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— Viorica Hrincu
Sometimes when you stare at the void, the void sends you a poem.
Universe—Superclusters and Voids
The average density of the universe is about `10 \times 10^{-30} \text{ g/cm}^3` or about 6 protons per cubic meter. This should put some perspective in what we mean when we speak about voids as "underdense regions".
references
contents
Before you delve into the background material for the map, calm the nerves and awaken the imagination with these space-themed tunes.
Perfect to listen to while perusing the map ... or the terrain.
2 Wicky by Hooverphonic (Live at Koningin Elisabethzaal 2012)
Space walk by Lemon Jelly
Exploration by Karminsky Experience Inc.
100 Billion Stars by Lux
Journey through the Boötes Void by Scott Lawlor
Ok, now let's get to it.
The individual catalogues of objects (stars, clusters, superclusters, voids) shown on the map are available as a parsed single file.
n TYPE
----- ------------
2 quasar
1024 supercluster
2555 void
5250 abell
9096 hr
18707 zwicky
Each element is represented by a single line and all objects start with the same fields:
TYPE ID CONSTELLATION NAME radec RA DEC lb GALACTIC_LONG GALACTGIC_LAT sglb SUPERGALACTIC_LONG SUPERGALACTIC_LAT z REDSHIFT d DISTANCE(Mly)
For some objects the NAME is blank ("-").
In addition to these fields, each object type has additional information.
Abell cluters have the number of galaxies in them (N) and the IDs of the superclusters to which they belong listed.
abell ... count N mscc/sscc ID1,ID2,...
Superclusters have the number of galaxies in them (N), their size (SIZE) and the two constellation of the supercluster's Abell's clusters (same as CONSTELLATION if the supercluster's Abell clusters are all in the same constellation).
supercluster ... count N size SIZE(Mly) con_compound CON_COMPOUND
Voids have their size void ... size SIZE
The stars, taken from the Yale Catalogue of Bright Stars, do not have a distance or redshift but have a magnitude
hr ... mag MAGNITUDE
These are the individual catalogues from Vizier used in the map and to create the single parsed file above.
V/50 Bright Star Catalogue, 5th Revised Ed., Hoffleit+, 1991
VII/110A Rich Clusters of Galaxies, Abell+, 1989
VII/4A Abell and Zwicky Clusters of Galaxies, Abell+, 1974
VII/56 Redshifts for Abell Clusters, Sarazin+, 1982
J/APJ/365/66 Redshifts of a sample of distant Abell clusters, Huchra+, 1990
VII/165A Measured Redshifts of Abell Clusters of Galaxies, Andernach, 1991
VII/177 Redshifts and Velocity Dispersions for Abell Clusters, Struble+, 1991
J/APJS/96/343 Redshifts of rich clusters of galaxies, Quintana+, 1995
J/A+A/310/8 The ESO Nearby Abell Cluster Survey I., Katgert+, 1996
J/A+A/310/31 The ESO Nearby Abell Cluster Survey. II., Mazure+, 1996
J/APJS/126/1 Abell clusters photometry, Quintana+, 2000
J/AJ/126/119 Optical and radio data for rich Abell clusters, Rizza+, 2003
VII/190 Zwicky Galaxy Catalog, Zwicky+, 1968
J/PASP/111/438 Updated Zwicky catalog (UZC), Falco+, 1999
J/MNRAS/445/4073 Two catalogues of superclusters, Chow-Martinez+, 2014
J/APJ/744/82 Catalog of cosmic voids from the SDSS-DR7, Varela+, 2012
J/MNRAS/440/1248 SDSS DR7 voids and superclusters, Nadathur+, 2014
J/APJ/835/161 A cosmic void catalog of SDSS DR12 BOSS galaxies, Mao+, 2017
VI/42 Identification of a Constellation From Position, Roman, 1987
Good places to start your exploration of the Universe.
Hoffleit, D. & Warren, Jr., W.H. The Bright Star Catalog, 5th Revised Edition (Preliminary Version) (1991)
Roman N.G. Identification of a constellation from a position Publications of the Astronomical Society of the Pacific 99 695–699 (1987)
To determine constellation shapes, I originally started with a list by Marc van der Sluys
BSC (Yale Catalogue of Bright Stars) constellation edges by Marc van der Sluys
However, many of these constellations were not the asterisms sanctioned by the IAU. I therefore corrected all the constellation shapes by manually examining the IAU map and cross-referencing the stars to the Yale Catalogue of Bright Stars. Ugh.
IAU Constellation shapes as edges between BSC stars (Yale Catalogue of Bright Stars) by Martin Krzywinski
For more details about the constellations see my IAU Constellation Shape Resources.
