@article{21062,
  abstract     = {JWST observations have unveiled faint active galactic nuclei (AGNs) at high redshift that provide insights into the formation of supermassive black holes (SMBHs). However, disentangling their stellar from AGN light is challenging. Here, we use an empirical approach to infer the average stellar mass of five faint broad-line (BL) Hα emitters at z = 4–5 with BH masses ≈6 × 10^6 M⊙, with a method independent of their spectral energy distribution (SED). We use the deep JWST/NIRcam grism survey “All the Little Things” to measure the overdensities around BL-Hα emitters and around a spectroscopic reference sample of ∼300 galaxies. In our reference sample, we find that megaparsec-scale overdensity correlates with stellar mass. Their large-scale environments suggest that BL-Hα emitters are hosted by galaxies with stellar masses ≈5 × 10^7 M⊙, ≈40 times lower than those inferred from galaxy-only SED fits. Adding measurements around more luminous z ≈ 6 AGNs, we find tentative correlations between line width, BH mass, and the overdensity, suggestive of a steep BH to halo mass relation. The main implications are (1) when BH masses are taken at face value, we confirm extremely high BH to stellar mass ratios of ≈10%, (2) the galaxies of low stellar mass that host growing SMBHs are in tension with typical hydrodynamical simulations, except those without feedback, (3) a 1% duty cycle implied by the host mass hints at super-Eddington accretion, (4) the masses are at odds with an interpretation of the line broadening in terms of high stellar density, (5) our results imply a luminosity-dependent diversity of galaxy masses, environments, and SEDs among AGN samples.},
  author       = {Matthee, Jorryt J and Naidu, Rohan P. and Kotiwale, Gauri and Furtak, Lukas J. and Kramarenko, Ivan and Mackenzie, Ruari and Greene, Jenny and Adamo, Angela and Bouwens, Rychard J. and Di Cesare, Claudia and Eilers, Anna-Christina and de Graaff, Anna and Heintz, Kasper E. and Kashino, Daichi and Maseda, Michael V. and Tacchella, Sandro and Torralba Torregrosa, Alberto},
  issn         = {1538-4357},
  journal      = {The Astrophysical Journal},
  number       = {2},
  publisher    = {IOP Publishing},
  title        = {{Environmental evidence for overly massive Black Holes in low-mass galaxies and a Black Hole–Halo mass relation at z ∼ 5}},
  doi          = {10.3847/1538-4357/ade886},
  volume       = {988},
  year         = {2025},
}

@article{21063,
  abstract     = {We report the detection of a 13σ Hα emission line from HDF850.1 at z = 5.188 ± 0.001 using the FRESCO (First Reionization Era SpectroscopicallyComplete Observations) NIRCam F444W grism observations. Detection of Hα in HDF850.1 is noteworthy, given its high far-infrared (IR) luminosity, substantial dust obscuration, and the historical challenges in deriving its redshift.
HDF850.1 shows a clear detection in the F444W imaging data, distributed between a northern and southern component, mirroring that seen in [C II] from the Plateau de Bure Interferometer. Modelling the spectral energy distribution of each component separately, we find that the northern component has a higher mass, star formation rate (SFR), and dust extinction than the southern component. The observed Hα emission appears to arise entirely from the less-obscured southern component and shows a similar v∼ + 130 km s −1 velocity offset to that seen for [C II] relative to the source systemic redshift. Leveraging Hα-derived redshiftsfrom FRESCO observations, we find that HDF850.1 isforming in one of the richest environments identified to date at z > 5, with 100 z = 5.17–5.20 galaxies distributed across 13 smaller structures and a ∼(15 cMpc)3 volume. Based on the evolution of analogous structures in cosmological simulations, the z = 5.17–5.20 structures seem likely to collapse into
a single > 1014M cluster by z ∼ 0. Comparing galaxy properties forming within this overdensity with those outside, we find the masses, SFRs, and UV luminosities inside the overdensity to be clearly higher. The prominence of Hα line emission from HDF850.1 and other known highly obscured z > 5 galaxies illustrates the potential of NIRCam-grism programs to map both
the early build-up of IR-luminous galaxies and overdense structures.},
  author       = {Herard-Demanche, Thomas and Bouwens, Rychard J and Oesch, Pascal A and Naidu, Rohan P and Decarli, Roberto and Nelson, Erica J and Brammer, Gabriel and Weibel, Andrea and Xiao, Mengyuan and Stefanon, Mauro and Walter, Fabian and Matthee, Jorryt J and Meyer, Romain A and Wuyts, Stijn and Reddy, Naveen and Rowland, Lucie and van Leeuwen, Ivana and Haro, Pablo Arrabal and Dannerbauer, Helmut and Shapley, Alice E and Chisholm, John and van Dokkum, Pieter and Labbe, Ivo and Illingworth, Garth and Schaerer, Daniel and Shivaei, Irene},
  issn         = {1365-2966},
  journal      = {Monthly Notices of the Royal Astronomical Society},
  number       = {2},
  pages        = {788--808},
  publisher    = {Oxford University Press},
  title        = {{Mapping dusty galaxy growth at z > 5 with FRESCO: Detection of Hα in submm galaxy HDF850.1 and the surrounding overdense structures}},
  doi          = {10.1093/mnras/staf030},
  volume       = {537},
  year         = {2025},
}

