<p>The origin of supermassive black holes (SMBHs) is a pivotal problem in modern cosmology. This work explores the potential of the Taiji-TianQin space-borne gravitational-wave (GW) detector network to identify the formation channels of massive black hole binaries (MBHBs) at high redshifts (<i>z</i> ≳ 10). The network substantially improves detection capability, boosting the signal-to-noise ratio by a factor of 2.2–3.0 (1.06–1.14) relative to TianQin (Taiji) alone. It increases the detection rate of MBHBs formed from light seeds (LS) by more than 2.2 times and achieves over 96% detection efficiency for those originating from heavy seeds (HS). Furthermore, the network enables component mass estimation with relative uncertainties as low as ∼ 10<sup>−4</sup> at the 2<i>σ</i> level. These improvements facilitate the assembly of a well-constrained population sample, allowing robust measurement of the fractional contributions from different formation pathways. The network achieves high precision in distinguishing between LS and HS origins (7.4% relative uncertainty at 2<i>σ</i>) and offers moderate discrimination between delay and no-delay channels in HS-origin binaries (24%). However, classification remains challenging for delay versus no-delay scenarios in LS-origin systems (58%) due to significant population overlap. In conclusion, the Taiji-TianQin network will serve as a powerful tool for unveiling the origins of SMBHs through GW population studies.</p>

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Revealing the origin of supermassive black holes with Taiji-TianQin network

  • Ping Shen,
  • Wen-Biao Han,
  • Wen-Xin Zhong

摘要

The origin of supermassive black holes (SMBHs) is a pivotal problem in modern cosmology. This work explores the potential of the Taiji-TianQin space-borne gravitational-wave (GW) detector network to identify the formation channels of massive black hole binaries (MBHBs) at high redshifts (z ≳ 10). The network substantially improves detection capability, boosting the signal-to-noise ratio by a factor of 2.2–3.0 (1.06–1.14) relative to TianQin (Taiji) alone. It increases the detection rate of MBHBs formed from light seeds (LS) by more than 2.2 times and achieves over 96% detection efficiency for those originating from heavy seeds (HS). Furthermore, the network enables component mass estimation with relative uncertainties as low as ∼ 10−4 at the 2σ level. These improvements facilitate the assembly of a well-constrained population sample, allowing robust measurement of the fractional contributions from different formation pathways. The network achieves high precision in distinguishing between LS and HS origins (7.4% relative uncertainty at 2σ) and offers moderate discrimination between delay and no-delay channels in HS-origin binaries (24%). However, classification remains challenging for delay versus no-delay scenarios in LS-origin systems (58%) due to significant population overlap. In conclusion, the Taiji-TianQin network will serve as a powerful tool for unveiling the origins of SMBHs through GW population studies.