The rotational memory effect of a multimode fiber

We demonstrate the rotational memory effect in a multimode fiber. Rotating the incident wavefront around the fiber core axis leads to a rotation of the resulting pattern of the fiber output without significant changes in the resulting speckle pattern. The rotational memory effect can be exploited for non-invasive imaging or ultrafast high-resolution scanning through a multimode fiber. Our experiments demonstrate this effect over a full range of angles in two experimental configurations.Comment: 7 pages, 3 figure

Air-guided photonic-crystal-fiber pulse-compression delivery of multimegawatt femtosecond laser output for nonlinear-optical imaging and neurosurgery

Cataloged from PDF version of article.Large-core hollow photonic- crystal fibers (PCFs) are shown to enable a fiber-format air-guided delivery of ultrashort infrared laser pulses for neurosurgery and nonlinear-optical imaging. With an appropriate dispersion precompensation, an anomalously dispersive 15-mu m-core hollow PCF compresses 510-fs, 1070-nm light pulses to a pulse width of about 110 fs, providing a peak power in excess of 5 MW. The compressed PCF output is employed to induce a local photodisruption of corpus callosum tissues in mouse brain and is used to generate the third harmonic in brain tissues, which is captured by the PCF and delivered to a detector through the PCF cladding. (C) 2012 American Institute of Physics

Implantable fiber-optic interface for parallel multisite long-term optical dynamic brain interrogation in freely moving mice

Seeing the big picture of functional responses within large neural networks in a freely functioning brain is crucial for understanding the cellular mechanisms behind the higher nervous activity, including the most complex brain functions, such as cognition and memory. As a breakthrough toward meeting this challenge, implantable fiber-optic interfaces integrating advanced optogenetic technologies and cutting-edge fiber-optic solutions have been demonstrated, enabling a long-term optogenetic manipulation of neural circuits in freely moving mice. Here, we show that a specifically designed implantable fiber-optic interface provides a powerful tool for parallel long-term optical interrogation of distinctly separate, functionally different sites in the brain of freely moving mice. This interface allows the same groups of neurons lying deeply in the brain of a freely behaving mouse to be reproducibly accessed and optically interrogated over many weeks, providing a long-term dynamic detection of genome activity in response to a broad variety of pharmacological and physiological stimuli

Electron spin manipulation and readout through an optical fiber

The electron spin of nitrogen--vacancy (NV) centers in diamond offers a solid-state quantum bit and enables high-precision magnetic-field sensing on the nanoscale. Implementation of these approaches in a fiber format would offer unique opportunities for a broad range of technologies ranging from quantum information to neuroscience and bioimaging. Here, we demonstrate an ultracompact fiber-optic probe where a diamond microcrystal with a well-defined orientation of spin quantization NV axes is attached to the fiber tip, allowing the electron spins of NV centers to be manipulated, polarized, and read out through a fiber-optic waveguide integrated with a two-wire microwave transmission line. The microwave field transmitted through this line is used to manipulate the orientation of electron spins in NV centers through the electron-spin resonance tuned by an external magnetic field. The electron spin is then optically initialized and read out, with the initializing laser radiation and the photoluminescence spin-readout return from NV centers delivered by the same optical fiber

