利用交叉偏振波濾波與基於機器學習脈衝診斷�提升雙 CPA 前端架構之中央大學一百兆瓦�雷射系統時間對比
2026/06/25
研究生:楊世帆
指導教授:白植豪 教授
Temporal Contrast Enhancement of the NCU 100-TW
Laser System through a Double-CPA Front End Incorporating Cross-Polarized Wave Filtering and Machine-Learning Pulse Diagnostic
Outline
1
2
Introduction
Laser evolution
Source:
[1] Laser Programs The First 25 Years… 1972–1997 https://www.osti.gov/servlets/purl/16710
[2] F. J. McClung, R. W. Hellwarth; Giant Optical Pulsations from Ruby. J. Appl. Phys. 1 March 1962; 33 (3): 828–829.
[3] Shinji Yamashita, Sze Yun Set, Advances and challenges of mode-locked fiber lasers, Optics Communications, Volume 578, 2025, 131406
[1]
[2]
[3]
3
Introduction
Chirped Pulse Amplification – CPA (1985)
© Johan Jarnestad/The Royal Swedish Academy of Sciencesa
4
Introduction
Laser evolution
5
Introduction
Definition of the temporal contrast
(Not Enough for experiment)
Double CPA
6
Theory - Double CPA
CPA 1
Nonlinear Contrast Filter
CPA 2
Ring Regenerative
Amplifier
Cross-Polarization Wave
generation (XPW)
Multi-pass
Amplifier
Effects that would affect the spectral bandwidth in CPA amplifier
Gain narrowing ↑
Dynamic gain saturation ↑
7
Theory - Double CPA
Spectral Shaping Filter
Source: Alphine Research Optics.
The depth of the dip is control by the angle between incident polarization.
The position of the dip is control by the incident angle.
8
Theory - Double CPA
Gain / Loss / Transmission Spectrum ↑
Transmission Spectrum of New Polarizer
9
Theory - Double CPA
Without spectral shaping filter
With spectral shaping filter
38 nm
48 nm
Output spectrum bandwidth: 38 nm
Output Energy: 1.7 mJ
Output spectrum bandwidth: 48 nm
Output Energy: 1.3 mJ
Experiment measured maximum spectrum bandwidth: 51 nm
Cube polarizer transmission spectrum
Spectral shaping filter loss spectrum
Ti: Sapphire gain spectrum
Total loss spectrum
Amplifier input spectrum
Amplifier output spectrum
10
Theory - XPW process
With Maxwell’s equations, the coupled-wave equation for XPW
12
Theory - XPW process
Numerical calculation of the coupled-wave equation for XPW
Initial Conditions
13
Theory - XPW process
Split-Step Fourier Method (SSFM)
14
Theory - XPW process
Compare of [001]-cut and [011]-cut
[001]-cut
[011]-cut
15
Theory - XPW process
[011]-cut crystal with different input intensity
16
Theory - XPW process
Spectrum change
When the intensity increase, self-phase modulation would dominant the spectrum broadening.
Spectrum unstable, self focusing, etc.
The XPW spectrum remain the same when the input intensity is low.
17
Theory - Dispersion Control via Machine Learning
Convolutional Neural Network (CNN)
Convolutional Layer – Extract features from the input data
Pooling Layer – Reduce the dimensionality of the data
Fully connected Layer – Combined all the features
Training: (Input Data, Output Data) → Feature Tensor (model)
18
Theory - Dispersion Control via Machine Learning
Dual-Input Convolutional Neural Network (CNN)
2nd, 3rd, 4th dispersion
19
Theory - Dispersion Control via Machine Learning
Data generation
Amplitude
Amplitude from superposition of random gaussian function with noise ↑
20
Theory - Dispersion Control via Machine Learning
Data generation
21
Theory - Dispersion Control via Machine Learning
After Training
22
Construction of Laser System - Overview
23
Construction of Laser System - Overview
76 MHZ
10 HZ
10 HZ
2 HZ
0.5 mJ (1%)
2 mJ
1 mJ
200 mJ
3J
CPA 1
CPA 2
24
Construction of Laser System - Pulse stretcher
Offner-type pulse stretcher
25
Construction of Laser System - Pulse compressor
26
Construction of Laser System - Ring Regenerative Amplifier
27
Construction of Laser System - XPW
28
100-TW After Upgrade - Ring Regenerative Amplifier
Pump beam on crystal
Total energy: 4.3 (mJ)
29
100-TW After Upgrade - Ring Regenerative Amplifier
Seed on crystal
30
100-TW After Upgrade - Ring Regenerative Amplifier
Loss of Regenerative Cavity
Loss = 5.2 %
Output Energy = 1.2 mJ / pulse
Without Spectral Shaping Filter
With Spectral Shaping Filter
Loss = 14.4 %
Output energy = 0.56 mJ / pulse
31
100-TW After Upgrade - Ring Regenerative Amplifier
Spectrum Bandwidth with Spectral Shaping Filter
Without Spectral Shaping Filter
With Spectral Shaping Filter
FWHM = 28.5 nm
Central Wavelength = 800.0 nm
FWHM = 51.7 nm
Central Wavelength = 796.6 nm
28.5 nm
51.7 nm
Minimum Pulse duration = 41.3 fs
Minimum Pulse duration = 30.1 fs
Avg. 100 shots
Avg. 100 shots
32
100-TW After Upgrade - Ring Regenerative Amplifier
Output Beam Profile
Before Beam Expander
After Beam Expander
Beam Diameter X: 2.4 mm
Beam Diameter Y: 2.2 mm
Beam Diameter X: 5.2 mm
Beam Diameter Y: 5.0 mm
33
100-TW After Upgrade – XPW
XPW Beam Profile
Before XPW
After XPW
Beam Diameter X: 1.7 mm
Beam Diameter Y: 1.7 mm
Beam Diameter X: 2.3 mm
Beam Diameter Y: 3.0 mm
34
100-TW After Upgrade - XPW
Single Crystal
35
100-TW After Upgrade - XPW
XPW with different input intensity
Measurement error due to the energy meter.
