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Matteo Viel

Publications and source records attributed to Matteo Viel.

At least 37 records · Page 2Linked to original sources

Cosmo-FOLD: Fast generation and upscaling of field-level cosmological maps with overlap latent diffusion

We demonstrate the capabilities of probabilistic diffusion models to reduce dramatically the computational cost of expensive hydrodynamical simulations to study the relationship between observable baryonic cosmological probes and dark matter at field level and well into the non-linear regime. We introduce a novel technique, Cosmo-FOLD (Cosmological Fields via Overlap Latent Diffusion) to rapidly generate accurate and arbitrarily large cosmological and astrophysical 3-dimensional fields, conditioned on a given input field. We are able to generate TNG300-2 dark matter density and gas temperature fields from a model trained only on ~1% of the volume (a process we refer to as `upscaling'), reproducing both large scale coherent dark matter filaments and power spectra to within 10% for wavenumbers k <= 5 h Mpc^-1. These results are obtained within a small fraction of the original simulation cost and produced on a single GPU. Beyond one and two points statistics, the bispectrum is also faithfully reproduced through the inclusion of positional encodings. Finally, we demonstrate Cosmo-FOLD's generalisation capabilities by upscaling a CAMELS volume of 25 (Mpc h^-1)^3 to a full TNG300-2 volume of 205 (Mpc h^-1)^3$ with no fine-tuning. Cosmo-FOLD opens the door to full field-level simulation-based inference on cosmological scale.

astro-ph.CO↗

From the Intergalactic to the Interstellar Scales -- EQUALS: a High-resolution Legacy Survey of Gas in the Distant Universe Using ESPRESSO

Understanding how the Universe evolved from diffuse primordial gas into the rich cosmic web we observe today is one of the great challenges of modern astrophysics. Quasar absorption lines - the imprints left by intervening gas on the light from distant quasars - provide key diagnostics of many aspects of this investigation, ranging from fundamental physics to cosmology and galaxy formation. The unprecedented combination of extremely precise wavelength calibration, high spectral resolution and high sensitivity of the Echelle SPectrograph for Rocky Exoplanet and Stable Spectroscopic Observations (ESPRESSO) has finally enabled observations that will further constrain both state-of-the-art cosmological simulations of galaxy evolution and theoretical stellar nucleosynthetic yields. In this article, we present the ESPRESSO Quasar Absorption Line Survey (EQUALS), an ESO Large Programme, designed to tackle several outstanding questions from constraining the properties of dark matter at the smallest scales probed by the Lyman-alpha forest to determining the temperature of the intergalactic medium at z ~ 4 and precisely quantifying the chemical contributions of stellar populations in the early Universe. EQUALS will provide a legacy sample of deep spectra to showcase ESPRESSO capabilities to the quasar absorption line community whilst providing epoch measurements for the key science goals of upcoming spectroscopic instrumentation on the next generations of telescopes.

astro-ph.GA↗

The Denario project: Deep knowledge AI agents for scientific discovery

We present Denario, an AI multi-agent system designed to serve as a scientific research assistant. Denario can perform many different tasks, such as generating ideas, checking the literature, developing research plans, writing and executing code, making plots, and drafting and reviewing a scientific paper. The system has a modular architecture, allowing it to handle specific tasks, such as generating an idea, or carrying out end-to-end scientific analysis using Cmbagent as a deep-research backend. In this work, we describe in detail Denario and its modules, and illustrate its capabilities by presenting multiple AI-generated papers generated by it in many different scientific disciplines such as astrophysics, biology, biophysics, biomedical informatics, chemistry, material science, mathematical physics, medicine, neuroscience and planetary science. Denario also excels at combining ideas from different disciplines, and we illustrate this by showing a paper that applies methods from quantum physics and machine learning to astrophysical data. We report the evaluations performed on these papers by domain experts, who provided both numerical scores and review-like feedback. We then highlight the strengths, weaknesses, and limitations of the current system. Finally, we discuss the ethical implications of AI-driven research and reflect on how such technology relates to the philosophy of science. We publicly release the code at https://github.com/AstroPilot-AI/Denario. A Denario demo can also be run directly on the web at https://huggingface.co/spaces/astropilot-ai/Denario, and the full app will be deployed on the cloud.

cs.AI↗

Detecting the IGM metal enrichment with the 2-point correlation function of the flux. Application to the UVES deep spectrum

