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DOE OSTI2023

Neural Network Water Model Based on the MB-Pol Many-Body Potential

The MB-pol many-body potential accurately predicts many properties of water, including cluster, liquid phase, and vapor–liquid equilibrium properties, but its high computational cost can make applying it in large-scale simulations quite challenging. Here, in order to address this limitation, we developed a “deep potential” neural network (DPMD) model based on the MB-pol potential for water. We find that a DPMD model trained on mostly liquid configurations yields a good description of the bulk liquid phase but severely underpredicts vapor–liquid coexistence densities. By contrast, adding cluster configurations to the neural network training set leads to a good agreement for the vapor coexistence densities. Liquid phase densities under supercooled conditions are also represented well, even though they were not included in the training set. These results confirm that neural network models can combine accuracy and transferability if sufficient attention is given to the construction of a representative training set for the target system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Theory of the photomolecular effect

It is well-known that water in liquid and vapor phases exhibits weak visible-light absorption. Recent experiments, however, show that at the liquid-air interface, absorption drastically increases, accelerating evaporation beyond thermal limits by 2–5 times. Strikingly, evaporation peaks at green wavelengths, despite no corresponding absorptance peak. The underlying mechanism of this observation, termed the photomolecular effect, remains puzzling, particularly as water molecules do not exhibit resonance peaks in the visible spectrum. Here, we present a theoretical model explaining the effect. We show that surface-bound water clusters undergo non-resonant photon-driven evaporation, with green light being particularly effective. Crucially, we do not expect green light to couple more strongly than other wavelengths to the molecules at the surface, rather the energy of green light is more effectively used to vaporize water. Our model accounts for why the evaporation peak does not align with absorptance and provides a quantum mechanical explanation of how a single photon can vaporize an entire molecular cluster. This model challenges conventional views on water-light interactions, revealing a fundamentally non-thermal evaporation mechanism. Furthermore, our findings have implications for water purification, energy-efficient drying, and climate modeling, opening new pathways for optimizing evaporation-based technologies.

Interfacial evaporation↗

DOE OSTI2021

Hybrid deep learning architecture for general disruption prediction across tokamaks

In this paper, we present a new deep learning disruption prediction algorithm based on important findings from explorative data analysis which effectively allows knowledge transfer from existing devices to new ones, thereby predicting disruptions using very limited disruptive data from the new devices. The explorative data analysis conducted via unsupervised clustering techniques confirms that time-sequence data are much better separators of disruptive and non-disruptive behavior than the instantaneous plasma state data with further advantageous implications for a sequence-based predictor. Based on such important findings, we have designed a new algorithm for multi-machine disruption prediction that achieves high predictive accuracy on the C-Mod (AUC=0.801), DIII-D (AUC=0.947) and EAST (AUC=0.973). tokamaks with limited hyperparameter tuning. Through numerical experiments, we show that boosted accuracy (AUC=0.959) is achieved on EAST predictions by including in the training only 20 disruptive discharges, thousands of non-disruptive discharges from EAST, and combining this with more than a thousand discharges from DIII-D and C-Mod. The improvement of predictive ability obtained by combining disruptive data from other devices is found to be true for all permutations of the three devices. Furthermore, by comparing the predictive performance of each individual numerical experiment, we find that non-disruptive data are machine-specific while disruptive data from multiple devices contain device-independent knowledge that can be used to inform predictions for disruptions occurring on a new device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Joint Analysis of Small-scale Galaxy Clustering and Galaxy–Galaxy Lensing from BOSS Galaxies

We present a joint analysis of galaxy clustering and galaxy–galaxy lensing measurements from BOSS galaxies using a simulation-based emulation method combined with a halo occupation distribution model. Our emulators are constructed with the Aemulus ν simulations, a suite of wνCDM N-body simulations with massive neutrinos as independent particle species. We combine small-scale analysis of clustering from 0.1 to 60.2 h −1 Mpc and lensing from 1.7 to 60.2 h −1 Mpc to perform cosmological constraints. We split the BOSS galaxies into three redshift bins to measure their clustering and employ galaxies from Dark Energy Camera Legacy Survey and Hyper Suprime-Cam as source galaxies to measure lensing separately. We find that the addition of lensing significantly improves the constraining power on $S_8 = σ_8(Ω_m/0.3)^{0.5}$, with a weak improvement for fσ 8 . Our results of fσ 8 indicate tensions of around 1σ−4σ below the results of the cosmic microwave background observations of Planck. For S 8 , our results are also lower than Planck, and the tension can be mitigated when considering possible systematics in lensing measurement. As a by-product, our analysis prefers a nonzero neutrino mass but without strong significance, with the constraining power dominated by the clustering. Given the accuracy and precision of our model and the observational data, it is anticipated that larger and higher-quality spectroscopic data sets will improve the constraints on this fundamental property in the near future.

