arXiv subjects

Boryana Hadzhiyska

Publications and source records attributed to Boryana Hadzhiyska.

At least 19 recordsLinked to original sources

arXiv2026

Shear-kSZ: A New Estimator for the Matter-Electron Power Spectrum from kSZ Tomography and Weak Lensing

We propose a new estimator of the electron--matter power spectrum, $P_{me}(k)$, which correlates the kinematic Sunyaev--Zel'dovich (kSZ) temperature with the product of the line-of-sight velocity field and the weak-lensing convergence. Like the stacked kSZ estimator, it factorizes into a calibratable velocity kernel times $P_{me}(k)$, but it probes the full matter distribution rather than the gas around a biased tracer. It therefore measures the baryonic suppression of the matter power spectrum, $S(k)$, one of the dominant astrophysical systematics for Stage-IV cosmic shear. We derive an analytic expression for the estimator, validate it against simulations at the per-cent level, and show that its parity structure cancels cosmic microwave background (CMB) foregrounds. We forecast the detectability with a realistic pipeline: velocities reconstructed from the simulated tracers, with and without photometric-redshift errors; the kSZ signal of all the ionized gas along the line of sight; a CMB map with Simons Observatory (SO) noise; and LSST source samples free of intrinsic alignments. A DESI-like spectroscopic sample at $0.5<z<1$ over the $20\%$ of the sky that DESI, LSST and SO share gives a $4$--$7σ$ detection. Photometric redshifts cost only $5$--$10\%$ of the significance, so LSST can supply its own velocity tracers over its full overlap with SO: with tracers at $0.1<z<1.3$ and five source samples we find $10σ$ in an end-to-end simulation, and $13σ$ with Advanced SO (16$σ$ if extending to $z < 1.5$). This corresponds to a few-per-cent measurement of $S(k)$ at $k\simeq1$--$4\,h\,{\rm Mpc}^{-1}$, the scales that matter most for cosmic shear.

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arXiv2026

Interpreting the stacked kinetic SZ signal II: the degeneracy between satellite galaxies and baryonic feedback

The kinetic Sunyaev-Zel'dovich (kSZ) signal stacked around a galaxy sample traces the gas around halos and is a powerful probe of baryonic feedback. Its interpretation, however, depends on the satellite galaxies in the sample. Using the FLAMINGO hydrodynamical simulations and DESI-like samples of luminous red galaxies (LRGs), bright galaxies survey (BGS), and emission-line galaxies (ELGs), we show that satellites and feedback have similar effects: both suppress the small-scale signal. This degeneracy arises because stacking on satellites, which are offset from the centre of their host haloes, mimics the extended gas distribution produced by feedback. Although satellites make up only 20-30% of each sample, they account for 50-80% of the signal because they occupy more massive halos than centrals; thus their imprint on the stacked profiles can be as large as that of feedback. At the precision of current DESI$\times$ACT data, neglecting satellites in the modelling biases the inferred gas fractions low, by up to a factor of two, and overestimates the feedback strength, particularly for the LRG and BGS samples. Remaining agnostic about the satellite population avoids this bias but reduces the constraining power, so robust constraints would require knowing the satellite fraction to better than 10%, for instance from lensing and clustering data of the same galaxy samples. Finally, a further contribution from satellites will become statistically significant with upcoming surveys: satellites trace the anisotropic gas distribution around their host haloes, an effect that contributes 10% of the signal, and will likely require simulation-based models to capture.

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arXiv2026

Probing Baryons with the Kinematic Sunyae Zel'dovich Effect and Machine Learning Derived Peculiar Velocities using DESI DR2 and ACT DR6

