptive feedback in the architecture of deep convolutional neural networks (CNN). The feedback is based only on available system output measurements and is applied in the encoded low-dimensional dense layers of the encoder-decoder CNNs. First, we develop an inverse model of a complex accelerator system to map output beam measurements to input beam distributions, while both the accelerator components and the unknown input beam distribution vary rapidly with time. We then demonstrate our method on experimental measurements of the input and output beam distributions of the HiRES ultra-fast electron diffraction (UED) beam line at Lawrence Berkeley National Laboratory, and showcase its ability for automatic tracking of the time varying photocathode quantum efficiency map. Our method can be successfully used to aid both physics and ML-based surrogate online models to provide non-invasive beam diagnostics.

Nematic Dispersive Shock Waves from Nonlocal to Local

The structure of optical dispersive shock waves in nematic liquid crystals is investigated as the power of the optical beam is varied, with six regimes identified, which complements previous work pertinent to low power beams only. It is found that the dispersive shock wave structure depends critically on the input beam power. In addition, it is known that nematic dispersive shock waves are resonant and the structure of this resonance is also critically dependent on the beam power. Whitham modulation theory is used to find solutions for the six regimes with the existence intervals for each identified. These dispersive shock wave solutions are compared with full numerical solutions of the nematic equations, and excellent agreement is found.

Adaptive Deep Learning for Time-Varying Systems With Hidden Parameters: Predicting Changing Input Beam Distributions of Compact Particle Accelerators

Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no longer accurately represented by the data with which the ML models were trained. For complex systems, re-training is only possible if the changes are slow relative to the rate at which large numbers of new input-output training data can be non-invasively recorded. In this work, we present an approach to deep learning for time-varying systems which does not require re-training. Our approach is to include adaptive feedback in the architecture of deep generative convolutional neural networks (CNN). The feedback is based only on available system output measurements and is applied in the encoded low-dimensional dense layers of the encoder-decoder CNNs. Our approach is inspired by biological systems in which separate groups of neurons interact and are controlled and synchronized by external feedbacks. We demonstrate this approach by developing an inverse model of a complex charged particle accelerator system, mapping output beam measurements to input beam distributions, while both the accelerator components and the unknown input beam distribution vary rapidly with time. We demonstrate our methods on experimental measurements of the input and output beam distributions of the HiRES ultra-fast electron diffraction (UED) beam line at Lawrence Berkeley National Laboratory. Our method can be successfully used to aid both physics and ML-based surrogate online models to provide non-invasive beam diagnostics. We also demonstrate our method for automatically tracking the time varying quantum efficiency map of a particle accelerator’s photocathode.

Nonlinear optical properties of arsenic telluride and its use in ultrafast fiber lasers

We report the first investigation results of the nonlinear optical properties of As2Te3. More specifically, the nonlinear optical absorption properties of the prepared α-As2Te3 were investigated at wavelengths of 1.56 and 1.9 μm using the open-aperture (OA) Z-scan technique. Using the OA Z-scan technique, the nonlinear absorption coefficients (β) of α-As2Te3 were estimated in a range from (− 54.8 ± 3.4) × 104 cm/GW to (− 4.9 ± 0.4) × 104 cm/GW depending on the irradiance of the input beam at 1.56 μm, whereas the values did from (− 19.8 ± 0.8) × 104 cm/GW to (− 3.2 ± 0.1) × 104 cm/GW at 1.9 μm. In particular, the β value at 1.56 μm is an order of magnitude larger than the previously reported values of other group-15 sesquichalcogenides such as Bi2Se3, Bi2Te3, and Bi2TeSe2. Furthermore, this is the first time report on β value of a group-15 sesquichalcogenide at a 1.9-μm wavelength. The density functional theory (DFT) calculations of the electronic band structures of α-As2Te3 were also conducted to obtain a better understanding of their energy band structure. The DFT calculations indicated that α-As2Te3 possess sufficient optical absorption in a wide wavelength region, including 1.5 μm, 1.9 μm, and beyond (up to 3.7 μm). Using both the measured nonlinear absorption coefficients and the theoretically obtained refractive indices from the DFT calculations, the imaginary parts of the third-order optical susceptibilities (Im χ(3)) of As2Te3 were estimated and they were found to vary from (− 39 ± 2.4) × 10–19 m2/V2 to (− 3.5 ± 0.3) × 10–19 m2/V2 at 1.56 μm and (− 16.5 ± 0.7) × 10–19 m2/V2 to (− 2.7 ± 0.1) × 10–19 m2/V2 at 1.9 μm, respectively, depending on the irradiance of the input beam. Finally, the feasibility of using α-As2Te3 for SAs was investigated, and the prepared SAs were thus tested by incorporating them into an erbium (Er)-doped fiber cavity and a thulium–holmium (Tm–Ho) co-doped fiber cavity for both 1.5 and 1.9 μm operation.

Analysis of Hybrid Vector Beams Generated with a Detuned Q-Plate

We use a tunable commercial liquid-crystal device tuned to a quarter-wave retardance to study the generation and dynamics of different types of hybrid vector beams. The standard situation where the q-plate is illuminated by a Gaussian beam is compared with other cases where the input beam is a vortex or a pure vector beam. As a result, standard hybrid vector beams but also petal-like hybrid vector beams are generated. These beams are analyzed in the near field and compared with the far field distribution, where their hybrid nature is observed as a transformation of the intensity and polarization patterns. Analytical calculations and numerical results confirm the experiments. We include an approach that provides an intuitive physical explanation of the polarization patterns in terms of mode superpositions and their transformation upon propagation based on their different Gouy phase. The tunable q-plate device presents worthy advantages, since it allows a compact and efficient generation of pure and hybrid vector beams to study these effects.

Optical design of a variable angle irradiation system for skin cancer laser phototherapy

Photothermal therapy is a developing therapeutic technic mainly regarding the usage of nanoparticles considering their proneness to assemble around malignant tissue and induce their destruction by converting electromagnetic radiation into thermal radiation. In order to optimize this process, controlling the area of incidence in a way that it can fit the tumour and prevent damage of healthy cells is of great importance. This study was conducted by designing an optical system based on zoom systems for manipulating an initial input beam and adjust it to the most common skin cancer sizes. Two solutions are proposed, accomplishing spot sizes at 150 mm from the last lens within the approximate range of 2 mm to 76 mm, with beam divergences lower than 3 mrad.

Imaging trace-element zoning in pyroxenes using synchrotron XRF mapping with the Maia detector array: Benefit of low-incident energy

Trace-element zoning in igneous phenocrysts and cumulus phases is an informative record of magmatic evolution. The advent of microbeam X-ray fluorescence (XRF) mapping has allowed rapid chemical imaging of samples at thin section to decimeter scale, revealing such zoning patterns. Mapping with synchrotron radiation using multidetector arrays has proved especially effective, allowing entire thin sections to be imaged at micrometer-scale resolution in a matter of hours. The resolution of subtle minor element zoning, particularly in first-row transition metals, is greatly enhanced in synchrotron X-ray fluorescence microscopy (XFM) images by scanning with input beam energy below the FeKα line. In the examples shown here, from a phenocryst rich trachybasalt from Mt Etna (Italy) and from a Ni-Cu-PGE ore-bearing intrusion at Norilsk (Siberia), the zoning patterns revealed in this way record aspects of the crystallization history that are not readily evident from XFM images collected using higher incident energies and that cannot be obtained at comparable spatial resolutions by any other methods within reasonable scan times. This approach has considerable potential as a geochemical tool for investigating magmatic processes and is also likely to be applicable in a wide variety of other fields.