Globular clusters (GCs) are big, round groups of stars that are some of the oldest things in our universe. They help scientists learn how stars and galaxies formed. A team led by Jiaqi Ying studied 8 old globular clusters in our Milky Way to find out their exact ages. They used powerful computer models and real data from the Hubble Space Telescope (HST) to match star patterns and test different star evolution factors. These included things like how stars mix inside, how hot they are, and how fast they burn fuel. By using 10,000 models and millions of data points, they found that the clusters are between 11.5 to 13.5 billion years old. They also discovered that the lower the metal content in a cluster, the older it usually is. More than half of the age uncertainty comes from figuring out how far the clusters are and how dust affects the light from them. This study is important because it gives scientists better tools to understand the age of the universe and how our Milky Way galaxy grew over time and the idea that if globular clusters are 13.5 billion years old, then the universe must be older than that.
Globular clusters (GCs) are some of the oldest and most fascinating objects in the universe. They are tightly packed groups of stars that orbit around galaxies, including our Milky Way. Because they are so old and contain many stars of different ages and types, scientists use them as “natural laboratories” to study how stars change over time and how galaxies like ours formed.
In a recent scientific study, researcher Jiaqi Ying and their team looked at eight very old globular clusters in the Milky Way. By using powerful computer models and data from space telescopes like the Hubble Space Telescope (HST), they were able to estimate the true age of these clusters. Their work helps us understand how old the Milky Way is and gives us clues about the early history of the universe.
Let’s explore what they found—and why it matters.
What Are Globular Clusters?
Globular clusters are big, spherical collections of stars—each cluster can have tens of thousands to millions of stars. These stars are held together by gravity, which keeps them tightly packed in a ball-like shape. They usually orbit in the outer parts (or halos) of galaxies.
What makes GCs special is that they are very old—most of them formed over 10 billion years ago. This means they were born just a few hundred million years after the Big Bang, when the universe itself was still young.
Because all the stars in a globular cluster formed around the same time, they are useful for studying stellar evolution—how stars change as they get older. They also help scientists learn about the formation of galaxies and cosmic history.
Why Study the Age of Globular Clusters?
Knowing how old globular clusters are helps scientists answer big questions like:
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How old is our galaxy, the Milky Way?
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How and when did galaxies form?
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How old is the universe?
If we know the oldest globular clusters are, say, 13 billion years old, then the universe must be at least that old.
However, measuring the exact age of a globular cluster is difficult. There are many uncertainties—things like distance, how much dust is blocking the light, or how stars behave under different conditions.
That’s why the recent work by Jiaqi Ying and their team is so important. They found new ways to measure the age of globular clusters more accurately by accounting for many sources of error.
The Study: Eight Ancient Clusters Under the Microscope
The researchers focused on eight globular clusters in the Milky Way:
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NGC 104 (also known as 47 Tucanae)
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NGC 4147
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NGC 5053
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NGC 5466
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NGC 6362
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NGC 6809 (M55)
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NGC 7078 (M15)
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NGC 7099 (M30)
These clusters were chosen because they are very old and have different metal contents. (In astronomy, “metallicity” refers to the amount of elements heavier than hydrogen and helium in a star. Older stars usually have lower metallicity.)
The researchers wanted to find the absolute age of each cluster—not just how old one is compared to another, but the actual number in billions of years. They used a powerful computer program called the Dartmouth Stellar Evolution Program to simulate how stars evolve.
They ran 10,000 different models for each cluster, changing parameters like how energy moves inside a star (convection), how elements mix, and how nuclear reactions happen in the star’s core.
How Did They Do It?
The team used a process called isochrone fitting. An isochrone is a line on a chart called a color-magnitude diagram (CMD) that shows where stars of the same age and different masses should appear.
Here’s how it worked:
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Create synthetic star data: They made fake star data using their models, including about 4 million data points for each scenario.
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Compare with real data: They used two advanced statistical methods:
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Voronoi binning
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2D Kolmogorov–Smirnov test
These techniques compared the theoretical models with the real observational data from the Hubble Space Telescope (HST). They also used Gaussian process minimization to find the best-fitting distance and reddening values.
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Adjust for dust and distance: They used smart methods to figure out how much interstellar dust (called reddening) and how far away the clusters are. These factors can change how the stars appear to us.
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Estimate age: After comparing all the data, they used bootstrap resampling, a statistics technique to determine the best possible age for each cluster. They also measured the uncertainty (how sure they are of the results).
What Did They Find?
The team found that the absolute ages of the eight globular clusters ranged from about 11.5 billion years to 13.5 billion years. That means these clusters formed very early in the universe’s history.
They also found:
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Lower metallicity clusters are older: Clusters with fewer heavy elements tended to be older, which makes sense since the first stars had fewer metals.
