Femtosecond pulse parameter estimation from photoelectron momenta using machine learning

Szołdra, Tomasz; Ciappina, Marcelo F.; Werby, Nicholas; Bucksbaum, Philip H.; Lewenstein, Maciej; Zakrzewski, Jakub; Maxwell, Andrew S.

doi:10.1088/1367-2630/acee19

Title: Femtosecond pulse parameter estimation from photoelectron momenta using machine learning

Journal Article · 23 August 2023 · New Journal of Physics

DOI: https://doi.org/10.1088/1367-2630/acee19 · OSTI ID:1996590

;

Abstract Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we test CNNs on strong-field ionization photoelectron spectra, training on theoretical data sets to ‘invert’ experimental data. Pulse characterization is used as a ‘testing ground’, specifically we retrieve the laser intensity, where ‘traditional’ measurements typically lead to 20% uncertainty. We report on crucial data augmentation techniques required to successfully train on theoretical data and return consistent results from experiments, including accounting for detector saturation. The same procedure can be repeated to apply CNNs in a range of scenarios for strong-field ionization. Using a predictive uncertainty estimation, reliable laser intensity uncertainties of a few percent can be extracted, which are consistently lower than those given by traditional techniques. Using interpretability methods can reveal parts of the distribution that are most sensitive to laser intensity, which can be directly associated with holographic interferences. The CNNs employed provide an accurate and convenient ways to extract parameters, and represent a novel interpretational tool for strong-field ionization spectra.

View Journal Article

Cite

Export

Save

Sponsoring Organization:: USDOE; USDOE Office of Science (SC), Basic Energy Sciences (BES)

OSTI ID:: 1996590

Journal Information:: New Journal of Physics, Journal Name: New Journal of Physics Journal Issue: 8 Vol. 25; ISSN 1367-2630

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United Kingdom

Language:: English

References (60)