@inproceedings{21066,
  abstract     = {Causal discovery from observational data holds great promise, but existing methods rely on strong assumptions about the underlying causal structure, often requiring full observability of all relevant variables. We tackle these challenges by leveraging the score function ∇logp(X)
 of observed variables for causal discovery and propose the following contributions. First, we generalize the existing results of identifiability with the score to additive noise models with minimal requirements on the causal mechanisms. Second, we establish conditions for inferring causal relations from the score even in the presence of hidden variables; this result is two-faced: we demonstrate the score’s potential as an alternative to conditional independence tests to infer the equivalence class of causal graphs with hidden variables, and we provide the necessary conditions for identifying direct causes in latent variable models. Building on these insights, we propose a flexible algorithm for causal discovery across linear, nonlinear, and latent variable models, which we empirically validate.},
  author       = {Montagna, Francesco and Faller, Philipp and Blöbaum, Patrik and Kirschbaum, Elke and Locatello, Francesco},
  booktitle    = {Proceedings of the Fourth Conference on Causal Learning and Reasoning},
  issn         = {2640-3498},
  location     = {Lausanne, Switzerland},
  pages        = {552--605},
  publisher    = {ML Research Press},
  title        = {{Score matching through the roof: Linear, nonlinear, and latent variables causal discovery}},
  volume       = {275},
  year         = {2025},
}

@inproceedings{21068,
  abstract     = {Causal reasoning and discovery, two fundamental tasks of causal analysis,
often face challenges in applications due to the complexity, noisiness, and highdimensionality of real-world data. Despite recent progress in identifying latent
causal structures using causal representation learning (CRL), what makes learned
representations useful for causal downstream tasks and how to evaluate them are
still not well understood. In this paper, we reinterpret CRL using a measurement
model framework, where the learned representations are viewed as proxy measurements of the latent causal variables. Our approach clarifies the conditions under
which learned representations support downstream causal reasoning and provides
a principled basis for quantitatively assessing the quality of representations using
a new Test-based Measurement EXclusivity (T-MEX) score. We validate T-MEX
across diverse causal inference scenarios, including numerical simulations and
real-world ecological video analysis, demonstrating that the proposed framework
and corresponding score effectively assess the identification of learned representations and their usefulness for causal downstream tasks. Reproducible code can
be found at https://github.com/shimenghuang/a-measurement-perspective-of-crl.},
  author       = {Yao, Dingling and Huang, Shimeng and Cadei, Riccardo and Zhang, Kun and Locatello, Francesco},
  booktitle    = {39th Annual Conference on Neural Information Processing Systems},
  issn         = {1049-5258},
  location     = {San Diego, CA, United States},
  publisher    = {Neural Information Processing Systems Foundation},
  title        = {{The third pillar of causal analysis? A measurement perspective on causal representations}},
  volume       = {38},
  year         = {2025},
}