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Uncertainty comes mainly from distance and reddening: More than 50% of the error in age estimation came from not knowing the exact distance or how much dust was in the way.
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Other important factors included:
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Metal content (metallicity)
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The way stars mix their internal materials (mixing length)
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How helium spreads in stars (helium diffusion)
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Interestingly, even though many globular clusters have multiple stellar populations (groups of stars with slightly different compositions), these differences did not strongly affect the age estimates.
Why Does This Matter?
This study is important for several reasons:
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Better age estimates for GCs: Until now, many studies only estimated relative ages—which cluster is older than another. This study provides absolute ages with improved accuracy.
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Improves models of stellar evolution: By testing many different parameters, the researchers help improve how scientists simulate how stars evolve over time.
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Connects GCs to galaxy formation: The age-metallicity relation found in this study tells us about how and when the Milky Way built up its stars. It suggests that metal-poor stars formed early, possibly in smaller galaxies that later merged into the Milky Way.
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Helps estimate the age of the universe: If globular clusters are 13.5 billion years old, then the universe must be older than that. These results help confirm other measurements, like those from the cosmic microwave background or Hubble’s expansion law.
Looking Forward
The researchers suggest that future studies should:
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Analyze more metal-rich globular clusters.
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Use newer data from telescopes like James Webb Space Telescope (JWST).
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Improve models that take ultraviolet (UV) light into account.
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Tackle challenges like modeling how stars are affected by being part of binary systems.
Their ultimate goal is to build a full age-metallicity relation for all Milky Way globular clusters. This will be a powerful tool to understand not just when these clusters formed, but how our galaxy grew over billions of years.
Conclusion
Globular clusters are more than just beautiful balls of stars—they are ancient record-keepers of the cosmos. By studying them closely, we can unlock secrets about how stars live and die, how galaxies form, and how old our universe truly is.
The work by Jiaqi Ying and their team shows that with careful modeling, smart use of telescope data, and a lot of computing power, we can measure the ages of these clusters more accurately than ever before. Their findings push the boundaries of our cosmic knowledge and bring us one step closer to answering one of humanity’s oldest questions: How did the universe begin?
Reference: Jiaqi (Martin)Ying, Brian Chaboyer, Michael Boylan-Kolchin, Daniel Weisz, Rowan Goebel-Bain, "The Absolute Age of Milky Way Globular Clusters", ApJ, 2025. https://arxiv.org/abs/2505.02969
Technical Terms
1. Globular Clusters (GCs)
A group of thousands to millions of stars tightly packed together by gravity. They are some of the oldest objects in the universe and are found around galaxies like the Milky Way.
2. Metallicity ([Fe/H])
This tells us how much metal (like iron) a star has compared to the Sun. In astronomy, everything heavier than hydrogen and helium is called a metal.
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A lower number (like -2.3) means the star has very few metals and is very old.
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A higher number means it has more metals and is younger.
3. Isochrone
A curve on a star diagram that shows stars of the same age but different masses. Scientists use isochrones to compare theory and observation and to figure out how old stars or star clusters are.
4. Stellar Evolution
It’s how stars change over time—from birth to death. Depending on the star's mass, it can become a white dwarf, neutron star, or black hole.
5. Color-Magnitude Diagram (CMD)
It’s like a star report card. It shows a graph where stars are placed based on their brightness (magnitude) and color (temperature). Scientists use it to study star ages and properties.
6. Main-Sequence Turn-Off
This is the point on the CMD where stars begin to leave the main part of their life and start to get older. It helps scientists estimate the age of a star cluster.
7. Reddening
When starlight passes through dust, it looks redder and dimmer than it actually is. This effect needs to be corrected to measure stars properly.
8. Distance Modulus
A way to calculate the distance to stars or clusters by comparing how bright they appear from Earth vs how bright they actually are.
9. Alpha Abundance
It shows how much of certain elements (like oxygen, magnesium) a star has. These elements are made in massive stars and are important for knowing how and when stars formed.
10. Mixing Length
It’s a way to describe how heat moves inside a star. It’s like describing how bubbles rise in boiling water. This helps scientists build accurate star models.
11. Helium Diffusion
It means helium slowly moves inside a star due to gravity and pressure. This small change affects how a star evolves over time.
12. Monte Carlo Method
A way to solve problems using random sampling. It helps scientists test many possibilities quickly to find the most likely result.
13. Synthetic CMD
A computer-made star diagram that shows what a star cluster would look like based on a model. Scientists compare it with real data to test their theories.
14. Bootstrap Resampling
A statistical method where the computer takes many random samples from the data to estimate how uncertain or reliable the results are.
15. Isochrone Fitting
The process of matching real star data to theoretical isochrones to estimate the age and other properties of a star cluster.
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