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A global model of intensity autocorrelation to determine laser pulse duration |
Yufei Peng(彭雨菲), Liqiang Liu(刘励强), Lihong Hong(洪丽红), and Zhiyuan Li(李志远)† |
School of Physics and Optoelectronics, South China University of Technology, Guangzhou 510640, China |
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Abstract We present a new global model of collinear autocorrelation based on second harmonic generation nonlinearity. The model is rigorously derived from the nonlinear coupled wave equation specific to the autocorrelation measurement configuration, without requiring a specific form of the incident pulse function. A rigorous solution of the nonlinear coupled wave equation is obtained in the time domain and expressed in a general analytical form. The global model fully accounts for the nonlinear interaction and propagation effects within nonlinear crystals, which are not captured by the classical local model. To assess the performance of the global model compared to the classic local model, we investigate the autocorrelation signals obtained from both models for different incident pulse waveforms and different full-widthes at half-maximum (FWHMs). When the incident pulse waveform is Lorentzian with an FWHM of 200 fs, the global model predicts an autocorrelation signal FWHM of 399.9 fs, while the classic local model predicts an FWHM of 331.4 fs. The difference between the two models is 68.6 fs, corresponding to an error of 17.2%. Similarly, for a sech-type incident pulse with an FWHM of 200 fs, the global model predicts an autocorrelation signal FWHM of 343.9 fs, while the local model predicts an FWHM of 308.8 fs. The difference between the two models is 35.1 fs, with an error of 10.2%. We further examine the behavior of the models for Lorentzian pulses with FWHMs of 100 fs, 200 fs and 500 fs. The differences between the global and local models are 17.1 fs, 68.6 fs and 86.0 fs, respectively, with errors approximately around 17%. These comparative analyses clearly demonstrate the superior accuracy of the global model in intensity autocorrelation modeling.
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Received: 01 September 2023
Revised: 24 November 2023
Accepted manuscript online: 09 January 2024
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PACS:
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42.65.-k
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(Nonlinear optics)
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42.65.Ky
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(Frequency conversion; harmonic generation, including higher-order harmonic generation)
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42.65.Re
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(Ultrafast processes; optical pulse generation and pulse compression)
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Fund: Project supported by the Science and Technology Project of Guangdong (Grant No. 2020B010190001), the National Natural Science Foundation of China (Grant No. 11974119), the Guangdong Innovative and Entrepreneurial Research Team Program (Grant No. 2016ZT06C594), and the National Key R&D Program of China (Grant No. 2018YFA0306200). |
Corresponding Authors:
Zhiyuan Li
E-mail: phzyli@scut.edu.cn
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Cite this article:
Yufei Peng(彭雨菲), Liqiang Liu(刘励强), Lihong Hong(洪丽红), and Zhiyuan Li(李志远) A global model of intensity autocorrelation to determine laser pulse duration 2024 Chin. Phys. B 33 054207
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[1] Hendow S T and Shakir S A 2010 Opt. Express 18 10188 [2] Cheng J, Perrie W, Sharp M, Edwardson S P, Semaltianos N G, Dearden G and Watkins K G 2009 Appl. Phys. A 95 739 [3] Soong H K and Malta J B 2009 American Journal of Ophthalmology 147 189 [4] Strickland D and Mourou G 1985 Opt. Commun. 55 447 [5] Maine P, Strickland D, Bado P, Pessot M and Mourou G 1988 IEEE Journal of Quantum Electronics 24 398 [6] Maine P and Mourou G 1988 Opt. Lett. 13 467 [7] Nakane T, Kotecha A, Sente A, McMullan G, Masiulis S, Brown P M G E, Grigoras I T, Malinauskaite L, Malinauskas T, Miehling J, Uchański T, Yu L, Karia D, Pechnikova E V, de Jong E, Keizer J, Bischoff M, McCormack J, Tiemeijer P, Hardwick S W, Chirgadze D Y, Murshudov G, Aricescu A R and Scheres S H W 2020 Nature 587 152 [8] Klimov V I, Ivanov S A, Nanda J, Achermann M, Bezel I, McGuire J A and Piryatinski A 2007 Nature 447 441 [9] Engel G S, Calhoun T R, Read E L, Ahn T K, Mančal T, Cheng Y C, Blankenship R E and Fleming G R 2007 Nature 446 782 [10] Davis K M, Miura K, Sugimoto N and Hirao K 1996 Opt. Lett. 21 1729 [11] Deubel M, von Freymann G, Wegener M, Pereira S, Busch K and Soukoulis C M 2004 Nat. Mater. 3 444 [12] Trebino R and Kane D J 1993 J. Opt. Soc. Am. A 10 1101 [13] Kane D J and Trebino R 1993 Opt. Lett. 18 823 [14] Iaconis C and Walmsley I A 1998 Opt. Lett. 23 792 [15] Gallmann L, Sutter D H, Matuschek N, Steinmeyer G, Keller U, Iaconis C and Walmsley I A 1999 Opt. Lett. 24 1314 [16] Akturk S, Kimmel M, O’Shea P and Trebino R 2003 Opt. Express 11 491 [17] Bowlan P, Gabolde P, Shreenath A, McGresham K, Trebino R and Akturk S 2006 Opt. Express 14 11892 [18] Weber H P 1967 J. Appl. Phys. 38 2231 [19] Weber H P 1968 J. Appl. Phys. 39 6041 [20] Diels J C M, Fontaine J J, McMichael I C and Simoni F 1985 Appl. Opt. 24 1270 [21] Hirayama T and Sheik-Bahae M 2002 Opt. Lett. 27 860 |
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