@inproceedings{21070,
  abstract     = {Deep learning systems deployed in real-world applications often encounter data that is different from their in-distribution (ID). A reliable model should ideally abstain from making decisions in this out-of-distribution (OOD) setting. Existing state-of-the-art methods primarily focus on feature distances, such as k-th nearest neighbors and distances to decision boundaries, either overlooking or ineffectively using in-distribution statistics. In this work, we propose a novel angle-based metric for OOD detection that is computed relative to the in-distribution structure. We demonstrate that the angles between feature representations and decision boundaries, viewed from the mean of in-distribution features, serve as an effective discriminative factor between ID and OOD data. We evaluate our method on nine ImageNet-pretrained models. Our approach achieves the lowest FPR in 5 out of 9 ImageNet models, obtains the best average FPR overall, and consistently ranking among the top 3 across all evaluated models. Furthermore, we highlight the benefits of contrastive representations by showing strong performance with ResNet SCL and CLIP architectures. Finally, we demonstrate that the scale-invariant nature of our score enables an ensemble strategy via simple score summation. },
  author       = {Demirel, Berker and Fumero, Marco  and Locatello, Francesco},
  booktitle    = {39th Annual Conference on Neural Information Processing Systems},
  issn         = {1049-5258},
  location     = {San Diego, CA, United States},
  publisher    = {Neural Information Processing Systems Foundation},
  title        = {{Out-of-Distribution detection with relative angles}},
  volume       = {38},
  year         = {2025},
}

@inproceedings{21072,
  abstract     = {Language and vision-language models have shown impressive performance across a wide range of tasks, but their internal mechanisms remain only partly understood. In this work, we study how individual attention heads in text-generative models specialize in specific semantic or visual attributes. Building on an established interpretability method, we reinterpret the practice of probing intermediate activations with the final decoding layer through the lens of signal processing. This lets us analyze multiple samples in a principled way and rank attention heads based on their relevance to target concepts. Our results show consistent patterns of specialization at the head level across both unimodal and multimodal transformers. Remarkably, we find that editing as few as 1% of the heads, selected using our method, can reliably suppress or enhance targeted concepts in the model output. We validate our approach on language tasks such as question answering and toxicity mitigation, as well as vision-language tasks including image classification and captioning. Our findings highlight an interpretable and controllable structure within attention layers, offering simple tools for understanding and editing large-scale generative models.},
  author       = {Basile, Lorenzo and Maiorca, Valentino and Doimo, Diego and Locatello, Francesco and Cazzaniga, Alberto},
  booktitle    = {39th Annual Conference on Neural Information Processing Systems},
  issn         = {1049-5258},
  location     = {San Diego, CA, United States},
  publisher    = {Neural Information Processing Systems Foundation},
  title        = {{Head pursuit: Probing attention specialization in multimodal transformers}},
  volume       = {38},
  year         = {2025},
}

@inproceedings{21074,
  abstract     = {Neural models learn representations of high-dimensional data on low-dimensional manifolds. Multiple factors, including stochasticities in the training process, model architectures, and additional inductive biases, may induce different representations, even when learning the same task on the same data. However, it has recently been shown that when a latent structure is shared between distinct latent spaces, relative distances between representations can be preserved, up to distortions. Building on this idea, we demonstrate that exploiting the differential-geometric structure of latent spaces of neural models, it is possible to capture precisely the transformations between representational spaces trained on similar data distributions. Specifically, we assume that distinct neural models parametrize approximately the same underlying manifold, and introduce a representation based on the pullback metric that captures the intrinsic structure of the latent space, while scaling efficiently to large models. We validate experimentally our method on model stitching and retrieval tasks, covering autoencoders and vision foundation discriminative models, across diverse architectures, datasets, pretraining schemes and modalities. Code is available at the following link.},
  author       = {Yu, Hanlin and Inal, Befrin and Arvanitidis, Georgios and Hauberg, Soren and Locatello, Francesco and Fumero, Marco},
  booktitle    = {39th Annual Conference on Neural Information Processing Systems},
  issn         = {1049-5258},
  location     = {San Diego, CA, United States},
  publisher    = {Neural Information Processing Systems Foundation},
  title        = {{Connecting neural models latent geometries with relative geodesic representations}},
  volume       = {38},
  year         = {2025},
}

@inproceedings{21076,
  abstract     = {In many scientific experiments, the data annotating cost constraints the pace for testing novel hypotheses. Yet, modern machine learning pipelines offer a promising solution—provided their predictions yield correct conclusions. We focus on Prediction-Powered Causal Inferences (PPCI), i.e., estimating the treatment effect in an unlabeled target experiment, relying on training data with the same outcome annotated but potentially different treatment or effect modifiers. We first show that conditional calibration guarantees valid PPCI at population level. Then, we introduce a sufficient representation constraint transferring validity across experiments, which we propose to enforce in practice in Deconfounded Empirical Risk Minimization, our new model-agnostic training objective. We validate our method on synthetic and real-world scientific data, solving impossible problem instances for Empirical Risk Minimization even with standard invariance constraints. In particular, for the first time, we achieve valid causal inference on a scientific experiment with complex recording and no human annotations, fine-tuning a foundational model on our similar annotated experiment.},
  author       = {Cadei, Riccardo and Demirel, Ilker and De Bartolomeis, Piersilvio and Lindorfer, Lukas and Cremer, Sylvia and Schmid, Cordelia and Locatello, Francesco},
  booktitle    = {39th Annual Conference on Neural Information Processing Systems},
  issn         = {1049-5258},
  location     = {San Diego, CA, United States},
  publisher    = {Neural Information Processing Systems Foundation},
  title        = {{Prediction-powered causal inferences}},
  volume       = {38},
  year         = {2025},
}

