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Pooled single-cell perturbation screens represent powerful experimental platforms for functional genomics, yet interpreting these rich datasets for meaningful biological conclusions remains challenging. Most current methods fall at one of two extremes: either opaque deep learning models that obscure biological meaning, or simplified frameworks that treat genes as isolated units. As such, these approaches overlook a crucial insight: gene co-fluctuations in unperturbed cellular states can be harnessed to model perturbation responses. Here we present CIPHER (Covariance Inference for Perturbation and High-dimensional Expression Response), a framework leveraging linear response theory from statistical physics to predict transcriptome-wide perturbation outcomes using gene co-fluctuations in unperturbed cells. We validated CIPHER on synthetic regulatory networks before applying it to 11 large-scale single-cell perturbation datasets covering 4,234 perturbations and over 1.36M cells. CIPHER robustly recapitulated genome-wide responses to single and double perturbations by exploiting baseline gene covariance structure. Importantly, eliminating gene-gene covariances, while retaining gene-intrinsic variances, reduced model performance by 11-fold, demonstrating the rich information stored within baseline fluctuation structures. Moreover, gene-gene correlations transferred successfully across independent experiments of the same cell type, revealing stereotypic fluctuation structures. Furthermore, CIPHER outperformed conventional differential expression metrics in identifying true perturbations while providing uncertainty-aware effect size estimates through Bayesian inference. Finally, most genome-wide responses propagated through the covariance matrix along approximately three independent and global gene modules. CIPHER underscores the importance of theoretically-grounded models in capturing complex biological responses, highlighting fundamental design principles encoded in cellular fluctuation patterns. 

We present uniformly measured resolved stellar photometry and star formation histories (SFHs) for 36 nearby (≲400 kpc) ultra-faint dwarf galaxies (UFDs; −7.1 ≤M_V≤ +0.0) from new and archival Hubble Space Telescope (HST) imaging. We measure homogeneous distances to all systems via isochrone fitting and find good agreement (≤2%) for the 18 UFDs that have literature RR Lyrae distances. From the ensemble of SFHs, we find (i) an average quenching time (here defined as the lookback time by which 80% of the stellar mass formed,τ₈₀) of 12.48  ±  0.18 Gyr ago ( $z=4.6_{-0.5}^{+0.6}$), which is compatible with reionization-based quenching scenarios; and (ii) modest evidence of a delay (≲800 Myr) in quenching times of UFDs thought to be satellites of the LMC or on their first infall, relative to long-term Galactic satellites, which is consistent with previous findings. We show that robust SFH measurement via the ancient main-sequence turnoff (MSTO) requires a minimum effective luminosity (i.e., luminosity within the observed field of view) ofM_V≤ −2.5, which corresponds to ∼100 stars around the MSTO. We also find that increasing the signal-to-noise ratio above ∼100 at the MSTO does not improve SFH precision, which remains dominated by stochastic effects associated with the number of available stars. A main challenge driving the precision of UFD SFHs is the limitations in the accuracy of foreground dust maps. We make all photometry catalogs public as the first data release of a larger HST archival program targeting all dwarf galaxies within ∼1.3 Mpc. 

Abstract The merger timescales of isolated low-mass pairs (10⁸<M_*< 5 × 10⁹M_⊙) on cosmologically motivated orbits have not yet been studied in detail, though isolated high-mass pairs (5 × 10⁹<M_*< 10¹¹M_⊙) have been studied extensively. It is common to apply the same separation criteria and expected merger timescales of high-mass pairs to low-mass systems, however, it is unclear if their merger timescales are similar, or if they evolve similarly with redshift. We use the Illustris TNG100 simulation to quantify the merger timescales of isolated low-mass and high-mass major pairs as a function of cosmic time, and explore how different selection criteria impact the mass and redshift dependence of merger timescales. In particular, we present a physically motivated framework for selecting pairs via a scaled separation criterion, wherein pair separations are scaled by the virial radius of the primary’s Friends-of-Friends (FoF) group halo (r_sep< 1R_vir). Applying these scaled separation criteria yields equivalent merger timescales for both mass scales at all redshifts. Alternatively, static physical separation selections applied equivalently to all galaxy pairs at all redshifts lead to a difference in merger rate of up to ∼1 Gyr between low- and high-mass pairs, particularly forr_sep< 150 kpc. As a result, applying the same merger timescales to physical-separation-selected pairs will lead to a bias that systematically overpredicts low-mass galaxy merger rates. 