A Survey on Deep Transfer Learning Tan, Chuanqi; Sun, Fuchun; Kong, Tao Artificial Neural Networks and Machine Learning – ICANN 2018 https://doi.org/10.1007/978-3-030-01424-7_27	book	January 2018
Reconstruction of attosecond harmonic beating by interference of two-photon transitions Muller, H. G. Applied Physics B, Vol. 74, Issue S1 https://doi.org/10.1007/s00340-002-0894-8	journal	June 2002
Laser-induced electron diffraction: a new tool for probing ultrafast molecular dynamics Zuo, T.; Bandrauk, A. D.; Corkum, P. B. Chemical Physics Letters, Vol. 259, Issue 3-4 https://doi.org/10.1016/0009-2614(96)00786-5	journal	September 1996
Qprop with faster calculation of photoelectron spectra Tulsky, Vasily; Bauer, Dieter Computer Physics Communications, Vol. 251 https://doi.org/10.1016/j.cpc.2019.107098	journal	June 2020
A review of uncertainty quantification in deep learning: Techniques, applications and challenges Abdar, Moloud; Pourpanah, Farhad; Hussain, Sadiq Information Fusion, Vol. 76 https://doi.org/10.1016/j.inffus.2021.05.008	journal	December 2021
Explaining nonlinear classification decisions with deep Taylor decomposition Montavon, Grégoire; Lapuschkin, Sebastian; Binder, Alexander Pattern Recognition, Vol. 65 https://doi.org/10.1016/j.patcog.2016.11.008	journal	May 2017
Attosecond metrology Hentschel, M.; Kienberger, R.; Spielmann, Ch. Nature, Vol. 414, Issue 6863, p. 509-513 https://doi.org/10.1038/35107000	journal	November 2001
Tomographic imaging of molecular orbitals Itatani, J.; Levesque, J.; Zeidler, D. Nature, Vol. 432, Issue 7019 https://doi.org/10.1038/nature03183	journal	December 2004
Fast automated analysis of strong gravitational lenses with convolutional neural networks Hezaveh, Yashar D.; Levasseur, Laurence Perreault; Marshall, Philip J. Nature, Vol. 548, Issue 7669 https://doi.org/10.1038/nature23463	journal	August 2017
Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning Sanchez-Gonzalez, A.; Micaelli, P.; Olivier, C. Nature Communications, Vol. 8, Issue 1 https://doi.org/10.1038/ncomms15461	journal	June 2017
Machine learning for laser-induced electron diffraction imaging of molecular structures Liu, Xinyao; Amini, Kasra; Sanchez, Aurelien Communications Chemistry, Vol. 4, Issue 1 https://doi.org/10.1038/s42004-021-00594-z	journal	November 2021
Machine learning in the search for new fundamental physics Karagiorgi, Georgia; Kasieczka, Gregor; Kravitz, Scott Nature Reviews Physics, Vol. 4, Issue 6 https://doi.org/10.1038/s42254-022-00455-1	journal	May 2022
Measuring ultrashort laser pulses in the time-frequency domain using frequency-resolved optical gating Trebino, Rick; DeLong, Kenneth W.; Fittinghoff, David N. Review of Scientific Instruments, Vol. 68, Issue 9, p. 3277-3295 https://doi.org/10.1063/1.1148286	journal	September 1997
Toward real-time charged-particle image reconstruction using polar onion-peeling Roberts, G. M.; Nixon, J. L.; Lecointre, J. Review of Scientific Instruments, Vol. 80, Issue 5 https://doi.org/10.1063/1.3126527	journal	May 2009
Restoration of the focal parameters for an extreme-power laser pulse with ponderomotively scattered proton spectra by using a neural network algorithm Bukharskii, N. D.; Vais, O. E.; Korneev, Ph. A. Matter and Radiation at Extremes, Vol. 8, Issue 1 https://doi.org/10.1063/5.0126571	journal	December 2022
Multiple absorption of laser photons by atoms Faisal, F. H. M. Journal of Physics B: Atomic and Molecular Physics, Vol. 6, Issue 4 https://doi.org/10.1088/0022-3700/6/4/011	journal	April 1973
Empirical formula for static field ionization rates of atoms and molecules by lasers in the barrier-suppression regime Tong, X. M.; Lin, C. D. Journal of Physics B: Atomic, Molecular and Optical Physics, Vol. 38, Issue 15 https://doi.org/10.1088/0953-4075/38/15/001	journal	July 2005
Benchmarking strong-field ionization with atomic hydrogen Kielpinski, D.; Sang, R. T.; Litvinyuk, I. V. Journal of Physics B: Atomic, Molecular and Optical Physics, Vol. 47, Issue 20 https://doi.org/10.1088/0953-4075/47/20/204003	journal	October 2014
Analytic quantum-interference conditions in Coulomb corrected photoelectron holography Maxwell, A. S.; Al-Jawahiry, A.; Lai, X. Y. Journal of Physics B: Atomic, Molecular and Optical Physics, Vol. 51, Issue 4 https://doi.org/10.1088/1361-6455/aa9e81	journal	January 2018
Coulomb-free and Coulomb-distorted recolliding quantum orbits in photoelectron holography Maxwell, A. S.; de Morisson Faria, C. Figueira Journal of Physics B: Atomic, Molecular and Optical Physics, Vol. 51, Issue 12 https://doi.org/10.1088/1361-6455/aac164	journal	May 2018