Gao, Wenhao [Shanghai Jiao Tong University (China)↗

DOE OSTI2020

The Distant, Galaxy Cluster Environment of the Short GRB 161104A at $z\sim 0.8$ and a Comparison to the Short GRB Host Population

We present optical observations of the Swift short-duration gamma-ray burst (GRB) GRB 161104A and its host galaxy at z = 0.793 ± 0.003. We model the multiband photometry and spectroscopy with the stellar population inference code Prospector and explore the posterior using nested sampling. We find a mass-weighted age of $t_m = 2.12^{+0.23}_{-0.21}$ Gyr, stellar mass of log(M/M ⊙ ), metallicity of log(Z/Z ⊙ ), dust extinction of $A_V = 0.08^{+0.08}_{-0.05}$, and low star formation rate of 9.9 × 10 -2 M ⊙ yr -1 . These properties, along with a prominent 4000 Å break and optical absorption lines, classify this host as an early-type, quiescent galaxy. Using Dark Energy Survey galaxy catalogs, we demonstrate that the host of GRB 161104A resides on the outskirts of a galaxy cluster at z ≈ 0.8, situated ≈1 Mpc from the likely brightest cluster galaxy. We also present new modeling for 20 additional short GRB hosts (≈33% of which are early-type galaxies), finding population medians of and $t_m = 1.07^{+1.98}_{-0.67}$ Gyr (68% confidence). We further find that the host of GRB 161104A is more distant, less massive, and younger than the four other short GRB hosts known to be associated with galaxy clusters. Cluster short GRBs have faint afterglows, in the lower ≈11% (≈30%) of observed X-ray (optical) luminosities. We place a lower limit on the fraction of short GRBs in galaxy clusters versus those in the field of ≈5%–13%, consistent with the fraction of stellar mass of ≈10%–20% in galaxy clusters at redshifts 0.1 ≤ z ≤ 0.8. Future studies that take advantage of wider-field and deeper cluster surveys are needed to understand the true rate of short GRBs in clusters and their effect on heavy-element enrichment in the intracluster medium.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Multi stage and illumination dependent segregation in MAPb(I,Br)3

© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. An unsolved problem of mixed halide perovskites is the light induced compositional instability. Under illumination microscopic clusters with a higher iodide content form which act as efficient recombination centers reducing device performance. In photoluminescence measurements this leads to the development of a secondary peak at low energies that increases in intensity and shifts towards lower energies. Different theories for about the origin have been developed but the underlying key mechanisms are still under debate. In the presented study the photoluminescence evolution of MAPb(I1.5Br1.5) perovskites with varying microstructure is investigated at various excitation densities and temperatures. We find a more evolved segregation mechanism with an intermediate stage between the commonly reported mixed phase and the appearance of the I-rich clusters (Br content < 50%). In this intermediate stage perovskite domains with nearly pure iodide content form (Br content < 25%). Using low excitation densities, the interplay between the I-rich domains and the I-rich clusters leads to a blue shift of the conjunct I-rich luminescence peak. At high excitation densities the I-rich domains and the I-rich clusters are clearly distinguishable, due to a stronger PL response of the I-rich domains. With continuous illumination more I-rich cluster form acting as carrier traps and recombination centers. Due to this, the influence of the few I-rich domains on the PL signature decreases leaving only the commonly reported red shift of the I-rich clusters at later stages of the segregation. The formation of the I-rich domains is fully reversible in the dark and occurs also at elevated temperatures. Measurements on sample with varying grain size further indicate an enhanced formation of those I-rich domains on samples with high grain boundary density possibly by a faster halide mobility along them.