The distribution and the abundance of metals in the intergalactic medium (IGM) have strong implications on galaxy formation and evolution models. The ionic transitions of heavy elements in quasar spectra can probe both the mechanisms and the sources of chemical pollution, but high resolution, high signal-to-noise ratio (S/N) spectra are required, as the IGM absorbers can be too weak for direct detection. In this work, we investigate the IGM metallicity, focusing on the detection of the weak absorption lines. We exploited the cosmological tool of the two-point correlation function (TPCF) and applied it to the transmitted flux in the CIV forest of the ultra-high S/N UVES spectrum of the quasar HE0940-1050 (z~3). We also "deabsorbed" the strongest circum-galactic medium (CGM) systems to reveal the underlying IGM signal. For each test, we generated 1000 mock spectra with shuffled line positions to derive an estimate for the TPCF noise level. The TPCF shows a clear peak at the characteristic velocity separation of the CIV doublet, but when deabsorbing the CGM contribution (i.e. all metal lines and CIV lines associated with logN(HI)>14.0), the peak is no longer significant at 1$σ$, although 7 weak CIV systems remain visible. Even adding up to 135 additional weak mock CIV systems (logN(HI)<14.0) to the spectrum does not produce a significant CIV peak. Eventually, when we create a synthetic spectrum with gaussian distributed noise and same S/N as the complete spectrum, we remove the signal caused by the spectral intrinsic features and thus find a peak compatible with a metallicity of -3.80<[C/H]<-3.50. We conclude that the TPCF method is not sensitive to the presence of the weakest systems in the real spectrum, despite the extremely high S/N and high resolution of the data. However, the results of this statistical technique would possibly change when combining more than one line of sight.

astro-ph.GA↗

Constraints on Primordial Magnetic Fields from the Lyman-α forest

We present the first constraints on primordial magnetic fields from the Lyman-$α$ forest using full cosmological hydrodynamic simulations. At the scales and redshifts probed by the data, the flux power spectrum is extremely sensitive to the extra power induced by primordial magnetic fields in the linear matter power spectrum, at a scale that we parametrize with $k_{\rm peak}$. We rely on a set of more than a quarter million flux models obtained by varying thermal, reionization histories and cosmological parameters. We find a hint of extra power that is well fitted by the PMF model with $B\sim 0.2$ nG, corresponding to $k_{\rm peak}\sim 20$ Mpc$^{-1}$. However, when applying very conservative assumptions on the modelling of the noise, we obtain a 3$σ$ C.L. lower limit $k_{\rm peak}> 30$ Mpc$^{-1}$ which translates into the tightest bounds on the strength of primordial intergalactic magnetic fields: $B < 0.30$ nG (for fixed, nearly scale-invariant $n_{\rm B}=-2.9$).

astro-ph.CO↗

Constraining Mixed Dark Matter models with high redshift Lyman-alpha forest data

This study sets new constraints on Cold+Warm Dark Matter (CWDM) models by leveraging the small-scale suppression of structure formation imprinted in the Lyman-$α$ forest. Using the Sherwood-Relics suite, we extract high-fidelity flux power spectra from simulated Lyman-$α$ forest data, spanning a broad range of cosmologies and thermal histories. This enables precise constraints on the warm dark matter (WDM) fraction, $f_{\mathrm{WDM}}$, and the mass of the WDM particle, $m_{\mathrm{WDM}}$. A key advancement of our analysis is the integration of a neural network emulator directly at the likelihood level, significantly accelerating Bayesian parameter inference. With new observations of high-redshift ($z$ = 4.2$-$5.0) quasar spectra from UVES and HIRES, we establish stringent upper limits: for $m_{\mathrm{WDM}}$ = 1 keV, we find $f_{\mathrm{WDM}} < 0.16$ (2$σ$), with constraints loosening to 35\%, 50\%, and 67\% for $m_{\mathrm{WDM}}$ = 2, 3, and 4 keV, respectively. Our results for pure WDM reaffirm the lower bounds of previous work. Crucially, we account for the fixed resolution of simulations and the impact of patchy reionization, demonstrating their minimal influence on mixed dark matter constraints. This robustness paves the way for tighter bounds with improved statistical samples in the future. Our findings suggest that CWDM models can naturally accommodate mild suppression of matter clustering in the high redshift Lyman-$α$ forest 1D flux power, potentially offering a resolution to some of the ongoing cosmological tensions at low redshifts, namely the $S_{8}$ tension.

