Deep Learning Reconstruction of Ultra-Short Pulses

Ultra-short laser pulses with femtosecond to attosecond pulse duration are the shortest systematic events humans can create. Characterization (amplitude and phase) of these pulses is a key ingredient in ultrafast science, e.g., exploring chemical reactions and electronic phase transitions. Here, we propose and demonstrate, numerically and experimentally, the first deep neural network technique to reconstruct ultra-short optical pulses. We anticipate that this approach will extend the range of ultrashort laser pulses that can be characterized, e.g., enabling to diagnose very weak attosecond pulses.

[1]  Rob Fergus,et al.  Visualizing and Understanding Convolutional Networks , 2013, ECCV.

[2]  Claude Froehly,et al.  New Experimental Methods for the Analysis of Light Pulses and Partial Coherent Laser Beams , 1975 .

[3]  Pascal Vincent,et al.  Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion , 2010, J. Mach. Learn. Res..

[4]  M. Kling,et al.  Attosecond electron dynamics. , 2008, Annual review of physical chemistry.

[5]  Yaron Silberberg,et al.  Quantum coherent control for nonlinear spectroscopy and microscopy. , 2009, Annual review of physical chemistry.

[6]  Saulius Juodkazis,et al.  Ultrafast laser processing of materials: from science to industry , 2016, Light: Science & Applications.

[7]  Ahmed H. Zewail,et al.  Femtochemistry: Atomic-Scale Dynamics of the Chemical Bond† , 2000 .

[8]  Demis Hassabis,et al.  Mastering the game of Go with deep neural networks and tree search , 2016, Nature.

[9]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[10]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[11]  Lawrence D. Jackel,et al.  Handwritten Digit Recognition with a Back-Propagation Network , 1989, NIPS.

[12]  Liang Gao,et al.  Ultrafast optical imaging technology: principles and applications of emerging methods , 2016 .

[13]  R. Trebino,et al.  Highly simplified device for ultrashort-pulse measurement. , 2001, Optics letters.

[14]  Rudolf Sprik,et al.  PHASE-SENSITIVE INTERFEROMETRY WITH ULTRASHORT OPTICAL PULSES , 1995 .

[15]  Marc J. J. Vrakking,et al.  Attosecond molecular dynamics: fact or fiction? , 2014, Nature Photonics.

[16]  R. Trebino,et al.  Noise sensitivity in frequency-resolved optical-gating measurements of ultrashort pulses , 1995 .

[17]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[18]  Yibo Zhang,et al.  Deep Learning Microscopy , 2017, ArXiv.

[19]  Quoc V. Le,et al.  Sequence to Sequence Learning with Neural Networks , 2014, NIPS.

[20]  Günter Steinmeyer,et al.  Interferometric frequency-resolved optical gating. , 2005, Optics express.

[21]  G. Gómez-Moreno,et al.  Femtosecond laser microstructuring of zirconia dental implants. , 2011, Journal of biomedical materials research. Part B, Applied biomaterials.

[22]  Yonina C. Eldar,et al.  Phase Retrieval with Application to Optical Imaging: A contemporary overview , 2015, IEEE Signal Processing Magazine.

[23]  Yoshua Bengio,et al.  Why Does Unsupervised Pre-training Help Deep Learning? , 2010, AISTATS.

[24]  Rick Trebino,et al.  The Measurement of Ultrashort Light Pulses—Simple Devices, Complex Pulses , 2004 .

[25]  Laurence Perreault Levasseur,et al.  Fast automated analysis of strong gravitational lenses with convolutional neural networks , 2017, Nature.

[26]  Yonina C. Eldar,et al.  On the Uniqueness of FROG Methods , 2017, IEEE Signal Processing Letters.

[27]  Sebastian Thrun,et al.  Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.

[28]  Kilian Q. Weinberger,et al.  Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[29]  D N Fittinghoff,et al.  Direct ultrashort-pulse intensity and phase retrieval by frequency-resolved optical gating and a computational neural network. , 1996, Optics letters.

[30]  Geoff Holmes,et al.  Classifier chains for multi-label classification , 2009, Machine Learning.

[31]  Pavel Sidorenko,et al.  Ptychographic reconstruction algorithm for frequency resolved optical gating: super-resolution and supreme robustness , 2016 .

[32]  D. Kane Principal components generalized projections: a review [Invited] , 2008 .

[33]  F. Ardana-Lamas,et al.  Streaking of 43-attosecond soft-X-ray pulses generated by a passively CEP-stable mid-infrared driver. , 2017, Optics express.

[34]  Rick Trebino,et al.  Measuring ultrashort laser pulses in the time-frequency domain using frequency-resolved optical gating , 1997 .

[35]  I. Walmsley,et al.  Spectral phase interferometry for direct electric-field reconstruction of ultrashort optical pulses. , 1998, Optics letters.