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Quantum imaging
Quantum imaging
Quantum imaging
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Quantum imaging[1][2] is a new sub-field of quantum optics that exploits quantum correlations such as quantum entanglement of the electromagnetic field in order to image objects with a resolution or other imaging criteria that is beyond what is possible in classical optics. Examples of quantum imaging are quantum ghost imaging,[3] quantum lithography,[4] imaging with undetected photons,[5] sub-shot-noise imaging,[6][7] and quantum sensing. Quantum imaging may someday be useful for storing patterns of data in quantum computers and transmitting large amounts of highly secure encrypted information. Quantum mechanics has shown that light has inherent "uncertainties" in its features, manifested as moment-to-moment fluctuations in its properties. Controlling these fluctuations—which represent a sort of "noise"—can improve detection of faint objects, produce better amplified images, and allow workers to more accurately position laser beams.[8]

Quantum imaging methods

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Quantum imaging can be done in different methods. One method uses scattered light from a free-electron laser. This method converts the light to quasi-monochromatic pseudo-thermal light.[9] Another method known as interaction-free imaging is used to locate an object without absorbing photons.[10] One more method of quantum imaging is known as ghost imaging. This process uses a photon pair to define an image. The image is created by correlations between the two photons, the stronger the correlations the greater the resolution.[11]

Quantum lithography is a type of quantum imaging that focuses on aspects of photons to surpass the limits of classical lithography. Using entangled light, the effective resolution becomes a factor of N lesser than the Rayleigh limit of .[12] Another study determines that waves created by Raman pulses have narrower peaks and have a width that is four times smaller than the diffraction limit in classical lithography.[13] Quantum lithography has potential applications in communications and computing.

Another type of quantum imaging is called quantum metrology, or quantum sensing. The goal of these processes is to achieve higher levels of accuracy than equivalent measurements from classical optics. They take advantage of quantum properties of individual particles[14] or quantum systems[15] to create units of measurement. By doing this, quantum metrology enhances the limits of accuracy beyond classical attempts.[16]

Photonics

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In photonics and quantum optics, quantum sensors are often built on continuous variable systems, i.e., quantum systems characterized by continuous degrees of freedom such as position and momentum quadratures. The basic working mechanism typically relies on using optical states of light which have squeezing or two-mode entanglement. These states are particularly sensitive to record physical transformations that are finally detected by interferometric measurements.

In practice

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Absolute photon sources
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Many of the procedures for executing quantum metrology require certainty in the measurement of light. An absolute photon source is knowing the origin of the photon which helps determine which measurements relate for the sample being imaged. The best methods for approaching an absolute photon source is through spontaneous parametric down-conversion (SPDC). Coincidence measurements are a key component for reducing noise from the environment by factoring in the amount of the incident photons registered with respect to the photon number.[17] However, this is not a perfected system as error can still exist through inaccurate detection of the photons.

Types of quantum metrology

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Quantum ellipsometry
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Classical ellipsometry is a thin film material characterization methodology used to determine reflectivity, phase shift, and thickness resulting from light shining on a material. Though, it can only be effectively used if the properties are well known for the user to reference and calibrate. Quantum ellipsometry has the distinct advantage of not requiring the properties of the material to be well-defined for calibration. This is because any detected photons will already have a relative phase relation with another detected photon assuring the measured light is from the material being studied.[18]

Quantum optical coherence tomography (QOCT)
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Optical coherence tomography uses Michelson interferometry with a distance adjustable mirror. Coherent light passes through a beam splitter where one path hits the mirror then the detector and the other hits a sample then reflects into the detector. The quantum analogue uses the same premise with entangle photons and a Hong–Ou–Mandel interferometer. Coincidence counting of the detected photons permits more recognizable interference leading to less noise and higher resolution.