We present novel empirical constraints on average optical depths and gas density profiles from combining kinematic Sunyaev Zel'dovich effect (kSZ) measurements and nonlinear peculiar velocities, reconstructed using machine learning, for massive halos traced by DESI DR2 luminous red galaxies (LRG). The pairwise kSZ is measured using two ACT DR6 cosmic microwave background (CMB) temperature maps (ILC and 150 GHz maps) for seven luminosity-selected LRG samples. We find consistent results between the two maps and significant detections across the samples. We reconstruct LRG line-of-sight peculiar velocities in two cosmic epochs, centered on $z=$ 0.55 and 0.8, using a simulation-trained Transformer machine learning model to extend beyond the linear approximation. Average optical depths are inferred by comparing the kSZ pairwise correlation to the measured pairwise velocity correlation from the reconstructed velocity field and, separately, from a theoretical prediction using the best fit Planck cosmology, with the highest significance reaching SNR = 14.2 and 15.1 respectively. We also obtain velocity-weighted AP-filtered kSZ-stacked cluster density profiles, which show evidence of extended ionized gas around massive LRG groups and no strong redshift evolution within current measurement uncertainties. These results demonstrate the power of combining spectroscopic galaxy and CMB data, and employing machine learning methods, to probe diffuse baryons and coherent large-scale velocity fields. They open up new avenues to leverage upcoming galaxy survey data from Euclid, Roman and Rubin LSST, in tandem with multi-frequency CMB/sub-mm data from CCAT and Simons Observatory.

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arXiv2026

Model-Independent Measurement of Baryon Gas Fractions through Galaxy-Galaxy Lensing and the Kinematic Sunyaev-Zel'dovich Effect

Baryon feedback is a leading source of systematic uncertainty for cosmology from weak lensing, but measurements of the gas distribution around galaxies have largely relied on parametric profile models or simulation-calibrated frameworks. We present model independent measurements of the radial gas fraction profile around galaxies, combining galaxy-galaxy lensing and kinematic Sunyaev-Zel'dovich (kSZ) effect. We introduce a method that applies the same radial $ΔΣ$ aperture filter to both the galaxy-galaxy lensing shear field and the velocity-weighted kSZ temperature maps; their ratio directly yields $ΔΣ$ filtered gas fraction $f_{\rm gas}(R)$, the ratio of ionized gas to total matter as a function of projected radius. We apply this approach to DESI DR2 Bright Galaxy Survey (BGS, $\bar{z} \approx 0.26$) and Luminous Red Galaxy (LRG, $0.4 < z < 1.1$) samples, using ACT DR6 component-separated CMB maps for kSZ, and the HSC Year 3 shear catalog for weak lensing. After correcting for ACT beam suppression using a simulation-calibrated compensation factor, we detect baryon depletion relative to the cosmic mean baryon fraction at SNR = 17.2 (BGS) and SNR = 13.8 (LRG bin 1). Comparison with six hydrodynamical simulations from the Illustris, IllustrisTNG, SIMBA, and FLAMINGO suites shows that the fiducial FLAMINGO run most closely tracks the observed radial gas distribution in both samples, with Illustris-1 and TNG300-1 bracketing the data from below and above at small radii. We find a mild discrepancy between the kSZ measurements in the South and North Galactic Caps in one LRG redshift bin, which may indicate residual systematics. We show that the ratio is robust to splits by stellar mass and to the removal of close pairs. These results establish $ΔΣ$ filtering of kSZ versus weak lensing signal as a model-independent probe of the baryon distribution around galaxies.

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arXiv2026

BIND (Baryonic INpainting with Deep learning): A Field-level Emulator for Galaxy Groups and Clusters

Baryonic feedback is a dominant source of systematic uncertainty for upcoming weak-lensing surveys, but current tools for modeling its effect rely on spherical approximations and density profiles calibrated almost entirely on two-point statistics. We introduce BIND (Baryonic INpainting with Deep learning), a conditional flow-matching model that learns a field-level mapping from dark-matter-only halos to their hydrodynamical counterparts. BIND is trained on halos from the 1024 paired hydrodynamical and dark-matter-only simulations of the CAMELS $50\,h^{-1}\,\mathrm{Mpc}$ SB35 suite and samples dark matter, gas, and stellar mass fields over redshift across the full 35-dimensional $Λ$CDM and IllustrisTNG galaxy formation parameter space. BIND recovers dark matter, gas, and stellar masses at the percent level, reproduces azimuthally averaged profiles to $\lesssim10\%$ at all radii, and matches halo shape distributions with high fidelity. The learned parameter dependence captures the rank correlations between the generated fields and the subgrid parameters, and the field-level response to individual parameter variations is recovered in both sign and morphology. Halo mass is never supplied as conditioning, yet the baryon fraction, stellar-to-halo mass relation, inter-component scaling relations, and the joint covariance of their residuals are all reproduced. We finally show that, applied halo-by-halo to a $(50\,h^{-1}\,\mathrm{Mpc})^3$ $N$-body volume with $512^3$ particles, BIND reproduces the projected matter power spectrum suppression to the accuracy ceiling set by pasting in the hydrodynamical halos themselves, in minutes on one GPU. We release the trained BIND models and all generated halos as open-source tools. A companion paper extends BIND to thermodynamic fields and non-Gaussian weak-lensing statistics.