Computational optical imaging with a photonic lantern

[EN] The thin and flexible nature of optical fibres often makes them the ideal technology to view biological processes in-vivo, but current microendoscopic approaches are limited in spatial resolution. Here, we demonstrate a route to high resolution microendoscopy using a multicore fibre (MCF) with an adiabatic multimode-to-single-mode "photonic lantern" transition formed at the distal end by tapering. We show that distinct multimode patterns of light can be projected from the output of the lantern by individually exciting the single-mode MCF cores, and that these patterns are highly stable to fibre movement. This capability is then exploited to demonstrate a form of single-pixel imaging, where a single pixel detector is used to detect the fraction of light transmitted through the object for each multimode pattern. A custom computational imaging algorithm we call SARA-COIL is used to reconstruct the object using only the pre-measured multimode patterns themselves and the detector signals.This work was funded through the "Proteus" Engineering and Physical Sciences Research Council (EPSRC) Interdisciplinary Research Collaboration (IRC) (EP/K03197X/1), by the Science and Technology Facilities Council (STFC) through STFC-CLASP grants ST/K006509/1 and ST/K006460/1, STFC Consortium grants ST/N000625/1 and ST/N000544/1. S.L. acknowledges support from the National Natural Science Foundation of China under Grant no. 61705073. DBP acknowledges support from the Royal Academy of Engineering, and the European Research Council (PhotUntangle, 804626). The authors thank Philip Emanuel for the use of his confocal image of A549 cells and Eckhardt Optics for their image of the USAF 1951 target. The authors sincerely thank the anonymous reviewers of this paper for their detailed and considered feedback which helped us to improve the quality of this paper significantly.Choudhury, D.; Mcnicholl, DK.; Repetti, A.; Gris-Sánchez, I.; Li, S.; Phillips, DB.; Whyte, G.... (2020). Computational optical imaging with a photonic lantern. Nature Communications. 11(1):1-9. https://doi.org/10.1038/s41467-020-18818-6S19111Wood, H. A. C., Harrington, K., Birks, T. A., Knight, J. C. & Stone, J. M. High-resolution air-clad imaging fibers. Opt. Lett. 43, 5311–5314 (2018).Akram, A. R. et al. In situ identification of Gram-negative bacteria in human lungs using a topical fluorescent peptide targeting lipid A. Sci. Transl. Med. 10, eaal0033 (2018).Shin, J., Bosworth, B. T. & Foster, M. A. Compressive fluorescence imaging using a multi-core fiber and spatially dependent scattering. Opt. Lett. 42, 109–112 (2017).Papadopoulos, I. N., Farahi, S., Moser, C. & Psaltis, D. Focusing and scanning light through a multimode optical fiber using digital phase conjugation. Opt. Express 20, 10583–10590 (2012).Čižmár, T. & Dholakia, K. Exploiting multimode waveguides for pure fibre-based imaging. Nat. Commun. 3, 1027 (2012).Plöschner, M., Tyc, T. & Čižmár, T. Seeing through chaos in multimode fibres. Nat. Photon. 9, 529–535 (2015).Birks, T. A., Gris-Sánchez, I., Yerolatsitis, S., Leon-Saval, S. G. & Thomson, R. R. The photonic lantern. Adv. Opt. Photon. 7, 107–167 (2015).Birks, T. A., Mangan, B. J., Díez, A., Cruz, J. L. & Murphy, D. F. Photonic lantern’ spectral filters in multi-core fiber. Opt. Express 20, 13996–14008 (2012).Edgar, M. P., Gibson, G. M. & Padgett, M. J. Principles and prospects for single-pixel imaging. Nat. Photon. 13, 13–20 (2019).Mahalati, R. N., Yu, Gu. R. & Kahn, J. M. Resolution limits for imaging through multi-mode fiber. Opt. Express 21, 1656–1668 (2013).Amitonova, L. V. & de Boer, J. F. Compressive imaging through a multimode fiber. Opt. Lett. 43, 5427–5430 (2018).Mallat, S. A Wavelet Tour of Signal Processing 2nd edn (Academic Press, Burlington, MA, 2009).Lustig, M., Donoho, D. & Pauly, J. M. Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn. Reson. Med. 58, 1182–1195 (2007).Davies, M., Puy, G., Vandergheynst, P. & Wiaux, Y. A compressed sensing framework for magnetic resonance fingerprinting. SIAM J. Imaging Sci. 7, 2623–2656 (2014).Wiaux, Y., Puy, G., Scaife, A. M. M. & Vandergheynst, P. Compressed sensing imaging techniques in radio interferometry. Mon. Not. R. Astron. Soc. 395, 1733–1742 (2009).Carrillo, R. E., McEwen, J. D. & Wiaux, Y. Sparsity averaging reweighted analysis (SARA): a novel algorithm for radio-interferometric imaging. Mon. Not. R. Astron. Soc. 426, 1223–1234 (2012).Katz, O., Bromberg, Y. & Silberberg, Y. Compressive ghost imaging. Appl. Phys. Lett. 95, 131110 (2009).Sun, B., Welsh, S. S., Edgar, M. P., Shapiro, J. H. & Padgett, M. J. Normalized ghost imaging. Opt. Express 20, 16892–16901 (2012).Kim, M., Park, C., Rodriguez, C., Park, Y. & Cho, Y.-H. Superresolution imaging with optical fluctuation using speckle patterns illumination. Sci. Rep. 5, 16525 (2015).Combettes, P. L. & Pesquet, J. -C. in Fixed-Point Algorithms for Inverse Problems in Science and Engineering (Springer, New York, 2011).Komodakis, N. & Pesquet, J.-C. Playing with duality: an overview of recent primal dual approaches for solving large-scale optimization problems. IEEE Signal Proc. Mag. 32, 31–54 (2015).Chandrasekharan, H. K. et al. Multiplexed single-mode wavelength-to-time mapping of multimode light. Nat. Commun. 8, 14080 (2017).Wadsworth, W. J. et al. Very high numerical aperture fibers. Photon. Technol. Lett. 16, 843–845 (2004).Pesquet, J.-C. & Repetti, A. A class of randomized primal-dual algorithms for distributed optimization. J. Nonlinear Convex Anal. 16, 2353–2490 (2015).Chambolle, A., Ehrhardt, M. J., Richtárik, P. & Schönlieb, C.-B. Stochastic primal-dual hybrid gradient algorithm with arbitrary sampling and imaging applications. SIAM J. Optim. 28, 2783–2808 (2018).Bolte, J., Sabach, S. & Teboulle, M. Proximal alternating linearized minimization for nonconvex and nonsmooth problems. Math. Program. 146, 459–494 (2014).Chouzenoux, E., Pesquet, J.-C. & Repetti, A. A block coordinate variable metric forward-backward algorithm. J. Glob. Optim. 66, 457–485 (2016).Flusberg, B. A. et al. Fiber-optic fluorescence imaging. Nat. Methods 2, 941–950 (2005).Tsvirkun, V. et al. Bending-induced inter-core group delays in multicore fibers. Opt. Express 25, 31863–31875 (2017).Candès, E. J., Wakin, M. B. & Boyd, S. Enhancing sparsity by reweighted l1 minimization. J. Fourier Anal. Appl. 14, 877–905 (2008).Condat, L. A primal–dual splitting method for convex optimization involving lipschitzian, proximable and linear composite terms. J. Optim. Theory Appl. 158, 460–479 (2013).Vu, B. C. A splitting algorithm for dual monotone inclusions involving cocoercive operators. Adv. Comp. Math. 38, 667–681 (2013)

High-resolution wavefront shaping with a photonic crystal fiber for multimode fiber imaging

We demonstrate that a high-numerical-aperture photonic crystal fiber allows lensless focusing at an unparalleled res- olution by complex wavefront shaping. This paves the way toward high-resolution imaging exceeding the capabilities of imaging with multi-core single-mode optical fibers. We analyze the beam waist and power in the focal spot on the fiber output using different types of fibers and different wavefront shaping approaches. We show that the complex wavefront shaping technique, together with a properly de- signed multimode photonic crystal fiber, enables us to create a tightly focused spot on the desired position on the fiber output facet with a subwavelength beam waist

High-resolution wavefront shaping with a photonic crystal fiber for multimode fiber imaging

We demonstrate that a high-numerical-aperture photonic crystal fiber allows lensless focusing at an unparalleled res- olution by complex wavefront shaping. This paves the way toward high-resolution imaging exceeding the capabilities of imaging with multi-core single-mode optical fibers. We analyze the beam waist and power in the focal spot on the fiber output using different types of fibers and different wavefront shaping approaches. We show that the complex wavefront shaping technique, together with a properly de- signed multimode photonic crystal fiber, enables us to create a tightly focused spot on the desired position on the fiber output facet with a subwavelength beam waist