A new method could improve cosmology research by analyzing supernovae together with the galaxies that host them.
An international collaboration led by scientists at the Institute of Cosmos Sciences of the University of Barcelona (ICCUB) has created a new approach that may sharpen what researchers can learn about how the Universe expands and what dark energy is.
The research, published in Nature Astronomy, introduces a framework called CIGaRS. It is designed to pull more information from Type Ia supernovae, exploding stars that are central to cosmology, mainly by using imaging data rather than relying on expensive spectroscopic observations.
The method could help scientists take full advantage of the enormous datasets expected from upcoming astronomical surveys, especially those from the Vera C. Rubin Observatory.
Why supernovae are important for understanding the Universe
Type Ia supernovae occur when white dwarf stars explode. Because these explosions usually have nearly the same true brightness, astronomers treat them as “standard candles.” By comparing how bright they should be with how bright they appear from Earth, researchers can estimate distances across the cosmos.
This method played a crucial role in revealing that the Universe’s expansion is speeding up, an effect linked to dark energy, one of the deepest unsolved questions in physics. But there is an important complication: Type Ia supernovae are not perfectly identical.
The problem: supernovae are affected by their environments
During the past 20 years, astronomers have found that the brightness of Type Ia supernovae is subtly influenced by the galaxies where they occur. For instance, supernovae in older or more massive galaxies can appear slightly different from those in younger or smaller galaxies.
Until now, researchers have typically corrected for these effects using relatively simple approximations. Those shortcuts may limit how precisely scientists can use supernovae to measure cosmic distances.
A unified solution: comprehensive models
The new work addresses this challenge by modeling many connected factors together: the supernova explosions, their host galaxies, dust that dims and reddens their light, how often supernovae occur across cosmic history, and the expansion of the Universe itself.
Rather than treating each element separately, the team created one self-consistent model that connects them through both physical and statistical relationships.
“A powerful way of modeling the Universe is to simulate it ab initio in the computer using Bayesian inference,” says Raúl Jiménez (ICREA-ICCUB), co-author of the study. “This provides a way to vary all possible parameters at the same time to predict what Universe we live in. Furthermore, by having this capacity, one can look into possible ‘unknown unknown’ systematics to understand their effect. The impact of these systematics in our inference is arguably the most important missing ingredient in current approaches to model the Universe.”
Artificial intelligence and cosmology
To make this broad modeling strategy practical, the researchers used a modern approach called simulation-based inference.
The process begins with scientists creating many simulated universes based on physical models. A neural network (a type of artificial intelligence) then learns how the simulated observations connect to the underlying physical parameters. Once trained, the system can use real astronomical data to infer those parameters directly.
This makes it possible to analyze tens of thousands of supernovae together, a scale that traditional techniques could not realistically handle.
A key result: precise distances without spectroscopy
One major finding is that the method can accurately estimate galaxy distances, known as redshifts, using images alone.
Redshift describes how much a galaxy’s light has been stretched by the expansion of the Universe. It helps astronomers determine both how distant a galaxy is and how far back in time we are seeing it.
The new approach reaches a level of precision similar to spectroscopic measurements, but without requiring spectra. That matters because future sky surveys will identify millions of possible supernovae, while only a small share can be followed up with spectroscopy.
Preparation for the Rubin Observatory era
The Vera C. Rubin Observatory, now being built in Chile, will soon launch a 10-year survey of the sky. It is expected to detect an extraordinary number of supernovae, and roughly 99% of them will be observed only photometrically, meaning through images taken in different colors.
The CIGaRS framework is designed specifically for this kind of data-rich environment.
“Unlike other frameworks, which require analytic simplifications, our no-compromise end-to-end simulation-based inference approach is uniquely capable of extracting the full cosmological and astrophysical information from the Rubin Observatory’s hard-earned data, while avoiding the pitfalls of selection and modeling biases,” says Konstantin Karchev (ICCUB-SISSA Trieste), lead author of the study.
Beyond cosmology: discovering how stars explode
Beyond improving dark energy measurements, the study may also help researchers better understand how Type Ia supernovae form and when they occur. By reconstructing how supernova rates depend on the ages of stars in galaxies, the model offers a way to investigate long-standing questions about the stellar systems that produce these explosions.
