arXiv subjects

Julie Hlavacek-Larrondo

Publications and source records attributed to Julie Hlavacek-Larrondo.

At least 55 records · Page 3Linked to original sources

arXiv2023

The SPT-Chandra BCG Spectroscopic Survey I: Evolution of the Entropy Threshold for Cooling and Feedback in Galaxy Clusters Over the Last 10 Gyr

We present a multi-wavelength study of the brightest cluster galaxies (BCGs) in a sample of the 95 most massive galaxy clusters selected from South Pole Telescope (SPT) Sunyaev-Zeldovich (SZ) survey. Our sample spans a redshift range of 0.3 < z < 1.7, and is complete with optical spectroscopy from various ground-based observatories, as well as ground and space-based imaging from optical, X-ray and radio wavebands. At z~0, previous studies have shown a strong correlation between the presence of a low-entropy cool core and the presence of star-formation and a radio-loud AGN in the central BCG. We show for the first time that a central entropy threshold for star formation persists out to z~1. The central entropy (measured in this work at a radius of 10 kpc) below which clusters harbor star-forming BCGs is found to be as low as $K_\mathrm{10 ~ kpc} = 35 \pm 4$ keV cm$^2$ at z < 0.15 and as high as $K_\mathrm{10 ~ kpc} = 52 \pm 11$ keV cm$^2$ at z~1. We find only marginal (~1$σ$) evidence for evolution in this threshold. In contrast, we do not find a similar high-z analog for an entropy threshold for feedback, but instead measure a strong evolution in the fraction of radio-loud BCGs in high-entropy cores as a function of redshift. This could imply that the cooling-feedback loop was not as tight in the past, or that some other fuel source like mergers are fueling the radio sources more often with increasing redshift, making the radio luminosity an increasingly unreliable proxy for radio jet power. We also find that our SZ-based sample is missing a small (~4%) population of the most luminous radio sources ($νL_ν > 10^{42}$ erg/s), likely due to radio contamination suppressing the SZ signal with which these clusters are detected.

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arXiv2023

NuSTAR Observations of Abell 665 and 2146: Constraints on Non-Thermal Emission

Observations from past missions such as RXTE and Beppo-SAX suggested the presence of inverse Compton (IC) scattering at hard X-ray energies within the intracluster medium of some massive galaxy clusters. In subsequent years, observations by, e.g., Suzaku, and now NuSTAR, have not been able to confirm these detections. We report on NuSTAR hard X-ray searches for IC emission in two massive galaxy clusters, Abell 665 and Abell 2146. To constrain the global IC flux in these two clusters, we fit global NuSTAR spectra with three models: single (1T) and two-temperature (2T) models, and a 1T plus power law component (T$+$IC). The temperature components are meant to characterize the thermal ICM emission, while the power law represents the IC emission. We find that the 3-30 keV Abell 665 and 3-20 keV Abell 2146 spectra are best described by thermal emission alone, with average global temperatures of $kT = (9.15\pm 0.1)$ keV for Abell 665 and $kT = (8.29\pm 0.1)$ keV for Abell 2146. We constrain the IC flux to $F_{\rm NT} < 0.60 \times 10^{-12}$ erg s$^{-1}$ cm$^{-2}$ and $F_{\rm NT} < 0.85 \times 10^{-12}$ erg s$^{-1}$ cm$^{-2}$ (20-80 keV) for Abell 665 and Abell 2146, respectively both at the 90% confidence level. When we couple the IC flux limits with 1.4 GHz diffuse radio data from the VLA, we set lower limits on the average magnetic field strengths of $>$0.14 $μ$G and $>$0.011 $μ$G for Abell 665 and Abell 2146, respectively.