@inproceedings{21089,
  abstract     = {Hypertrace logic is a sorted first-order logic with separate sorts for time and execution traces. Its formulas specify hyperproperties, which are properties relating multiple traces. In this work, we extend hypertrace logic by introducing trace quantifiers that range over the set of all possible traces. In this extended logic, formulas can quantify over two kinds of trace variables: constrained trace variables, which range over a fixed set of traces defined by the model, and unconstrained trace variables, which can be assigned to any trace. In comparison, hyperlogics such as HyperLTL have only constrained trace quantifiers. We use hypertrace logic to study how different quantifier patterns affect the decidability of the satisfiability problem. We prove that hypertrace logic without constrained trace quantifiers is equivalent to monadic second-order logic of one successor (S1S), and therefore satisfiable, and that the trace-prefixed fragment (all trace quantifiers precede all time quantifiers) is equivalent to HyperQPTL. Moreover, we show that all hypertrace formulas where the only alternation between constrained trace quantifiers is from an existential to a universal quantifier are equisatisfiable to formulas without constraints on their trace variables and, therefore, decidable as well. Our framework allows us to study also time-prefixed hyperlogics, for which we provide new decidability and undecidability results.},
  author       = {Chalupa, Marek and Henzinger, Thomas A and Oliveira da Costa, Ana A},
  booktitle    = {45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science},
  location     = {Pilani, India},
  pages        = {20:1--20:18},
  publisher    = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
  title        = {{Flavors of quantifiers in hyperlogics}},
  doi          = {10.4230/LIPICS.FSTTCS.2025.20},
  volume       = {360},
  year         = {2025},
}

@inproceedings{21090,
  abstract     = {Fairness in AI is traditionally studied as a static property evaluated once, over a fixed dataset. However, real-world AI systems operate sequentially, with outcomes and environments evolving over time. This paper proposes a framework for analysing fairness as a runtime property. Using a minimal yet expressive model based on sequences of coin tosses with possibly evolving biases, we study the problems of monitoring and enforcing fairness expressed in either toss outcomes or coin biases. Since there is no one-size-fits-all solution for either problem, we provide a summary of monitoring and enforcement strategies, parametrised by environment dynamics, prediction horizon, and confidence thresholds. For both problems, we present general results under simple or minimal assumptions. We survey existing solutions for the monitoring problem for Markovian and additive dynamics, and existing solutions for the enforcement problem in static settings with known dynamics.},
  author       = {Cano Cordoba, Filip and Henzinger, Thomas A and Kueffner, Konstantin},
  booktitle    = {25th International Conference on Runtime Verification},
  issn         = {1611-3349},
  location     = {Graz, Austria},
  pages        = {1--21},
  publisher    = {Springer Nature},
  title        = {{Algorithmic fairness: A runtime perspective}},
  doi          = {10.1007/978-3-032-05435-7_1},
  volume       = {16087},
  year         = {2025},
}

@inproceedings{21091,
  abstract     = {Neural certificates have emerged as a powerful tool in cyber-physical systems control, providing witnesses of correctness. These certificates, such as barrier functions, often learned alongside control policies, once verified, serve as mathematical proofs of system safety. However, traditional formal verification of their defining conditions typically faces scalability challenges due to exhaustive state-space exploration. To address this challenge, we propose a lightweight runtime monitoring framework that integrates real-time verification and does not require access to the underlying control policy. Our monitor observes the system during deployment and performs on-the-fly verification of the certificate over a lookahead region to ensure safety within a finite prediction horizon. We instantiate this framework for ReLU-based control barrier functions and demonstrate its practical effectiveness in a case study. Our approach enables timely detection of safety violations and incorrect certificates with minimal overhead, providing an effective but lightweight alternative to the static verification of the certificates.},
  author       = {Henzinger, Thomas A and Kueffner, Konstantin and Yu, Zhengqi},
  booktitle    = {25th International Conference on Runtime Verification},
  issn         = {1611-3349},
  location     = {Graz, Austria},
  pages        = {54--72},
  publisher    = {Springer Nature},
  title        = {{Formal verification of neural certificates done dynamically}},
  doi          = {10.1007/978-3-032-05435-7_4},
  volume       = {16087},
  year         = {2025},
}

