Matthew C. Johnson

Over the last year, kinematic Sunyaev–Zel'dovich (kSZ) velocity reconstruction — the measurement of the large-scale velocity field using the anisotropic statistics of the small-scale kSZ-galaxy overdensity correlation — has emerged as a statistically significant probe of the large-scale Universe. In this work, we perform a 2-dimensional tomographic reconstruction using ACT DR6 CMB data and photometric DESI legacy luminous red galaxies (LRGs). We measure the cross-correlation of the kSZ-reconstructed velocity v ^kSZ with the velocity inferred from the continuity equation applied to the photometric DESI LRG sample v ^cont at the ∼10σ level, detecting the signal with an amplitude with respect to our theory of b _v = 0.339 ± 0.034. We fit a scale-dependent galaxy bias model to our measurement in order to constrain local primordial non-Gaussianity f _NL ^loc , finding f _NL ^loc =- 180 ⁺⁶¹ _-86 at 67% confidence, with f _NL ^loc consistent with zero at 95% confidence. We also measure an auto spectrum at 2.1σ significance which provides a constraint on b _v of b _v = 0.26 _-0.05 ^+0.11 , which is consistent with the measurement from the cross spectrum. Our combined measurement is b _v = 0.33 ± 0.03, an 11σ measurement. We find a good fit of our model to the data in all cases. Finally, we use different ACT frequency combinations to explore foreground contamination, finding no evidence for foreground contamination in our velocity cross correlation. We compare to a similar measurement where v ^kSZ is directly cross correlated with the large-scale galaxy field, and find signs of foreground contamination which is contained in the equal-redshift spectra.

For many analyses in cosmology it is necessary to reconstruct the likely distribution of unobserved fields, such as dark matter or non-luminous baryons, from observed luminous tracers. The dominant approach in cosmology has been to use the so-called halo model, which assumes radially symmetric profiles centered around luminous tracers such as galaxies. More recently, field-level machine learning methods have been proposed that can learn to estimate the unobserved field after being trained on simulations. However, it is unclear whether machine learning methods indeed significantly improve over linear methods or the halo model. In this paper we make a systematic comparison of different approaches to reconstruct dark matter and non-luminous baryons, from galaxy data using the CAMELS simulations. These simulations are in a 25 Mpc/h box, allowing us to compare performance on the mildly non-linear scales ( k ∼ 0.4 h/Mpc) down to the size of individual halos. We find the best results using a combined GNN-CNN approach. We also provide a general analysis and visualization of the relationship of matter, non-luminous baryons, halos, and galaxies in these simulations to interpret our results.

The kinematic Sunyaev-Zel'dovich (kSZ) effect induces a non-zero density-density-temperature bispectrum, which we can use to reconstruct the large-scale velocity field from a combination of cosmic microwave background (CMB) and galaxy density measurements, in a procedure known as “kSZ velocity reconstruction”. This method has been forecast to constrain large-scale modes with future galaxy and CMB surveys, improving their measurement beyond what is possible with the galaxy surveys alone. Such measurements will enable tighter constraints on large-scale signals such as primordial non-Gaussianity, deviations from homogeneity, and modified gravity. In this work, we demonstrate a statistically significant measurement of kSZ velocity reconstruction for the first time, by applying quadratic estimators to the combination of the ACT DR6 CMB+kSZ map and the DESI LRG galaxies (with photometric redshifts) in order to reconstruct the velocity field. We do so using a formalism appropriate for the 2-dimensional projected galaxy fields that we use, which naturally incorporates the curved-sky effects important on the largest scales. We find evidence for the signal by cross-correlating with an external estimate of the velocity field from the spectroscopic BOSS survey and rejecting the null (no-kSZ) hypothesis at 3.8σ. Our work presents a first step towards the use of this observable for cosmological analyses.

The resonant conversion of cosmic microwave background (CMB) photons into axions within large-scale structure induces an anisotropic spectral distortion in CMB temperature maps. Applying state-of-the-art foreground cleaning techniques to Planck CMB observations, we construct maps of axion-induced "patchy screening" of the CMB. We cross-correlate these maps with data from the unWISE galaxy survey and find no evidence of axions. We constrain the axion-photon coupling, g_{aγγ}≲2×10^{-12} GeV^{-1}, at the 95% confidence level for axion masses in the range 10^{-13} eV≲m_{a}≲10^{-12} eV. These constraints are competitive with the tightest astrophysical axion limits in this mass range and are inferred from robust population-level statistics, which makes them complementary to existing searches that rely on modeling of individual systems.

Metastable ‘false’ vacuum states are an important feature of the Standard Model of particle physics and many theories beyond it. Describing the dynamics of a phase transition out of a false vacuum via the nucleation of bubbles is essential for understanding the cosmology of vacuum decay and the full spectrum of observables. In this paper, we study vacuum decay by numerically evolving ensembles of field theories in 1+1 dimensions from a metastable state. We demonstrate that for an initial Bose-Einstein distribution of fluctuations, bubbles form with a Gaussian spread of center-of-mass velocities and that bubble nucleation events are preceded by an oscillon — a long-lived, time-dependent, pseudo-stable configuration of the field. Defining an effective temperature from the long-wavelength amplitude of fluctuations in the ensemble of simulations, we find good agreement between theoretical finite temperature predictions and empirical measurements of the decay rate, velocity distribution and critical bubble solution. We comment on the generalization of our results and the implications for cosmological observables.

We develop a hybrid GNN-CNN architecture for the reconstruction of 3-dimensional continuous cosmological matter fields from discrete point clouds, provided by observed galaxy catalogs. Using the CAMELS hydrodynamical cosmological simulations we demonstrate that the proposed architecture allows for an accurate reconstruction of both the dark matter and electron density given observed galaxies and their features. Our approach includes a learned grid assignment scheme that improves over the traditional cloud-in-cell method. Our method can improve cosmological analyses in situations where non-luminous (and thus unobservable) continuous fields need to be estimated from luminous (observable) discrete point cloud tracers.