Testing tiny telescope robots reveals design changes that could improve galaxy maps

Astronomers have cataloged billions of stars and hundreds of billions of galaxies. We have found thousands of planets orbiting stars. We can also map where galaxies sit and trace how the universe changes over time.

The universe also contains objects that are too faint, too far away or too crowded to study easily. Simply taking a picture of a galaxy tells us only parts of its story.

When we look at breathtaking pictures of the universe, we rarely see the hidden limits of the telescopes that produced them. Even the best telescopes have mechanical blind spots that can cause them to miss key galaxies. If we ignore these missed targets, they can affect our understanding of how galaxies and other cosmic objects evolve over time.

Our new paper, published in the Astronomical Journal, presents a computer tool that shows how instrument design can address these hardware limitations. It models how tiny telescope robots work so we can identify missed targets and map the universe more accurately.

Thousands of tiny robots

Modern astronomy is not just about individual stars and galaxies.

Instead, scientists design massive surveys to scan large areas of the sky multiple times. The bigger these surveys are, the easier it is to learn how stars form, how galaxies grow and how the universe changes over time.

Modern cosmic survey telescopes use thousands of tiny robots to position optical fibers that collect light from distant stars and galaxies. Future telescopes plan to use more than 20,000 of these at once.

Each robot’s optical fiber directs the light from a distant star or galaxy to a tool called a multi-object spectrograph. This splits the light to show astronomers what the galaxy is made of and how far away it is.

The tiny robots can do a great job, but they have physical limits. They can bump into each other if they get too close. In crowded parts of the sky where galaxies sit close together in dense clusters, the robots can run out of room.

As a result, the system skips some galaxies to avoid crashes. These missing galaxies can create blind spots. If we use these biased data, our maps can give us misleading answers about the universe.

Finding the blind spots

To keep the robots safe, engineers set strict rules for the space between robot bases (called pitch), how far each robot can move around its base (called patrol radius) and the safety gap two robots must keep so they do not touch (called exclusion radius).

To understand how these constraints introduce blind spots, our new study introduces a proof-of-concept computer tool that acts as a testing ground before a telescope turns on.

Our software can test many combinations of robot systems and astronomical targets. It acts like a flight simulator for telescopes. It mimics the process of moving a robot to position its optical fiber to observe many targets over repeated visits to the sky.

This tracks how well the system assigns fibers to targets, called allocation efficiency. It also tracks how many total galaxies are observed over time, called survey completeness.

In our study, we ran tests using specifications from real telescopes. Our results showed three key rules.

First, setting the smallest pitch, or using the highest fiber density, gives the best completeness and efficiency.

Second, when the pitch is fixed, increasing how far a robot can reach is the next best way to improve fiber assignment.

Third, making the safety gap smaller also helps prevent missed targets, but it has a smaller effect than changing the robot’s reach.

Our tool bridges the gap between science goals and machine limits. By testing these rules early, astronomers can identify and address technology limits when designing new instruments. Engineers can use our code to test ideas for future instruments before spending millions of dollars to build them.

There is still much of the universe that we haven’t mapped yet. Future maps of the universe will depend on more than just giant telescope mirrors. They will also need smart computer tools that improve how much telescopes can actually see.

Sometimes, mapping the whole universe starts with getting thousands of tiny robots to move in exactly the right way.

Who’s behind this story?

Swati Mestri

Swati Mestri holds a bachelor’s degree in Electronics Engineering and has worked as a content editor since 2019. She has experience editing research documents across technology, health care, and materials science, and has a particular interest in technology and space.

Full profile →

Robert Egan

Bachelor’s in mathematical biology, Master’s in creative writing. Well-traveled with unique perspectives on science and language.

Full profile →

This article is republished from The Conversation under a Creative Commons license. Read the original article.