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arXiv2026

BINDing the lightcone: A suite of astrophysical ray-traced weak lensing and SZ maps

Recent multiwavelength observations of galaxy group and cluster gas suggest stronger baryonic feedback than our best-calibrated hydrodynamical simulations produce, while modeling this feedback remains a primary source of uncertainty in Stage-IV weak-lensing (WL) analyses. We present a suite of ray-traced maps generated with BIND (Baryonic INpainting with Deep learning), a conditional flow-matching model that paints baryonic mass and gas thermodynamics onto the halos of dark-matter-only simulations, and which was developed in a companion paper. Applied to IllustrisTNG300-Dark and ray-traced, we generate convergence, optical depth, and Compton-$y$ maps at five source redshifts, each with $1000$ pseudo-independent realizations. We build lightcones across a 256-node Sobol sequence spanning the thirty-dimensional IllustrisTNG galaxy formation prior, with individual parameter variations and at the fiducial model. In validation, the maps match those built from the IllustrisTNG300 halos to within LSST-Y10-like precision for a range of WL statistics. Across the prior, the response to feedback exceeds Stage-IV statistical precision by more than an order of magnitude on small scales, and different statistics respond to different model sectors: galactic winds control the WL power spectrum and gas auto- and cross-spectra, while the stellar initial mass function slope and AGN parameters shape the morphological statistics (PDF, peaks, minima, and Minkowski functionals). Finally, we find that the response of statistics can be compressed into seven halo properties which linearly predict a range of WL and SZ statistics. We publicly release the maps, statistics, and model tables.

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arXiv2026

A new measurement of the FRB DM-galaxy cross correlation and a first joint analysis with the kinematic SZ effect

Understanding the distribution of cosmic baryons is crucial for advancing cosmology and galaxy formation. Localized Fast Radio Bursts (FRBs) are a promising new probe of the diffuse gas, but measurements thus far have been limited by small sample size. In this work, we measure the FRB dispersion measure (DM)-galaxy cross correlation with 130 localized FRBs, including new spectroscopic host redshifts from the DSA-110, and the DESI Legacy Survey Bright Galaxy Sample. We detect this signal at the highest significance to date ($6.5σ$) in both configuration and harmonic space. By comparing to simulations and a halo model, we demonstrate that this statistic can constrain the strength of baryonic feedback. Our measurements disfavor a no-feedback scenario in which gas traces the underlying dark matter at $\sim\,9σ$. In addition to small scale feedback, this represents one of the first direct measurements of the clustering of electrons on scales larger than a few Mpc. We compare our measurement to recent kinematic Sunyaev-Zeldovich effect (kSZ) studies, which show good agreement despite the differences in observational methods and sample selection. Finally, we make a first attempt at breaking the kSZ optical depth degeneracy with FRBs, jointly measuring the growth rate of large-scale structure $fσ_8$. With future samples, FRB two-point statistics will provide precision constraints on the distribution of cosmic baryons and complement other probes.

