Frequency-resolved optical gating
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In optics, frequency-resolved optical gating (FROG) is a derivative of autocorrelation, but is far superior in its ability to measure ultrafast optical pulse shapes. Further, it can determine the phase of the pulse. In the most common configuration, FROG is simply a background-free autocorrelator followed by a spectrometer. It is the two-dimensional nature of the FROG trace that allows the extraction of the actual pulse shape and phase from the data.
The basics
Frequency-Resolved refers to the fact that the final signal is a spectrum. Before explaining Optical Gating, it helps to recognize that the pulse is really interacting with itself. In most configurations, the pulse is split and recombined, as in an interferometer. However, in this case, the recombination does not occur on a beam-splitter, but rather in a nonlinear medium, which allows the two beams to interact with each other. It is this interaction that allows the pulses to "gate" the spectral information of the other pulse. So Optical Gating refers to the fact that the measured spectrum is really from a time-slice of the pulse, and that time-slice is determined by the pulse nonlinear interaction. The gate function depends on the type of nonlinear interaction allowed.Mathematically the FROG trace is simply a spectrogram but with an unknown gate function:
- [I_(\omega,\tau) = \left | \int_^ P(t) G(t-\tau) e^ dt \right | ^2]
| [P^(t) = E(t)] | [G^(t) = E(t)] | : Second-harmonic generation FROG |
| [P^(t)=E(t)] | E(t)|^2] | : Polarization gating FROG |
| [P^(t)=E(t)^2] | [G^(t)=E(t)] | : Self-diffraction FROG |
| [P^(t)=E(t)] | [G^(t)=E(t)^2] | : Third-harmonic generation FROG |
For example second-harmonic generation FROG (SHG FROG) would be:
- [I^_(\omega,\tau) = \left | \int_^ E(t)E(t-\tau)e^ dt \right | ^2]
- [I^_(\omega,\tau) = \left | \int_^ E(t)|E(t-\tau)|^2 e^ dt \right | ^2]
FROG algorithm
The FROG algorithm is all about phase retrieval. The FROG trace measured in the lab is the exact intensity of [I_(\omega,\tau)]; however, it is missing the phase information. To start off with define a signal field:
- [E_(t,\tau) = P(t)G(t-\tau)]
- [\tilde_(\omega,\tau) = \int_^ E_(t,\tau)e^ dt]
- [I_(\omega,\tau) = \left | \tilde_(\omega,\tau) \right | ^2]
- [\left | \tilde_(\omega,\tau) \right | = \sqrt(\omega,\tau)}]
An iterative algorithm is used to determine this unknown phase.
- Start with an initial guess for [E(t)\,].
- Synthetically create [E_(t,\tau)\,] from [E(t)\,].
- Fourier transform the time axis to the frequency domain, yielding [\tilde_(\omega,\tau)].
- Replace the amplitude (preserving the phase) of [\tilde_(\omega,\tau)] with the amplitude measured in the lab ([I_(\omega,\tau)\,]). Call this [\tilde_(\omega,\tau)].
- Take [\tilde_(\omega,\tau)] and inverse Fourier transform it back into the time domain ([E'_(t,\tau)\,]).
- Apply a little magic (more on that later) to extract the best [E(t)\,] from [E'_(t,\tau)\,].
- Synthetically create [E_(t,\tau)\,] from [E(t)\,].
- Fourier transform the time axis to the frequency domain, yielding [\tilde_(\omega,\tau)].
- Compare [\left |\tilde_(\omega,\tau)\right |] to [I_(\omega,\tau)\,] (generally the rms difference). If this error (termed the "G" error) is sufficiently small, exit the loop.
- GOTO 4.
The \"Magic step\"
More on this later, or consult the FROG book below.Competing techniques
- Spectral phase interferometry for direct electric-field reconstruction
- Streak camera - not a significant competitor. Streak cameras have picosecond response times.
Further reading
External links
- [FROG Page by Rick Trebino] (the co-inventor of FROG)
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