astro-ph.CO↗

DeepCHART: Mapping the 3D dark matter density field from Ly$α$ forest surveys using deep learning

We present DeepCHART (Deep learning for Cosmological Heterogeneity and Astrophysical Reconstruction via Tomography), a deep learning framework designed to reconstruct the three-dimensional dark matter density field at redshift $z=2.5$ from Ly$α$ forest spectra. Leveraging a 3D variational autoencoder with a U-Net architecture, DeepCHART performs fast, likelihood-free inference, accurately capturing the non-linear gravitational dynamics and baryonic processes embedded in cosmological hydrodynamical simulations. When applied to joint datasets combining Ly$α$ forest absorption and coeval galaxy positions, the reconstruction quality improves further. For current surveys, such as Subaru/PFS, CLAMATO, and LATIS, with an average transverse sightline spacing of $d_\perp=2.4h^{-1}$cMpc, DeepCHART achieves high-fidelity reconstructions over the density range $0.4<Δ_{\rm DM}<15$, with a voxel-wise Pearson correlation coefficient of $ρ\simeq 0.77$. These reconstructions are obtained using Ly$α$ forest spectra with signal-to-noise ratios as low as 2 and instrumental resolution $R=2500$, matching Subaru/PFS specifications. For future high-density surveys enabled by instruments such as ELT/MOSAIC and WST/IFS with $d_\perp\simeq 1h^{-1}\mathrm{cMpc}$, the correlation improves to $ρ\simeq 0.90$ across a wider dynamic range ($0.25<Δ_{\rm DM}<40$). The framework reliably recovers the dark matter density PDF as well as the power spectrum, with only mild suppression at intermediate scales. In terms of cosmic web classification, DeepCHART successfully identifies 81% of voids, 75% of sheets, 63% of filaments, and 43% of nodes. We propose DeepCHART as a powerful and scalable framework for field-level cosmological inference, readily generalisable to other observables, and offering a robust, efficient means of maximising the scientific return of upcoming spectroscopic surveys.

astro-ph.CO↗

Matter power spectrum induced by primordial magnetic fields: from the linear to the non-linear regime

Linear theory predicts that primordial magnetic fields (PMFs) enhance the matter power spectrum on small scales. However, the linear approximation breaks down on sufficiently small scales where PMF-induced baryon perturbations back-react onto the magnetic fields. Previous studies assumed that the baryon power spectrum would be sharply suppressed in this non-linear regime, based on arguments related to the magnetic Jeans scale. For the first time, we perform dedicated magnetohydrodynamic (MHD) simulations to investigate the transition from the linear to the non-linear regime. Our simulations confirm the expected linear behavior on large scales. In the non-linear regime, however, we find that the dimensionless baryon power spectrum saturates to an $\mathcal{O}(1)$ value, which contrasts with previous analytical expectations. Additionally, our results show that several past studies overestimated the total matter power spectrum by orders of magnitude near the transition to non-linearity. Thus, the results presented in this work are useful to obtain more accurate constraints on PMFs from structure formation processes and/or different tracers of cosmic structures.

astro-ph.CO↗

Weighing neutrinos with 21cm Intensity Mapping at the SKAO

We explore the constraining power of future 21cm intensity mapping (IM) observations at the SKAO, focusing primarily on the sum of neutrino masses, $Σm_ν$. We forecast observations of the 21cm IM auto-power spectrum as well as the 21cm IM and galaxy surveys cross-correlation power spectrum. We construct different synthetic data sets of observations for the 21cm IM observables. For galaxy clustering, we consider two stage-IV surveys to mimic a DESI-like and Euclid-like cross-correlation signal. We study the impact of assuming three different fiducial values for the sum of neutrino masses, i.e. $Σm_ν= 0.06, 0.1, 0.4$ eV, in the synthetic data sets. To investigate the constraining power of the forecasted 21cm observations, we build a likelihood code. We find that the 21cm auto-power spectrum alone could provide an upper limit on the sum of neutrino masses of $Σm_ν< 0.287$ eV, at $95\%$ confidence level, for the case of the lowest fiducial value of $Σm_ν$. This result is comparable to the upper limits provided by cosmic microwave background (CMB) observations alone. When combining the 21cm auto-power spectrum synthetic data set with Planck 2018 CMB measurements, we find a tighter upper limit of $Σm_ν< 0.105$ eV, which improves on the constraints from Planck alone. We obtain a similar result with 21cm and galaxy clustering cross-correlation power spectrum, whose detection is more easily achieved as they are less affected by systematic effects. Combining with Planck 2018 data, we find the upper limits of $Σm_ν< 0.116$ eV and $Σm_ν< 0.117$ eV for the 21cm signal in cross-correlation with the DESI-like and Euclid-like surveys, respectively. These constraints are comparable to those obtained by combining Planck data with the 21cm auto-power spectrum synthetic data sets, thus supporting the case for 21cm cross-correlation detections.

