Solar energy paper index
Smoking-gun evidence for hierarchical black-hole mergers
One-line summary
A solar energy research paper on Smoking-gun evidence for hierarchical black-hole mergers.
Engineering notes
Engineering notes will be added by the Power for Solar editorial team.
Chinese explanation / 中文解读
中文解读待补充:本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
How stellar-mass black holes grow after their birth is a central open question in astrophysics. Gravitational-wave observations have revealed a subpopulation of coalescing black holes with both high masses and high spins, but whether these properties arise from hierarchical mergers in dense stellar environments or from accretion onto isolated black holes has remained unresolved. Here, using a flexible mixture population model applied to the 259 binary black hole mergers in GWTC-5, we show that the mass function of the high-spin subpopulation traces, peak by peak, the predicted remnant-mass distribution of the low-spin, stellar-collapse-origin subpopulation up to $\sim80\,M_\odot$. This morphological match, quantified by a Bhattacharyya coefficient as high as $\sim0.95$, is naturally expected if the high-spin black holes are themselves the products of earlier mergers, whereas any alternative scenario would require fine-tuning, thereby providing smoking-gun evidence for hierarchical mergers. In addition, the sharp upper-mass cutoff of the low-spin subpopulation at $m_{\rm max,1}=54.2^{+7.7}_{-7.2}\,M_\odot$ yields an astrophysical $S$-factor of $S_{300}=151^{+30}_{-26}$~keV~b (68\% credible interval) for the $^{12}{\rm C}(α,γ)^{16}{\rm O}$ reaction, in agreement with the benchmark theoretical value. These results establish that the entire observed black-hole population can be accounted for by stellar collapse followed by dynamical hierarchical assembly, without invoking primordial black holes.
Links and sources
Need this topic turned into a technical roadmap?
Power for Solar can prepare a custom solar energy literature review, simulation code map, dataset map, and B2B photovoltaic technology assessment.
Request B2B research
Comments