astro-ph.HE↗

arXiv2023

A Machine Learning Approach to Galactic Emission-Line Region Classification

Diagnostic diagrams of emission-line ratios have been used extensively to categorize extragalactic emission regions; however, these diagnostics are occasionally at odds with each other due to differing definitions. In this work, we study the applicability of supervised machine-learning techniques to systematically classify emission-line regions from the ratios of certain emission lines. Using the Million Mexican Model database, which contains information from grids of photoionization models using \texttt{cloudy}, and from shock models, we develop training and test sets of emission line fluxes for three key diagnostic ratios. The sets are created for three classifications: classic \hii{} regions, planetary nebulae, and supernova remnants. We train a neural network to classify a region as one of the three classes defined above given three key line ratios that are present both in the SITELLE and MUSE instruments' band-passes: [{\sc O\,iii}]$\lambda5007$/H$β$, [{\sc N\,ii}]$\lambda6583$/H$α$, ([{\sc S\,ii}]$\lambda6717$+[{\sc S\,ii}]$\lambda6731$)/H$α$. We also tested the impact of the addition of the [{\sc O\,ii}]$\lambda3726,3729$/[{\sc O\,iii}]$\lambda5007$ line ratio when available for the classification. A maximum luminosity limit is introduced to improve the classification of the planetary nebulae. Furthermore, the network is applied to SITELLE observations of a prominent field of M33. We discuss where the network succeeds and why it fails in certain cases. Our results provide a framework for the use of machine learning as a tool for the classification of extragalactic emission regions. Further work is needed to build more comprehensive training sets and adapt the method to additional observational constraints.

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arXiv2023

Extended Line Emission in the BCG of Abell 2390

We report CFHT/SITELLE imaging Fourier Transform Spectrograph observations of the Brightest Cluster Galaxy (BCG) of galaxy cluster Abell 2390 at z=0.228. The BCG displays a prominent cone of emission in H$α$, H$β$, [NII], and [OII] to the North-West with PA = 42$^o$, 4.4 arcsec in length (15.9 kpc), which is associated with elongated and asymmetric Chandra soft X-ray emission. The H$α$ flux map also contains a "hook" of H$α$ and [NII] emission resulting in a broadened northern edge to the cone. Using SITELLE/LUCI software we extract emission line flux, velocity, velocity dispersion, and continuum maps, and utilize them to derive flux ratio maps to determine ionization mechanisms and dynamical information in the BCG's emission line region. The Baldwin-Phillips-Terlevich diagnostics on the BCG cone indicate a composite ionization origin of photoionization due to star formation and shock. Strong LINER-like emission is seen in the nuclear region which hosts an AGN. As Abell 2390 is a cool-core cluster, we suggest that the cooling flow is falling onto the central BCG and interacting with the central AGN. The AGN produces jets that inflate "bubbles" of plasma in the ICM, as is often observed in local galaxy clusters. Furthermore, combining signs of AGN activities from radio, optical emission line and X-ray data over a large range of physical scale, we find evidence for three possible episodes of AGN activity in different epochs associated with the Abell 2390 BCG.

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arXiv2023

SPT-CL J2215-3537: A Massive Starburst at the Center of the Most Distant Relaxed Galaxy Cluster

We present the discovery of the most distant, dynamically relaxed cool core cluster, SPT-CL J2215-3537 (SPT2215) and its central brightest cluster galaxy (BCG) at z=1.16. Using new X-ray observations, we demonstrate that SPT2215 harbors a strong cool core, with a central cooling time of 200 Myr (at 10 kpc) and a maximal intracluster medium cooling rate of 1900+/-400 Msun/yr. This prodigious cooling may be responsible for fueling extended, star-forming filaments observed in Hubble Space Telescope imaging. Based on new spectrophotometric data, we detect bright [O II] emission in the BCG, implying an unobscured star formation rate (SFR) of 320^{+230}_{-140} Msun/yr. The detection of a weak radio source (2.0+/-0.8 mJy at 0.8 GHz) suggests ongoing feedback from an active galactic nucleus (AGN), though the implied jet power is less than half the cooling luminosity of the hot gas, consistent with cooling overpowering heating. The extreme cooling and SFR of SPT2215 is rare among known cool core clusters, and it is even more remarkable that we observe these at such high redshift, when most clusters are still dynamically disturbed. The high mass of this cluster, coupled with the fact that it is dynamically relaxed with a highly-isolated BCG, suggests that it is an exceptionally rare system that must have formed very rapidly in the early Universe. Combined with the high SFR, SPT2215 may be a high-z analog of the Phoenix cluster, potentially providing insight into the limits of AGN feedback and star formation in the most massive galaxies.