@inproceedings{21092,
  abstract     = {Formal verification provides assurances that a probabilistic system satisfies its specification—conditioned on the system model being aligned with reality. We propose alignment monitoring to watch that this assumption is justified. We consider a probabilistic model well aligned if it accurately predicts the behaviour of an uncertain system in advance. An alignment score measures this by quantifying the similarity between the model’s predicted and the system’s (unknown) actual distributions. An alignment monitor observes the system at runtime; at each point in time it uses the current state and the model to predict the next state. After the next state is observed, the monitor updates the verdict, which is a high-probability interval estimate for the true alignment score. We utilize tools from sequential forecasting to construct our alignment monitors. Besides a monitor for measuring the expected alignment score, we introduce a differential alignment monitor, designed for comparing two models, and a weighted alignment monitor, which permits task-specific alignment monitoring. We evaluate our monitors experimentally on the PRISM benchmark suite. They are fast, memory-efficient, and detect misalignment early.},
  author       = {Henzinger, Thomas A and Kueffner, Konstantin and Singh, Vasu and Sun, I},
  booktitle    = {25th International Conference on Runtime Verification},
  issn         = {1611-3349},
  location     = {Graz, Austria},
  pages        = {140--159},
  publisher    = {Springer Nature},
  title        = {{Alignment monitoring}},
  doi          = {10.1007/978-3-032-05435-7_9},
  volume       = {16087},
  year         = {2025},
}

@inproceedings{21093,
  abstract     = {We propose a monitoring approach for hyperproperties where the system’s observations range over infinite domains. The specifications are given as formulas of symbolic hypernode logic, an extension of earlier versions of hypernode logic that supports events with data. We demonstrate how to translate terms of symbolic hypernode logic into multi-tape symbolic transducers and we present a monitoring algorithm for universally quantified formulas that is based on this translation. We evaluate our approach against the previous approach for monitoring hypernode logic, and we also compare it to other monitors for hyperproperties.},
  author       = {Chalupa, Marek and Henzinger, Thomas A and Oliveira da Costa, Ana A},
  booktitle    = {25th International Conference on Runtime Verification},
  issn         = {1611-3349},
  location     = {Graz, Austria},
  pages        = {417--437},
  publisher    = {Springer Nature},
  title        = {{Monitoring hypernode logic over infinite domains}},
  doi          = {10.1007/978-3-032-05435-7_23},
  volume       = {16087},
  year         = {2025},
}

@article{21121,
  abstract     = {The relation between the masses of supermassive black holes (SMBHs) and their host galaxies encodes information on their mode of growth, especially at the earliest epochs. The James Webb Space Telescope (JWST) has opened such investigations by detecting the host galaxies of active galactic nuclei (AGN) and more luminous quasars within the first billion years of the Universe (z ≳ 6). Here, we evaluate the relation between the mass of SMBHs and the total stellar mass of their host galaxies using a sample of nine quasars at 6.18 ≤ z ≤ 6.4 from the Subaru High-z Exploration of Low-luminosity Quasars survey with NIRCam and NIRSpec observations. We find that the observed location of these quasars in the SMBH–galaxy mass plane (logMBH/M 8–9; logM*/M 9.5–11) is consistent with a nonevolving intrinsic mass relation with dispersion (0.80 +0.23 -0.28 dex) higher than the local value (∼0.3–0.4 dex) of their more massive descendants. Our analysis is based on a forward model of systematics and includes a consideration of the impact of selection effects and measurement uncertainties with an assumption on the slope of the mass relation. While degeneracies between parameters persist, the best-fit solution has a reasonable AGN fraction (2.3%) of galaxies at z ∼ 6 with an actively growing UV-unobscured black hole. In particular, models with a substantially higher normalisation in MBH would require an unrealistically low intrinsic dispersion (∼0.22 dex). Consequently, our results predict a large population of AGN at lower black hole masses, as are now just starting to be discovered in focused efforts with JWST.},
  author       = {Silverman, John David and Li, Junyao and Ding, Xuheng and Onoue, Masafusa and Strauss, Michael A. and Matsuoka, Yoshiki and Izumi, Takuma and Jahnke, Knud and Treu, Tommaso and Volonteri, Marta and Phillips, Camryn L. and Andika, Irham T. and Aoki, Kentaro and Arita, Junya and Baba, Shunsuke and Bosman, Sarah E. I. and Eilers, Anna-Christina and Fan, Xiaohui and Fujimoto, Seiji and Habouzit, Melanie and Haiman, Zoltán and Imanishi, Masatoshi and Inayoshi, Kohei and Iwasawa, Kazushi and Kashikawa, Nobunari and Kawaguchi, Toshihiro and Lee, Chien-Hsiu and Lupi, Alessandro and Nagao, Tohru and Schindler, Jan-Torge and Schramm, Malte and Shimasaku, Kazuhiro and Toba, Yoshiki and Trakhtenbrot, Benny and Umehata, Hideki and Vestergaard, Marianne and Walter, Fabian and Wang, Feige and Yang, Jinyi},
  issn         = {2041-8213},
  journal      = {The Astrophysical Journal Letters},
  number       = {2},
  publisher    = {IOP Publishing},
  title        = {{SHELLQs–JWST perspective on the intrinsic mass relation between supermassive black holes and their host galaxies at z > 6}},
  doi          = {10.3847/2041-8213/ae279c},
  volume       = {995},
  year         = {2025},
}