Abstract Stellar streams in the Milky Way are promising detectors of low-mass dark matter (DM) subhalos predicted by ΛCDM. Passing subhalos induce perturbations in streams that indicate the presence of the subhalos. Understanding how known DM-dominated satellites impact streams is a crucial step toward using stream perturbations to constrain the properties of dark perturbers. Here, we cross-match a Gaia Early Data Release 3 and SEGUE member catalog of the Cetus-Palca stream (CPS) with H3 for additional radial velocity measurements and fit the orbit of the CPS using this six-dimensional (6D) data. We demonstrate for the first time that the ultra-faint dwarf Segue 2 had a recent (77 ± 5 Myr ago) close flyby (within the stream's 2σwidth) with the CPS. This interaction enables constraints on Segue 2’s mass and density profile at larger radii ( $O\left(1\right)$kpc) than are probed by its stars ( $O\left(10\right)$pc). While Segue 2 is not expected to strongly affect the portion of the stream covered by our 6D data, we predict that if Segue 2’s mass within ∼ 6 kpc is 5 × 10⁹M_⊙, the CPS's velocity dispersion will be ∼ 40 km s⁻¹larger atϕ₁ > 20° than atϕ₁ < 0°. If no such heating is detected, Segue 2’s mass cannot exceed 10⁹M_⊙within ∼ 6 kpc. The proper motion distribution of the CPS near the impact site is mildly sensitive to the shape of Segue 2’s density profile. This study presents a critical test for frameworks designed to constrain properties of dark subhalos from stream perturbations. 

Metal nanocrystals (NCs) with different structural features are produced by seeded-electrodeposition. 

ABSTRACT Understanding the evolution of satellite galaxies of the Milky Way (MW) and M31 requires modelling their orbital histories across cosmic time. Many works that model satellite orbits incorrectly assume or approximate that the host halo gravitational potential is fixed in time and is spherically symmetric or axisymmetric. We rigorously benchmark the accuracy of such models against the FIRE-2 cosmological baryonic simulations of MW/M31-mass haloes. When a typical surviving satellite fell in ($$3.4\!-\!9.7\, \rm {Gyr}$$ ago), the host halo mass and radius were typically 26–86 per cent of their values today, respectively. Most of this mass growth of the host occurred at small distances, $$r\lesssim 50\, \rm {kpc}$$, opposite to dark matter only simulations, which experience almost no growth at small radii. We fit a near-exact axisymmetric gravitational potential to each host at z = 0 and backward integrate the orbits of satellites in this static potential, comparing against the true orbit histories in the simulations. Orbital energy and angular momentum are not well conserved throughout an orbital history, varying by 25 per cent from their current values already $$1.6\!-\!4.7\, \rm {Gyr}$$ ago. Most orbital properties are minimally biased, ≲10 per cent, when averaged across the satellite population as a whole. However, for a single satellite, the uncertainties are large: recent orbital properties, like the most recent pericentre distance, typically are ≈20 per cent uncertain, while earlier events, like the minimum pericentre or the infall time, are ≈40–80 per cent uncertain. Furthermore, these biases and uncertainties are lower limits, given that we use near-exact host mass profiles at z = 0. 

Abstract The interaction between the supersonic motion of the Large Magellanic Cloud (LMC) and the circumgalactic medium (CGM) is expected to result in a bow shock that leads the LMC’s gaseous disk. In this letter, we use hydrodynamic simulations of the LMC’s recent infall to predict the extent of this shock and its effect on the Milky Way’s (MW) CGM. The simulations clearly predict the existence of an asymmetric shock with a present-day standoff radius of ∼6.7 kpc and a transverse diameter of ∼30 kpc. Over the past 500 Myr, ∼8% of the MW’s CGM in the southern hemisphere should have interacted with the shock front. This interaction may have had the effect of smoothing over inhomogeneities and increasing mixing in the MW CGM. We find observational evidence of the existence of the bow shock in recent Hαmaps of the LMC, providing a potential explanation for the envelope of ionized gas surrounding the LMC. Furthermore, the interaction of the bow shock with the MW CGM may also explain the observations of ionized gas surrounding the Magellanic Stream. Using recent orbital histories of MW satellites, we find that many satellites have likely interacted with the LMC shock. Additionally, the dwarf galaxy Ret2 is currently sitting inside the shock, which may impact the interpretation of the reported gamma-ray excess in Ret2. This work highlights how bow shocks associated with infalling satellites are an underexplored yet potentially very important dynamical mixing process in the circumgalactic and intracluster media.