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Can we take 3D pictures with single mid-infrared photons?

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Converting mid-infrared echoes into visible light with a femtosecond laser gate lets an ordinary silicon camera build detailed 3D images from extremely few photons.

Source

Mid-infrared single-photon 3D imaging

Fang J, Huang K, Wu E, et al. · Light, science & applications · 2023

doi.org/10.1038/s41377-023-01179-2Read the full paper ↗19 citationscc by

Study at a glance

Design
Other — Time-of-flight imaging: 3070 nm pulses illuminate a scene; returning photons are upconverted to 771 nm in a chirped-poled lithium niobate crystal by a delayed femtosecond pump and recorded on an EMCCD
N
No sample count; test objects were a coin under a silicon wafer, stacked silicon wafers and a ceramic goldfish
Population
Test objects imaged with a lab-built mid-infrared upconversion imaging system
Outcome
Depth and lateral resolution, volumetric reconstruction of layered samples, and image recovery at very low signal-to-noise

Structured fields used in claim comparison tables when every cited study has a complete layer.

What they did

The researchers illuminated objects with ultrashort mid-infrared pulses and collected the reflected light in a nonlinear crystal where a synchronized femtosecond pump pulse converted it to near-visible light only when both pulses overlapped in time. Scanning the pump delay sliced the scene by depth, and a megapixel silicon camera recorded each slice. They imaged a coin through a thick silicon wafer, two stacked wafers, and a ceramic goldfish at very low light, using a neighbour-product denoising algorithm for the dimmest data.

What they found

The system resolved a height difference of 30 micrometres on the coin through the wafer, with a lateral resolution of about 60 micrometres over a field roughly 2.5 cm wide. It located every internal interface of the stacked wafers, allowing the refractive index to be inferred from the axial offset. With the denoiser, the goldfish's 3D shape was recovered at a detected signal of only 0.05 photons per pixel per second, far below the background noise.

The limits

What it doesn't show

This is a technique demonstration on a few static, hand-picked objects, not a systematic comparison with mid-infrared OCT on the same samples. Low-light imaging needed long exposures (seconds per frame across hundreds of depth slices), so it is slow for moving scenes. The denoiser assumes smooth, spatially correlated surfaces and could suppress real fine or isolated features; performance on scattering biological tissue was not tested.

Key terms

Sum-frequency upconversion
A nonlinear optical process that combines an infrared photon with a pump photon to produce a higher-energy photon that silicon detectors can see.
Optical gating
Using a short pump pulse so conversion only happens when signal and pump overlap in time, selecting photons from a narrow depth slice.
Time-of-flight imaging
Measuring distance from the time light takes to travel to an object and back.
Quasi-phase matching
Periodically reversing a crystal's poling so a nonlinear process stays efficient; a chirped period accepts many angles for wide-field imaging.
EMCCD
An electron-multiplying camera sensitive enough to register single photons.

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Quiz yourself

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What converts the reflected mid-infrared light into light a silicon camera can detect?

Common questions

Why not just use a mid-infrared camera?

Direct mid-infrared detectors are noisy, often need cryogenic cooling and are slow; converting the light lets a low-noise, fast silicon camera do the detection.

What sets the depth resolution?

The width of the cross-correlation between the pump and signal pulses, not the camera's speed.

Why use mid-infrared at all?

It passes through materials like silicon and scatters less, and molecules have distinctive absorption bands there.

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