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Optical autocorrelation

Optical autocorrelation is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Optical autocorrelation rather than just read about it. In short: In optics, various autocorrelation functions can be experimentally realized. The field autocorrelation may be used to calculate the spectrum of a source of light, while the intensity autocorrelation and the interferometric autocorrelation are commonly used to estimate the duration of ultrashort pulses produced by modelocked lasers.

Optical autocorrelation — main illustration
Optical autocorrelation — illustration

Key takeaways

  • Optical autocorrelation belongs to physics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Optical autocorrelation to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Optical autocorrelation from memory before moving on to harder problems.

Reference excerpt

In optics, various autocorrelation functions can be experimentally realized. The field autocorrelation may be used to calculate the spectrum of a source of light, while the intensity autocorrelation and the interferometric autocorrelation are commonly used to estimate the duration of ultrashort pulses produced by modelocked lasers. The laser pulse duration cannot be easily measured by optoelectronic methods, since the response time of photodiodes and oscilloscopes are at best of the order of 200 femtoseconds, yet laser pulses can be made as short as a few femtoseconds. In the following examples, the autocorrelation signal is generated by the nonlinear process of second-harmonic generation (SHG). Other techniques based on two-photon absorption may also be used in autocorrelation measurements, as well as higher-order nonlinear optical processes such as third-harmonic generation, in which case the mathematical expressions of the signal will be slightly modified, but the basic interpretation of an autocorrelation trace remains the same. A detailed discussion on interferometric autocorrelation is given in several well-known textbooks.

Field autocorrelation

For a complex electric field E ( t ) {\displaystyle E(t)} , the field autocorrelation function is defined by

A ( τ ) = ∫ − ∞ + ∞ E ( t ) E ∗ ( t − τ ) d t {\displaystyle A(\tau )=\int _{-\infty }^{+\infty }E(t)E^{*}(t-\tau )dt}

The Wiener-Khinchin theorem states that the Fourier transform of the field autocorrelation is the spectrum of E ( t ) {\displaystyle E(t)} , i.e., the square of the magnitude of the Fourier transform of E ( t ) {\displaystyle E(t)} . As a result, the field autocorrelation is not sensitive to the spectral phase.

The field autocorrelation is readily measured experimentally by placing a slow detector at the output of a Michelson interferometer. The detector is illuminated by the input electric field E ( t ) {\displaystyle E(t)} coming from one arm, and by the delayed replica E ( t − τ ) {\displaystyle E(t-\tau )} from the other arm. If the time response of the detector is much larger than the time duration of the signal E ( t ) {\displaystyle E(t)} , or if the recorded signal is integrated, the detector measures the intensity I M {\displaystyle I_{M}} as the delay τ {\displaystyle \tau } is scanned:

I M ( τ ) = ∫ − ∞ + ∞ | E ( t ) + E ( t − τ ) | 2 d t {\displaystyle I_{M}(\tau )=\int _{-\infty }^{+\infty }|E(t)+E(t-\tau )|^{2}dt}

Expanding I M ( τ ) {\displaystyle I_{M}(\tau )} reveals that one of the terms is A ( τ ) {\displaystyle A(\tau )} , proving that a Michelson interferometer can be used to measure the field autocorrelation, or the spectrum of E ( t ) {\displaystyle E(t)} (and only the spectrum). This principle is the basis for Fourier transform spectroscopy.

Intensity autocorrelation To a complex electric field E ( t ) {\displaystyle E(t)} corresponds an intensity I ( t ) = | E ( t ) | 2 {\displaystyle I(t)=|E(t)|^{2}} and an intensity autocorrelation function defined by

A ( τ ) = ∫ − ∞ + ∞ I ( t ) I ( t − τ ) d t {\displaystyle A(\tau )=\int _{-\infty }^{+\infty }I(t)I(t-\tau )dt}

The optical implementation of the intensity autocorrelation is not as straightforward as for the field autocorrelation. Similarly to the previous setup, two parallel beams with a variable delay are generated, then focused into a second-harmonic-generation crystal (see nonlinear optics) to obtain a signal proportional to ( E ( t ) + E ( t − τ ) ) 2 {\displaystyle (E(t)+E(t-\tau ))^{2}} . Only the beam propagating on the optical axis, proportional to the cross-product E ( t ) E ( t − τ ) {\displaystyle E(t)E(t-\tau )} , is retained. This signal is then recorded by a slow detector, which measures

… excerpt ends here. Continue reading the full article.