Real-world applications

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As research in quantum imaging continues, more and more real-world methods arise. Two important ones are ghost imaging and quantum illumination. Ghost imaging takes advantage of two light detectors to create an image of an object that is not directly visible to the naked eye. The first detector is a multi-pixel detector that does not view the subject object while the second, a single-pixel (bucket) detector, views the object.[18] The performance is measured through the resolution and signal-to-noise ratio (SNR). SNRs are important to determine how well an image looks as a result of ghost imaging. On the other hand, resolution and the attention to detail is determined by the number of "specks" in the image.[19] Ghost imaging is important as it allows an image to be produced when a traditional camera is not sufficient.

Quantum Illumination was first introduced by Seth Lloyd and collaborators at MIT in 2008[20] and takes advantage of quantum states of light. The basic setup is through target detection in which a sender prepares two entangled system, signal and idler. The idler is kept in place while the signal is sent to check out an object with a low-reflective rate and high noise background. A reflection of the object is sent back and then the idler and reflected signal combined to create a joint measurement to tell the sender one of two possibilities: an object is present or an object is absent. A key feature of quantum illumination is entanglement between the idler and reflected signal is lost completely. Therefore, it is heavily reliant on the presence of entanglement in the initial idler-signal system.[21]

Current uses

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Quantum imaging is expected to have a lot of potential to expand. In the future, it could be used to store patterns of data in quantum computers and allow communication through highly encrypted information [citation needed]. Quantum imaging techniques can allow improvement in detection of faint objects, amplified images, and accurate position of lasers. Today, quantum imaging (mostly ghost imaging) is studied and tested in areas of military and medical use. The military aims to use ghost imaging to detect enemies and objects in situations where the naked eye and traditional cameras fail. For example, if an enemy or object is hidden in a cloud of smoke or dust, ghost imaging can help an individual to know where a person is located and if they are an ally or foe. In the medical field, imaging is used to increase the accuracy and lessen the amount of radiation exposed to a patient during x-rays. Ghost imaging could allow doctors to look at a part of the human body without having direct contact with it, therefore, lowering the amount of direct radiation to the patient [citation needed]. Similar to the military, it is used to look at objects that cannot be seen with the human eye such as bones and organs with a light with beneficial properties.[22]

References

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Bibliography

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Quantum imaging

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from Grokipedia
Quantum imaging is a subfield of that harnesses non-classical properties of light, such as entanglement, squeezing, and spatial correlations, to achieve imaging capabilities that surpass the limitations of , including enhanced resolution beyond the diffraction limit, sub-shot-noise sensitivity, and the ability to form images without direct detection of interacting with the object. These quantum advantages stem primarily from sources like (SPDC) in nonlinear crystals, which generate entangled pairs, and advanced detectors such as (SPAD) arrays that resolve spatial correlations. The field traces its origins to the 1990s, building on foundational experiments testing , such as Bell inequality violations using entangled produced via SPDC, first demonstrated in 1988. A pivotal milestone was the 1995 demonstration of ghost imaging by Shih and colleagues, which used correlated pairs—one interacting with the object and the other serving as a reference—to reconstruct images through coincidence detection, highlighting non-local quantum correlations akin to the Einstein-Podolsky-Rosen (EPR) paradox. Subsequent developments in the integrated array detectors to enable faster, parallel measurements, transitioning from scanned point detectors to full-field imaging. Key techniques in quantum imaging include quantum ghost imaging (QGI), which reconstructs object details via intensity correlations between spatially separated beams, and quantum imaging with undetected photons (QIUP), employing nonlinear interferometers to detect phase shifts in entangled pairs without the imaging s ever reaching the detector. Other methods leverage squeezed light to suppress in amplitude or phase measurements, achieving precision below the standard , and NOON states (entangled states of N s in two modes) for super-resolution in interferometric setups. Recent advances, particularly since 2019, incorporate single- emitters and bright squeezed sources for practical implementations, addressing challenges like low flux through hybrid classical-quantum protocols. Applications of quantum imaging span biological microscopy, where low-light techniques minimize sample damage; and , enhancing target detection in noisy environments via quantum illumination; and astronomy, for resolving faint celestial objects with reduced background noise. In , it enables non-invasive probing at unconventional wavelengths, such as mid-infrared imaging using visible detectors. Ongoing challenges include scaling source brightness and detector efficiency for real-world deployment, but emerging technologies like metasurface-based SPDC and machine learning-enhanced reconstruction promise broader impact.