Abell clusters [Wikipedia]
Abell, G.O. The distribution of rich clusters of galaxies. A catalog of 2712 rich clusters found on the National Geographic Society Palomar Observatory Sky Survey The Astrophysical Journal Supplement Series 3 211–88 (1958)
LC 1101: supergiant elliptical galaxy [Wikipedia]
Abell 2029 galaxy cluster [Wikipedia]
The universe within 2 billion light years. by Richard Powell
Finelli F. et al. Supervoids in the WISE–2MASS catalogue imprinting cold spots in the cosmic microwave background Monthly Notices of the Royal Astronomical Society 455 (2016)
Kopylov A.I. & Kopylova F.G. Search for streaming motion of galaxy clusters around the Giant Void Astronomy and Astrophysics 382 389–396 (2002)
Linder U. et al. The structure of supervoids. I. Void hierarchy in the Northern Local Supervoid. Astronomy and Astrophysics 329–347 (1995)
El-Ad H. & Piran T. Voids in the large-scale structure The Astrophysical Journal 491 421–435 (1997)
List of voids [Wikipedia]
Giant void [Wikipedia]
Boötes void [Wikipedia]
Northern local supervoid [Wikipedia]
Southern local supervoid [Wikipedia]
Eridanus supervoid (CMBR Cold spot) [Wikipedia]
J1120+0641 [Wikipedia]
Mortlock D.J. et al A luminous quasar at a redshift of z = 7.085 474 616–619 (2011)
Bañados E. et al An 800-million-solar-mass black hole in a significantly neutral universe at a redshift of 7.5 Nature 553 (2018)
J1342+0928 [Wikipedia]
Celestial coordinate system [Wikipedia]
NASA/IPAC Extragalactic Database: Coordinate Transformation & Galactic Extinction Calculator
RA DEC flexible converter by Jan Skowron
How far out in the universe can we see? by Harald Lang
Redshift and distance calculator by Edward Wright
Wright, E.L. The Publications of the Astronomical Society of the Pacific 118 1711–1715 (2006)
Loeb, A. Long-term future of extragalactic astronomy Physical Review D 65 047301.1–047301.4 (2002)
Bennett, C.L. et al The 1% Concordance Hubble Constant Astrophysical Journal 794 (2014)
Propensity score weighting
The needs of the many outweigh the needs of the few. —Mr. Spock (Star Trek II)
This month, we explore a related and powerful technique to address bias: propensity score weighting (PSW), which applies weights to each subject instead of matching (or discarding) them.
Kurz, C.F., Krzywinski, M. & Altman, N. (2025) Points of significance: Propensity score weighting. Nat. Methods 22:1–3.
Happy 2025 π Day—
TTCAGT: a sequence of digits
Celebrate π Day (March 14th) and sequence digits like its 1999. Let's call some peaks.
Crafting 10 Years of Statistics Explanations: Points of Significance
I don’t have good luck in the match points. —Rafael Nadal, Spanish tennis player
Points of Significance is an ongoing series of short articles about statistics in Nature Methods that started in 2013. Its aim is to provide clear explanations of essential concepts in statistics for a nonspecialist audience. The articles favor heuristic explanations and make extensive use of simulated examples and graphical explanations, while maintaining mathematical rigor.
Topics range from basic, but often misunderstood, such as uncertainty and P-values, to relatively advanced, but often neglected, such as the error-in-variables problem and the curse of dimensionality. More recent articles have focused on timely topics such as modeling of epidemics, machine learning, and neural networks.
In this article, we discuss the evolution of topics and details behind some of the story arcs, our approach to crafting statistical explanations and narratives, and our use of figures and numerical simulations as props for building understanding.
Altman, N. & Krzywinski, M. (2025) Crafting 10 Years of Statistics Explanations: Points of Significance. Annual Review of Statistics and Its Application 12:69–87.
Propensity score matching
I don’t have good luck in the match points. —Rafael Nadal, Spanish tennis player
In many experimental designs, we need to keep in mind the possibility of confounding variables, which may give rise to bias in the estimate of the treatment effect.
If the control and experimental groups aren't matched (or, roughly, similar enough), this bias can arise.
Sometimes this can be dealt with by randomizing, which on average can balance this effect out. When randomization is not possible, propensity score matching is an excellent strategy to match control and experimental groups.
Kurz, C.F., Krzywinski, M. & Altman, N. (2024) Points of significance: Propensity score matching. Nat. Methods 21:1770–1772.
Understanding p-values and significance
P-values combined with estimates of effect size are used to assess the importance of experimental results. However, their interpretation can be invalidated by selection bias when testing multiple hypotheses, fitting multiple models or even informally selecting results that seem interesting after observing the data.
We offer an introduction to principled uses of p-values (targeted at the non-specialist) and identify questionable practices to be avoided.
Altman, N. & Krzywinski, M. (2024) Understanding p-values and significance. Laboratory Animals 58:443–446.
Depicting variability and uncertainty using intervals and error bars
Variability is inherent in most biological systems due to differences among members of the population. Two types of variation are commonly observed in studies: differences among samples and the “error” in estimating a population parameter (e.g. mean) from a sample. While these concepts are fundamentally very different, the associated variation is often expressed using similar notation—an interval that represents a range of values with a lower and upper bound.
In this article we discuss how common intervals are used (and misused).
Altman, N. & Krzywinski, M. (2024) Depicting variability and uncertainty using intervals and error bars. Laboratory Animals 58:453–456.