arXiv subjects

Joseph Adamo

Publications and source records attributed to Joseph Adamo.

5 recordsLinked to original sources

arXiv2026

Emulation of SPHEREx Galaxy Power Spectra I: Neural Network Details and Optimization

We present neural networks to generate redshift-space galaxy power spectrum multipoles for multiple tracer and redshift bins simultaneously given a set of input cosmology and galaxy bias parameters. This emulator utilizes a combination of fully-connected layers and transformer architecture to accurately predict galaxy power spectrum multipoles $900$ times faster than the SPHEREx pipeline. We quantify network performance using both $\Delta \chi^2$, and likelihood contours for simulated SPHEREx analyses, using two correlated tracer bins and two independent redshift bins. After optimizing network architecture, the loss function, and training set sampling strategy, we achieve $\operatorname{Med}\left( \Delta \chi^2\right) = 0.069$ when comparing to our testing set. At the contour-level our emulator agrees with EFT predictions over a realistic parameter range, with an average 1D best-fit shift of $0.078\sigma$ and $0.82 \%$ change in 1D error bars. These results demonstrate the feasibility of using neural-network emulators to accelerate SPHEREx redshift-space power-spectrum analyses.

astro-ph.CO↗

arXiv2025

The SPHEREx Satellite Mission

SPHEREx, a NASA explorer satellite launched on 11 March 2025, is carrying out the first all-sky near-infrared spectral survey. The satellite observes in 102 spectral bands from 0.75 to 5.0 um with a resolving power ranging from 35 to 130 in 6.2 arcsecond pixels. The observatory obtains a 5-sigma depth of 19.5 - 19.9 AB mag for 0.75 to 3.8 um and 17.8 - 18.8 AB mag for 3.8 to 5.0 um after mapping the full sky four times over two years. Scientifically, SPHEREx will produce a large galaxy redshift survey over the full sky, intended to constrain the amplitude of inflationary non-Gaussianity. The observations will produce two deep spectral maps near the ecliptic poles that will use intensity mapping to probe the evolution of galaxies over cosmic history. By mapping the depth of infrared absorption features over the Galactic plane, SPHEREx will comprehensively survey the abundance and composition of water and other biogenic ice species in the interstellar medium. The initial data are rapidly released in the form of spectral images to the public. The project will release specialized data products over the life of the mission as the surveys proceed. The science team will also produce specialized spectral catalogs on planet-bearing and low-mass stars, solar system objects, and galaxy clusters 3 years after launch. We describe the design of the instrument and spacecraft, which flow from the core science requirements. Finally, we present an initial evaluation of the in-flight performance and key characteristics.

astro-ph.IM↗

arXiv2024

Neural network based emulation of galaxy power spectrum covariances -- A reanalysis of BOSS DR12 data

We train neural networks to quickly generate redshift-space galaxy power spectrum covariances from a given parameter set (cosmology and galaxy bias). This covariance emulator utilizes a combination of traditional fully-connected network layers and transformer architecture to accurately predict covariance matrices for the high redshift, north galactic cap sample of the BOSS DR12 galaxy catalog. We run simulated likelihood analyses with emulated and brute-force computed covariances, and we quantify the network's performance via two different metrics: 1) difference in $χ^2$ and 2) likelihood contours for simulated BOSS DR 12 analyses. We find that the emulator returns excellent results over a large parameter range. We then use our emulator to perform a re-analysis of the BOSS HighZ NGC galaxy power spectrum, and find that varying covariance with cosmology along with the model vector produces $Ω_m = 0.276^{+0.013}_{-0.015}$, $H_0 = 70.2\pm 1.9$ km/s/Mpc, and $σ_8 = 0.674^{+0.058}_{-0.077}$. These constraints represent an average $0.46σ$ shift in best-fit values and a $5\%$ increase in constraining power compared to fixing the covariance matrix ($Ω_m = 0.293\pm 0.017$, $H_0 = 70.3\pm 2.0$ km/s/Mpc, $σ_8 = 0.702^{+0.063}_{-0.075}$). This work demonstrates that emulators for more complex cosmological quantities than second-order statistics can be trained over a wide parameter range at sufficiently high accuracy to be implemented in realistic likelihood analyses.

astro-ph.CO↗

arXiv2022

Simulating Hydrodynamics in Cosmology with CRK-HACC

We introduce CRK-HACC, an extension of the Hardware/Hybrid Accelerated Cosmology Code (HACC), to resolve gas hydrodynamics in large-scale structure formation simulations of the universe. The new framework couples the HACC gravitational N-body solver with a modern smoothed particle hydrodynamics (SPH) approach called CRKSPH. $\underline{\text{C}}$onservative $\underline{\text{R}}$eproducing $\underline{\text{K}}$ernel $\underline{\text{SPH}}$ utilizes smoothing functions that exactly interpolate linear fields while manifestly preserving conservation laws (momentum, mass, and energy). The CRKSPH method has been incorporated to accurately model baryonic effects in cosmology simulations - an important addition targeting the generation of precise synthetic sky predictions for upcoming observational surveys. CRK-HACC inherits the codesign strategies of the HACC solver and is built to run on modern GPU-accelerated supercomputers. In this work, we summarize the primary solver components and present a number of standard validation tests to demonstrate code accuracy, including idealized hydrodynamic and cosmological setups, as well as self-similarity measurements.

astro-ph.CO↗

arXiv2021

Observation of eccentric binary black hole mergers with second and third generation gravitational wave detector networks

[Abridged] We introduce an improved version of the Eccentric, Non-spinning, Inspiral-Gaussian-process Merger Approximant (ENIGMA) waveform model. We find that this ready-to-use model can: (i) produce physically consistent signals when sampling over 1M samples chosen over the $m_{\{1,\,2\}}\in[5M_{\odot},\,50M_{\odot}]$ parameter space, and the entire range of binary inclination angles; (ii) produce waveforms within 0.04 seconds from an initial gravitational wave frequency $f_{\textrm{GW}} =15\,\textrm{Hz}$ and at a sample rate of 8192 Hz; and (iii) reproduce the physics of quasi-circular mergers. We utilize ENIGMA to compute the expected signal-to-noise ratio (SNR) distributions of eccentric binary black hole mergers assuming the existence of second and third generation gravitational wave detector networks that include the twin LIGO detectors, Virgo, KAGRA, LIGO-India, a LIGO-type detector in Australia, Cosmic Explorer, and the Einstein Telescope. In the context of advanced LIGO-type detectors, we find that the SNR of eccentric mergers is always larger than quasi-circular mergers for systems with $e_0\leq0.4$ at $f_{\textrm{GW}} =10\,\textrm{Hz}$, even if the timespan of eccentric signals is just a third of quasi-circular systems with identical total mass and mass-ratio. For Cosmic Explorer-type detector networks, we find that eccentric mergers have similar SNRs than quasi-circular systems for $e_0\leq0.3$ at $f_{\textrm{GW}} =10\,\textrm{Hz}$. Systems with $e_0\sim0.5$ at $f_{\textrm{GW}} =10\,\textrm{Hz}$ have SNRs that range between 50%-90% of the SNR produced by quasi-circular mergers, even if these eccentric signals are just between a third to a tenth the length of quasi-circular systems. For Einstein Telescope-type detectors, we find that eccentric mergers have similar SNRs than quasi-circular systems for $e_0\leq0.4$ at $f_{\textrm{GW}} =5\,\textrm{Hz}$.

gr-qc↗