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arXiv2026

Interpreting the stacked kinetic SZ effect I: velocity reconstruction and non-linear velocity effects

The stacked kinetic Sunyaev-Zel'dovich (kSZ) signal probes the velocity-weighted projected gas momentum around galaxies, and is emerging as a powerful probe of gas fractions and baryonic feedback. Its interpretation, however, rests on several assumptions that we test in this pair of companion papers. Using the FLAMINGO hydrodynamical simulations and DESI-like galaxy mocks for luminous red galaxies (LRGs), the bright galaxy sample (BGS), and emission-line galaxies (ELGs), we identify the ingredients required to model the signal to better than $10\%$. This first paper focuses on velocities. We decompose the signal into a dominant bulk-flow term, proportional to the mean optical depth, plus non-linear terms arising from the small-scale gas momentum and its coupling to the stacking velocity. When the stacking velocities are reconstructed from linear information in real space alone -- an idealisation which is not possible in practice -- the non-linear terms cancel and the signal traces the mean optical depth to within a few per cent. When the stacking velocity instead retains non-linear information or is affected by redshift-space distortions, the non-linear terms suppress the signal by $10-20\%$: a $1-2σ$ effect for current data that is expected to be statistically significant for upcoming surveys, and one that depends only weakly on baryonic feedback. Our results reveal a trade-off: velocity estimators that retain small-scale information boost signal-to-noise but require simulation-based modelling, whereas conservative reconstructions simplify the interpretation at the cost of signal-to-noise.

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arXiv2026

Fewer simulations, sharper covariances: Reducing mock covariance noise with Zeldovich approximation control variates

We present a control-variate method for reducing the variance of power spectrum covariance matrix estimates from simulations of large-scale structure. The key idea is to pair each mock simulation with a cheap Zeldovich-approximation realization sharing the same initial conditions, and to use the known statistical properties of the Zeldovich field to remove correlated sample variance from the covariance estimator. Under a Gaussian disconnected approximation, we derive fully analytic expressions for both the optimal control-variate coefficient, $β(k,\ell;k',\ell')$, and the corresponding correlation, $ρ(k,\ell;k',\ell')$, in terms of the auto- and cross-power spectra of the target and control fields. In the monopole case, the correlation takes the particularly simple form $ρ(k,k') = r^2(k),r^2(k')$, where $r(k)$ is the standard cross-correlation coefficient between the target and Zeldovich fields, implying that covariance estimation remains highly efficient whenever the two fields are strongly correlated. For masked redshift-space lognormal mocks, resembling Luminous Red Galaxies from the Dark Energy Spectroscopic Instrument (DESI), we find that the control-variate estimator reduces the variance of the covariance matrix by approximately an order of magnitude on large scales, $k \lesssim 0.05\,h\,{\rm Mpc}^{-1}$, precisely where accurate covariance estimation is most challenging. The gains are smaller for higher $k$ but typically accelerate convergence by a factor of 2-3, substantially lowering the computational cost of covariance estimation for current and upcoming large-scale structure surveys. Due to its simplicity, this method is readily implementable in current imaging and spectroscopic surveys (e.g., DESI, Euclid, LSST, PFS, SPHEREx).

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arXiv2026

Estimating the triaxiality of massive clusters from 2D observables in MillenniumTNG with machine learning

Properties of massive galaxy clusters, such as mass abundance and concentration, are sensitive to cosmology, making cluster statistics a powerful tool for cosmological studies. However, favoring a more simplified, spherically symmetric model for galaxy clusters can lead to biases in the estimates of cluster properties. In this work, we present a deep-learning approach for estimating the triaxiality and orientations of massive galaxy clusters (those with masses $\gtrsim 10^{14}\,M_\odot h^{-1}$) from 2D observables. We utilize the flagship hydrodynamical volume of the suite of cosmological-hydrodynamical MillenniumTNG (MTNG) simulations as our ground truth. Our model combines the feature extracting power of a convolutional neural network (CNN) and the message passing power of a graph neural network (GNN) in a multi-modal, fusion network. Our model is able to extract 3D geometry information from 2D idealized cluster multi-wavelength images (soft X-ray, medium X-ray, hard X-ray and tSZ effect) and mathematical graph representations of 2D cluster member observables (line-of-sight radial velocities, 2D projected positions and V-band luminosities). Our network improves cluster geometry estimation in MTNG by $30\%$ compared to assuming spherical symmetry. We report an $R^2 = 0.85$ regression score for estimating the major axis length of triaxial clusters and correctly classifying $71\%$ of prolate clusters with elongated orientations along our line-of-sight.