@article{21122,
  abstract     = {The multimessenger combination of gravitational waves (GWs) from merging massive black hole binaries (MBHBs) and the electromagnetic (EM) counterpart from the surrounding circumbinary disc (CBD) will open avenues to new scientific pursuits. In order to realize this science, we need to correctly localize the host galaxy of the merging MBHB. Multiwavelength, time-dependent EM signatures can greatly facilitate the identification of the unique EM counterpart among many sources in LISA’s localization volume. To this end, we studied merging unequal-mass MBHBs embedded in a CBD using high-resolution 2D simulations, with a $\Gamma$-law equation of state, incorporating viscous heating, shock heating, and radiative cooling. We simulate each binary starting from before it decouples from the CBD until just after the merger. We compute EM signatures and identify distinct features before, during, and after the merger. We corroborate previous findings of a several orders of magnitude drop in the thermal X-ray luminosity near the time of merger, but with delayed timing compared to an equal-mass system. The source remains X-ray dark for hours post-merger. Our main results are a potential new signature of a sharp spike in the thermal X-ray emission just before the tell-tale steep drop occurs. This feature may further help to identify EM counterparts of LISA’s unequal MBHBs before merger without the need for extensive pre-merger monitoring. Additionally, we find a role-reversal in which the primary out-accretes the secondary during late inspiral, which may diminish signatures originating from Doppler modulation.},
  author       = {Krauth, Luke Major and Davelaar, Jordy and Haiman, Zoltán and Westernacher-Schneider, John Ryan and Zrake, Jonathan and MacFadyen, Andrew},
  issn         = {1365-2966},
  journal      = {Monthly Notices of the Royal Astronomical Society},
  number       = {3},
  pages        = {2670--2685},
  publisher    = {Oxford University Press},
  title        = {{Thermal X-ray signatures in late-stage unequal-mass massive black hole binary mergers}},
  doi          = {10.1093/mnras/staf1583},
  volume       = {543},
  year         = {2025},
}

@article{21123,
  abstract     = {We present a study of the late-time interaction between supermassive black hole binaries and retrograde circumbinary disks during the period of gravitational wave-driven inspiral. While mergers in prograde disks have received extensive study, retrograde disks offer distinct dynamics that could promote mergers and produce unique observational signatures. Through 2D numerical hydrodynamical simulations, we explore the process of binary-disk decoupling, where the binary’s orbital decay rate is faster than the disk’s viscous response rate. We find the point of decoupling to be comparable in prograde and retrograde disks, suggesting that any associated electromagnetic (EM) signatures will be produced at comparable times preceding the merger. However, we find smaller central cavities for retrograde disks, likely leading to higher-frequency EM emissions and shorter postmerger rebrightening timescales compared to their prograde counterparts. Retrograde disks form intrabinary bridges, which are prone to instabilities when the viscosity is low. These instabilities manifest as quasiperiodic flares in the accretion rate, which may produce distinctive EM signatures for retrograde disks.},
  author       = {O’Neill, David and Tiede, Christopher and D’Orazio, Daniel J. and Haiman, Zoltán and MacFadyen, Andrew},
  issn         = {1538-4357},
  journal      = {The Astrophysical Journal},
  number       = {2},
  publisher    = {IOP Publishing},
  title        = {{Gravitational wave decoupling in retrograde circumbinary disks}},
  doi          = {10.3847/1538-4357/ae0ca8},
  volume       = {993},
  year         = {2025},
}