Babbe, F↗

DOE OSTI2024

FPGA-Accelerated Range-Limited Molecular Dynamics

Long timescale Molecular Dynamics (MD) simulation of small molecules is crucial in drug design and basic science. To accelerate a small data set that is executed for a large number of iterations, high-efficiency is required. Recent work in this domain has demonstrated that among COTS devices only FPGA-centric clusters can scale beyond a few processors. The problem addressed here is that, as the number of on-chip processors has increased from fewer than 10 into the hundreds, previous intra-chip routing solutions are no longer viable. We find, however, that through various design innovations, high efficiency can be maintained. These include replacing the previous broadcast networks with ring-routing and then augmenting the rings with out-of-order and caching mechanisms. Others are adding a level of hierarchical filtering and memory recycling. Two novel optimized architectures emerge, together with a number of variations. These are validated, analyzed, and evaluated. We find that in the domain of interest speed-ups over GPUs are achieved. Finally, the potential impact is that this system promises to be the basis for scalable long timescale MD with commodity clusters.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Subaru Hyper Suprime-Cam revisits the large-scale environmental dependence on galaxy morphology over 360 deg2 at z = 0.3–0.6

This study investigates the role of large-scale environments on the fraction of spiral galaxies at z = 0.3–0.6 sliced to three redshift bins of Δz = 0.1. Here, we sample 276220 massive galaxies in a limited stellar mass of 5 × 1010 solar mass (~M*) over 360 deg2, as obtained from the Second Public Data Release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). By combining projected two-dimensional density information (Shimakawa et al. 2021, MNRAS, 503, 3896) and the CAMIRA cluster catalog (Oguri et al. 2018, PASJ, 70, S20), we investigate the spiral fraction across large-scale overdensities and in the vicinity of red sequence clusters. We adopt transfer learning to reduce the cost of labeling spiral galaxies significantly and then perform stacking analysis across the entire field to overcome the limitations of sample size. Here we employ a morphological classification catalog by the Galaxy Zoo Hubble (Willett et al., 2017, MNRAS, 464, 4176) to train the deep learning model. Based on 74103 sources classified as spirals, we find moderate morphology–density relations on a 10 comoving Mpc scale, thanks to the wide-field coverage of HSC-SSP. Clear deficits of spiral galaxies have also been confirmed, in and around 1136 red sequence clusters. Furthermore, we verify whether there is a large-scale environmental dependence on rest-frame u - r colors of spiral galaxies; such a tendency was not observed in our sample.

Astronomy & Astrophysics↗

DOE OSTI2023

DELVE 6: An Ancient, Ultra-faint Star Cluster on the Outskirts of the Magellanic Clouds

Abstract We present the discovery of DELVE 6, an ultra-faint stellar system identified in the second data release of the DECam Local Volume Exploration (DELVE) survey. Based on a maximum-likelihood fit to its structure and stellar population, we find that DELVE 6 is an old ( τ > 9.8 Gyr at 95% confidence) and metal-poor ([Fe/H] < −1.17 dex at 95% confidence) stellar system with an absolute magnitude of M V = − 1.5 − 0.6 + 0.4 mag and an azimuthally averaged half-light radius of r 1 / 2 = 10 − 3 + 4 pc. These properties are consistent with the population of ultra-faint star clusters uncovered by recent surveys. Interestingly, DELVE 6 is located at an angular separation of ∼10° from the center of the Small Magellanic Cloud (SMC), corresponding to a 3D physical separation of ∼20 kpc given the system’s observed distance ( D ⊙ = 80 kpc). This also places the system ∼35 kpc from the center of the Large Magellanic Cloud (LMC), lying within recent constraints on the size of the LMC’s dark matter halo. We tentatively measure the proper motion of DELVE 6 using data from Gaia, which we find supports a potential association between the system and the LMC/SMC. Although future kinematic measurements will be necessary to determine its origins, we highlight that DELVE 6 may represent only the second or third ancient ( τ > 9 Gyr) star cluster associated with the SMC, or one of fewer than two dozen ancient clusters associated with the LMC. Nonetheless, we cannot currently rule out the possibility that the system is a distant Milky Way halo star cluster.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2005

At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms

The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.