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arXiv2022

Signature of Supersonic Turbulence in Galaxy Clusters Revealed by AGN-driven H$α$ Filaments

The hot intracluster medium (ICM) is thought to be quiescent with low observed velocity dispersions. Surface brightness fluctuations of the ICM also suggest that its turbulence is subsonic with a Kolmogorov scaling relation, indicating that the viscosity is suppressed and the kinetic energy cascades to small scales unscathed. However, recent observations of the cold gas filaments in galaxy clusters find that the scaling relations are steeper than that of the hot plasma, signaling kinetic energy losses and the presence of supersonic flows. In this work we use high-resolution simulations to explore the turbulent velocity structure of the cold filaments at the cores of galaxy clusters. Our results indicate that supersonic turbulent structures can be "frozen" in the cold gas that cools and fragments out of a fast, $10^7$ K outflow driven by the central active galactic nucleus (AGN), when the radiative cooling time is shorter than the dynamical sound-crossing time. After the cold gas formation, however, the slope of the velocity structure function (VSF) flattens significantly over short, 10 Myr timescales. The lack of flattened VSF in observations of H$α$ filaments indicates that the H$α$-emitting phase is short-lived for the cold gas in galaxy clusters. On the other hand, the ubiquity of supersonic turbulence revealed by observed filaments strongly suggests that supersonic outflows are an integral part of AGN-ICM interaction, and that AGN activity plays a crucial role at driving turbulence in galaxy clusters.

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arXiv2022

An Assessment of the In-Situ Growth of the Intracluster Light in the High Redshift Galaxy Cluster SpARCS1049+56

The formation of the stellar mass within galaxy cluster cores is a poorly understood process. It features the complicated physics of cooling flows, AGN feedback, star formation and more. Here, we study the growth of the stellar mass in the vicinity of the Brightest Cluster Galaxy (BCG) in a z = 1.7 cluster, SpARCS1049+56. We synthesize a reanalysis of existing HST imaging, a previously published measurement of the star formation rate, and the results of new radio molecular gas spectroscopy. These analyses represent the past, present and future star formation respectively within this system. We show that a large amount of stellar mass -- between $(2.2 \pm 0.5) \times 10^{10} \: M_\odot$ and $(6.6 \pm 1.2) \times 10^{10}\: M_\odot$ depending on the data processing -- exists in a long and clumpy tail-like structure that lies roughly 12 kpc off the BCG. Spatially coincident with this stellar mass is a similarly massive reservoir ($(1.0 \pm 0.7) \times 10^{11} \: M_\odot$) of molecular gas that we suggest is the fuel for the immense star formation rate of $860 \pm 130 \: M_\odot$/yr, as measured by infrared observations. Hlavacek-Larrondo et al. 2021 surmised that massive, runaway cooling of the hot intracluster X-ray gas was feeding this star formation, a process that had not been observed before at high-redshift. We conclude, based on the amount of fuel and current stars, that this event may be rare in the lifetime of a cluster, producing roughly 15 to 21% of the Intracluster Light (ICL) mass in one go, though perhaps a common event for all galaxy clusters.

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arXiv2021

Updates to LUCI: A New Fitting Paradigm Using Mixture Density Networks

LUCI is an general-purpose spectral line-fitting pipeline which natively integrates machine learning algorithms to initialize fit functions. LUCI currently uses point-estimates obtained from a convolutional neural network (CNN) to inform optimization algorithms; this methodology has shown great promise by reducing computation time and reducing the chance of falling into a local minimum using convex optimization methods. In this update to LUCI, we expand upon the CNN developed in Rhea et al. 2020 so that it outputs Gaussian posterior distributions of the fit parameters of interest (the velocity and broadening) rather than simple point-estimates. Moreover, these posteriors are then used to inform the priors in a Bayesian inference scheme, either emcee or dynesty. The code is publicly available at https://github.com/crhea93/LUCI.

astro-ph.IM↗

arXiv2021

A Machine Learning Approach to Integral Field Unit Spectroscopy Observations: III. Disentangling Multiple Components in Hii regions