astro-ph.CO↗

Constraints on dark photon dark matter from Lyman-$α$ forest simulations and an ultra-high signal-to-noise quasar spectrum

The ultralight dark photon is a well-motivated, hypothetical dark matter candidate. In a dilute plasma, they can resonantly convert into photons, and heat up the intergalactic medium between galaxies. In this work, we explore the dark photon dark matter parameter space by comparing synthetic Lyman-$α$ forest data from cosmological hydrodynamical simulations to observational data from VLT/UVES of the quasar HE0940-1050 ($z_{\rm em}=3.09$). We use a novel flux normalization technique that targets under-dense gas, reshaping the flux probability distribution. Not only do we place robust constraints on the kinetic mixing parameter of dark photon dark matter, but notably our findings suggest that this model can still reconcile simulated and observed Doppler parameter distributions of $z\sim0$ Lyman-$α$ lines, as seen by HST/COS. This work opens new pathways for the use of the Lyman-$α$ forest to explore new physics, and can be extended to other scenarios such as primordial black hole evaporation, dark matter decay, and annihilation.

astro-ph.CO↗

Reconstructing the dark energy density in light of DESI BAO observations

In light of the evidence for dynamical dark energy (DE) found from the most recent Dark Energy Spectroscopic Instrument (DESI) baryon acoustic oscillation (BAO) measurements, we perform a non-parametric, model-independent reconstruction of the DE density evolution. To do so, we develop and validate a new framework that reconstructs the DE density through a third-degree piece-wise polynomial interpolation, allowing for direct constraints on its redshift evolution without assuming any specific functional form. The strength of our approach resides in the choice of directly reconstructing the DE density, which provides a more straightforward relation to the distances measured by BAO than the equation of state parameter. We investigate the constraining power of cosmic microwave background (CMB) observations combined with supernovae (SNe) and BAO measurements. In agreement with results from other works, we find a preference for deviations from $Λ$CDM, with a significance of $2.4σ$ when using the Dark Energy Survey Year 5 (DESY5) SNe data, and $1.3σ$ with PantheonPlus. In all the cases we consider, the derived DE equation of state parameter presents evidence for phantom crossing. By investigating potential systematic effects in the low-redshift samples of DESY5 observations, we confirm that correcting for the offset in apparent magnitude with respect to PantheonPlus data, as suggested in previous studies, completely removes the tension. Furthermore, we assess the risk of potentially overfitting the data by changing the number of interpolation nodes. As expected, we find that with lesser nodes we get a smoother reconstructed behavior of the DE density, although with similar overall features. The pipeline developed in this work is ready to be used with future high-precision data to further investigate the evidence for a non-standard background evolution.

astro-ph.CO↗

Redshift-Space Distortions in Massive Neutrinos Cosmologies

We study the Kaiser formula for biased tracers in massive neutrino cosmologies by comparing its predictions with a large set of N-body simulations. In particular, we examine the ambiguity in the definition of the peculiar velocity contribution at linear level, whether it should be expressed in terms of the total matter velocity field or only the cold-matter component, comprised of cold dark matter and baryons. We revisit and extend previous qualitative studies on the topic with larger statistics and including a full fit of halo power spectrum and halo-matter cross-power spectrum measurements. We find clear evidence that the clustering of halos in redshift space is correctly described assuming that halo velocity is tracing the velocity field of cold-matter. The opposite assumption provides a worse fit to the simulated data and can lead to a spurious running of nuisance parameters in the perturbative galaxy power spectrum model.

astro-ph.CO↗

JERALD: high-fidelity dark matter, stellar mass and neutral hydrogen maps from fast N-body simulations