Janich, Karl W.↗

DOE OSTI2020

Hybrid deep learning architecture for general disruption prediction across tokamaks

In this paper, we present a new deep learning disruption prediction algorithm based on important findings from explorative data analysis which effectively allows knowledge transfer from existing devices to new ones, thereby predicting disruptions using very limited disruptive data from the new devices. Here, the explorative data analysis conducted via unsupervised clustering techniques confirms that time-sequence data are much better separators of disruptive and non-disruptive behavior than the instantaneous plasma state data with further advantageous implications for a sequence-based predictor. Based on such important findings, we have designed a new algorithm for multi-machine disruption prediction that achieves high predictive accuracy on the C-Mod (AUC=0.801), DIII-D (AUC=0.947) and EAST (AUC=0.973) tokamaks with limited hyperparameter tuning. Through numerical experiments, we show that boosted accuracy (AUC=0.959) is achieved on EAST predictions by including in the training only 20 disruptive discharges, thousands of non-disruptive discharges from EAST, and combining this with more than a thousand discharges from DIII-D and C-Mod. The improvement of predictive ability obtained by combining disruptive data from other devices is found to be true for all permutations of the three devices. Furthermore, by comparing the predictive performance of each individual numerical experiment, we find that non-disruptive data are machine-specific while disruptive data from multiple devices contain device-independent knowledge that can be used to inform predictions for disruptions occurring on a new device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

The DESI One-Percent survey: exploring the Halo Occupation Distribution of Emission Line Galaxies with AbacusSummit simulations

The One-Percent survey of the Dark Energy Spectroscopic Instrument collected ~ 270k emission line galaxies (ELGs) at 0.8 < z < 1.6. The high completeness of the sample allowed the clustering to be measured down to scales never probed before, 0.04 Mpc/h in rp for the projected 2-point correlation function (2PCF) and 0.17 Mpc/h in galaxy pair separation s for the 2PCF monopole and quadrupole. The most striking feature of the measurements is a strong signal at the smallest scales, below 0.2 Mpc/h in rp and 1 Mpc/h in s. We analyse these data in the halo occupation distribution framework. We consider different distributions for central galaxies, a standard power law for satellites with no condition on the presence of a central galaxy and explore several extensions of these models. For all considered models, the mean halo mass of the sample is found to be log10 $\langle$Mh$\rangle$ ~ 11.9. We obtain a satellite mean occupation function which agrees with physically motivated ELG models only if we introduce central-satellite conformity, meaning that the satellite occupation is conditioned by the presence of central galaxies of the same type. To achieve in addition a good modelling of the clustering between 0.1 and 1 Mpc/h in rp, we allow for ELG positioning outside of the halo virial radius and find 0.5% of ELGs residing in the outskirts of halos. Furthermore, the satellite velocity dispersion inside halos is found to be ~ 30% larger than that of the halo dark matter particles. These are the main findings of our work. Here we investigate assembly bias as a function of halo concentration, local density or local density anisotropies and observe no significant change in our results. We split the data sample in two redshift bins and report no significant evolution with redshift. Lastly, changing the cosmology in the modelling impacts only slightly our results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Diagnosing Open Cluster Stock 2: Member Candidates and Mass Distribution with Gaia DR2 and LAMOST

We identify 1325 member candidates of the open cluster (OC) Stock 2 using data from Gaia DR2. We use the algorithms Clusterix 2.0 and HDBSCAN to select cluster candidates and further refine the final cluster membership by defining neighbors in 5D phase space (X {sub cp}, Y {sub cp}, Z{sub cp},κ⋅μ{sub α}{sup ∗}/ϖ, κ · μ {sub δ}/ϖ). Among these candidates, less than half have G, G {sub BP}, and G {sub RP} extinctions from Gaia. When Gaia extinctions are unavailable, we compute extiction using empirical formulas and E(B − V) = 0.350. We analyze the spatial distribution and mass profile of Stock 2. Our results reveal Stock 2 is still a bound OC and we find evidence of mass segregation. By comparing initial mass functions, the present-day mass function indicates that Stock 2 is a massive stellar cluster with a mass of 4000 M {sub ⊙}. The core radius and tidal radius, calculated via the radial density profile and total mass, are 3.97 pc and 22.65 pc, respectively. Common stars between our selected member candidates and the Large Sky Area Multi-Object Fiber Spectroscopic Telescope DR7 medium-resolution catalog give a metalliclity of [Fe/H] = −0.040 ± 0.147.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