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arXiv2026

ELG$\times$LRG distribution through dark matter halo dynamics

We investigate the clustering and halo occupation distribution (HOD) of DESI Y1 emission-line (ELGs) and luminous red (LRGs) galaxies at $0.8<z<1.1$, including their cross-correlation (ELG$\times$LRG), using the AbacusSummit suite and a new Halo Occupation Model (HOMe) for galaxy multi-tracers. This integrates intra-halo dynamics, halo exclusion, and quenching, bridging insights from hydrodynamical, HOD, abundance-matching, and semi-analytic studies. Leveraging full phase-space information from the Uchuu N-body simulation, and sampling satellites from dark-matter particle positions via physically motivated prescriptions, HOMe reproduces the anisotropic clustering down to $s=200\,h^{-1}$kpc with unprecedented accuracy. Model parameters are inferred solely from two-point statistics using a two-level Bayesian framework, yielding high-fidelity ELG, LRG and cross-reference catalogs. We find that satellite ELGs behave as incoherent flows within their parent halos, dominating the clustering below $4\,h^{-1}$Mpc. The HOD from the best-fit HOMe has the following properties: (i) 90.50% (85.91%) of ELGs (LRGs) are central galaxies without satellites, residing in halos of $M_{\rm vir}\sim6.6\times10^{11}\,(1.2\times10^{13})\,h^{-1}{\rm M}_\odot$; (ii) the ELG$\times$LRG cross-correlation is governed by central-central pairs and shaped by halo exclusion on $2-5\,h^{-1}$Mpc scales; (iii) 9.50% (14.09%) of ELGs (LRGs) are satellites, of which 1.09% (3.52%) inhabit halos with a central galaxy of the same species in a maximally conformal configuration, 7.02% (0.005%) orbit complementary hosts in a minimally conformal state, and 0.58% (10.57%) are orphans. The high sensitivity of HOMe precisely captures the dynamics of satellites in different host environments, opening a promising avenue for understanding systematics, the dynamical nature of dark matter, potentially distinguishing gravity models.

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arXiv2026

Cosmological constraints from the small scale clustering of Emission Line Galaxies

Spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI) and Euclid are mapping the spatial distribution of millions of galaxies, with Emission Line Galaxies (ELGs) serving as the dominant tracer in the redshift range $0.8<z<1.6$. Standard approaches for extracting cosmological information from galaxy clustering, however, typically discard highly constraining measurements from the nonlinear regime. We apply SHAMe-SF - a modification of Subhalo Abundance Matching tailored for star-forming galaxy samples - to analyse the three-dimensional clustering of DESI ELGs from the One-Percent data release, extending their cosmological analysis deep into the nonlinear regime. We validate our pipeline using two mock ELG samples drawn from the state-of-the-art cosmological hydrodynamical simulation MillenniumTNG, demonstrating that our model yields unbiased constraints on $σ_8$ and $Ω_{\rm m}h^2$ down to scales of $0.3~h^{-1}$Mpc on both samples. We find that including scales below $0.8~h^{-1}$Mpc is critical for mitigating projection effects and obtaining unbiased constraints on $σ_8$. Applied to the DESI One-Percent measurements, our analysis yields $\sim6$% constraints on $σ_8 = 0.81^{+0.05}_{-0.06}$ and $Ω_{\rm m}h^2=0.146^{+0.009}_{-0.009}$. Remarkably, the accuracy of these constraints is similar to that obtained from the combined full-shape analysis of all DESI DR1 tracers, yet using only 1% of the survey volume. A naive extrapolation of our results from the One-Percent to the full survey area suggests that the complete survey could deliver roughly an order-of-magnitude improvement in precision - a prospect that, while subject to significant practical challenges, illustrates the cosmological potential encoded in the nonlinear regime.