@article{21124,
  abstract     = {The advent of the James Webb Space Telescope (JWST) has opened new horizons in the study of quasar host galaxies during the reionization epoch (z > 6). Building upon our previous initial measurements of stellar light from two quasar host galaxies at these redshifts, we now report the detection of the stellar light from the full Cycle 1 sample of 12 distant moderate-luminosity quasar (M1450 > −24 mag) host galaxies at z > 6 from the Hyper Suprime-Cam Subaru Strategic Program. Using JWST/NIRCam observations at 1.5 and 3.6 μm combined with 2D image decomposition analysis, we successfully detect the host galaxies in 11 of the 12 targets, underscoring the high detection rates achievable with moderate-luminosity quasars. Based on two-band photometry and spectral energy distribution fitting, we find that our host galaxies are massive, with log M*/M⊙ = 9.5–11.0. The effective radii range from 0.6 to 3.2 kpc, comparable to the sizes of inactive galaxies with similar masses at z ∼ 6 as measured with imaging from COSMOS-Web. Intriguingly, the two quasar hosts with post-starburst features, which reside at the high-mass end of our sample and exhibit relatively compact morphologies, have similar size and stellar mass surface densities to quiescent galaxies at z ∼ 4–5. These findings suggest that the so-called galaxy compaction scenario is already in place at the reionization epoch, in which gas inflows during starburst phases drive centrally concentrated star formation followed by rapid quenching, bridging the structural transition of massive galaxies from relatively extended star-forming disks to compact quiescent systems.},
  author       = {Ding, Xuheng and Onoue, Masafusa and Silverman, John D. and Matsuoka, Yoshiki and Izumi, Takuma and Strauss, Michael A. and Yang, Lilan and Jahnke, Knud and Phillips, Camryn L. and Treu, Tommaso and Andika, Irham T. and Aoki, Kentaro and Arita, Junya and Baba, Shunsuke and Bosman, Sarah E. I. and Eilers, Anna-Christina and Fujimoto, Seiji and Haiman, Zoltán and Imanishi, Masatoshi and Inayoshi, Kohei and Iwasawa, Kazushi and Kartaltepe, Jeyhan and Kashikawa, Nobunari and Kawaguchi, Toshihiro and Li, Junyao and Lee, Chien-Hsiu and Lupi, Alessandro and Schindler, Jan-Torge and Schramm, Malte and Shimasaku, Kazuhiro and Shuntov, Marko and Tanaka, Takumi S. and Toba, Yoshiki and Trakhtenbrot, Benny and Umehata, Hideki and Vestergaard, Marianne and Wang, Feige and Yang, Jinyi},
  issn         = {1538-4357},
  journal      = {The Astrophysical Journal},
  number       = {1},
  publisher    = {IOP Publishing},
  title        = {{SHELLQs-JWST unveils the host galaxies of 12 quasars at z > 6}},
  doi          = {10.3847/1538-4357/ae045b},
  volume       = {993},
  year         = {2025},
}

@article{21125,
  abstract     = {The thermal Sunyaev-Zel’dovich effect (tSZ) is a sensitive probe of cosmology, as it traces the abundance of galaxy clusters and groups in the late-time Universe. Upcoming cosmic microwave background experiments such as the Simons Observatory (SO) and CMB-S4 will provide low-noise and high-resolution component-separated tSZ maps covering a large sky fraction. The tSZ signal is highly non-Gaussian; therefore, higher-order statistics are needed to optimally extract information from these maps. In this work, we study the cosmological constraining power of several tSZ statistics—Minkowski functionals (MFs), peaks, minima, and moments—that have yielded promising results in capturing non-Gaussian information from other cosmological data. Using a large suite of halo-model-based tSZ simulations with varying Ω𝑐 and 𝜎8 (154 cosmologies and over 800,000 maps, each 10.5×10.5  deg2), we show that by combining these observables, we can achieve  ≈29 × tighter constraints compared to using the tSZ power spectrum alone in an idealized noiseless case, with the MFs dominating the constraints. We show that much of the MF constraining power arises from halos below the detection threshold of cluster surveys, suggesting promising synergies with cluster-count analyses. Finally, we demonstrate that these statistics have the potential to deliver tight constraints even in the presence of noise. For example, using post-component-separation tSZ noise expected for SO, we obtain  ≈1.6 × and  ≈1.8 × tighter constraints than the power spectrum with MFs and all statistics combined, respectively. We show that the constraints from MFs approach the noiseless case for white-noise levels ≲1  𝜇⁢K−arcmin.},
  author       = {Sabyr, Alina and Hill, J. Colin and Haiman, Zoltán},
  issn         = {2470-0029},
  journal      = {Physical Review D},
  number       = {10},
  publisher    = {American Physical Society},
  title        = {{Constraining cosmology with thermal Sunyaev-Zel’dovich maps: Minkowski functionals, peaks, minima, and moments}},
  doi          = {10.1103/physrevd.111.103536},
  volume       = {111},
  year         = {2025},
}