The outer stellar mass of massive galaxies: a simple tracer of halo mass with scatter comparable to richness and reduced projection effects

ABSTRACT Using the weak gravitational lensing data from the Hyper Suprime-Cam Subaru Strategic Program (HSC survey), we study the potential of different stellar mass estimates in tracing halo mass. We consider galaxies with log10(M⋆/M⊙) > 11.5 at 0.2 < z < 0.5 with carefully measured light profiles, and clusters from the redMaPPer and CAMIRA richness-based algorithms. We devise a method (the ‘Top-N test’) to evaluate the scatter in the halo mass–observable relation for different tracers, and to inter-compare halo mass proxies in four number density bins using stacked galaxy–galaxy lensing profiles. This test reveals three key findings. Stellar masses based on CModel photometry and aperture luminosity within R <30 kpc are poor proxies of halo mass. In contrast, the stellar mass of the outer envelope is an excellent halo mass proxy. The stellar mass within R = [50, 100] kpc, M⋆, [50, 100], has performance comparable to the state-of-the-art richness-based cluster finders at log10Mvir ≳ 14.0 and could be a better halo mass tracer at lower halo masses. Finally, using N-body simulations, we find that the lensing profiles of massive haloes selected by M⋆, [50, 100] are consistent with the expectation for a sample without projection or mis-centring effects. Richness-selected clusters, on the other hand, display an excess at R ∼ 1 Mpc in their lensing profiles, which may suggest a more significant impact from selection biases. These results suggest that M⋆-based tracers have distinct advantages in identifying massive haloes, which could open up new avenues for cluster cosmology. The codes and data used in this work can be found here:

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2002

The Soft X-Ray Emission in a Large Sample of Galaxy Clusters with ROSAT PSPC

The study of soft X-ray emission of 38 X-ray selected galaxy clusters observed by ROSAT PSPC indicates that the soft excess phenomenon may be a common occurrence in galaxy clusters. Excess soft X-ray radiation, above the contribution from the hot intra-cluster medium, is evident in a large fraction of sources, and is clearly detected with large statistical significance in the deepest observations. The investigation relies on new, high resolution 21 cm HI observations. The sample selection also features analysis of infrared images, to further ensure reliability of results with respect to the characteristics of Galactic absorption. The possibility of background or calibration effects as cause of the excess emission is likewise investigated; a detailed analysis of the distribution of the excess emission with respect to detector position and Galactic HI column density shows that the excess emission is a genuine celestial phenomenon. We find evidence for a preferential distribution of the soft excess emission at distances larger than approx. 150-200 kpc from the centers of clusters; this behavior may be naturally explained in the context of a non-thermal Inverse-Compton scenario. Alternatively, we propose that the phenomenon maybe caused by thermal emission of very large-scale 'warm' filaments seen in recent hydrodynamic simulations. This new interpretation relieves the very demanding requirements of either the traditional intra-cluster 'warm' gas and the non-thermal scenarios. We also investigate the possibility of the soft excess originating from unresolved, X-ray faint cluster galaxies.

Bonamente, Massimiliano↗

DOE OSTI2020

CODEX weak lensing mass catalogue and implications on the mass–richness relation

The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at 0.35 < z < 0.65. It was selected from ROSAT data in the 10 000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX programme on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ lensfit shape measurement and perform a conservative colour–space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large-scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope α, normalization β, and scatter σln λ|μ of our richness–mass scaling relation model in log-space: ${\langle {\rm In}\,\, \lambda\!\!\mid\!\!\mu\rangle = \alpha\mu + \beta,} $ with μ = ln (M 200c /M piv ), and M piv = 10 14.81 M ⊙ . We find a slope $\alpha = 0.49^{+0.20}_{-0.15}$, normalization $\exp (\beta) = 84.0^{+9.2}_{-14.8}$, and $\sigma _{\ln \lambda | \mu } = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness–mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range (0.0 < z < 0.65) and with different cluster selection (X-ray, Sunyaev–Zeldovich, and optical).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