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arXiv2026

Detection of the Pairwise Kinematic Sunyaev-Zel'dovich Effect and Pairwise Velocity with DESI DR1 Galaxies and ACT DR6 and Planck CMB Data

We present a 9.3-sigma detection of the pairwise kinematic Sunyaev-Zeldovich (kSZ) effect by combining a sample of 913,286 Luminous Red Galaxies (LRGs) from the Dark Energy Spectroscopic Instrument Data Release 1 (DESI DR1) catalog and co-added Atacama Cosmology Telescope (ACT DR6) and Planck cosmic microwave background (CMB) temperature maps. This represents the highest-significance pairwise kSZ measurement to date. The analysis uses three ACT CMB temperature maps: co-added 150 GHz, total frequency maps, and a component-separated Internal Linear Combination (ILC) map, all of which cover 19,000 square degrees of the sky from Advanced ACTPol observations conducted between 2017 and 2022. Comparison of the results of these three maps serves as a consistency check for potential foreground contamination that may depend on the observation frequency. An estimate of the best-fit mass-averaged optical depth is obtained by comparing the pairwise kSZ curve with the linear-theory prediction of the pairwise velocity under the best-fit Planck cosmology, and is compared with predictions from simulations. This estimate serves as a reference point for future comparisons with thermal SZ-derived optical depth measurements for the same DESI cluster samples, which will be presented in a companion paper. Finally, we employ a machine-learning approach trained on simulations to estimate the optical depth for 456,803 DESI LRG-identified clusters within the simulated mass range (greater than about 1e13 solar masses). These are combined with the measured kSZ signal to infer the individual cluster peculiar velocities, providing the opportunity to constrain the behavior of gravity and the dark sector over a range of cosmic scales and epochs.

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arXiv2026

AbacusPNG: A modest set of simulations of local-type primordial non-Gaussianity in the DESI era

A measurement of a primordial non-Gaussianity (PNG) signal through late- or early-Universe probes has the potential to transform our understanding of the physics of the primordial Universe. $N$-body simulations, such as the public \textsc{AbacusPNG} set presented in this study, consisting of 9 boxes, each of size $L_{\rm box} = 2~{\rm Gpc}/h$ and particle mass of $1.01 \times 10^{10} \ M_\odot/h$, provide a viable path forward. As validation, we find good agreement between the simulations and our expectations from one-loop perturbation theory and the `separate universe' method for the matter bispectrum, matter power spectrum and the halo bias parameter associated with PNG, $b_ϕ$. As a science application, we investigate the link between halo assembly bias and $b_ϕ$ for halo properties known to play a vital role in accurately predicting galaxy clustering: concentration, shear (environment), and accretion rate. We find a strong response for all three parameters, suggesting that the connection between $b_ϕ$ and the assembly history of halos needs to be taken into account by future PNG analyses. We further perform the first study of the $b_ϕ$ parameter from fits to early DESI data of the luminous red galaxy (LRG) and quasi-stellar object (QSO) samples and comment on the effect on $f_{\rm NL}$ constraints for the allowed galaxy-halo models (note that $σ[f_{\rm NL}] \propto \frac{σ[b_ϕ]}{b_ϕ}$). We find that the error on $f_{\rm NL}$ is 21, 6, 22 for the LRGs at $z = 0.5$ and $z = 0.8$ and QSOs at $z = 1.4$, respectively, suggesting that a thorough understanding of galaxy assembly bias is warranted so as to perform robust high-precision analysis of local-type PNG with future surveys. Simulations publicly available at https://app.globus.org/file-manager?origin_id=ffc65d7a-0bf9-11ec-90b4-41052087bc27

astro-ph.CO↗

arXiv2026

Measurements of the Thermal Sunyaev-Zel'dovich Effect with ACT and DESI Luminous Red Galaxies