In the first two papers of this series (Rhea et al. 2020; Rhea et al. 2021), we demonstrated the dynamism of machine learning applied to optical spectral analysis by using neural networks to extract kinematic parameters and emission-line ratios directly from the spectra observed by the SITELLE instrument located at the Canada-France-Hawai'i Telescope. In this third installment, we develop a framework using a convolutional neural network trained on synthetic spectra to determine the number of line-of-sight components present in the SN3 filter (656--683nm) spectral range of SITELLE. We compare this methodology to standard practice using Bayesian Inference. Our results demonstrate that a neural network approach returns more accurate results and uses less computational resources over a range of spectral resolutions. Furthermore, we apply the network to SITELLE observations of the merging galaxy system NGC2207/IC2163. We find that the closest interacting sector and the central regions of the galaxies are best characterized by two line-of-sight components while the outskirts and spiral arms are well-constrained by a single component. Determining the number of resolvable components is crucial in disentangling different galactic components in merging systems and properly extracting their respective kinematics.

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arXiv2021

LUCI: A Python package for SITELLE spectral analysis

High-resolution optical integral field units (IFUs) are rapidly expanding our knowledge of extragalactic emission nebulae in galaxies and galaxy clusters. By studying the spectra of these objects -- which include classic HII regions, supernova remnants, planetary nebulae, and cluster filaments -- we are able to constrain their kinematics (velocity and velocity dispersion). In conjunction with additional tools, such as the BPT diagram, we can further classify emission regions based on strong emission-line flux ratios. LUCI is a simple-to-use python module intended to facilitate the rapid analysis of IFU spectra. LUCI does this by integrating well-developed pre-existing python tools such as astropy and scipy with new machine learning tools for spectral analysis (Rhea et al. 2020). Furthermore, LUCI provides several easy-to-use tools to access and fit SITELLE data cubes.

astro-ph.IM↗

arXiv2021

A Data-driven Approach to X-ray Spectral Fitting: Quasi-Deconvolution

X-ray spectral fitting of astronomical sources requires convolving the intrinsic spectrum or model with the instrumental response. Standard forward modeling techniques have proven success in recovering the underlying physical parameters in moderate to high signal-to-noise regimes; however, they struggle to achieve the same level of accuracy in low signal-to-noise regimes. Additionally, the use of machine learning techniques on X-ray spectra requires access to the intrinsic spectrum. Therefore, the measured spectrum must be effectively deconvolved from the instrumental response. In this note, we explore numerical methods for inverting the matrix equation describing X-ray spectral convolution. We demonstrate that traditional methods are insufficient to recover the intrinsic X-ray spectrum and argue that a novel approach is required.

astro-ph.IM↗

arXiv2021

A Machine Learning Approach to Integral Field Unit Spectroscopy Observations: II. HII Region LineRatios

In the first paper of this series (Rhea et al. 2020), we demonstrated that neural networks can robustly and efficiently estimate kinematic parameters for optical emission-line spectra taken by SITELLE at the Canada-France-Hawaii Telescope. This paper expands upon this notion by developing an artificial neural network to estimate the line ratios of strong emission-lines present in the SN1, SN2, and SN3 filters of SITELLE. We construct a set of 50,000 synthetic spectra using line ratios taken from the Mexican Million Model database replicating Hii regions. Residual analysis of the network on the test set reveals the network's ability to apply tight constraints to the line ratios. We verified the network's efficacy by constructing an activation map, checking the [N ii] doublet fixed ratio, and applying a standard k-fold cross-correlation. Additionally, we apply the network to SITELLE observation of M33; the residuals between the algorithm's estimates and values calculated using standard fitting methods show general agreement. Moreover, the neural network reduces the computational costs by two orders of magnitude. Although standard fitting routines do consistently well depending on the signal-to-noise ratio of the spectral features, the neural network can also excel at predictions in the low signal-to-noise regime within the controlled environment of the training set as well as on observed data when the source spectral properties are well constrained by models. These results reinforce the power of machine learning in spectral analysis.