Controlling quantum effects in enhanced strong-field ionisation with machine-learning techniques Chomet, H.; Plesnik, S.; Nicolae, D. C. Journal of Physics B: Atomic, Molecular and Optical Physics, Vol. 55, Issue 24 https://doi.org/10.1088/1361-6455/aca4b0	journal	December 2022
Attosecond physics at the nanoscale Ciappina, M. F.; Pérez-Hernández, J. A.; Landsman, A. S. Reports on Progress in Physics, Vol. 80, Issue 5 https://doi.org/10.1088/1361-6633/aa574e	journal	March 2017
Symphony on strong field approximation Amini, Kasra; Biegert, Jens; Calegari, Francesca Reports on Progress in Physics, Vol. 82, Issue 11 https://doi.org/10.1088/1361-6633/ab2bb1	journal	October 2019
It is all about phases: ultrafast holographic photoelectron imaging Figueira de Morisson Faria, C.; Maxwell, A. S. Reports on Progress in Physics, Vol. 83, Issue 3 https://doi.org/10.1088/1361-6633/ab5c91	journal	January 2020
Holographic detection of parity in atomic and molecular orbitals Kang, HuiPeng; Maxwell, Andrew S.; Trabert, Daniel Physical Review A, Vol. 102, Issue 1 https://doi.org/10.1103/PhysRevA.102.013109	journal	July 2020
Spiral-like holographic structures: Unwinding interference carpets of Coulomb-distorted orbits in strong-field ionization Maxwell, Andrew S.; Faria, Carla Figueira de Morisson; Lai, XuanYang Physical Review A, Vol. 102, Issue 3 https://doi.org/10.1103/PhysRevA.102.033111	journal	September 2020
Quantum estimation in strong fields: In situ ponderomotive sensing Maxwell, A. S.; Serafini, A.; Bose, S. Physical Review A, Vol. 103, Issue 4 https://doi.org/10.1103/PhysRevA.103.043519	journal	April 2021
Dissecting subcycle interference in photoelectron holography Werby, Nicholas; Maxwell, Andrew S.; Forbes, Ruaridh Physical Review A, Vol. 104, Issue 1 https://doi.org/10.1103/PhysRevA.104.013109	journal	July 2021
Deep learning for retrieval of the internuclear distance in a molecule from interference patterns in photoelectron momentum distributions Shvetsov-Shilovski, N. I.; Lein, M. Physical Review A, Vol. 105, Issue 2 https://doi.org/10.1103/PhysRevA.105.L021102	journal	February 2022
Transfer learning, alternative approaches, and visualization of a convolutional neural network for retrieval of the internuclear distance in a molecule from photoelectron momentum distributions Shvetsov-Shilovski, N. I.; Lein, M. Physical Review A, Vol. 107, Issue 3 https://doi.org/10.1103/PhysRevA.107.033106	journal	March 2023
Effect of an intense electromagnetic field on a weakly bound system Reiss, Howard R. Physical Review A, Vol. 22, Issue 5 https://doi.org/10.1103/PhysRevA.22.1786	journal	November 1980
High-order above-threshold ionization: The uniform approximation and the effect of the binding potential Figueira de Morisson Faria, C.; Schomerus, H.; Becker, W. Physical Review A, Vol. 66, Issue 4 https://doi.org/10.1103/PhysRevA.66.043413	journal	October 2002
Measurement of laser intensities approaching 10 15 W/cm 2 with an accuracy of 1 % Pullen, M. G.; Wallace, W. C.; Laban, D. E. Physical Review A, Vol. 87, Issue 5 https://doi.org/10.1103/PhysRevA.87.053411	journal	May 2013
Coulomb-corrected quantum interference in above-threshold ionization: Working towards multitrajectory electron holography Maxwell, A. S.; Al-Jawahiry, A.; Das, T. Physical Review A, Vol. 96, Issue 2 https://doi.org/10.1103/PhysRevA.96.023420	journal	August 2017
Temporal power reconstruction for an x-ray free-electron laser using convolutional neural networks Ren, X.; Edelen, A.; Lutman, A. Physical Review Accelerators and Beams, Vol. 23, Issue 4 https://doi.org/10.1103/PhysRevAccelBeams.23.040701	journal	April 2020
Deep neural networks for classifying complex features in diffraction images Zimmermann, Julian; Langbehn, Bruno; Cucini, Riccardo Physical Review E, Vol. 99, Issue 6 https://doi.org/10.1103/PhysRevE.99.063309	journal	June 2019
Interference Carpets in Above-Threshold Ionization: From the Coulomb-Free to the Coulomb-Dominated Regime Korneev, Ph. A.; Popruzhenko, S. V.; Goreslavski, S. P. Physical Review Letters, Vol. 108, Issue 22 https://doi.org/10.1103/PhysRevLett.108.223601	journal	May 2012
Direct Visualization of Laser-Driven Electron Multiple Scattering and Tunneling Distance in Strong-Field Ionization Hickstein, Daniel D.; Ranitovic, Predrag; Witte, Stefan Physical Review Letters, Vol. 109, Issue 7 https://doi.org/10.1103/PhysRevLett.109.073004	journal	August 2012
Deep Learning for Feynman’s Path Integral in Strong-Field Time-Dependent Dynamics Liu, Xiwang; Zhang, Guojun; Li, Jie Physical Review Letters, Vol. 124, Issue 11 https://doi.org/10.1103/PhysRevLett.124.113202	journal	March 2020
Attosecond Streak Camera Itatani, J.; Quéré, F.; Yudin, G. L. Physical Review Letters, Vol. 88, Issue 17 https://doi.org/10.1103/PhysRevLett.88.173903	journal	April 2002
