The evidence
The Sloan Digital Sky Survey (SDSS) data, combined with the work of Sylos Labini's team, continues to reignite discussions on the fractal nature of galaxies and the potential implications this discovery bears for our understanding of the Universe. Though the core findings date back nearly two decades, they continue to question prevailing cosmological models.
The fractal pattern hypothesized by Labini's team indicates that galaxies are not randomly distributed throughout the Universe but instead exhibit a repeating, self-similar arrangement at various scales—simply put a pattern.
What lends weight to Labini's team's argument is the collaboration of physicists Nikolay Vasilyev and Yurij Baryshev from St. Petersburg State University.
Their analysis suggests that the fractal nature of galaxies persists up to scales of approximately 100 million light years.
The universe’s homogeneity—the principle that the universe appears uniform on a large scale—is a significant aspect of modern cosmology, but do the implications of this fractal pattern question this fundamental principle?
One Hundred Million light years
Since the findings span a range of around 100 million light-years, the observed self-similarity is limited, meaning that large-scale homogeneity remains valid with the broader observational consensus.
Limited self-similarity, also known as approximate self-similarity, refers to the recurrence of patterns across different scales, typically in an approximate or statistical sense rather than through exact replication.
This differs from strict self-similarity, where patterns repeat identically across scales.
Strict self-similarity, as seen in perfect fractals such as the Koch snowflake, involves exact replication of patterns at all scales. Limited self-similarity acknowledges that real-world phenomena do not exhibit such perfection.
Coastlines, mountain ranges, tree branches, clouds, and even blood vessels exhibit repeating, self-similar patterns—but only across a specific range of scales. These natural fractals exhibit genuine fractal behaviour but are constrained by physical limitations, including energy, material composition, and spatial scale.
At microscopic or macroscopic extremes, the pattern breaks down. Such bounded repetition is far more representative of natural phenomena, as strict fractals exist only within mathematical constructs and their digital visualizations, not in the physical world. For this reason, limited self-similarity proves more practical in modelling real-world systems.
While mathematical fractals like the Koch snowflake repeat endlessly, natural structures only do so up to a point — their patterns are approximate, not infinite.
Globular clusters exhibit fractal-like structure within their bounds — dense star fields repeating in approximate patterns across scales. But unlike mathematical fractals, the self-similarity fades as we zoom in.
Once we step outside these clusters, the pattern changes. The interstellar medium takes over, with new fractal-like structures appearing in molecular clouds, filaments, and nebulae — each shaped by different physical processes, each with its own kind of self-similarity.
Beyond Uniformity
Fractal cosmology remains a minority view, but many anticipate it won't stay on the fringe for much longer. As science enthusiasts sift through data, the general public is expected to begin to utilize more fractal terminology, such as self-similarity, to describe the universe in the years ahead. It can be argued that this is already occurring.
Although it may seem that fractal cosmology may be out of the game given that the evidence applies only up to a limited range of around 100 million light-years, interestingly, a fractal cosmology does not require that its structure remain entirely constant at every scale, as long as it shows repeating patterns in its structure in the same way. Small-scale fractal cosmology is undoubtedly still in the game as well.
All in all, it's still promising for fractal cosmologists and enthusiasts alike, as they continue to push beyond uniformity.
Comments