The dynamical state of RXCJ1230.7+3439: A multi-substructured merging galaxy cluster

We analyse the kinematical and dynamical state of the galaxy cluster RXCJ1230.7+3439 (RXCJ1230), at $z$ = 0.332 using 93 new spectroscopic redshifts of galaxies acquired at the Telescopio Nazionale Galileo and from SDSS DR16 public data. We study the density galaxy distribution retrieved from photometric SDSS multiband data and find that RXCJ1230 appears as a clearly isolated peak in the redshift space, with a global line-of-sight (LOS) velocity dispersion of $σ$ v = 1004 -122 +147 km s -1 . Several tests applied to the spatial and velocity distributions reveal that RXCJ1230 is a complex system with the presence of three subclusters, located to the southwest, east, and south with respect to the main body of the cluster, containing several bright galaxies (BGs) in their respective cores. Our analyses confirm that the three substructures are in a pre-merger phase, where the main interaction takes place with the southwest subclump, almost in the plane of the sky. We compute a velocity dispersion of $σ$ v ~ 1000 and $σ$ v ~ 800 km s -1 for the main cluster and the southwest substructure, respectively. The central main body and southwest substructure differ by ~870 km s -1 in the LOS velocity. From these data, we estimate a dynamical mass of $M$ 200 = 9.0 ± 1.5 × 1014 $M$ ⊙ and 4.4 ± 3.3 × 1014 $M$ ⊙ for the RXCJ1230 main body and southwest clump, respectively, which reveals that the cluster will undergo a merger characterised by a 2:1 mass ratio impact. We solve a two-body problem for this interaction and find that the most likely solution suggests that the merging axis lies ~17° from the plane of the sky and the subcluster will fully interact in ~0.3 Gyr. However, a slight excess in the X-ray temperature observed in the southwest clump confirms a certain degree of interaction already. The comparison between the dynamical masses and those derived from X-ray data reveals good agreement within errors (differences ~15%), which suggests that the innermost regions (< r 500 ) of the galaxy clumps are almost in hydrostatical equilibrium. In summary, RXCJ1230 is a young but also massive cluster in a pre-merging phase accreting other galaxy systems from its environment.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Cosmological constraints from the Planck cluster catalogue with DES shear profiles and Chandra observations

We present cosmological constraints from the Planck PSZ2 cosmological cluster sample, using weak-lensing shear profiles from Dark Energy Survey (DES) data and X-ray observations from the Chandra telescope for the mass calibration. We compute hydrostatic mass estimates for all clusters in the PSZ2 sample with a scaling relation between their Sunyaev-Zeldovich signal and X-ray derived hydrostatic mass, calibrated with the Chandra data. We introduce a method to correct these masses with a hydrostatic mass bias using shear profiles from wide-field galaxy surveys. We simultaneously fit the number counts of the PSZ2 sample and the mass calibration with the DES data, finding $Ω_\text{m}=0.312^{+0.018}_{-0.024}$, $σ_8=0.777\pm 0.024$, $S_8\equiv σ_8 \sqrt{Ω_\text{m} / 0.3}=0.791^{+0.023}_{-0.021}$, and $(1-b)=0.844^{+0.055}_{-0.062}$ for our baseline analysis when combined with BAO data. When considering a hydrostatic mass bias evolving with mass, we find $Ω_\text{m}=0.353^{+0.025}_{-0.031}$, $σ_8=0.751\pm 0.023$, and $S_8=0.814^{+0.019}_{-0.020}$. We verify the robustness of our results by exploring a variety of analysis settings, with a particular focus on the definition of the halo centre used for the extraction of shear profiles. We compare our results with a number of other analyses, in particular two recent analyses of cluster samples obtained from SPT and eROSITA data that share the same mass calibration data set. We find that our results are in overall agreement with most late-time probes, in very mild tension with CMB results (1.6$σ$), and in significant tension with results from eROSITA clusters (2.9$σ$). We confirm that our mass calibration is consistent with the eROSITA analysis by comparing masses for clusters present in both Planck and eROSITA samples, eliminating it as a potential cause of tension.

Aymerich, G. [Orsay, IAS; AIM, Saclay] (ORCID:0009↗