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arXiv2021

VLA resolves unexpected radio structures in the Perseus cluster of galaxies

We present new deep, high-resolution, 1.5 GHz observations of the prototypical nearby Perseus galaxy cluster from the Karl G. Jansky Very Large Array. We isolate for the first time the complete tail of radio emission of the bent-jet radio galaxy NGC 1272, which had been previously mistaken to be part of the radio mini-halo. The possibility that diffuse radio galaxy emission contributes to mini-halo emission may be a general phenomenon in relaxed cool-core clusters, and should be explored. The collimated jets of NGC 1272 initially bend to the west, and then transition eastward into faint, 60 kpc-long extensions with eddy-like structures and filaments. We suggest interpretations for these structures that involve bulk motions of intracluster gas, the galaxy's orbit in the cluster including projection effects, and the passage of the galaxy through a sloshing cold front. Instabilities and turbulence created at the surface of this cold front and in the turbulent wake of the infalling host galaxy most likely play a role in the formation of the observed structures. We also discover a series of faint rings, south-east of NGC 1272, which are a type of structure that has never been seen before in galaxy clusters.

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arXiv2020

High-resolution VLA low radio frequency observations of the Perseus cluster: radio lobes, mini-halo and bent-jet radio galaxies

We present the first high-resolution 230-470 MHz map of the Perseus cluster obtained with the Karl G. Jansky Very Large Array. The high dynamic range and resolution achieved has allowed the identification of previously-unknown structures in this nearby galaxy cluster. New hints of sub-structures appear in the inner radio lobes of the brightest cluster galaxy NGC 1275. The spurs of radio emission extending into the outer X-ray cavities, inflated by past nuclear outbursts, are seen for the first time at these frequencies, consistent with spectral aging. Beyond NGC 1275, we also analyze complex radio sources harbored in the cluster. Two new distinct, narrowly-collimated jets are visible in IC 310, consistent with a highly-projected narrow-angle tail radio galaxy infalling into the cluster. We show how this is in agreement with its blazar-like behavior, implying that blazars and bent-jet radio galaxies are not mutually exclusive. We report the presence of filamentary structures across the entire tail of NGC 1265, including two new pairs of long filaments in the faintest bent extension of the tail. Such filaments have been seen in other cluster radio sources such as relics and radio lobes, indicating that there may be a fundamental connection between all these radio structures. We resolve the very narrow and straight tail of CR 15 without indication of double jets, so that the interpretation of such head-tail sources is yet unclear. Finally, we note that only the brightest western parts of the mini-halo remain, near NGC 1272 and its bent double jets.

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arXiv2020

A Novel Machine Learning Approach to Disentangle Multi-Temperature Regions in Galaxy Clusters

The hot intra-cluster medium (ICM) surrounding the heart of galaxy clusters is a complex medium comprised of various emitting components. Although previous studies of nearby galaxy clusters, such as the Perseus, the Coma, or the Virgo cluster, have demonstrated the need for multiple thermal components when spectroscopically fitting the ICM's X-ray emission, no systematic methodology for calculating the number of underlying components currently exists. In turn, underestimating or overestimating the number of components can cause systematic errors in the emission parameter estimations. In this paper, we present a novel approach to determining the number of components using an amalgam of machine learning techniques. Synthetic spectra containing a various number of underlying thermal components were created using well-established tools available from the \textit{Chandra} X-ray Observatory. The dimensions of the training set was initially reduced using the Principal Component Analysis and then categorized based on the number of underlying components using a Random Forest Classifier. Our trained and tested algorithm was subsequently applied to \textit{Chandra} X-ray observations of the Perseus cluster. Our results demonstrate that machine learning techniques can efficiently and reliably estimate the number of underlying thermal components in the spectra of galaxy clusters, regardless of the thermal model (MEKAL versus APEC). %and signal-to-noise ratio used. We also confirm that the core of the Perseus cluster contains a mix of differing underlying thermal components. We emphasize that although this methodology was trained and applied on \textit{Chandra} X-ray observations, it is readily portable to other current (e.g. XMM-Newton, eROSITA) and upcoming (e.g. Athena, Lynx, XRISM) X-ray telescopes. The code is publicly available at \url{https://github.com/XtraAstronomy/Pumpkin}.

