Could quantum physics help us find Earth 2.0?
When astronomers talk about directly imaging an exoplanet orbiting a faraway star, the analogy they most commonly use is trying to spot a firefly next to a massive searchlight. An Earth-like exoplanet is incredibly dim—usually between 100 million and 10 billion times fainter than its host star.
Understandably, that makes them very difficult to see. But a new paper by Hyunsoo Choi of Hanyang University in South Korea and his co-authors, which is available as a preprint on arXiv, describes a theoretical solution—using a mix of smart computer algorithms and quantum physics.
Quantum physics is probably not the first thing that comes to mind when thinking about imaging something as large as a planet. In fact, the fundamental tension at the heart of physics between quantum mechanics and relativity doesn't bode well for its usefulness either. But to understand how it can be useful, it's first helpful to understand the concept of the Rayleigh limit.
If two objects are incredibly close to each other and each is emitting photons, their light blurs together into a single blob if they are separated by less than a distance known as the Rayleigh limit. In the case of exoplanets, this would mean the planet's light is completely subsumed by that of a star. A normal photodetector will detect a photon but will not be able to distinguish whether it came from the planet or its host star.
Enter quantum mechanics. In quantum mechanics, photons contain much more information than just their energy level, or "brightness." One such tidbit of information is known as wave shape, and measuring a photon based on its wave shape is known as spatial-mode measurement.
By designing a system in which photons are sorted by their wave patterns before they hit a photon detector, the system can extract additional information that regular cameras miss.
Making this work in real time required building a continuous feedback loop into the image-analysis software. First, the researchers introduced a logarithmic scale to ensure their algorithm could track extreme differences in brightness between the planet and the star.
As the algorithm begins to guess what the star system looks like (i.e., how many planets and stars there are), it calculates something called the Symmetric Logarithmic Derivative, which tells the photon sorter how to shift and adjust to ensure the maximum amount of quantum information is retained.
Crucially, they replaced a human-generated guess about the number of planets the algorithm should look for with a statistical tool called the Bayesian Information Criterion.
After implementing their feedback loop, the authors ran the algorithm on a simulated star system with one star and two planets—one of which was only 10,000 times dimmer than its host star, while the other was 100 million times dimmer. Both were well within the Rayleigh limit.
Using Monte Carlo simulations (which slightly vary starting conditions over multiple runs), the algorithm correctly guessed the total number of objects (i.e., 3) 72.5% of the time.
When the system worked, it could locate the planets in the simulation to within a single pixel. It was also able to estimate the true brightness of the ultra-dim planet within a factor of two 99.7% of the time, assuming it had correctly estimated the number of objects.
Simulations are great, but they don't always translate neatly into the real world. The authors did their best to simulate it, intentionally disrupting the alignment of the virtual telescope and creating the datasets used in the simulation.
The algorithm was able to adapt to this artificially introduced noise on the fly, with its success rate dropping only to 71.3%. However, there are numerous other sources of noise in real-world telescopes, and it's unclear how well the algorithm can handle other noise at this point.
Admittedly, the paper describes only a computer simulation. But even so, it represents a massive leap forward in developing quantum imaging systems that could find planets up to 100 million times dimmer than their star—a massive improvement from current quantum imaging systems that can manage only a 1/1,000 contrast between their target planet and its host star.
It also clearly delineates a path forward for hardware developers. While physical implementations typically lag well behind theoretical advances, it's only a matter of time before someone builds one of these systems and attempts to find a new exoplanet with it.
It remains to be seen what other kinks will need to be worked out for that effort to be successful. But from a purely theoretical physics standpoint, this combination of exoplanet hunting with quantum imaging is a truly unique take on one of the most fascinating areas of modern astronomy.
Publication details
Hyunsoo Choi et al, Exoplanet Detection Using Adaptive Quantum-Optimal Measurement, arXiv (2026). DOI: 10.48550/arxiv.2607.06931
Who's behind this story?
BSc Life Sciences & Ecology. Microbiology lab background with pharmaceutical news experience in oil, gas, and renewable industries. Full profile →
Master's in physics with research experience. Long-time science news enthusiast. Plays key role in Science X's editorial success. Full profile →
Citation: Could quantum physics help us find Earth 2.0? (2026, July 30) retrieved 30 July 2026 from https://phys.org/news/2026-07-quantum-physics-earth.html
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.