Cosmic Microwave Background (CMB) photons scatter off the free-electron gas in galaxies and clusters, allowing us to use the CMB as a backlight to probe the gas in and around low-redshift galaxies. The thermal Sunyaev-Zel'dovich effect, sourced by hot electrons in high-density environments, measures the thermal pressure of the target objects, shedding light on halo thermodynamics and galaxy formation and providing a path toward understanding the baryon distribution around cosmic structures. We use a combination of high-resolution CMB maps from the Atacama Cosmology Telescope (ACT) and photometric luminous red galaxy (LRG) catalogues from the Dark Energy Spectroscopic Instrument (DESI) to measure the thermal Sunyaev-Zel'dovich signal in four redshift bins from $z=0.4$ to $z=1.2$, with a combined detection significance of 19$σ$ when stacking on the fiducial CMB Compton-$y$ map. We discuss possible sources of contamination, finding that residual dust emission associated with the target galaxies is important and limits current analyses. We discuss several mitigation strategies and quantify the residual modelling uncertainty. This work complements closely related measurements of the kinematic Sunyaev-Zel'dovich and weak lensing of the same galaxies.

astro-ph.CO↗

arXiv2026

Illuminating the Physics of Cosmic Origin and Evolution: A UK Space Frontiers 2035 White Paper

Understanding the Universe's origins and evolution remains one of the most fundamental challenges in modern cosmology. This white paper explores three key science priorities in this field: unravelling the physics of cosmic inflation, investigating the accelerating expansion of the Universe, and precisely measuring the sum of the neutrino masses. Achieving these goals requires a dedicated survey to map the large-scale structure at high redshift in unprecedented detail. We describe how this can be achieved through a mission concept called SIRMOS, providing a high-throughput, highly multiplexed spectroscopic capability to obtain accurate redshifts for over 100 million galaxies over a wide sky area. Such a survey would leverage the deepest existing wide-area photometric catalogues for targeting, with spectra offering continuous 1.25-2.5~$μ$m wavelength coverage at moderate resolution, allowing precise redshift measurements in the $1<z<4$ range with minimal bias. We outline the scientific opportunities this presents. Recent years have seen significant advances in instrumentation, including digital micromirror devices, complex telescope mirrors, large detector arrays, and data processing pipelines. While these technologies have been demonstrated in terrestrial applications, such a survey is a unique opportunity to apply these proven capabilities in space to address fundamental questions in cosmology. Participation in such a mission will simultaneously deliver a compelling science case, help align UK Space Agency and STFC strategies, demonstrate the UK's growing capability in end-to-end space missions, and strengthen the national space economy through high-value industrial participation.

astro-ph.IM↗

arXiv2026

Disentangling the Halo: Joint Model for Measurements of the Kinetic Sunyaev-Zeldovich Effect and Galaxy-Galaxy Lensing

We present the first joint analysis of the kinetic Sunyaev-Zeldovich (kSZ) effect with galaxy-galaxy lensing (GGL) for CMASS galaxies in the Baryon Oscillation Spectroscopic Survey (BOSS). We show these complementary probes can disentangle baryons from dark matter in the outskirts of galactic halos by alleviating model degeneracies that are present when fitting to kSZ or GGL measurements alone. In our joint kSZ+GGL analysis we show that the baryon density profile is well constrained on scales from 0.3 to 50 Mpc/$h$. With our well constrained profile of the baryon density, we provide direct comparisons to simulations. For our model we find an outer slope of the baryon distribution that is shallower than predicted by some hydrodynamical simulations, consistent with enhanced baryonic feedback. We also show that not including baryons in a model for GGL can bias halo mass estimates low by $\sim 20\%$ compared to a model that includes baryons and is jointly fit to kSZ+GGL measurements. Our modelling code galaxy-galaxy lensing and kSZ (\texttt{glasz}) is publicly available at https://github.com/James11222/glasz.

astro-ph.CO↗

arXiv2025

kSZ for everyone: the pseudo-Cl approach to stacking

We present a harmonic-space estimator for the cross-correlation between the kinematic Sunyaev-Zel'dovich effect and the reconstructed galaxy momentum field that offers several practical advantages over the traditional stacking approach. The estimator is easy to deploy using relatively modest computational resources and recovers all information available in the galaxy-kSZ cross-correlation. In particular, by using well-understood power spectrum estimation techniques, its statistical uncertainties, including potential correlated uncertainties with other large-scale structure observables, can be easily and accurately estimated. Moreover, standard kSZ stacking measurements can be reconstructed exactly from the estimator at a lower computational cost, employing harmonic-space, catalog-level techniques to recover all small-scale information.

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