The results suggest that combining physics-based modeling with artificial intelligence can address major weaknesses in current cosmological analyses. According to the authors, this method could improve cosmological constraints by as much as a factor of four compared with traditional approaches that depend only on a smaller group of spectroscopically observed supernovae.
As the Rubin Observatory prepares to reshape astronomy, tools such as CIGaRS could help researchers interpret its data more completely and better understand the Universe those observations reveal.
Reference: “CIGaRS I: combined simulation-based inference from type Ia supernovae and host photometry” by Konstantin Karchev, Roberto Trotta and Raúl Jiménez, 6 May 2026, Nature Astronomy.
DOI: 10.1038/s41550-026-02842-5
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3 Comments
B Memo 2605311346_Source 1. Reinterpretation 【()】
Source 1.
https://scitechdaily.com/scientists-find-a-smarter-way-to-measure-the-universe-using-exploding-stars/
1. Scientists have discovered a smarter way to measure the universe using exploding stars.
_Astronomers have developed a new AI-based framework that can obtain much more information from exploding stars used to measure the universe.
_The new method is expected to improve cosmological research by analyzing supernovae and the galaxies harboring them together.
ㅡㅡㅡㅡㅡㅡ
【&&&&b1.() Within the next 50 years, future astronomical observations are expected to see active data sharing through the linkage of observation equipment networks with observatories on the Earth’s surface, utilizing the Lagrange point 1.2.3.4.5 between the Earth and the Moon. —Furthermore, it seems that real-time data sharing via Lagrange point ‘five’ will be achieved in the latter half of the year between the Sun, each planet in the solar system, and their moons.
—Due to gravitational quasypros, the numerous Lagrange point clouds in the solar system will overlap with electromagnetic waves and various cosmic rays, serving as large-capacity data storage devices capable of reprocessing and transmitting/receiving data. Hmm. 1416.
—Thus, my prediction regarding humanity’s future scientific civilization ten centuries from now is that it will make it possible to map 100 percent of the entire galaxy, including subsurface resource information and GPS geography of planets within less than one meter. Hmm. 1424.
—30,000 years from now, in 2026, human civilization will become the master of our galaxy, ourmsbase.galaxy. Hmm. 1501. However, the universe still has separate masters for countless massive galaxies. Hmm. 1303.
—How will humans evolve? Are you curious?
I am a future civilization prophet on msbase master. Hmm. 1322.
—My guess is that ordinary stone fragments, stones.face, exist as multiple personalities. They live for a biological lifespan of 10,000 years with up to 100 personalities.
—That ordinary 22nd-century future human will live out their life vigorously spreading the noble romance of life to 100 million extraterrestrial descendants in our galaxy. Heh. 1519.
】
1-1.
_An international collaborative research team led by scientists at the Institute of Space Sciences (ICCUB) at the University of Barcelona has developed a new approach that allows researchers to find out more details about the expansion patterns of the universe and the nature of dark energy.
_Published in Nature Astronomy, this study introduces a framework called CIGaRS. This framework is designed to extract more information about Type Ia supernova explosions, which play a significant role in cosmology, by utilizing image data primarily instead of relying on expensive spectroscopic observations.
_This method could help scientists make the most of future astronomical investigations, particularly the vast datasets expected to emerge from the Vera C. Rubin Observatory.
ㅡㅡㅡㅡㅡ
【&&&&&&a1. Light reveals images in darkness. The longer light shines, the more detailed information about the surroundings it provides.
ㅡThe Rubin Observatory intends to use this very method to peer into the universe from any location within Rubin’s observable instrument system capabilities in space. Hmm. 1330.
ㅡThe cosmic information imaged by supernova explosions is so vast that it could be efficient to direct arbitrary storage to exosphere Lagrange points.
—At an arbitrary point in the universe (sidems4.xyz.position,topological_shape), the superimposed image information of a specific region of the universe resulting from a supernova explosion could be reflected and stored, leaving behind chemical and physical traces. Aha. 1344.
—Since that place could be the same as the arbitrary location observed by James Webb, it might be possible to edit the shared cosmic information. Aha. 1332.
】
1-2. Why are supernovae important for understanding the universe?
_Type Ia supernovae occur when a white dwarf explodes. Because these explosions generally have nearly identical actual brightness, astronomers treat them as “standard candles.”
