Grey-body factors describe the frequency-dependent transmission of fields through the effective potential generated by a black hole or another compact object. They convert the idealized thermal spectrum of Hawking radiation into the spectrum measured by an observer, determine absorption and scattering cross sections, and provide real-frequency observables complementary to quasinormal modes. In this review, we present a unified account of grey-body factors in black-hole physics and related systems. We formulate the scattering problem for asymptotically flat, de Sitter, and anti-de Sitter spacetimes, and discuss the connections between transmission coefficients, absorption cross sections, Hawking radiation, and ringdown. We also review methods for their computation and survey recent developments, including the correspondence between grey-body factors and quasinormal modes, their stability under deformations of the effective potential, wormhole transmission and superradiance, and their behavior in modified theories of gravity. Finally, we discuss the appearance of grey-body factors in gauge/gravity duality, where absorption probabilities in the bulk are related to correlation functions and transport coefficients in the boundary theory.
Abstract Efficient sampling from high-dimensional, multi-modal posteriors is a central challenge in Bayesian inference across the physical sciences. Gravitational-wave (GW) astronomy, where likelihood evaluations are computationally expensive and posteriors are complex, is one application motivating this work. Popular families of methods like Markov-chain Monte Carlo, Snested sampling, and importance sampling (IS) all rely on proposal distributions to guide exploration. Because prior knowledge of the target is often limited, practitioners can adopt adaptive proposals that iteratively refine themselves using information gained from previously drawn samples. Traditional adaptive strategies, however, struggle in high-dimensional multi-modal settings: complex, non-linear correlations are hard to capture, and hyperparameters typically require tedious, problem-specific tuning. To address these issues, we introduce parallel adaptive reweighting IS (PARIS; descriptively, ‘seed sampling’). PARIS models its proposal as a Gaussian mixture whose component centers are the existing samples and whose component weights match the current importance weights. New draws from the proposal therefore concentrate around high-weight regions, while candidate points in unexplored areas receive intentionally inflated weights. As the algorithm continuously reweights all samples up to the latest proposal, any initial over-weighting self-corrects once additional neighbor samples are collected. To enable rapid reweighting, we present an efficient update scheme and evaluate PARIS on illustrative toy problems and more realistic GW parameter estimation tasks. PARIS achieves accurate posterior reconstruction and evidence estimation with substantially fewer function evaluations than competing approaches, highlighting its promise for widespread use in astrophysical data analysis.
Abstract Establishing collective flow in small collision systems is a crucial and necessary condition for pinning down the minimum conditions for quark-gluon plasma formation. In two-particle correlations, nonflow has been subtracted with good control, pushing the reach of flow measurements down to very small event particle multiplicity N . However, the multi-particle nature of collectivity has not been established in the same N regime, because the residual nonflow surviving the subevent procedure in multi-particle cumulants has never been quantified. We develop a general nonflow subtraction framework for m -particle cumulants, built around the approximate 1 / N m − 1 scaling of nonflow in the independent-source picture. Correlators containing v 1 serve as nonflow-dominated estimators, since the p T -integrated dipolar flow is expected to be small. Using hijing as a controlled nonflow-only environment, we test the subtraction for three target observables ( ⟨ v 2 2 ⟩ , ⟨ v 2 2 δ p T ⟩ , and c 2 { 4 } ) in O+O at s NN = 5.36 TeV and 200 GeV and in d +Au at s NN = 200 GeV. Most of the nonflow is removed, with residual fractions typically within 20%–30% when converted to the two-particle level, though the best estimator differs across the three targets. We identify a multiplicity-reweighting correction, previously overlooked in two-particle correlations, that explains the long-standing undersubtraction of the naive 1 / N -scaling method; its impact grows as a power of the correlator order. The framework gives a systematic route to nonflow subtraction beyond two-particle correlations, broadening the class of multi-particle observables accessible to the small-system flow program.
Abstract Conventional understanding of iron-based superconductivity is usually established based on electronic bands at the Fermi level, leaving deeper bands overlooked as potential factor. Here, we expand this view by demonstrating that a deep-lying d z 2 band below the Fermi level can be employed to enhance the superconducting paring strength. By using scanning tunneling microscope to mechanically change the crystal lattice of an iron-based superconductor, we observe an upward shift of the deep-lying d z 2 band related feature, leading to hybridization with the primary superconducting bands at the Fermi level. We visualize the novel evidence of this band hybridization and resulting enhanced superconducting gap through quasiparticle interference imaging, providing conclusive evidence that engineering such correlations between deep and pairing-active bands is a potent mechanism for amplifying the superconducting gap. This work refines the conventional view of pairing-relevant electronic structures and establishes band hybridization as an effective way to optimize superconducting materials.
Abstract Colloidal semiconductor nanocrystals (NCs) are widely explored as optical gain materials, and throughout over 20 years of research their performance is evaluated through transient absorption spectroscopy (TAS) using parameters such as gain magnitude, lifetime, and threshold. In this work, we discuss some of the literature values reported and couple that to different gain mechanisms. Next, we take a closer look at how these actually relate to the physical parameters that govern lasing, as described by the semiconductor laser rate equations, and found some discrepancy with what is usually reported and what is necessary. We introduce a new analytical framework that connects TAS data to two new fundamental quantities: the stimulated emission rate, representing the intrinsic light–matter interaction speed, and the carrier recombination time, which determines the competing nonradiative loss channel. Together with the already typically reported transparency density, these parameters enable direct prediction of key laser characteristics, like threshold behavior for both femto- and quasi-CW excitation, without requiring full device fabrication. Applying this methodology to a range of colloidal NC systems, we demonstrate that their intrinsic gain performance approaches that of epitaxially grown quantum wells. Analysis of colloidal NC laser literature data further confirms the consistency and predictive power of this approach. This work establishes a unified basis for interpreting ultrafast spectroscopy of NCs and provides a more quantitative route to benchmarking emerging materials for integrated laser technologies.