Attosecond physics Krausz, Ferenc; Ivanov, Misha Reviews of Modern Physics, Vol. 81, Issue 1 https://doi.org/10.1103/RevModPhys.81.163	journal	February 2009
Machine learning and the physical sciences Carleo, Giuseppe; Cirac, Ignacio; Cranmer, Kyle Reviews of Modern Physics, Vol. 91, Issue 4 https://doi.org/10.1103/RevModPhys.91.045002	journal	December 2019
Xception: Deep Learning with Depthwise Separable Convolutions Chollet, Francois 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR.2017.195	conference	July 2017
Evaluating the Visualization of What a Deep Neural Network Has Learned Samek, Wojciech; Binder, Alexander; Montavon, Gregoire IEEE Transactions on Neural Networks and Learning Systems, Vol. 28, Issue 11 https://doi.org/10.1109/TNNLS.2016.2599820	journal	November 2017
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects Li, Zewen; Liu, Fan; Yang, Wenjie IEEE Transactions on Neural Networks and Learning Systems, Vol. 33, Issue 12 https://doi.org/10.1109/TNNLS.2021.3084827	journal	December 2022
Observation of a Train of Attosecond Pulses from High Harmonic Generation Paul, P. M. Science, Vol. 292, Issue 5522 https://doi.org/10.1126/science.1059413	journal	June 2001
Time-Resolved Holography with Photoelectrons Huismans, Y.; Rouzee, A.; Gijsbertsen, A. Science, Vol. 331, Issue 6013 https://doi.org/10.1126/science.1198450	journal	December 2010
Crystal symmetry determination in electron diffraction using machine learning Kaufmann, Kevin; Zhu, Chaoyi; Rosengarten, Alexander S. Science, Vol. 367, Issue 6477 https://doi.org/10.1126/science.aay3062	journal	January 2020
Deep learning and high harmonic generation Lytova, Marianna; Spanner, Michael; Tamblyn, Isaac Canadian Journal of Physics, Vol. 101, Issue 3 https://doi.org/10.1139/cjp-2022-0115	journal	March 2023
“The Even-Lavie valve as a source for high intensity supersonic beam” Even, U. EPJ Techniques and Instrumentation, Vol. 2, Issue 1 https://doi.org/10.1140/epjti/s40485-015-0027-5	journal	December 2015
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems Mohseni, Sina; Zarei, Niloofar; Ragan, Eric D. ACM Transactions on Interactive Intelligent Systems, Vol. 11, Issue 3-4 https://doi.org/10.1145/3387166	journal	September 2021
Backpropagation Applied to Handwritten Zip Code Recognition LeCun, Y.; Boser, B.; Denker, J. S. Neural Computation, Vol. 1, Issue 4 https://doi.org/10.1162/neco.1989.1.4.541	journal	December 1989
Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review Rawat, Waseem; Wang, Zenghui Neural Computation, Vol. 29, Issue 9 https://doi.org/10.1162/neco_a_00990	journal	September 2017
A survey on Image Data Augmentation for Deep Learning Shorten, Connor; Khoshgoftaar, Taghi M. Journal of Big Data, Vol. 6, Issue 1 https://doi.org/10.1186/s40537-019-0197-0	journal	July 2019
Deep learning in attosecond metrology Brunner, Christian; Duensing, Andreas; Schröder, Christian Optics Express, Vol. 30, Issue 9 https://doi.org/10.1364/OE.452108	journal	April 2022
Neural-network-powered pulse reconstruction from one-dimensional interferometric correlation traces Kolesnichenko, Pavel V.; Zigmantas, Donatas Optics Express, Vol. 31, Issue 7 https://doi.org/10.1364/OE.479638	journal	March 2023
In situ characterization of few-femtosecond laser pulses by learning from first-principles calculations Geffert, Otfried; Kolbasova, Daria; Trabattoni, Andrea Optics Letters, Vol. 47, Issue 16 https://doi.org/10.1364/OL.460513	journal	August 2022
On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation Bach, Sebastian; Binder, Alexander; Montavon, Grégoire PLOS ONE, Vol. 10, Issue 7 https://doi.org/10.1371/journal.pone.0130140	journal	July 2015
Explainable AI: A Review of Machine Learning Interpretability Methods Linardatos, Pantelis; Papastefanopoulos, Vasilis; Kotsiantis, Sotiris Entropy, Vol. 23, Issue 1 https://doi.org/10.3390/e23010018	journal	December 2020
iNNvestigate neural networks! Alber, Maximilian; Lapuschkin, Sebastian; Seegerer, Philipp arXiv https://doi.org/10.48550/arXiv.1808.04260	preprint	January 2018

Similar Records

Criteria for the observation of strong-field photoelectron holography

Journal Article · 2011 · Physical Review. A · OSTI ID:22093576

Marchenko, T.; Huismans, Y.; Schafer, K. J.; +1 more

Strong-field ionization of helium in the independent-electron model

Journal Article · 1995 · Physical Review A · OSTI ID:115917

Geltman, S

Ionization-induced frequency shifts in intense femtosecond laser pulses

Journal Article · 1992 · Journal of the Optical Society of America, Part B: Optical Physics; (United States) · OSTI ID:6897668

Penetrante, B M; Bardsley, J N; Wood, W M; +2 more

Title: Femtosecond pulse parameter estimation from photoelectron momenta using machine learning

Citation Formats

References (60)

Similar Records

Related Subjects