Illustrations

Optical autocorrelation: Classification of the different kinds of optical autocorrelation.
Classification of the different kinds of optical autocorrelation.
Optical autocorrelation: Setup for a field autocorrelator, based on a Michelson interferometer. L: modelocked laser, BS: beam splitter, M1: moveable mirror providing a variable delay line, M2: fixed mirror, D: energy detector.
Setup for a field autocorrelator, based on a Michelson interferometer. L: modelocked laser, BS: beam splitter, M1: moveable mirror providing a variable delay line, M2: fixed mirror, D: energy detector.
Optical autocorrelation: Two ultrashort pulses (a) and (b) with their respective field autocorrelation (c) and (d). Note that the autocorrelations are symmetric and peak at zero delay. Unlike pulse (a), pulse (b) exhibits an instantaneous frequency sweep, called chirp, and therefore contains more bandwidth than pulse (a). Therefore, the field autocorrelation (d) is shorter than (c), because the spectrum is the Fourier transform of the field autocorrelation (Wiener-Khinchin theorem).
Two ultrashort pulses (a) and (b) with their respective field autocorrelation (c) and (d). Note that the autocorrelations are symmetric and peak at zero delay. Unlike pulse (a), pulse (b) exhibits an instantaneous frequency sweep, called chirp, and therefore contains more bandwidth than pulse (a). Therefore, the field autocorrelation (d) is shorter than (c), because the spectrum is the Fourier transform of the field autocorrelation (Wiener-Khinchin theorem).
Optical autocorrelation: Two ultrashort pulses (a) and (b) with their respective intensity autocorrelation (c) and (d). Because the intensity autocorrelation ignores the temporal phase of pulse (b) that is due to the instantaneous frequency sweep (chirp), both pulses yield the same intensity autocorrelation.  Here, identical Gaussian temporal profiles have been used, resulting in an intensity autocorrelation width 21/2 longer than the original intensities. Note that an intensity autocorrelation has a background that is ideally half as big as the actual signal. The zero in this figure has been shifted to omit this background.
Two ultrashort pulses (a) and (b) with their respective intensity autocorrelation (c) and (d). Because the intensity autocorrelation ignores the temporal phase of pulse (b) that is due to the instantaneous frequency sweep (chirp), both pulses yield the same intensity autocorrelation. Here, identical Gaussian temporal profiles have been used, resulting in an intensity autocorrelation width 21/2 longer than the original intensities. Note that an intensity autocorrelation has a background that is ideally half as big as the actual signal. The zero in this figure has been shifted to omit this background.
Optical autocorrelation: Setup for an interferometric autocorrelator, similar to the field autocorrelator above, with the following optics added: L: converging lens, SHG: second-harmonic generation crystal, F: spectral filter to block the fundamental wavelength.
Setup for an interferometric autocorrelator, similar to the field autocorrelator above, with the following optics added: L: converging lens, SHG: second-harmonic generation crystal, F: spectral filter to block the fundamental wavelength.

Worked examples

Example 1 — a first encounter with Optical autocorrelation

Start with the simplest possible case. Write down what Optical autocorrelation claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Optical autocorrelation before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Optical autocorrelation ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Optical autocorrelation

In research
Optical autocorrelation appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Optical autocorrelation in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Optical autocorrelation is common in secondary-school and first-year university syllabi. It links to neighbouring topics Laser science, Nonlinear optics, Optical metrology, so understanding it makes those chapters shorter.
In everyday life
Look for Optical autocorrelation outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Optical autocorrelation in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Optical autocorrelation means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Optical autocorrelation out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Optical autocorrelation in simple terms?

In optics, various autocorrelation functions can be experimentally realized. The field autocorrelation may be used to calculate the spectrum of a source of light, while the intensity autocorrelation and the interferometric autocorrelation are commonly used to estimate the duration of ultrashort pul…

Why does Optical autocorrelation matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Optical autocorrelation?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Optical autocorrelation.

Tags

  • Laser science
  • Nonlinear optics
  • Optical metrology

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