We present a new code and approach, JERALD -- JAX Enhanced Resolution Approximate Lagrangian Dynamics -- , that improves on and extends the Lagrangian Deep Learning method of Dai & Seljak (2021), producing high-resolution dark matter, stellar mass and neutral hydrogen maps from lower-resolution approximate $N$-body simulations. The model is trained using the Sherwood-Relics simulation suite (for a fixed cosmology), specifically designed for the intergalactic medium and the neutral hydrogen distribution in the cosmic web. The output is tested in the redshift range from $z=5$ to $z=0$ and the generalization properties of the learned mapping is demonstrated. JERALD produces maps with dark matter, stellar and neutral hydrogen power spectra in excellent agreement with full-hydrodynamic simulations with $8\times$ higher resolution, at large and intermediate scales; in particular, JERALD's neutral hydrogen power spectra agree with their higher-resolution full-hydrodynamic counterparts within 90% up to $k\simeq1\,h$Mpc$^{-1}$ and within 70% up to $k\simeq10\,h$Mpc$^{-1}$. JERALD provides a fast, accurate and physically motivated approach that we plan to embed in a statistical inference pipeline, such as Simulation-Based Inference, to constrain dark matter properties from large- to intermediate-scale structure observables.

astro-ph.CO↗

Primordial magnetic fields: consistent initial conditions and impact on high-z structures

Primordial magnetic fields (PMFs) can enhance matter power spectrum on small scales ($\lesssim$ Mpc) and still agree with bounds from cosmic microwave background (CMB) and Faraday rotation measurements. As modes on scales smaller than Mpc have already become non-linear today, exploring PMFs' impact on small-scale structures requires dedicated cosmological simulations. Here, for the first time, we perform a suite of hydrodynamical simulations that take into account the different impacts of PMFs on baryons and dark matter. Specifically, in the initial conditions we displace particles according to the Lorentz force from PMFs. We also highlight the large theoretical uncertainty in the peak enhancement of the matter power spectrum due to PMFs, which was not considered in previous studies. We present halo mass functions and show that they can be accurately reproduced using Sheth-Torman formalism. Moreover, we show that PMFs can generate galaxies with baryon fraction several times larger than the cosmic average at high redshifts. This is simply a consequence of the fact that PMFs enhance baryon perturbations, causing them to be larger than dark matter perturbations. We argue that this scenario could be tested soon by obtaining accurate estimates of the baryon fraction in high redshift galaxies.

astro-ph.CO↗

Anharmonic Effects on the Squeezing of Axion Perturbations

It is assumed in standard cosmology that the Universe underwent a period of inflation in its earliest phase, providing the seeds for structure formation through vacuum fluctuations of the inflaton scalar field. These fluctuations get stretched by the quasi-exponential expansion of the Universe and become squeezed. The aim of this paper is to deepen the understanding of the squeezing process, considering the effect of self-interactions. Axion-like particles can provide a useful setup to study this effect. Specifically we focus on the consequences that a non-trivial evolution of the background axion field has on the squeezing of the perturbations. We follow the evolution of the axion's fluctuation modes from the horizon exit during inflation to the radiation-dominated epoch. We compute Bogoliubov coefficients and squeezing parameters, which are linked to the axion particle number and isocurvature perturbation. We find that the quantum mechanical particle production and the squeezing of the perturbations are enhanced, if one accounts for anharmonic effects, i.e., the effect of higher order terms in the potential. This effect becomes particularly strong towards the hilltop of the potential.

hep-ph↗

21cm Intensity Mapping cross-correlation with galaxy surveys: current and forecasted cosmological parameters estimation for the SKAO

We present a comprehensive set of forecasts for the cross-correlation signal between 21cm intensity mapping and galaxy redshift surveys. We focus on the data sets that will be provided by the SKAO for the 21cm signal, DESI and Euclid for galaxy clustering. We build a likelihood which takes into account the effect of the beam for the radio observations, the Alcock-Paczynski effect, a simple parameterization of astrophysical nuisances, and fully exploit the tomographic power of such observations in the range $z=0.7-1.8$ at linear and mildly non-linear scales ($k<0.25 h/$Mpc). The forecasted constraints, obtained with Monte Carlo Markov Chains techniques in a Bayesian framework, in terms of the six base parameters of the standard $Λ$CDM model, are promising. The predicted signal-to-noise ratio for the cross-correlation can reach $\sim 50$ for $z\sim 1$ and $k\sim 0.1 h/$ Mpc. When the cross-correlation signal is combined with current Cosmic Microwave Background (CMB) data from Planck, the error bar on $Ω_{\rm c}\,h^2$ and $H_0$ is reduced by a factor 3 and 6, respectively, compared to CMB only data, due to the measurement of matter clustering provided by the two observables. The cross-correlation signal has a constraining power that is comparable to the auto-correlation one and combining all the clustering measurements a sub-percent error bar of 0.33% on $H_0$ can be achieved, which is about a factor 2 better than CMB only measurement. Finally, as a proof-of-concept, we test the full pipeline on the real data measured by the MeerKat collaboration (Cunnington et al. 2022) presenting some (weak) constraints on cosmological parameters.