@article{21126,
  abstract     = {Subparsec supermassive black hole (SMBH) binaries are expected to be common in active galactic nuclei as a result of the hierarchical buildup of galaxies via mergers. While direct evidence for these compact binaries is lacking, a few hundred candidates have been identified, most based on the apparent periodicities of their optical light curves. Since these signatures can be mimicked by active galactic nuclei red noise, additional evidence is needed to confirm their binary nature. Recurring self-lensing flares, occurring whenever the two BHs are aligned with the line of sight within their Einstein radii, have been suggested as additional binary signatures. Furthermore, in many cases, lensing flares are also predicted to contain a “dip,” whenever the lensed SMBH’s shadow is comparable in angular size to the binary’s Einstein radius. This feature would unambiguously confirm binaries and additionally identify SMBH shadows that are spatially unresolvable by high-resolution Very Long Baseline Interferometry (VLBI). Here we estimate the number of quasars for which these dips may be detectable by Legacy Survey of Space and Time (LSST) by extrapolating the quasar luminosity function to faint magnitudes and assuming that SMBH binaries are randomly oriented and have mass ratios following those in the Illustris simulations. Under plausible assumptions about quasar lifetimes, binary fractions, and Eddington ratios, we expect tens of thousands of detectable flares, of which several dozen contain measurable dips.},
  author       = {Park, Kevin and Xin, Chengcheng and Davelaar, Jordy and Haiman, Zoltán},
  issn         = {2470-0029},
  journal      = {Physical Review D},
  number       = {6},
  publisher    = {American Physical Society},
  title        = {{Self-lensing flares from black hole binaries. IV. The number of detectable shadows}},
  doi          = {10.1103/physrevd.111.063011},
  volume       = {111},
  year         = {2025},
}

@article{21127,
  abstract     = {The early growth of black holes (BHs) in atomic-cooling haloes is likely influenced by feedback on the surrounding gas. While the effects of radiative feedback are well-documented, mechanical feedback, particularly from active galactic nucleus (AGN) jets, has been comparatively less explored. Building on our previous work that examined the growth of a 100 M BH in a constant density environment regulated by AGN jets, we expand the initial BH mass range from 1 to 104 M and adopt a more realistic density profile for atomic-cooling haloes. We reaffirm the validity of our analytic models for jet cocoon propagation and feedback regulation. We identify several critical radii – namely, the terminal radius of jet cocoon propagation, the isotropization radius of the jet cocoon, and the core radius of the atomic-cooling halo – that are crucial in determining BH growth given specific gas properties and jet feedback parameters. In a significant portion of the parameter space, our findings show that jet feedback substantially disrupts the halo’s core during the initial feedback episode, preventing BH growth beyond 104 M.
Conversely, conditions characterized by low jet velocities and high gas densities enable sustained BH growth over extended periods. We provide a prediction for the BH mass growth as a function of time and feedback parameters. We found that, to form a supermassive BH (> 106 M) within 1 Gyr entirely by accreting gas from an atomic-cooling halo, the jet energy feedback
efficiency must be  10−4M˙ BHc2 even if the seed BH mass is 104 M.},
  author       = {Su, Kung-Yi and Bryan, Greg L and Haiman, Zoltán},
  issn         = {1365-2966},
  journal      = {Monthly Notices of the Royal Astronomical Society},
  number       = {1},
  pages        = {11--30},
  publisher    = {Oxford University Press},
  title        = {{Self-regulation of high-redshift black hole accretion via jets: Challenges for SMBH formation}},
  doi          = {10.1093/mnras/staf228},
  volume       = {538},
  year         = {2025},
}