Testing a spread of black hole masses against many observations
Sandbox Physics ·
For an observation whose signal is a sum over individual black holes, a mass function is allowed when the integral of ψ/fmax over lnM is at most one. Each observation gets its own ratio. Combining them, or drawing one envelope through all the curves, needs assumptions that must be stated; merger rates do not satisfy the linear rule at all.
A limit curve caps a total, a mass function is a density
A published curve fmax(M) answers one question: if every black hole had mass M, how large could their total dark-matter fraction be? The mass function ψ(M)=df/dlnM is a different quantity, the fraction per logarithmic mass interval. Drawing ψ on the same axes and checking that it stays below every curve compares a density with a total. The 2026 review states this directly in its Sec. VI.
An example shows the size of the error. A lognormal with width σ=2 in lnM and f=1 has a peak height 1/(2π2)=0.20. It could sit below a curve at 0.3 everywhere and still hold more than three times the dark matter that curve allows at any single mass.
Deriving the weighted ratio for one linear observation
Let an observable A be bounded by a measurement, A≤Aexp. If each black hole adds to it independently of the others, it is linear in ψ: a background A0 plus an integral with a kernel A1(M) that encodes the physics and the instrument.
For a single mass, ψ=fδ(lnM−lnMc), the bound becomes f≤(Aexp−A0)/A1(Mc)≡fmax(Mc). The published curve therefore tells us the kernel, up to a constant. Substituting A1=(Aexp−A0)/fmax back into the general bound gives the weighted ratio. This is Eq. 12 of Carr et al. 2017 and Eqs. 25–28 of the 2026 review.
A[ψ]=A0+∫dlnMA1(M)ψ(M)≤Aexp
Linearity means no term involves two black holes at once.
Rj≡∫dlnMfmax,j(M)ψ(M)≤1
Apply it to each observation j separately. Outside the mass range where a table has data, that observation contributes nothing, and the mass there stays untested by it.
Write u=ln(M/Mc) and g(u)=1/fmax. For a narrow symmetric spread of width σ, expand g to second order. The linear term averages to zero, leaving the correction below. Where 1/fmax curves upward in lnM, a spread makes the limit stronger; where it curves downward, weaker.
The method tutorial checks this with the Subaru microlensing table. Centred at 10−8M⊙, where 1/fmax is falling away from its peak near 10−9M⊙ and bends downward, widening to σ=0.5 raises the allowed fraction from 0.00949 to 0.00964. Centred at 10−6M⊙, where 1/fmax bends upward, the same width lowers it from 0.169 to 0.160. Neither direction can be assumed.
R≈f[g(0)+2σ2g′′(0)],g(u)=fmax(Mceu)1
Valid while σ is small compared with the scale on which g changes curvature.
The safe statement is that every ratio Rj must be at most one. Carr et al. 2017 also derive a combined test in their appendix. It assumes independent observables with Gaussian errors, each linear in ψ, each with its expected value at zero black holes, and every bound quoted at the same confidence level. Under those assumptions the chi-squared statistic adds the ratios in quadrature.
The same appendix shows why a single envelope curve is not a shortcut. Folding all observations into one curve fmax=(∑jfmax,j−2)−1/2 and then applying the one-observation rule overestimates the constraint, by the triangle inequality. Taking the lowest curve at each mass has the same flaw. The Lab therefore shows each ratio on its own and puts the quadrature combination in a collapsed panel, for the linear tables only.
In the Lab’s stellar-mass preset, the OGLE ratio is 3.06 and the CMB accretion ratio is 3.58. Each alone excludes the spread. Their quadrature combination is 4.71, which holds only under the assumptions above.
j∑(∫dlnMfmax,jψ)2≤1
Carr et al. 2017 Eq. 13 and Appendix; Carr et al. 2026 Eq. 29.
Mergers involve two black holes, so the merger rate contains a term with ψ twice and the rule above does not apply. Clustering, mass segregation in galaxies and structure formation can also make an observable depend on more than one black hole at a time. The review names Lyman-alpha, dynamical and, to a lesser degree, lensing and accretion limits as affected.
For that reason the Lab draws the LIGO-Virgo-KAGRA table for reference and greys out its ratio. In the stellar-mass preset that number is 443, but it is not a valid application of the rule. The O3 analysis itself fits several mass functions directly with a hierarchical method and finds at most about 10−3 of the dark matter in black holes of 1 to 200 solar masses in every scenario it considers.
Masses can also change after formation. Accretion can grow heavy black holes and weaken limits above about ten solar masses, while clustering can strengthen accretion limits. The review suggests reading its mass functions as effective ones that already include such changes, possibly different for each observation. The Lab uses the formation mass function throughout.
Choose “Ruled out by microlensing” and predict which ratio exceeds one before reading the bars.
Choose “Stellar-mass black holes”, open the conventions panel, and compare the largest single ratio with the quadrature combination.
Drag the mass grip slowly across the Subaru curve and note where the ratio first passes one; compare that mass with where the curve itself looks lowest.
Exercises with explanations
Show that using the lowest curve at each mass, fenv(M)=minjfmax,j(M), in the one-observation rule gives a ratio at least as large as every individual Rj. Why is that not a derived bound?
Read the explanation
At each mass 1/fenv≥1/fmax,j for every j, and ψ≥0, so the integral is at least each Rj. The rule was derived for one observable with one kernel. The envelope switches kernels from mass to mass, which corresponds to no single measurement and no stated likelihood, so its value has no probabilistic meaning.
The Subaru table gives 1/fmax=120.5,105.4,86.9 at log10(M/M⊙)=−8.2,−8.0,−7.8, and 8.27,5.92,4.04 at −6.2,−6.0,−5.8. Use the second-order formula to predict whether widening a spread weakens or strengthens the limit at each centre.
Read the explanation
The second differences are 120.5−2(105.4)+86.9=−3.4 and 8.27−2(5.92)+4.04=+0.47. So g′′(0)<0 at 10−8M⊙: a spread lowers R per unit f and the limit weakens. At 10−6M⊙, g′′(0)>0 and the limit strengthens. The tutorial’s full integrals agree in both cases.
Two linear observations give R1=3.06 and R2=3.58. What is the quadrature combination, and what changes if one of them was quoted at 95% confidence and the other at 99%?
Read the explanation
3.062+3.582=4.71. The derivation needs every bound at the same confidence level, because each fmax,j is the kernel scaled by the same number of standard deviations. With mixed levels one must rescale to a common level before combining; otherwise only the separate tests are justified.
Review; arXiv lists the journal reference Riv. Nuovo Cim. (2026). Read in full: Sec. II.A.2 on non-Gaussianity, Sec. IV.C (gravitational waves), IV.E (accretion), V (asteroid-mass window), VI (Eqs. 25–29) and the captions of Figs. 2–6; parts of Sec. II and III.
Abstract only. Twenty years of OGLE data on nearly 80 million LMC stars: no events longer than one year, so compact objects from 1.8×10−4 to 6.3 solar masses make up at most 1% of the dark matter.
Abstract only. Accretion changes the ionization history seen in the CMB; the bound reaches a fraction of 3×10−9 near 104 solar masses and depends on accretion physics.
Abstract only. A hierarchical analysis of O3 mergers with several mass functions limits PBHs to at most about 10−3 of the dark matter between 1 and 200 solar masses.
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