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arXiv2020

Constraining the Mass of the Emerging Galaxy Cluster SpARCS1049+56 at z=1.71 with Infrared Weak Lensing

In the hierarchical structure formation model of the universe, galaxy clusters are assembled through a series of mergers. Accordingly, it is expected that galaxy clusters in the early universe are actively forming and dynamically young. Located at a high redshift of z=1.71, SpARCS1049+56 offers a unique look into the galaxy cluster formation process. This cluster has been shown to be rich in cluster galaxies and to have intense star formation. Its high redshift pushes a weak-lensing analysis beyond the regime of the optical spectrum into that of the infrared. Equipped with deep Hubble Space Telescope Wide Field Camera 3 UVIS and IR observations, we present a weak-lensing characterization of SpARCS1049+56. As few IR weak-lensing studies have been performed, we discuss the details of PSF modeling and galaxy shape measurement for an IR weak-lensing procedure and the systematics that come with the territory. It will be critical to understand these systematics in future weak-lensing studies in the IR with the next generation space telescopes such as JWST, Euclid, and WFIRST. Through a careful analysis, the mass distribution of this young galaxy cluster is mapped and the convergence peak is detected at a 3.3 sigma level. The weak-lensing mass of the cluster is estimated to be $3.5\pm1.2\times10^{14}\ \text{M}_\odot$ and is consistent with the mass derived from a mass-richness scaling relation. This mass is extreme for a cluster at such a high redshift and suggests that SpARCS1049+56 is rare in the standard $Λ$CDM universe.

astro-ph.CO↗

arXiv2019

Discovery of a Powerful >10^61 erg AGN Outburst in Distant Galaxy Cluster SPT-CLJ0528-5300

We present ~103 ks of Chandra observations of the galaxy cluster SPT-CLJ0528-5300 (SPT0528, z=0.768). This cluster harbors the most radio-loud (L_1.4GHz = 1.01 x 10^33 erg/s/Hz) central AGN of any cluster in the South Pole Telescope (SPT) SZ survey with available X-ray data. We find evidence of AGN-inflated cavities in the X-ray emission, which are consistent with the orientation of the jet direction revealed by ATCA radio data. The combined probability that two such depressions -- each at ~1.4-1.8sigma significance, oriented ~180 degrees apart and aligned with the jet axis -- would occur by chance is 0.1%. At >10^61 erg, the outburst in SPT0528 is among the most energetic known in the universe, and certainly the most powerful known at z>0.25. This work demonstrates that such powerful outbursts can be detected even in shallow X-ray exposures out to relatively high redshifts (z~0.8), providing an avenue for studying the evolution of extreme AGN feedback. The ratio of the cavity power (P_cav = 9.4+/-5.8 x 10^45 erg/s) to the cooling luminosity (L_cool = 1.5+/-0.5 x 10^44 erg/s) for SPT0528 is among the highest measured to date. If, in the future, additional systems are discovered at similar redshifts with equally high P_cav/L_cool ratios, it would imply that the feedback/cooling cycle was not as gentle at high redshifts as in the low-redshift universe.

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arXiv2019

Direct Detection of Black Hole-Driven Turbulence in the Centers of Galaxy Clusters

Supermassive black holes (SMBHs) are thought to provide energy that prevents catastrophic cooling in the centers of massive galaxies and galaxy clusters. However, it remains unclear how this "feedback" process operates. We use high-resolution optical data to study the kinematics of multi-phase filamentary structures by measuring the velocity structure function (VSF) of the filaments over a wide range of scales in the centers of three nearby galaxy clusters: Perseus, Abell 2597 and Virgo. We find that the motions of the filaments are turbulent in all three clusters studied. There is a clear correlation between features of the VSFs and the sizes of bubbles inflated by SMBH driven jets. Our study demonstrates that SMBHs are the main driver of turbulent gas motions in the centers of galaxy clusters and suggests that this turbulence is an important channel for coupling feedback to the environment. Our measured amplitude of turbulence is in good agreement with Hitomi Doppler line broadening measurement and X-ray surface brightness fluctuation analysis, suggesting that the motion of the cold filaments is well-coupled to that of the hot gas. The smallest scales we probe are comparable to the mean free path in the intracluster medium (ICM). Our direct detection of turbulence on these scales provides the clearest evidence to date that isotropic viscosity is suppressed in the weakly-collisional, magnetized intracluster plasma.

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