astro-ph.CO↗

Parameter estimation from Ly$α$ forest in Fourier space using Information Maximising Neural Network

We aim to present a robust parameter estimation with simulated Lya forest spectra from Sherwood-Relics simulations suite using Information Maximizing Neural Network(IMNN) to extract maximal information from Lya 1D-transmitted flux in Fourier space. We perform 1D estimations using IMNN for IGM thermal parameters $T_0$ & $γ$ at z=2-4 and cosmological parameters $σ_8$ & $n_s$ at z=3-4. We compare our results with estimates from power spectrum using posterior distribution from Markov Chain Monte Carlo(MCMC). We then check robustness of IMNN estimates against deviation in spectral noise levels,continuum uncertainties & instrumental smoothing effects. Using mock Lya forest sightlines from publicly available CAMELS project we also check the robustness of the trained IMNN on a different simulation. We also perform a 2D-parameter estimation for $T_0$ & HI photoionization rates $Γ_{HI}$. We obtain improved estimates of $T_0$ & $γ$ using IMNN over standard MCMC approach. These estimates are also more robust against SNR deviations at z=2 & 3. At z=4 the sensitivity to noise deviations is on par with MCMC estimates. The IMNN also provides $T_0$ and $γ$ estimates which are robust against continuum uncertainties by extracting continuum-independent small-scale information from Fourier domain. In case of $σ_8$ & $n_s$ IMNN performs on par with MCMC but still offers a significant speed boost in estimating parameters from a new dataset. The improved estimates with IMNN are seen for high instrumental-resolution(FWHM=6km/s). At medium or low resolutions IMNN performs similar to MCMC suggesting an improved extraction of small-scale information with IMNN. We also find that IMNN estimates are robust against the choice of simulation. By performing a 2D-parameter estimation for $T_0$ & $Γ_{HI}$ we also demonstrate how to take forward this approach observationally in the future.

astro-ph.CO↗

Unveiling Dark Matter free-streaming at the smallest scales with high redshift Lyman-alpha forest

This study introduces novel constraints on the free-streaming of thermal relic warm dark matter (WDM) from Lyman-$α$ forest flux power spectra. Our analysis utilises a high-resolution, high-redshift sample of quasar spectra observed using the HIRES and UVES spectrographs ($z=4.2-5.0$). We employ a Bayesian inference framework and a simulation-based likelihood that encompasses various parameters including the free-streaming of dark matter, cosmological parameters, the thermal history of the intergalactic medium, and inhomogeneous reionization, to establish lower limits on the mass of a thermal relic WDM particle of $5.7\;\mathrm{keV}$ (at 95\% C.L.). This result surpasses previous limits from the Lyman-$α$ forest through reduction of the measured uncertainties due to a larger statistical sample and by measuring clustering to smaller scales ($k_{\rm max}=0.2\;\mathrm{km^{-1}\,s}$). The approximately two-fold improvement due to the expanded statistical sample suggests that the effectiveness of Lyman-$α$ forest constraints on WDM models at high redshifts are limited by the availability of high-quality quasar spectra. Restricting the analysis to comparable scales and thermal history priors as in prior studies ($k_{\rm max}<0.1\;\mathrm{km^{-1}\,s}$) lowers the bound on the WDM mass to $4.1\;\mathrm{keV}$. As the precision of the measurements increases, it becomes crucial to examine the instrumental and modelling systematics. On the modelling front, we argue that the impact of the thermal history uncertainty on the WDM particle mass constraint has diminished due to improved independent observations. At the smallest scales, the primary source of modeling systematic arises from the structure in the peculiar velocity of the intergalactic medium and inhomogeneous reionization.

astro-ph.CO↗