Fundamentals

Definition and principles

Quantum imaging is a field within that utilizes non-classical properties of light, such as quantum correlations, entanglement, superposition, and non-classical states, to achieve imaging capabilities surpassing the limitations of classical optics, including sub-shot-noise sensitivity and enhanced resolution. These advancements stem from exploiting quantum mechanical effects to reduce noise and improve signal detection in low-light conditions. At the core of quantum imaging lie several key principles. Classical sources exhibit Poissonian , where the variance in number equals the , leading to shot-noise-limited performance. In contrast, non-classical sources produce sub-Poissonian statistics, with variance less than the , enabling sub-shot-noise sensitivity by suppressing arrival fluctuations. , particularly in biphoton pairs, introduces non-local correlations that allow joint measurements to extract information unattainable with independent photons, enhancing through spatial or temporal coincidences. The Heisenberg imposes fundamental limits on simultaneous measurements of like position and , setting the standard for resolution in classical ; however, quantum resources such as entanglement can approach the Heisenberg limit, scaling precision as the inverse of the number rather than its . Typical quantum imaging systems employ a source of entangled photons generated via (SPDC) in a nonlinear pumped by a , producing correlated signal and idler pairs. These pairs are spatially separated, with one beam interacting with the object of interest and the other serving as a reference; detection schemes, such as coincidence counting with single-photon detectors or bucket detectors, reconstruct the image by correlating the outputs. Non-classical correlations from such setups improve the (SNR) by suppressing noise below the classical shot-noise level.

Quantum advantages over classical

Quantum offers significant improvements in resolution over classical methods by leveraging quantum correlations to resolve features below the limit. In classical optical , the Rayleigh criterion limits resolution to approximately λ/(2NA), where λ is the and NA is the , but quantum approaches can achieve effective resolutions down to λ/(2N), with N the number of entangled photons. For instance, quantum using entangled photon pairs enables pattern resolutions twice that of classical , as the nonlinear scales as cos²(Nk·r), allowing subwavelength features. Similarly, quantum centroid estimation techniques have demonstrated the ability to localize point sources with variances approaching the Heisenberg limit, surpassing the standard by factors of up to 2 in one dimension. Sensitivity gains in quantum imaging arise from sub-shot-noise performance, which reduces the uncertainty in photon counting below the classical Poisson limit, enabling reliable detection in low-light conditions where classical imaging would be noise-dominated. By correlating photon detections, quantum methods suppress background noise and achieve signal-to-noise ratios superior to classical direct imaging, with noise reduction factors as low as 0.5 in spatial correlation measurements. This is particularly evident in quantum illumination protocols, where entangled states allow detection of weak targets against high noise, improving contrast by factors of 6 dB over classical strategies in certain regimes. Quantum imaging also enhances speed and efficiency through parallel processing of quantum correlations, permitting faster image acquisition with reduced exposure times in noisy or low-flux environments. For example, ghost imaging with entangled photons reconstructs images using fewer total photons per pixel—often below one—compared to classical methods requiring hundreds for comparable quality, thereby minimizing exposure durations and sample damage. This efficiency stems from the ability to extract spatial information from correlation statistics rather than sequential intensity measurements, achieving acquisition rates that scale favorably with photon budget in dim conditions. Quantitative comparisons between quantum and classical imaging are often framed using information-theoretic metrics such as the , which quantifies the amount of usable information about image parameters in the . The classical Cramér-Rao bound sets a lower limit on the variance of estimators as Var(θ) ≥ 1/F_C, where F_C is the classical , but quantum methods can access higher values via the F_Q ≥ F_C. In imaging tasks like object localization, F_Q can exceed F_C by factors approaching N for N-particle entangled states, tightening the bound and enabling precisions unattainable classically. The quantum Cramér-Rao bound formalizes this advantage for parameter estimation in : δθ≥1FQ,\delta \theta \geq \frac{1}{\sqrt{F_Q}},
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