_Researchers can estimate distances throughout the universe by comparing the actual brightness of a supernova with the brightness observed from Earth.
_This method played a crucial role in revealing that the expansion rate of the universe is accelerating, a phenomenon related to dark energy, one of the most profound unsolved questions in physics.
However, there is one significant problem: Type Ia supernovae are not perfectly identical.
1-3
Problem: Supernovae are affected by their surrounding environment.
Over the past 20 years, astronomers have discovered that the brightness of Type Ia supernovae is subtly influenced by the galaxy in which they occur. For example, supernovae in older or massive galaxies may appear slightly different from those in younger or less massive galaxies.
Until now, researchers have generally corrected for these effects using relatively simple approximations. Such simplistic methods can limit the accuracy with which scientists use supernovae to measure cosmic distances.
2. Integrated Solution: A Comprehensive Model
This new research solves this challenge by modeling several related factors together, including supernova explosions, the galaxies harboring the supernovae, the dust that dims or reddens the supernova light, the frequency of supernovae throughout cosmic history, and the expansion of the universe itself.
Instead of treating each element individually, the research team created a single, coherent model that connects the elements through physical and statistical relationships.
2-1.
“One of the powerful methods for modeling the universe is to simulate it from scratch on a computer using Bayesian inference,” says Raúl Jiménez (ICREA-ICCUB), a co-author of this study.
“This allows us to predict what the universe we live in will look like by changing all possible parameters simultaneously. Furthermore, leveraging this capability allows us to investigate ‘unknown’ systematic errors and understand their impact. The influence of these systematic errors on inference can be considered the most significant drawback of current approaches to cosmic modeling.”
2-2. Artificial Intelligence and Cosmology
To put this broad modeling strategy into practical use, the research team utilized a cutting-edge approach called simulation-based inference.
This process begins with scientists creating multiple virtual universes based on physical models. Then, a neural network (a type of artificial intelligence) learns how virtual observation results are linked to fundamental physical parameters. Once training is complete, the system can directly infer these parameters using actual astronomical data.
This enables the simultaneous analysis of tens of thousands of supernovae, a scale that was practically impossible with existing technology.
2-3.
Key Result: Accurate Distance Measurement Without Spectroscopic Analysis
One of the major achievements of this study is that this method can accurately estimate the distance of a galaxy—specifically its redshift—using only images.
Redshift is a phenomenon that indicates how much a galaxy’s light has stretched due to the expansion of the universe. This allows astronomers to determine the distance of a galaxy and the past time of the galaxy we are observing.
3.
This new approach achieves a level of precision similar to spectroscopic measurements but does not require spectral data. This is significant because while millions of potential supernovae will be discovered in future astronomical surveys, only a tiny fraction of them will be follow-up observations possible through spectroscopic observation. _Preparing for the Rubin Observatory Era
The Vera C. Rubin Observatory, currently under construction in Chile, is scheduled to begin a 10-year astronomical observation survey soon. This survey is expected to discover a massive number of supernovae, approximately 99% of which will be observed exclusively through photometric observations—that is, images captured in different colors.
_The CIGaRS framework has been specifically designed for this data-rich environment.
3-1.
“Unlike other frameworks that require analytical simplification, the uncompromising end-to-end simulation-based inference approach possesses a unique ability to fully extract cosmological and astrophysical information from the hard-won data of the Rubin Observatory while avoiding the pitfalls of selection bias and modeling bias,” says Konstantin Karchev (ICCUB-SISSA Trieste), the lead author of this study.
ㅡㅡㅡㅡㅡㅡㅡㅡ
【&&&&&a1.() Now, the futuristic future of the universe can be designed in detail. 1405.
.Using unique extraterrestrial gases or substances that react to electromagnetic waves, it would be possible to send massive amounts of data from Earth’s surface or L2 to the gravity-zero area of the extraterrestrial Lagrage. Aha. 1245. 1247.
—Thus, it is speculated that by the mid-22nd century, it will be possible to peer into the depths of the universe through real-time entangled motion data using more widely interconnected cosmic data, allowing for the creation of a GPS map for space travel.
】
Using a new AI assisted SN1a model also partly based on the assumption that the universe IS expanding, to prove that the universe is expanding ?
Sounds more like mumbo jumbo pseudoscience to me.
thanks for this