36
100-TW After Upgrade - XPW
XPW spectral bandwidth with different input intensity (Low intensity)
S = 0.77, FWHM = 50.6 nm
S = 1.12, FWHM = 47.4 nm
S = 1.35, FWHM = 48.1 nm
S = 1.67, FWHM = 48.7 nm
37
100-TW After Upgrade - XPW
XPW spectral bandwidth with different input intensity (High intensity)
S = 2.08, FWHM = 57.1 nm
S = 2.27, FWHM = 63.5 nm
S = 2.66, FWHM = 73.4 nm
S = 2.79, FWHM = 82.7 nm
S = 2.49, FWHM = 68.7 nm
38
100-TW After Upgrade - XPW
XPW spectral bandwidth with different input intensity
39
100-TW After Upgrade - XPW Contrast
ns-contrast with XPW
Improve 3 order
Before XPW
After XPW
40
100-TW After Upgrade - XPW Contrast
ps-contrast with XPW
Before XPW
After XPW
Improve 2 order
41
100-TW After Upgrade - XPW Contrast
Final XPW output
42
100-TW After Upgrade - 100-TW Beam Line
Spectrum and Pulse Duration Comparation
Spectrum FWHM = 31.5 nm
Pulse duration = 41 fs
Spectrum FWHM = 39.0 nm
Pulse duration = 37 fs
Source:
[1] EKSMA optics https://eksmaoptics.com/out/media/EKSMA_Optics_Thin_Film_Polarizers-56.pdf
[1]
43
100-TW After Upgrade - 100-TW Beam Line
100-TW Contrast after upgrade
(Close to the instrument measurement limitation)
44
Dispersion Retrieval with Machine Learning for SSA
Test With Fused Silica
Dispersion of Fused Silica
Transform limit add Fused silica
45
Dispersion Retrieval with Machine Learning for SSA
Machine Learning Input Spectrum
46
Dispersion Retrieval with Machine Learning for SSA
Test two Different Training Model – Different Trace Range
Model 1: -400 fs to 400 fs
0 mm ↑
1.6 mm ↑
8 mm ↑
16 mm ↑
| GDD | TOD | FOD |
MAE | | | |
R² | 0.99 | 0.97 | 0.92 |
| | | |
0 mm | 0 | 0 | 0 |
1.6 mm | 58 | 44 | 18 |
8 mm | 290 | 220 | 90 |
16 mm | 580 | 440 | 180 |
47
Dispersion Retrieval with Machine Learning for SSA
Test two Different Training Model – Different Trace Range
Model 2: -75 fs to 75 fs
0 mm ↑
1.6 mm ↑
8 mm ↑
16 mm ↑
| GDD | TOD | FOD |
MAE | | | |
R² | 0.98 | 0.89 | 0.48 |
| | | |
0 mm | 0 | 0 | 0 |
1.6 mm | 58 | 44 | 18 |
8 mm | 290 | 220 | 90 |
16 mm | 580 | 440 | 180 |
48
Conclusion and Prospects
Dual-Input CNN
With model 2, the prediction is close to the measurement result.
Problems
Resolving the absolute sign ambiguity of third-order and fourth-order dispersion within the experimental noise floor remains a limitation
Result and Conclusion
49
Conclusion and Prospects
Future Prospects - High Field Experiment
Proton Acceleration Experiment (TNSA)
Maximum Proton Energy: 3 MeV → 8 MeV (With the same conditions)
Future Publication
Optics Express - Construction of Double CPA and XPW, Enhancement of Temporal Contrast.
Thanks for listening
2
Reference